Sample records for identify causal genes
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Directory of Open Access Journals (Sweden)
Akira Ishikawa
2017-11-01
Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.
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Ishikawa, Akira
2017-11-27
Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.
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Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing
2011-07-01
Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.
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Causal gene identification using combinatorial V-structure search.
Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng
2013-07-01
With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Functional clustering of time series gene expression data by Granger causality
2012-01-01
Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425
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McGovern, Amanda; Schoenfelder, Stefan; Martin, Paul; Massey, Jonathan; Duffus, Kate; Plant, Darren; Yarwood, Annie; Pratt, Arthur G; Anderson, Amy E; Isaacs, John D; Diboll, Julie; Thalayasingam, Nishanthi; Ospelt, Caroline; Barton, Anne; Worthington, Jane; Fraser, Peter; Eyre, Stephen; Orozco, Gisela
2016-11-01
The identification of causal genes from genome-wide association studies (GWAS) is the next important step for the translation of genetic findings into biologically meaningful mechanisms of disease and potential therapeutic targets. Using novel chromatin interaction detection techniques and allele specific assays in T and B cell lines, we provide compelling evidence that redefines causal genes at the 6q23 locus, one of the most important loci that confers autoimmunity risk. Although the function of disease-associated non-coding single nucleotide polymorphisms (SNPs) at 6q23 is unknown, the association is generally assigned to TNFAIP3, the closest gene. However, the DNA fragment containing the associated SNPs interacts through chromatin looping not only with TNFAIP3, but also with IL20RA, located 680 kb upstream. The risk allele of the most likely causal SNP, rs6927172, is correlated with both a higher frequency of interactions and increased expression of IL20RA, along with a stronger binding of both the NFκB transcription factor and chromatin marks characteristic of active enhancers in T-cells. Our results highlight the importance of gene assignment for translating GWAS findings into biologically meaningful mechanisms of disease and potential therapeutic targets; indeed, monoclonal antibody therapy targeting IL-20 is effective in the treatment of rheumatoid arthritis and psoriasis, both with strong GWAS associations to this region.
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Inferring causal genomic alterations in breast cancer using gene expression data
2011-01-01
Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811
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Identifying causal linkages between environmental variables and African conflicts
Nguy-Robertson, A. L.; Dartevelle, S.
2017-12-01
Environmental variables that contribute to droughts, flooding, and other natural hazards are often identified as factors contributing to conflict; however, few studies attempt to quantify these causal linkages. Recent research has demonstrated that the environment operates within a dynamical system framework and the influence of variables can be identified from convergent cross mapping (CCM) between shadow manifolds. We propose to use CCM to identify causal linkages between environmental variables and incidences of conflict. This study utilizes time series data from Climate Forecast System ver. 2 and MODIS satellite sensors processed using Google Earth Engine to aggregate country and regional trends. These variables are then compared to Armed Conflict Location & Event Data Project observations at similar scales. Results provide relative rankings of variables and their linkage to conflict. Being able to identify which factors contributed more strongly to a conflict can allow policy makers to prepare solutions to mitigate future crises. Knowledge of the primary environmental factors can lead to the identification of other variables to examine in the causal network influencing conflict.
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Inferring the conservative causal core of gene regulatory networks
Directory of Open Access Journals (Sweden)
Emmert-Streib Frank
2010-09-01
Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.
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Inferring the conservative causal core of gene regulatory networks.
Altay, Gökmen; Emmert-Streib, Frank
2010-09-28
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.
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Identifying noncoding risk variants using disease-relevant gene regulatory networks.
Gao, Long; Uzun, Yasin; Gao, Peng; He, Bing; Ma, Xiaoke; Wang, Jiahui; Han, Shizhong; Tan, Kai
2018-02-16
Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.
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Zou, Cunlu; Ladroue, Christophe; Guo, Shuixia; Feng, Jianfeng
2010-06-21
Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE), Bayesian networks, information theory and Granger Causality. Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.
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Directory of Open Access Journals (Sweden)
Guo Shuixia
2010-06-01
Full Text Available Abstract Background Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE, Bayesian networks, information theory and Granger Causality. Results Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins. For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. Conclusions The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.
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Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
2016-01-01
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
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Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.
Directory of Open Access Journals (Sweden)
Saumya Gupta
2015-06-01
Full Text Available Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants' effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage
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Directory of Open Access Journals (Sweden)
Zara Ghodsi
2017-03-01
Full Text Available In developmental studies, inferring regulatory interactions of segmentation genetic network play a vital role in unveiling the mechanism of pattern formation. As such, there exists an opportune demand for theoretical developments and new mathematical models which can result in a more accurate illustration of this genetic network. Accordingly, this paper seeks to extract the meaningful regulatory role of the maternal effect genes using a variety of causality detection techniques and to explore whether these methods can suggest a new analytical view to the gene regulatory networks. We evaluate the use of three different powerful and widely-used models representing time and frequency domain Granger causality and convergent cross mapping technique with the results being thoroughly evaluated for statistical significance. Our findings show that the regulatory role of maternal effect genes is detectable in different time classes and thereby the method is applicable to infer the possible regulatory interactions present among the other genes of this network.
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Sensitivity Analysis and Bounding of Causal Effects with Alternative Identifying Assumptions
Jo, Booil; Vinokur, Amiram D.
2011-01-01
When identification of causal effects relies on untestable assumptions regarding nonidentified parameters, sensitivity of causal effect estimates is often questioned. For proper interpretation of causal effect estimates in this situation, deriving bounds on causal parameters or exploring the sensitivity of estimates to scientifically plausible…
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DEFF Research Database (Denmark)
Pers, Tune H; Timshel, Pascal; Ripke, Stephan
2016-01-01
Over 100 associated genetic loci have been robustly associated with schizophrenia. Gene prioritization and pathway analysis have focused on a priori hypotheses and thus may have been unduly influenced by prior assumptions and missed important causal genes and pathways. Using a data-driven approac...
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Causal models in epidemiology: past inheritance and genetic future
Directory of Open Access Journals (Sweden)
Kriebel David
2006-07-01
Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional
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Partial Granger causality--eliminating exogenous inputs and latent variables.
Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng
2008-07-15
Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.
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Hitomi, Yuki; Tokunaga, Katsushi
2017-01-01
Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.
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Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.
2018-04-01
Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.
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Teramoto, Reiji; Saito, Chiaki; Funahashi, Shin-ichi
2014-06-30
Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughput data that allow us to detect genes, it is important to identify genes that drive functional and phenotypic changes of cells. However, conventional methods rely heavily on the assumption of normality and they often give incorrect results when the assumption is not true. To relax the Gaussian assumption in causal inference, we introduce the non-paranormal method to test conditional independence in the PC-algorithm. Then, we present the non-paranormal intervention-calculus when the directed acyclic graph (DAG) is absent (NPN-IDA), which incorporates the cumulative nature of effects through a cascaded pathway via causal inference for ranking causal genes against a phenotype with the non-paranormal method for estimating DAGs. We demonstrate that causal inference with the non-paranormal method significantly improves the performance in estimating DAGs on synthetic data in comparison with the original PC-algorithm. Moreover, we show that NPN-IDA outperforms the conventional methods in exploring regulators of the flowering time in Arabidopsis thaliana and regulators that control the browning of white adipocytes in mice. Our results show that performance improvement in estimating DAGs contributes to an accurate estimation of causal effects. Although the simplest alternative procedure was used, our proposed method enables us to design efficient intervention experiments and can be applied to a wide range of research purposes, including drug discovery, because of its generality.
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Sritara, C; Thakkinstian, A; Ongphiphadhanakul, B; Chailurkit, L; Chanprasertyothin, S; Ratanachaiwong, W; Vathesatogkit, P; Sritara, P
2014-05-01
Using mediation analysis, a causal relationship between the AHSG gene and bone mineral density (BMD) through fetuin-A and body mass index (BMI) mediators was suggested. Fetuin-A, a multifunctional protein of hepatic origin, is associated with bone mineral density. It is unclear if this association is causal. This study aimed at clarification of this issue. A cross-sectional study was conducted among 1,741 healthy workers from the Electricity Generating Authority of Thailand (EGAT) cohort. The alpha-2-Heremans-Schmid glycoprotein (AHSG) rs2248690 gene was genotyped. Three mediation models were constructed using seemingly unrelated regression analysis. First, the ln[fetuin-A] group was regressed on the AHSG gene. Second, the BMI group was regressed on the AHSG gene and the ln[fetuin-A] group. Finally, the BMD model was constructed by fitting BMD on two mediators (ln[fetuin-A] and BMI) and the independent AHSG variable. All three analyses were adjusted for confounders. The prevalence of the minor T allele for the AHSG locus was 15.2%. The AHSG locus was highly related to serum fetuin-A levels (P Multiple mediation analyses showed that AHSG was significantly associated with BMD through the ln[fetuin-A] and BMI pathway, with beta coefficients of 0.0060 (95% CI 0.0038, 0.0083) and 0.0030 (95% CI 0.0020, 0.0045) at the total hip and lumbar spine, respectively. About 27.3 and 26.0% of total genetic effects on hip and spine BMD, respectively, were explained by the mediation effects of fetuin-A and BMI. Our study suggested evidence of a causal relationship between the AHSG gene and BMD through fetuin-A and BMI mediators.
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Bonnet, Crystel; Riahi, Zied; Chantot-Bastaraud, Sandra; Smagghe, Luce; Letexier, Mélanie; Marcaillou, Charles; Lefèvre, Gaëlle M; Hardelin, Jean-Pierre; El-Amraoui, Aziz; Singh-Estivalet, Amrit; Mohand-Saïd, Saddek; Kohl, Susanne; Kurtenbach, Anne; Sliesoraityte, Ieva; Zobor, Ditta; Gherbi, Souad; Testa, Francesco; Simonelli, Francesca; Banfi, Sandro; Fakin, Ana; Glavač, Damjan; Jarc-Vidmar, Martina; Zupan, Andrej; Battelino, Saba; Martorell Sampol, Loreto; Claveria, Maria Antonia; Catala Mora, Jaume; Dad, Shzeena; Møller, Lisbeth B; Rodriguez Jorge, Jesus; Hawlina, Marko; Auricchio, Alberto; Sahel, José-Alain; Marlin, Sandrine; Zrenner, Eberhart; Audo, Isabelle; Petit, Christine
2016-12-01
Usher syndrome (USH), the most prevalent cause of hereditary deafness-blindness, is an autosomal recessive and genetically heterogeneous disorder. Three clinical subtypes (USH1-3) are distinguishable based on the severity of the sensorineural hearing impairment, the presence or absence of vestibular dysfunction, and the age of onset of the retinitis pigmentosa. A total of 10 causal genes, 6 for USH1, 3 for USH2, and 1 for USH3, and an USH2 modifier gene, have been identified. A robust molecular diagnosis is required not only to improve genetic counseling, but also to advance gene therapy in USH patients. Here, we present an improved diagnostic strategy that is both cost- and time-effective. It relies on the sequential use of three different techniques to analyze selected genomic regions: targeted exome sequencing, comparative genome hybridization, and quantitative exon amplification. We screened a large cohort of 427 patients (139 USH1, 282 USH2, and six of undefined clinical subtype) from various European medical centers for mutations in all USH genes and the modifier gene. We identified a total of 421 different sequence variants predicted to be pathogenic, about half of which had not been previously reported. Remarkably, we detected large genomic rearrangements, most of which were novel and unique, in 9% of the patients. Thus, our strategy led to the identification of biallelic and monoallelic mutations in 92.7% and 5.8% of the USH patients, respectively. With an overall 98.5% mutation characterization rate, the diagnosis efficiency was substantially improved compared with previously reported methods.
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15 years of research on Oral-Facial-Digital syndromes: from 1 to 16 causal genes
Bruel, Ange-Line; Franco, Brunella; Duffourd, Yannis; Thevenon, Julien; Jego, Laurence; Lopez, Estelle; Deleuze, Jean-François; Doummar, Diane; Giles, Rachel H.; Johnson, Colin A.; Huynen, Martijn A.; Chevrier, Véronique; Burglen, Lydie; Morleo, Manuela; Desguerres, Isabelle; Pierquin, Geneviève; Doray, Bérénice; Gilbert-Dussardier, Brigitte; Reversade, Bruno; Steichen-Gersdorf, Elisabeth; Baumann, Clarisse; Panigrahi, Inusha; Fargeot-Espaliat, Anne; Dieux, Anne; David, Albert; Goldenberg, Alice; Bongers, Ernie; Gaillard, Dominique; Argente, Jesús; Aral, Bernard; Gigot, Nadège; St-Onge, Judith; Birnbaum, Daniel; Phadke, Shubha R.; Cormier-Daire, Valérie; Eguether, Thibaut; Pazour, Gregory J.; Herranz-Pérez, Vicente; Lee, Jaclyn S.; Pasquier, Laurent; Loget, Philippe; Saunier, Sophie; Mégarbané, André; Rosnet, Olivier; Leroux, Michel R.; Wallingford, John B.; Blacque, Oliver E.; Nachury, Maxence V.; Attie-Bitach, Tania; Rivière, Jean-Baptiste; Faivre, Laurence; Thauvin-Robinet, Christel
2017-01-01
Oral-facial-digital syndromes (OFDS) gather rare genetic disorders characterized by facial, oral and digital abnormalities associated with a wide range of additional features (polycystic kidney disease, cerebral malformations and several others) to delineate a growing list of OFD subtypes. The most frequent, OFD type I, is caused by a heterozygous mutation in the OFD1 gene encoding a centrosomal protein. The wide clinical heterogeneity of OFDS suggests the involvement of other ciliary genes. For 15 years, we have aimed to identify the molecular bases of OFDS. This effort has been greatly helped by the recent development of whole exome sequencing (WES). Here, we present all our published and unpublished results for WES in 24 OFDS cases. We identified causal variants in five new genes (C2CD3, TMEM107, INTU, KIAA0753, IFT57) and related the clinical spectrum of four genes in other ciliopathies (C5orf42, TMEM138, TMEM231, WDPCP) to OFDS. Mutations were also detected in two genes previously implicated in OFDS. Functional studies revealed the involvement of centriole elongation, transition zone and intraflagellar transport defects in OFDS, thus characterizing three ciliary protein modules: the complex KIAA0753-FOPNL-OFD1, a regulator of centriole elongation; the MKS module, a major component of the transition zone; and the CPLANE complex necessary for IFT-A assembly. OFDS now appear to be a distinct subgroup of ciliopathies with wide heterogeneity, which makes the initial classification obsolete. A clinical classification restricted to the three frequent/well-delineated subtypes could be proposed, and for patients who do not fit one of these 3 main subtypes, a further classification could be based on the genotype. PMID:28289185
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Park, Soojin
2015-01-01
Identifying the causal mechanisms is becoming more essential in social and medical sciences. In the presence of treatment non-compliance, the Intent-To-Treated effect (hereafter, ITT effect) is identified as long as the treatment is randomized (Angrist et al., 1996). However, the mediated portion of effect is not identified without additional…
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Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun
2016-01-01
Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082
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Lee, Yujung; Kim, Changshin; Park, YoungJoon; Pyun, Jung-A; Kwack, KyuBum
2016-12-01
Premature ovarian failure (POF) is characterized by heterogeneous genetic causes such as chromosomal abnormalities and variants in causal genes. Recently, development of techniques made next generation sequencing (NGS) possible to detect genome wide variants including chromosomal abnormalities. Among 37 Korean POF patients, XY karyotype with distal part deletions of Y chromosome, Yp11.32-31 and Yp12 end part, was observed in two patients through NGS. Six deleterious variants in POF genes were also detected which might explain the pathogenesis of POF with abnormalities in the sex chromosomes. Additionally, the two POF patients had no mutation in SRY but three non-synonymous variants were detected in genes regarding sex reversal. These findings suggest candidate causes of POF and sex reversal and show the propriety of NGS to approach the heterogeneous pathogenesis of POF. Copyright © 2016 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Marinela eCapanu
2015-05-01
Full Text Available Identifying the small number of rare causal variants contributing to disease has beena major focus of investigation in recent years, but represents a formidable statisticalchallenge due to the rare frequencies with which these variants are observed. In thiscommentary we draw attention to a formal statistical framework, namely hierarchicalmodeling, to combine functional genomic annotations with sequencing data with theobjective of enhancing our ability to identify rare causal variants. Using simulations weshow that in all configurations studied, the hierarchical modeling approach has superiordiscriminatory ability compared to a recently proposed aggregate measure of deleteriousness,the Combined Annotation-Dependent Depletion (CADD score, supportingour premise that aggregate functional genomic measures can more accurately identifycausal variants when used in conjunction with sequencing data through a hierarchicalmodeling approach
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Identifying X-consumers using causal recipes: "whales" and "jumbo shrimps" casino gamblers.
Woodside, Arch G; Zhang, Mann
2012-03-01
X-consumers are the extremely frequent (top 2-3%) users who typically consume 25% of a product category. This article shows how to use fuzzy-set qualitative comparative analysis (QCA) to provide "causal recipes" sufficient for profiling X-consumers accurately. The study extends Dik Twedt's "heavy-half" product users for building theory and strategies to nurture or control X-behavior. The study here applies QCA to offer configurations that are sufficient in identifying "whales" and "jumbo shrimps" among X-casino gamblers. The findings support the principle that not all X-consumers are alike. The theory and method are applicable for identifying the degree of consistency and coverage of alternative X-consumers among users of all product-service category and brands.
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Obesity and infection: reciprocal causality.
Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I
2015-01-01
Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.
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NIH Researchers Identify OCD Risk Gene
... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...
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Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information
Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David
2018-05-01
The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.
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Directory of Open Access Journals (Sweden)
Nicholas M Morton
Full Text Available Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L strain.To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney was performed. Known obesity quantitative trait loci (QTL information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity.A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.
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A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease
Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel
2013-01-01
Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213
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Inductive reasoning about causally transmitted properties.
Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B
2008-11-01
Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.
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Causal and causally separable processes
Oreshkov, Ognyan; Giarmatzi, Christina
2016-09-01
The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and
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Causal and causally separable processes
International Nuclear Information System (INIS)
Oreshkov, Ognyan; Giarmatzi, Christina
2016-01-01
The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B , either A is in the causal past of B , B is in the causal past of A , or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B , an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A ’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and
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DEFF Research Database (Denmark)
Danesh, J.; Hingorani, A.; Wensley, F.
2008-01-01
Many prospective studies have reported associations between circulating C-reactive protein (CRP) levels and risk of coronary heart disease (CHD), but causality remains uncertain. Studies of CHD are being conducted that involve measurement of common polymorphisms of the CRP gene known to be associ...
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Morabia, Alfredo
2005-01-01
Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.
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Gene-based Association Approach Identify Genes Across Stress Traits in Fruit Flies
DEFF Research Database (Denmark)
Rohde, Palle Duun; Edwards, Stefan McKinnon; Sarup, Pernille Merete
Identification of genes explaining variation in quantitative traits or genetic risk factors of human diseases requires both good phenotypic- and genotypic data, but also efficient statistical methods. Genome-wide association studies may reveal association between phenotypic variation and variation...... approach grouping variants accordingly to gene position, thus lowering the number of statistical tests performed and increasing the probability of identifying genes with small to moderate effects. Using this approach we identify numerous genes associated with different types of stresses in Drosophila...... melanogaster, but also identify common genes that affects the stress traits....
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Chemical-gene interaction networks and causal reasoning for ...
Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o
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Expression profiling identifies genes involved in emphysema severity
Directory of Open Access Journals (Sweden)
Bowman Rayleen V
2009-09-01
Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.
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Causally nonseparable processes admitting a causal model
International Nuclear Information System (INIS)
Feix, Adrien; Araújo, Mateus; Brukner, Caslav
2016-01-01
A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities ) while others do not (they admit a ‘causal model’ analogous to a local model ). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties. (paper)
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Directory of Open Access Journals (Sweden)
Xudong Dai
2007-03-01
Full Text Available Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs against the gene for peroxisome proliferator-activated receptor alpha (Ppara, our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARalpha-induced liver hypertrophy is supported by their ability to predict non-PPARalpha-induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005. Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug
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Directory of Open Access Journals (Sweden)
Elena Vigorito
Full Text Available Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases BRCA1 and 8,211 (631 ovarian cancer cases BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16. These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6. The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
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Directory of Open Access Journals (Sweden)
Lockwood William W
2010-05-01
Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.
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Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors
Directory of Open Access Journals (Sweden)
Victor M. Bii
2016-10-01
Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.
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Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng
2018-01-01
Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.
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Directory of Open Access Journals (Sweden)
Jie Luo
2018-04-01
Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.
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Sobreira, Nara; Schiettecatte, François; Boehm, Corinne; Valle, David; Hamosh, Ada
2015-04-01
Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s). © 2015 WILEY PERIODICALS, INC.
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Causality and headache triggers
Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.
2013-01-01
Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872
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DEFF Research Database (Denmark)
Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2...... mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively...... of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest...
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Rodriguez, Gabriela; Ueyama, Tomomi; Ogata, Takehiro; Czernuszewicz, Grazyna; Tan, Yanli; Dorn, Gerald W; Bogaev, Roberta; Amano, Katsuya; Oh, Hidemasa; Matsubara, Hiroaki; Willerson, James T; Marian, Ali J
2011-08-01
Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are classic forms of systolic and diastolic heart failure, respectively. Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of HCM and DCM. MURC, encoding muscle-restricted coiled-coil, a Z-line protein, regulates cardiac function in mice. We investigated potential causal role of MURC in human cardiomyopathies. We sequenced MURC in 1199 individuals, including 383 probands with DCM, 307 with HCM, and 509 healthy control subjects. We found 6 heterozygous DCM-specific missense variants (p.N128K, p.R140W, p.L153P, p.S307T, p.P324L, and p.S364L) in 8 unrelated probands. Variants p.N128K and p.S307T segregated with inheritance of DCM in small families (χ(2)=8.5, P=0.003). Variants p.N128K, p.R140W, p.L153P, and p.S364L were considered probably or possibly damaging. Variant p.P324L recurred in 3 independent probands, including 1 proband with a TPM1 mutation (p.M245T). A deletion variant (p.L232-R238del) was present in 3 unrelated HCM probands, but it did not segregate with HCM in a family who also had a MYH7 mutation (p.L907V). The phenotype in mutation carriers was notable for progressive heart failure leading to heart transplantation in 4 patients, conduction defects, and atrial arrhythmias. Expression of mutant MURC proteins in neonatal rat cardiac myocytes transduced with recombinant adenoviruses was associated with reduced RhoA activity, lower mRNA levels of hypertrophic markers and smaller myocyte size as compared with wild-type MURC. MURC mutations impart loss-of-function effects on MURC functions and probably are causal variants in human DCM. The causal role of a deletion mutation in HCM is uncertain.
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Causal inference in biology networks with integrated belief propagation.
Chang, Rui; Karr, Jonathan R; Schadt, Eric E
2015-01-01
Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.
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Identifying potential maternal genes of Bombyx mori using digital gene expression profiling
Xu, Pingzhen
2018-01-01
Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160
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Nazari-Ghadikolaei, Anahit; Mehrabani-Yeganeh, Hassan; Miarei-Aashtiani, Seyed R; Staiger, Elizabeth A; Rashidi, Amir; Huson, Heather J
2018-01-01
The Markhoz goat provides an opportunity to study the genetics underlying coat color and mohair traits of an Angora type goat using genome-wide association studies (GWAS). This indigenous Iranian breed is valued for its quality mohair used in ceremonial garments and has the distinction of exhibiting an array of coat colors including black, brown, and white. Here, we performed 16 GWAS for different fleece (mohair) traits and coat color in 228 Markhoz goats sampled from the Markhoz Goat Research Station in Sanandaj, Kurdistan province, located in western Iran using the Illumina Caprine 50K beadchip. The Efficient Mixed Model Linear analysis was used to identify genomic regions with potential candidate genes contributing to coat color and mohair characteristics while correcting for population structure. Significant associations to coat color were found within or near the ASIP, ITCH, AHCY , and RALY genes on chromosome 13 for black and brown coat color and the KIT and PDGFRA genes on chromosome 6 for white coat color. Individual mohair traits were analyzed for genetic association along with principal components that allowed for a broader perspective of combined traits reflecting overall mohair quality and volume. A multitude of markers demonstrated significant association to mohair traits highlighting potential candidate genes of POU1F1 on chromosome 1 for mohair quality, MREG on chromosome 2 for mohair volume, DUOX1 on chromosome 10 for yearling fleece weight, and ADGRV1 on chromosome 7 for grease percentage. Variation in allele frequencies and haplotypes were identified for coat color and differentiated common markers associated with both brown and black coat color. This demonstrates the potential for genetic markers to be used in future breeding programs to improve selection for coat color and mohair traits. Putative candidate genes, both novel and previously identified in other species or breeds, require further investigation to confirm phenotypic causality and
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Detectability of Granger causality for subsampled continuous-time neurophysiological processes.
Barnett, Lionel; Seth, Anil K
2017-01-01
Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity
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Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.
Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin
2017-08-01
This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.
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Causal imprinting in causal structure learning.
Taylor, Eric G; Ahn, Woo-Kyoung
2012-11-01
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.
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Defining a new candidate gene for amelogenesis imperfecta: from molecular genetics to biochemistry.
Urzúa, Blanca; Ortega-Pinto, Ana; Morales-Bozo, Irene; Rojas-Alcayaga, Gonzalo; Cifuentes, Víctor
2011-02-01
Amelogenesis imperfecta is a group of genetic conditions that affect the structure and clinical appearance of tooth enamel. The types (hypoplastic, hypocalcified, and hypomature) are correlated with defects in different stages of the process of enamel synthesis. Autosomal dominant, recessive, and X-linked types have been previously described. These disorders are considered clinically and genetically heterogeneous in etiology, involving a variety of genes, such as AMELX, ENAM, DLX3, FAM83H, MMP-20, KLK4, and WDR72. The mutations identified within these causal genes explain less than half of all cases of amelogenesis imperfecta. Most of the candidate and causal genes currently identified encode proteins involved in enamel synthesis. We think it is necessary to refocus the search for candidate genes using biochemical processes. This review provides theoretical evidence that the human SLC4A4 gene (sodium bicarbonate cotransporter) may be a new candidate gene.
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Diametrical clustering for identifying anti-correlated gene clusters.
Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman
2003-09-01
Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.
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Optimal causal inference: estimating stored information and approximating causal architecture.
Still, Susanne; Crutchfield, James P; Ellison, Christopher J
2010-09-01
We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.
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Amodal causal capture in the tunnel effect.
Bae, Gi Yeul; Flombaum, Jonathan I
2011-01-01
In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.
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ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism
Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry
2012-01-01
Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility. PMID:22258617
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Pearl, Judea
2000-03-01
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
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Causal events enter awareness faster than non-causal events
Directory of Open Access Journals (Sweden)
Pieter Moors
2017-01-01
Full Text Available Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967. Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946. Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world.
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Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.
Conlon, Anna; Taylor, Jeremy; Li, Yun; Diaz-Ordaz, Karla; Elliott, Michael
2017-11-30
Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities. Copyright © 2017 John Wiley & Sons, Ltd.
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CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.
Shpitser, Ilya; Tchetgen, Eric Tchetgen
2016-12-01
Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl's front-door criterion.
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Jones, Robert
2010-03-01
There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.
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Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D'Onofrio, Brian M
2013-02-01
Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behavior. It is not clear, however, if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children of siblings and children of twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant monozygotic twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association.
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Coyne, Claire A; Långström, Niklas; Rickert, Martin E; Lichtenstein, Paul; D’Onofrio, Brian M
2013-01-01
Teenage childbirth is a risk factor for poor offspring outcomes, particularly offspring antisocial behaviour. It is not clear if maternal age at first birth (MAFB) is causally associated with offspring antisocial behavior or if this association is due to selection factors that influence both the likelihood that a young woman gives birth early and that her offspring engage in antisocial behavior. The current study addresses the limitations of previous research by using longitudinal data from Swedish national registries and children-of-siblings and children-of-twins comparisons to identify the extent to which the association between MAFB and offspring criminal convictions is consistent with a causal influence and confounded by genetic or environmental factors that make cousins similar. We found offspring born to mothers who began childbearing earlier were more likely to be convicted of a crime than offspring born to mothers who delayed childbearing. The results from comparisons of differentially exposed cousins, especially born to discordant MZ twin sisters, provide support for a causal association between MAFB and offspring criminal convictions. The analyses also found little evidence for genetic confounding due to passive gene-environment correlation. Future studies are needed to replicate these findings and to identify environmental risk factors that mediate this causal association. PMID:23398750
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Lo, David; Weng, Jingning; Liu, xiaohong; Yang, Juhua; He, Fen; Wang, Yun; Liu, Xuyang
2016-01-01
PURPOSE To detect the disease-causing gene in a Chinese pedigree with autosomal-recessive retinitis pigmentosa (ARRP). METHODS All subjects in this family underwent a complete ophthalmic examination. Targeted-capture next generation sequencing (NGS) was performed on the proband to detect variants. All variants were verified in the remaining family members by PCR amplification and Sanger sequencing. RESULTS All the affected subjects in this pedigree were diagnosed with retinitis pigmentosa (RP). The compound heterozygous c.138delA (p.Asp47IlefsX24) and c.1841G>T (p.Gly614Val) mutations in the Crumbs homolog 1 (CRB1) gene were identified in all the affected patients but not in the unaffected individuals in this family. These mutations were inherited from their parents, respectively. CONCLUSION The novel compound heterozygous mutations in CRB1 were identified in a Chinese pedigree with ARRP using targeted-capture next generation sequencing. After evaluating the significant heredity and impaired protein function, the compound heterozygous c.138delA (p.Asp47IlefsX24) and c.1841G>T (p.Gly614Val) mutations are the causal genes of early onset ARRP in this pedigree. To the best of our knowledge, there is no previous report regarding the compound mutations. PMID:27806333
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Identifying Causal Gateways and Mediators in Complex Spatio-Temporal Systems
Czech Academy of Sciences Publication Activity Database
Runge, J.; Petoukhov, V.; Donges, J.F.; Hlinka, Jaroslav; Jajcay, Nikola; Vejmelka, Martin; Hartman, David; Marwan, N.; Paluš, Milan; Kurths, J.
2015-01-01
Roč. 6, 7 October (2015), Article 8502 ISSN 2041-1723 R&D Projects: GA ČR(CZ) GA14-02634S; GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Grant - others:GA MŠk(CZ) LL1201; AV ČR + DAAD(CZ-DE) DAAD-15-30 Program:Bilaterální spolupráce Institutional support: RVO:67985807 Keywords : causality * climate * complex systems * dimension reduction * atmospheric dynamics * networks * dynamical systems Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 11.329, year: 2015
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Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data
Directory of Open Access Journals (Sweden)
Bing Jiang
2017-01-01
Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.
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Hierarchical organisation of causal graphs
International Nuclear Information System (INIS)
Dziopa, P.
1993-01-01
This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs
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Directory of Open Access Journals (Sweden)
Anahit Nazari-Ghadikolaei
2018-04-01
Full Text Available The Markhoz goat provides an opportunity to study the genetics underlying coat color and mohair traits of an Angora type goat using genome-wide association studies (GWAS. This indigenous Iranian breed is valued for its quality mohair used in ceremonial garments and has the distinction of exhibiting an array of coat colors including black, brown, and white. Here, we performed 16 GWAS for different fleece (mohair traits and coat color in 228 Markhoz goats sampled from the Markhoz Goat Research Station in Sanandaj, Kurdistan province, located in western Iran using the Illumina Caprine 50K beadchip. The Efficient Mixed Model Linear analysis was used to identify genomic regions with potential candidate genes contributing to coat color and mohair characteristics while correcting for population structure. Significant associations to coat color were found within or near the ASIP, ITCH, AHCY, and RALY genes on chromosome 13 for black and brown coat color and the KIT and PDGFRA genes on chromosome 6 for white coat color. Individual mohair traits were analyzed for genetic association along with principal components that allowed for a broader perspective of combined traits reflecting overall mohair quality and volume. A multitude of markers demonstrated significant association to mohair traits highlighting potential candidate genes of POU1F1 on chromosome 1 for mohair quality, MREG on chromosome 2 for mohair volume, DUOX1 on chromosome 10 for yearling fleece weight, and ADGRV1 on chromosome 7 for grease percentage. Variation in allele frequencies and haplotypes were identified for coat color and differentiated common markers associated with both brown and black coat color. This demonstrates the potential for genetic markers to be used in future breeding programs to improve selection for coat color and mohair traits. Putative candidate genes, both novel and previously identified in other species or breeds, require further investigation to confirm phenotypic
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Wilson, Paul; Larminie, Christopher; Smith, Rona
2016-01-01
To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.
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Causal boundary for stably causal space-times
International Nuclear Information System (INIS)
Racz, I.
1987-12-01
The usual boundary constructions for space-times often yield an unsatisfactory boundary set. This problem is reviewed and a new solution is proposed. An explicit identification rule is given on the set of the ideal points of the space-time. This construction leads to a satisfactory boundary point set structure for stably causal space-times. The topological properties of the resulting causal boundary construction are examined. For the stably causal space-times each causal curve has a unique endpoint on the boundary set according to the extended Alexandrov topology. The extension of the space-time through the boundary is discussed. To describe the singularities the defined boundary sets have to be separated into two disjoint sets. (D.Gy.) 8 refs
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Automatically identifying gene/protein terms in MEDLINE abstracts.
Yu, Hong; Hatzivassiloglou, Vasileios; Rzhetsky, Andrey; Wilbur, W John
2002-01-01
Natural language processing (NLP) techniques are used to extract information automatically from computer-readable literature. In biology, the identification of terms corresponding to biological substances (e.g., genes and proteins) is a necessary step that precedes the application of other NLP systems that extract biological information (e.g., protein-protein interactions, gene regulation events, and biochemical pathways). We have developed GPmarkup (for "gene/protein-full name mark up"), a software system that automatically identifies gene/protein terms (i.e., symbols or full names) in MEDLINE abstracts. As a part of marking up process, we also generated automatically a knowledge source of paired gene/protein symbols and full names (e.g., LARD for lymphocyte associated receptor of death) from MEDLINE. We found that many of the pairs in our knowledge source do not appear in the current GenBank database. Therefore our methods may also be used for automatic lexicon generation. GPmarkup has 73% recall and 93% precision in identifying and marking up gene/protein terms in MEDLINE abstracts. A random sample of gene/protein symbols and full names and a sample set of marked up abstracts can be viewed at http://www.cpmc.columbia.edu/homepages/yuh9001/GPmarkup/. Contact. hy52@columbia.edu. Voice: 212-939-7028; fax: 212-666-0140.
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Identifying key genes associated with acute myocardial infarction.
Cheng, Ming; An, Shoukuan; Li, Junquan
2017-10-01
This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.
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Ellis, George FR; Pabjan, Tadeusz
2013-01-01
Written by philosophers, cosmologists, and physicists, this collection of essays deals with causality, which is a core issue for both science and philosophy. Readers will learn about different types of causality in complex systems and about new perspectives on this issue based on physical and cosmological considerations. In addition, the book includes essays pertaining to the problem of causality in ancient Greek philosophy, and to the problem of God's relation to the causal structures of nature viewed in the light of contemporary physics and cosmology.
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Di, Xin; Biswal, Bharat B
2014-02-01
The default mode network is part of the brain structure that shows higher neural activity and energy consumption when one is at rest. The key regions in the default mode network are highly interconnected as conveyed by both the white matter fiber tracing and the synchrony of resting-state functional magnetic resonance imaging signals. However, the causal information flow within the default mode network is still poorly understood. The current study used the dynamic causal modeling on a resting-state fMRI data set to identify the network structure underlying the default mode network. The endogenous brain fluctuations were explicitly modeled by Fourier series at the low frequency band of 0.01-0.08Hz, and those Fourier series were set as driving inputs of the DCM models. Model comparison procedures favored a model wherein the MPFC sends information to the PCC and the bilateral inferior parietal lobule sends information to both the PCC and MPFC. Further analyses provide evidence that the endogenous connectivity might be higher in the right hemisphere than in the left hemisphere. These data provided insight into the functions of each node in the DMN, and also validate the usage of DCM on resting-state fMRI data. © 2013.
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Bayesian detection of causal rare variants under posterior consistency.
Liang, Faming
2013-07-26
Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD), to tackle this problem. The new method simultaneously addresses two issues: (i) (Global association test) Are there any of the variants associated with the disease, and (ii) (Causal variant detection) Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI) Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.
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Bayesian detection of causal rare variants under posterior consistency.
Directory of Open Access Journals (Sweden)
Faming Liang
Full Text Available Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD, to tackle this problem. The new method simultaneously addresses two issues: (i (Global association test Are there any of the variants associated with the disease, and (ii (Causal variant detection Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.
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Bayesian detection of causal rare variants under posterior consistency.
Liang, Faming; Xiong, Momiao
2013-01-01
Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD), to tackle this problem. The new method simultaneously addresses two issues: (i) (Global association test) Are there any of the variants associated with the disease, and (ii) (Causal variant detection) Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI) Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.
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Causality violation, gravitational shockwaves and UV completion
Energy Technology Data Exchange (ETDEWEB)
Hollowood, Timothy J.; Shore, Graham M. [Department of Physics, Swansea University,Swansea, SA2 8PP (United Kingdom)
2016-03-18
The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of “time machines”, i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.
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Vigorito, E.; Kuchenbaecker, K.B.; Beesley, J.; Adlard, J.; Agnarsson, B.A.; Andrulis, I.L.; Arun, B.K.; Barjhoux, L.; Belotti, M.; Benitez, J.; Berger, A.; Bojesen, A.; Bonanni, B.; Brewer, C.; Caldes, T.; Caligo, M.A.; Campbell, I.; Chan, S.B.; Claes, K.B.; Cohn, D.E.; Cook, J.; Daly, M.B.; Damiola, F.; Davidson, R.; Pauw, A. de; Delnatte, C.; Diez, O.; Domchek, S.M.; Dumont, M.; Durda, K.; Dworniczak, B.; Easton, D.F.; Eccles, D.; Edwinsdotter Ardnor, C.; Eeles, R.; Ejlertsen, B.; Ellis, S.; Evans, D.G.; Feliubadalo, L.; Fostira, F.; Foulkes, W.D.; Friedman, E.; Frost, D.; Gaddam, P.; Ganz, P.A.; Garber, J.; Garcia-Barberan, V.; Gauthier-Villars, M.; Gehrig, A.; Gerdes, A.M.; Giraud, S.; Godwin, A.K.; Goldgar, D.E.; Hake, C.R.; Hansen, T.V.; Healey, S.; Hodgson, S.; Hogervorst, F.B.; Houdayer, C.; Hulick, P.J.; Imyanitov, E.N.; Isaacs, C.; Izatt, L.; Izquierdo, A.; Jacobs, L; Jakubowska, A.; Janavicius, R.; Jaworska-Bieniek, K.; Jensen, U.B.; John, E.M.; Vijai, J.; Karlan, B.Y.; Kast, K.; Khan, S.; Kwong, A.; Laitman, Y.; Lester, J.; Lesueur, F.; Liljegren, A.; Lubinski, J.; Mai, P.L.; Manoukian, S.; Mazoyer, S.; Meindl, A.; Mensenkamp, A.R.; Montagna, M.; Nathanson, K.L.; Neuhausen, S.L.; Nevanlinna, H.; Niederacher, D.; Olah, E.; Olopade, O.I.; Ong, K.R.; Osorio, A.; Park, S.K.; Paulsson-Karlsson, Y.; Pedersen, I.S.; Peissel, B.; Peterlongo, P.; et al.,
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2
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DEFF Research Database (Denmark)
Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 ...
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[Causal analysis approaches in epidemiology].
Dumas, O; Siroux, V; Le Moual, N; Varraso, R
2014-02-01
Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the
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Causal relationship: a new tool for the causal characterization of Lorentzian manifolds
International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Senovilla, Jose M M
2003-01-01
We define and study a new kind of relation between two diffeomorphic Lorentzian manifolds called a causal relation, which is any diffeomorphism characterized by mapping every causal vector of the first manifold onto a causal vector of the second. We perform a thorough study of the mathematical properties of causal relations and prove in particular that two given Lorentzian manifolds (say V and W) may be causally related only in one direction (say from V to W, but not from W to V). This leads us to the concept of causally equivalent (or isocausal in short) Lorentzian manifolds as those mutually causally related and to a definition of causal structure over a differentiable manifold as the equivalence class formed by isocausal Lorentzian metrics upon it. Isocausality is a more general concept than the conformal relationship, because we prove the remarkable result that a conformal relation φ is characterized by the fact of being a causal relation of the particular kind in which both φ and φ -1 are causal relations. Isocausal Lorentzian manifolds are mutually causally compatible, they share some important causal properties, and there are one-to-one correspondences, which are sometimes non-trivial, between several classes of their respective future (and past) objects. A more important feature is that they satisfy the same standard causality constraints. We also introduce a partial order for the equivalence classes of isocausal Lorentzian manifolds providing a classification of all the causal structures that a given fixed manifold can have. By introducing the concept of causal extension we put forward a new definition of causal boundary for Lorentzian manifolds based on the concept of isocausality, and thereby we generalize the traditional Penrose constructions of conformal infinity, diagrams and embeddings. In particular, the concept of causal diagram is given. Many explicit clarifying examples are presented throughout the paper
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Dediu, D.
2008-01-01
The causal correlations between human genetic variants and linguistic (typological) features could represent the mechanism required for gradual, accretionary models of language evolution. The causal link is mediated by the process of cultural transmission of language across generations in a population of genetically biased individuals. The particular case of Tone, ASPM and Microcephalin is discussed as an illustration. It is proposed that this type of genetically-influenced linguistic bias, c...
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Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G
2015-07-01
Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.
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Gene expression analysis identifies global gene dosage sensitivity in cancer
DEFF Research Database (Denmark)
Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata
2015-01-01
Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...
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Epidermal growth factor gene is a newly identified candidate gene for gout
Lin Han; Chunwei Cao; Zhaotong Jia; Shiguo Liu; Zhen Liu; Ruosai Xin; Can Wang; Xinde Li; Wei Ren; Xuefeng Wang; Changgui Li
2016-01-01
Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 re...
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Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
International Nuclear Information System (INIS)
Neelamkavil, Raphael
2014-01-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
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Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
Energy Technology Data Exchange (ETDEWEB)
Neelamkavil, Raphael
2014-07-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
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Directory of Open Access Journals (Sweden)
Cristina Puente Águeda
2011-10-01
Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.
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A theory of causal learning in children: causal maps and Bayes nets.
Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.
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Granger Causality Testing with Intensive Longitudinal Data.
Molenaar, Peter C M
2018-06-01
The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.
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Causal interpretation of stochastic differential equations
DEFF Research Database (Denmark)
Sokol, Alexander; Hansen, Niels Richard
2014-01-01
We give a causal interpretation of stochastic differential equations (SDEs) by defining the postintervention SDE resulting from an intervention in an SDE. We show that under Lipschitz conditions, the solution to the postintervention SDE is equal to a uniform limit in probability of postintervention...... structural equation models based on the Euler scheme of the original SDE, thus relating our definition to mainstream causal concepts. We prove that when the driving noise in the SDE is a Lévy process, the postintervention distribution is identifiable from the generator of the SDE....
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Cause and Event: Supporting Causal Claims through Logistic Models
O'Connell, Ann A.; Gray, DeLeon L.
2011-01-01
Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…
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Detecting causal drivers and empirical prediction of the Indian Summer Monsoon
Di Capua, G.; Vellore, R.; Raghavan, K.; Coumou, D.
2017-12-01
The Indian summer monsoon (ISM) is crucial for the economy, society and natural ecosystems on the Indian peninsula. Predict the total seasonal rainfall at several months lead time would help to plan effective water management strategies, improve flood or drought protection programs and prevent humanitarian crisis. However, the complexity and strong internal variability of the ISM circulation system make skillful seasonal forecasting challenging. Moreover, to adequately identify the low-frequency, and far-away processes which influence ISM behavior novel tools are needed. We applied a Response-Guided Causal Precursor Detection (RGCPD) scheme, which is a novel empirical prediction method which unites a response-guided community detection scheme with a causal discovery algorithm (CEN). These tool allow us to assess causal pathways between different components of the ISM circulation system and with far-away regions in the tropics, mid-latitudes or Arctic. The scheme has successfully been used to identify causal precursors of the Stratospheric polar vortex enabling skillful predictions at (sub) seasonal timescales (Kretschmer et al. 2016, J.Clim., Kretschmer et al. 2017, GRL). We analyze observed ISM monthly rainfall over the monsoon trough region. Applying causal discovery techniques, we identify several causal precursor communities in the fields of 2m-temperature, sea level pressure and snow depth over Eurasia. Specifically, our results suggest that surface temperature conditions in both tropical and Arctic regions contribute to ISM variability. A linear regression prediction model based on the identified set of communities has good hindcasting skills with 4-5 months lead times. Further we separate El Nino, La Nina and ENSO-neutral years from each other and find that the causal precursors are different dependent on ENSO state. The ENSO-state dependent causal precursors give even higher skill, especially for La Nina years when the ISM is relatively strong. These
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Normalizing the causality between time series
Liang, X. San
2015-08-01
Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.
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Frisch, Mathias
2014-01-01
Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.
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A theory of causal learning in children: Causal maps and Bayes nets
Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...
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Protein functional links in Trypanosoma brucei, identified by gene fusion analysis
Directory of Open Access Journals (Sweden)
Trimpalis Philip
2011-07-01
Full Text Available Abstract Background Domain or gene fusion analysis is a bioinformatics method for detecting gene fusions in one organism by comparing its genome to that of other organisms. The occurrence of gene fusions suggests that the two original genes that participated in the fusion are functionally linked, i.e. their gene products interact either as part of a multi-subunit protein complex, or in a metabolic pathway. Gene fusion analysis has been used to identify protein functional links in prokaryotes as well as in eukaryotic model organisms, such as yeast and Drosophila. Results In this study we have extended this approach to include a number of recently sequenced protists, four of which are pathogenic, to identify fusion linked proteins in Trypanosoma brucei, the causative agent of African sleeping sickness. We have also examined the evolution of the gene fusion events identified, to determine whether they can be attributed to fusion or fission, by looking at the conservation of the fused genes and of the individual component genes across the major eukaryotic and prokaryotic lineages. We find relatively limited occurrence of gene fusions/fissions within the protist lineages examined. Our results point to two trypanosome-specific gene fissions, which have recently been experimentally confirmed, one fusion involving proteins involved in the same metabolic pathway, as well as two novel putative functional links between fusion-linked protein pairs. Conclusions This is the first study of protein functional links in T. brucei identified by gene fusion analysis. We have used strict thresholds and only discuss results which are highly likely to be genuine and which either have already been or can be experimentally verified. We discuss the possible impact of the identification of these novel putative protein-protein interactions, to the development of new trypanosome therapeutic drugs.
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Repeated causal decision making.
Hagmayer, York; Meder, Björn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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Mapping of gene expression reveals CYP27A1 as a susceptibility gene for sporadic ALS.
Directory of Open Access Journals (Sweden)
Frank P Diekstra
Full Text Available Amyotrophic lateral sclerosis (ALS is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS have implicated a few susceptibility loci. However, many more causal loci remain to be discovered. Since it has been shown that genetic variants associated with complex traits are more likely to be eQTLs than frequency-matched variants from GWAS platforms, we conducted a two-stage genome-wide screening for eQTLs associated with ALS. In addition, we applied an eQTL analysis to finemap association loci. Expression profiles using peripheral blood of 323 sporadic ALS patients and 413 controls were mapped to genome-wide genotyping data. Subsequently, data from a two-stage GWAS (3,568 patients and 10,163 controls were used to prioritize eQTLs identified in the first stage (162 ALS, 207 controls. These prioritized eQTLs were carried forward to the second sample with both gene-expression and genotyping data (161 ALS, 206 controls. Replicated eQTL SNPs were then tested for association in the second-stage GWAS data to find SNPs associated with disease, that survived correction for multiple testing. We thus identified twelve cis eQTLs with nominally significant associations in the second-stage GWAS data. Eight SNP-transcript pairs of highest significance (lowest p = 1.27 × 10(-51 withstood multiple-testing correction in the second stage and modulated CYP27A1 gene expression. Additionally, we show that C9orf72 appears to be the only gene in the 9p21.2 locus that is regulated in cis, showing the potential of this approach in identifying causative genes in association loci in ALS. This study has identified candidate genes for sporadic ALS, most notably CYP27A1. Mutations in CYP27A1 are causal to cerebrotendinous xanthomatosis which can present as a clinical mimic of ALS with progressive upper motor neuron loss, making it a plausible
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Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series
Liang, X. S.
2017-12-01
Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming
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Causal ubiquity in quantum physics a superluminal and local-causal physical ontology
Neelamkavil, Raphael
2014-01-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly non-causal processes, something exists processually in extension-motion, between the causal and the non-causal. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That
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Directory of Open Access Journals (Sweden)
Cohn Zachary A
2007-06-01
Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.
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Encoding dependence in Bayesian causal networks
Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...
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Directory of Open Access Journals (Sweden)
Ämin Baumeler
2017-07-01
Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.
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D'Ariano, Giacomo Mauro
2018-07-13
Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).
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Directory of Open Access Journals (Sweden)
Yinping Jiao
2018-01-01
Full Text Available Sorghum (Sorghum bicolor Moench, L. plant accumulates copious layers of epi-cuticular wax (EW on its aerial surfaces, to a greater extent than most other crops. EW provides a vapor barrier that reduces water loss, and is therefore considered to be a major determinant of sorghum's drought tolerance. However, little is known about the genes responsible for wax accumulation in sorghum. We isolated two allelic mutants, bloomless40-1 (bm40-1 and bm40-2, from a mutant library constructed from ethyl methane sulfonate (EMS treated seeds of an inbred, BTx623. Both mutants were nearly devoid of the EW layer. Each bm mutant was crossed to the un-mutated BTx623 to generated F2 populations that segregated for the bm phenotype. Genomic DNA from 20 bm F2 plants from each population was bulked for whole genome sequencing. A single gene, Sobic.001G228100, encoding a GDSL-like lipase/acylhydrolase, had unique homozygous mutations in each bulked F2 population. Mutant bm40-1 harbored a missense mutation in the gene, whereas bm40-2 had a splice donor site mutation. Our findings thus provide strong evidence that mutation in this GDSL-like lipase gene causes the bm phenotype, and further demonstrate that this approach of sequencing two independent allelic mutant populations is an efficient method for identifying causal mutations. Combined with allelic mutants, MutMap provides powerful method to identify all causal genes for the large collection of bm mutants in sorghum, which will provide insight into how sorghum plants accumulate such abundant EW on their aerial surface. This knowledge may facilitate the development of tools for engineering drought-tolerant crops with reduced water loss.
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Rothammer, Sophie; Kunz, Elisabeth; Seichter, Doris; Krebs, Stefan; Wassertheurer, Martina; Fries, Ruedi; Brem, Gottfried; Medugorac, Ivica
2017-10-05
Cases of albinism have been reported in several species including cattle. So far, research has identified many genes that are involved in this eye-catching phenotype. Thus, when two paternal Braunvieh half-sibs with oculocutaneous albinism were detected on a private farm, we were interested in knowing whether their phenotype was caused by an already known gene/mutation. Analysis of genotyping data (50K) of the two albino individuals, their mothers and five other relatives identified a 47.61-Mb candidate haplotype on Bos taurus chromosome BTA20. Subsequent comparisons of the sequence of this haplotype with sequence data from four Braunvieh sires and the Aurochs genome identified two possible candidate causal mutations at positions 39,829,806 bp (G/A; R45Q) and 39,864,148 bp (C/T; T444I) that were absent in 1682 animals from various bovine breeds included in the 1000 bull genomes project. Both polymorphisms represent coding variants in the SLC45A2 gene, for which the human equivalent harbors numerous variants associated with oculocutaneous albinism type 4. We demonstrate an association of R45Q and T444I with the albino phenotype by targeted genotyping. Although the candidate gene SLC45A2 is known to be involved in albinism in different species, to date in cattle only mutations in the TYR and MITF genes were reported to be associated with albinism or albinism-like phenotypes. Thus, our study extends the list of genes that are associated with bovine albinism. However, further research and more samples from related animals are needed to elucidate if only one of these two single nucleotide polymorphisms or the combination of both is the actual causal variant.
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Lee, Dong-Gi; Shin, Hyunjung
2017-05-18
Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.
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International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Sanchez, Miguel
2005-01-01
Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R 2 (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries
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Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype
Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.
2016-01-01
Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680
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A quantum causal discovery algorithm
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
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Rice Transcriptome Analysis to Identify Possible Herbicide Quinclorac Detoxification Genes
Directory of Open Access Journals (Sweden)
Wenying eXu
2015-09-01
Full Text Available Quinclorac is a highly selective auxin-type herbicide, and is widely used in the effective control of barnyard grass in paddy rice fields, improving the world’s rice yield. The herbicide mode of action of quinclorac has been proposed and hormone interactions affect quinclorac signaling. Because of widespread use, quinclorac may be transported outside rice fields with the drainage waters, leading to soil and water pollution and environmental health problems.In this study, we used 57K Affymetrix rice whole-genome array to identify quinclorac signaling response genes to study the molecular mechanisms of action and detoxification of quinclorac in rice plants. Overall, 637 probe sets were identified with differential expression levels under either 6 or 24 h of quinclorac treatment. Auxin-related genes such as GH3 and OsIAAs responded to quinclorac treatment. Gene Ontology analysis showed that genes of detoxification-related family genes were significantly enriched, including cytochrome P450, GST, UGT, and ABC and drug transporter genes. Moreover, real-time RT-PCR analysis showed that top candidate P450 families such as CYP81, CYP709C and CYP72A genes were universally induced by different herbicides. Some Arabidopsis genes for the same P450 family were up-regulated under quinclorac treatment.We conduct rice whole-genome GeneChip analysis and the first global identification of quinclorac response genes. This work may provide potential markers for detoxification of quinclorac and biomonitors of environmental chemical pollution.
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Nakayama, A.; Nakaoka, H.; Yamamoto, K.; Sakiyama, M.; Shaukat, A.; Toyoda, Y.; Okada, Y.; Kamatani, Y.; Nakamura, T.; Takada, T.; Inoue, K.; Yasujima, T.; Yuasa, H.; Shirahama, Y.; Nakashima, H.; Shimizu, S.; Higashino, T.; Kawamura, Y.; Ogata, H.; Kawaguchi, M.; Ohkawa, Y.; Danjoh, I.; Tokumasu, A.; Ooyama, K.; Ito, T.; Kondo, T.; Wakai, K.; Stiburkova, B.; Pavelka, K.; Stamp, L.K.; Dalbeth, N.; Sakurai, Y.; Suzuki, H; Hosoyamada, M.; Fujimori, S.; Yokoo, T.; Hosoya, T.; Inoue, I.; Takahashi, A.; Kubo, M.; Ooyama, H.; Shimizu, T.; Ichida, K.; Shinomiya, N.; Merriman, T.R.; Matsuo, H.; Andres, M; Joosten, L.A.; Janssen, M.C.H.; Jansen, T.L.; Liote, F.; Radstake, T.R.; Riches, P.L.; So, A.; Tauches, A.K.
2017-01-01
OBJECTIVE: A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. METHODS: Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were
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Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.
Bonnefond, Amélie; Philippe, Julien; Durand, Emmanuelle; Dechaume, Aurélie; Huyvaert, Marlène; Montagne, Louise; Marre, Michel; Balkau, Beverley; Fajardy, Isabelle; Vambergue, Anne; Vatin, Vincent; Delplanque, Jérôme; Le Guilcher, David; De Graeve, Franck; Lecoeur, Cécile; Sand, Olivier; Vaxillaire, Martine; Froguel, Philippe
2012-01-01
Maturity-onset of the young (MODY) is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X). Here, we aimed to use whole-exome sequencing (WES) in a four-generation MODY-X family to identify a new susceptibility gene for MODY. WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing) was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay) of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130) present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11) co-segregated with diabetes in the family (with a LOD-score of 3.68). No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. Beyond neonatal diabetes mellitus (NDM), KCNJ11 is also a MODY gene ('MODY13'), confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS). Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.
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Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.
Directory of Open Access Journals (Sweden)
Amélie Bonnefond
Full Text Available BACKGROUND: Maturity-onset of the young (MODY is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X. Here, we aimed to use whole-exome sequencing (WES in a four-generation MODY-X family to identify a new susceptibility gene for MODY. METHODOLOGY: WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. PRINCIPAL FINDINGS: By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130 present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11 co-segregated with diabetes in the family (with a LOD-score of 3.68. No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. CONCLUSIONS/SIGNIFICANCE: Beyond neonatal diabetes mellitus (NDM, KCNJ11 is also a MODY gene ('MODY13', confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS. Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.
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Discrete causal theory emergent spacetime and the causal metric hypothesis
Dribus, Benjamin F
2017-01-01
This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.
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Beyond differential expression: the quest for causal mutations and effector molecules
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Hudson Nicholas J
2012-07-01
Full Text Available Abstract High throughput gene expression technologies are a popular choice for researchers seeking molecular or systems-level explanations of biological phenomena. Nevertheless, there has been a groundswell of opinion that these approaches have not lived up to the hype because the interpretation of the data has lagged behind its generation. In our view a major problem has been an over-reliance on isolated lists of differentially expressed (DE genes which – by simply comparing genes to themselves – have the pitfall of taking molecular information out of context. Numerous scientists have emphasised the need for better context. This can be achieved through holistic measurements of differential connectivity in addition to, or in replacement, of DE. However, many scientists continue to use isolated lists of DE genes as the major source of input data for common readily available analytical tools. Focussing this opinion article on our own research in skeletal muscle, we outline our resolutions to these problems – particularly a universally powerful way of quantifying differential connectivity. With a well designed experiment, it is now possible to use gene expression to identify causal mutations and the other major effector molecules with whom they cooperate, irrespective of whether they themselves are DE. We explain why, for various reasons, no other currently available experimental techniques or quantitative analyses are capable of reaching these conclusions.
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Applying causal mediation analysis to personality disorder research.
Walters, Glenn D
2018-01-01
This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Causal Analysis After Haavelmo
Heckman, James; Pinto, Rodrigo
2014-01-01
Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123
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Biological causal links on physiological and evolutionary time scales.
Karmon, Amit; Pilpel, Yitzhak
2016-04-26
Correlation does not imply causation. If two variables, say A and B, are correlated, it could be because A causes B, or that B causes A, or because a third factor affects them both. We suggest that in many cases in biology, the causal link might be bi-directional: A causes B through a fast-acting physiological process, while B causes A through a slowly accumulating evolutionary process. Furthermore, many trained biologists tend to consistently focus at first on the fast-acting direction, and overlook the slower process in the opposite direction. We analyse several examples from modern biology that demonstrate this bias (codon usage optimality and gene expression, gene duplication and genetic dispensability, stem cell division and cancer risk, and the microbiome and host metabolism) and also discuss an example from linguistics. These examples demonstrate mutual effects between the fast physiological processes and the slow evolutionary ones. We believe that building awareness of inference biases among biologists who tend to prefer one causal direction over another could improve scientific reasoning.
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Entanglement, holography and causal diamonds
de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.
2016-08-01
We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
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Entanglement, holography and causal diamonds
Energy Technology Data Exchange (ETDEWEB)
Boer, Jan de [Institute of Physics, Universiteit van Amsterdam,Science Park 904, 1090 GL Amsterdam (Netherlands); Haehl, Felix M. [Centre for Particle Theory & Department of Mathematical Sciences, Durham University,South Road, Durham DH1 3LE (United Kingdom); Heller, Michal P.; Myers, Robert C. [Perimeter Institute for Theoretical Physics,31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada)
2016-08-29
We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
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Gene networks specific for innate immunity define post-traumatic stress disorder.
Breen, M S; Maihofer, A X; Glatt, S J; Tylee, D S; Chandler, S D; Tsuang, M T; Risbrough, V B; Baker, D G; O'Connor, D T; Nievergelt, C M; Woelk, C H
2015-12-01
The molecular factors involved in the development of Post-Traumatic Stress Disorder (PTSD) remain poorly understood. Previous transcriptomic studies investigating the mechanisms of PTSD apply targeted approaches to identify individual genes under a cross-sectional framework lack a holistic view of the behaviours and properties of these genes at the system-level. Here we sought to apply an unsupervised gene-network based approach to a prospective experimental design using whole-transcriptome RNA-Seq gene expression from peripheral blood leukocytes of U.S. Marines (N=188), obtained both pre- and post-deployment to conflict zones. We identified discrete groups of co-regulated genes (i.e., co-expression modules) and tested them for association to PTSD. We identified one module at both pre- and post-deployment containing putative causal signatures for PTSD development displaying an over-expression of genes enriched for functions of innate-immune response and interferon signalling (Type-I and Type-II). Importantly, these results were replicated in a second non-overlapping independent dataset of U.S. Marines (N=96), further outlining the role of innate immune and interferon signalling genes within co-expression modules to explain at least part of the causal pathophysiology for PTSD development. A second module, consequential of trauma exposure, contained PTSD resiliency signatures and an over-expression of genes involved in hemostasis and wound responsiveness suggesting that chronic levels of stress impair proper wound healing during/after exposure to the battlefield while highlighting the role of the hemostatic system as a clinical indicator of chronic-based stress. These findings provide novel insights for early preventative measures and advanced PTSD detection, which may lead to interventions that delay or perhaps abrogate the development of PTSD.
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The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes
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Xinguo Lu
2018-01-01
Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.
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Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia
2015-06-01
To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.
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A search engine to identify pathway genes from expression data on multiple organisms
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Zambon Alexander C
2007-05-01
Full Text Available Abstract Background The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function. Results We developed a search engine, the Multiple-Species Gene Recommender (MSGR, which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana, and Helicobacter pylori. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway. Conclusion The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved.
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The discourse of causal explanations in school science
Slater, Tammy Jayne Anne
Researchers and educators working from a systemic functional linguistic perspective have provided a body of work on science discourse which offers an excellent starting point for examining the linguistic aspects of the development of causal discourse in school science, discourse which Derewianka (1995) claimed is critical to success in secondary school. No work has yet described the development of causal language by identifying the linguistic features present in oral discourse or by comparing the causal discourse of native and non-native (ESL) speakers of English. The current research responds to this gap by examining the oral discourse collected from ESL and non-ESL students at the primary and high school grades. Specifically, it asks the following questions: (1) How do the teachers and students in these four contexts develop causal explanations and their relevant taxonomies through classroom interactions? (2) What are the causal discourse features being used by the students in these four contexts to construct oral causal explanations? The findings of the social practice analysis showed that the teachers in the four contexts differed in their approaches to teaching, with the primary school mainstream teacher focusing largely on the hands-on practice , the primary school ESL teacher moving from practice to theory, the high school mainstream teacher moving from theory to practice, and the high school ESL teacher relying primarily on theory. The findings from the quantitative, small corpus approach suggest that the developmental path of cause which has been identified in the writing of experts shows up not only in written texts but also in the oral texts which learners construct. Moreover, this move appears when the discourse of high school ESL and non-ESL students is compared, suggesting a developmental progression in the acquisition of these features by these students. The findings also reveal that the knowledge constructed, as shown by the concept maps created
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Gene expression profile identifies potential biomarkers for human intervertebral disc degeneration.
Guo, Wei; Zhang, Bin; Li, Yan; Duan, Hui-Quan; Sun, Chao; Xu, Yun-Qiang; Feng, Shi-Qing
2017-12-01
The present study aimed to reveal the potential genes associated with the pathogenesis of intervertebral disc degeneration (IDD) by analyzing microarray data using bioinformatics. Gene expression profiles of two regions of the intervertebral disc were compared between patients with IDD and controls. GSE70362 containing two groups of gene expression profiles, 16 nucleus pulposus (NP) samples from patients with IDD and 8 from controls, and 16 annulus fibrosus (AF) samples from patients with IDD and 8 from controls, was downloaded from the Gene Expression Omnibus database. A total of 93 and 114 differentially expressed genes (DEGs) were identified in NP and AF samples, respectively, using a limma software package for the R programming environment. Gene Ontology (GO) function enrichment analysis was performed to identify the associated biological functions of DEGs in IDD, which indicated that the DEGs may be involved in various processes, including cell adhesion, biological adhesion and extracellular matrix organization. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in focal adhesion and the p53 signaling pathway. Further analysis revealed that there were 35 common DEGs observed between the two regions (NP and AF), which may be further regulated by 6 clusters of microRNAs (miRNAs) retrieved with WebGestalt. The genes in the DEG‑miRNA regulatory network were annotated using GO function and KEGG pathway enrichment analysis, among which extracellular matrix organization was the most significant disrupted biological process and focal adhesion was the most significant dysregulated pathway. In addition, the result of protein‑protein interaction network modules demonstrated the involvement of inflammatory cytokine interferon signaling in IDD. These findings may not only advance the understanding of the pathogenesis of IDD, but also identify novel potential
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Peñagaricano, Francisco; Valente, Bruno D; Steibel, Juan P; Bates, Ronald O; Ernst, Catherine W; Khatib, Hasan; Rosa, Guilherme J M
2015-09-16
Joint modeling and analysis of phenotypic, genotypic and transcriptomic data have the potential to uncover the genetic control of gene activity and phenotypic variation, as well as shed light on the manner and extent of connectedness among these variables. Current studies mainly report associations, i.e. undirected connections among variables without causal interpretation. Knowledge regarding causal relationships among genes and phenotypes can be used to predict the behavior of complex systems, as well as to optimize management practices and selection strategies. Here, we performed a multistep procedure for inferring causal networks underlying carcass fat deposition and muscularity in pigs using multi-omics data obtained from an F2 Duroc x Pietrain resource pig population. We initially explored marginal associations between genotypes and phenotypic and expression traits through whole-genome scans, and then, in genomic regions with multiple significant hits, we assessed gene-phenotype network reconstruction using causal structural learning algorithms. One genomic region on SSC6 showed significant associations with three relevant phenotypes, off-midline10th-rib backfat thickness, loin muscle weight, and average intramuscular fat percentage, and also with the expression of seven genes, including ZNF24, SSX2IP, and AKR7A2. The inferred network indicated that the genotype affects the three phenotypes mainly through the expression of several genes. Among the phenotypes, fat deposition traits negatively affected loin muscle weight. Our findings shed light on the antagonist relationship between carcass fat deposition and lean meat content in pigs. In addition, the procedure described in this study has the potential to unravel gene-phenotype networks underlying complex phenotypes.
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Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs
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Ye Zhi-Qiang
2011-08-01
Full Text Available Abstract Background Differential coexpression analysis (DCEA is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links. Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.
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A Theory of Causal Learning in Children: Causal Maps and Bayes Nets
Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…
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Scalar field Green functions on causal sets
International Nuclear Information System (INIS)
Nomaan Ahmed, S; Surya, Sumati; Dowker, Fay
2017-01-01
We examine the validity and scope of Johnston’s models for scalar field retarded Green functions on causal sets in 2 and 4 dimensions. As in the continuum, the massive Green function can be obtained from the massless one, and hence the key task in causal set theory is to first identify the massless Green function. We propose that the 2d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2-dimensional spacetime. We explicitly demonstrate that this is indeed the case in a Riemann normal neighbourhood. In 4d the model can again be used to provide a Green function for the massive scalar field in a Riemann normal neighbourhood which we compare to Bunch and Parker’s continuum Green function. We find that the same prescription can also be used for de Sitter spacetime and the conformally flat patch of anti-de Sitter spacetime. Our analysis then allows us to suggest a generalisation of Johnston’s model for the Green function for a causal set approximated by 3-dimensional flat spacetime. (paper)
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Directory of Open Access Journals (Sweden)
Andrew Williams
2015-12-01
Full Text Available Background: The presence of diverse types of nanomaterials (NMs in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2, carbon black (CB or carbon nanotubes (CNTs to determine the disease significance of these data-driven gene sets.Results: Biclusters representing inflammation (chemokine activity, DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032. The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles.Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several
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Energy Technology Data Exchange (ETDEWEB)
Salazar-Ferrer, P
1995-06-01
In complex industrial process control, causal reasoning appears as a major component in operators` cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs.
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Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.
Weed, Douglas L
2018-05-01
The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.
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ICan: an integrated co-alteration network to identify ovarian cancer-related genes.
Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan
2015-01-01
Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.
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DEFF Research Database (Denmark)
Husemoen, L. L. N.; Skaaby, T.; Martinussen, Torben
2014-01-01
Background/Objectives: The aim was to examine the causal effect of vitamin D on serum adiponectin using a multiple instrument Mendelian randomization approach. Subjects/Methods: Serum 25-hydroxy vitamin D (25(OH)D) and serum total or high molecular weight (HMW) adiponectin were measured in two...... doubling of 25(OH)D was 4.78, 95% CI: 1.96, 7.68, Pvitamin D-binding protein gene and the filaggrin gene as instrumental variables, the causal effect in % was estimated to 61.46, 95% CI: 17.51, 120.28, P=0.003 higher adiponectin per doubling of 25(OH)D. In the MONICA10...... effect estimate in % per doubling of 25(OH)D was 37.13, 95% CI:-3.67, 95.20, P=0.080). Conclusions: The results indicate a possible causal association between serum 25(OH)D and total adiponectin. However, the association was not replicated for HMW adiponectin. Thus, further studies are needed to confirm...
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Tzeremes, Panayiotis
2018-02-01
This study is the first attempt to investigate the relationship between CO 2 emissions, energy consumption, and economic growth at a state level, for the 50 US states, through a time-varying causality approach using annual data over the periods 1960-2010. The time-varying causality test facilitates the better understanding of the causal relationship between the covariates owing to the fact that it might identify causalities when the time-constant hypothesis is rejected. Our findings indicate the existence of a time-varying causality at the state level. Specifically, the results probe eight bidirectional time-varying causalities between energy consumption and CO 2 emission, six cases of two-way time-varying causalities between economic growth and energy consumption, and five bidirectional time-varying causalities between economic growth and CO 2 emission. Moreover, we examine the traditional environmental Kuznets curve hypothesis for the states. Notably, our results do not endorse the validity of the EKC, albeit the majority of states support an inverted N-shaped relationship. Lastly, we can identify multiple policy implications based on the empirical results.
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A graph-search framework for associating gene identifiers with documents
Directory of Open Access Journals (Sweden)
Cohen William W
2006-10-01
Full Text Available Abstract Background One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation of this problem suitable for semi-automated systems, in which each article is associated with a ranked list of possible gene identifiers, and experimentally compare methods for solving this geneId ranking problem. In addition to baseline approaches based on combining named entity recognition (NER systems with a "soft dictionary" of gene synonyms, we evaluate a graph-based method which combines the outputs of multiple NER systems, as well as other sources of information, and a learning method for reranking the output of the graph-based method. Results We show that named entity recognition (NER systems with similar F-measure performance can have significantly different performance when used with a soft dictionary for geneId-ranking. The graph-based approach can outperform any of its component NER systems, even without learning, and learning can further improve the performance of the graph-based ranking approach. Conclusion The utility of a named entity recognition (NER system for geneId-finding may not be accurately predicted by its entity-level F1 performance, the most common performance measure. GeneId-ranking systems are best implemented by combining several NER systems. With appropriate combination methods, usefully accurate geneId-ranking systems can be constructed based on easily-available resources, without resorting to problem-specific, engineered components.
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Identifying essential genes in bacterial metabolic networks with machine learning methods
2010-01-01
Background Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective. Results We developed a machine learning technique to identify essential genes using the experimental data of genome-wide knock-out screens from one bacterial organism to infer essential genes of another related bacterial organism. We used a broad variety of topological features, sequence characteristics and co-expression properties potentially associated with essentiality, such as flux deviations, centrality, codon frequencies of the sequences, co-regulation and phyletic retention. An organism-wise cross-validation on bacterial species yielded reliable results with good accuracies (area under the receiver-operator-curve of 75% - 81%). Finally, it was applied to drug target predictions for Salmonella typhimurium. We compared our predictions to the viability of experimental knock-outs of S. typhimurium and identified 35 enzymes, which are highly relevant to be considered as potential drug targets. Specifically, we detected promising drug targets in the non-mevalonate pathway. Conclusions Using elaborated features characterizing network topology, sequence information and microarray data enables to predict essential genes from a bacterial reference organism to a related query organism without any knowledge about the essentiality of genes of the query organism. In general, such a method is beneficial for inferring drug targets when experimental data about genome-wide knockout screens is not available for the investigated organism. PMID:20438628
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Network and system diagrams revisited: Satisfying CEA requirements for causality analysis
International Nuclear Information System (INIS)
Perdicoulis, Anastassios; Piper, Jake
2008-01-01
Published guidelines for Cumulative Effects Assessment (CEA) have called for the identification of cause-and-effect relationships, or causality, challenging researchers to identify methods that can possibly meet CEA's specific requirements. Together with an outline of these requirements from CEA key literature, the various definitions of cumulative effects point to the direction of a method for causality analysis that is visually-oriented and qualitative. This article consequently revisits network and system diagrams, resolves their reported shortcomings, and extends their capabilities with causal loop diagramming methodology. The application of the resulting composite causality analysis method to three Environmental Impact Assessment (EIA) case studies appears to satisfy the specific requirements of CEA regarding causality. Three 'moments' are envisaged for the use of the proposed method: during the scoping stage, during the assessment process, and during the stakeholder participation process
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Neural Correlates of Causal Power Judgments
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Denise Dellarosa Cummins
2014-12-01
Full Text Available Causal inference is a fundamental component of cognition and perception. Probabilistic theories of causal judgment (most notably causal Bayes networks derive causal judgments using metrics that integrate contingency information. But human estimates typically diverge from these normative predictions. This is because human causal power judgments are typically strongly influenced by beliefs concerning underlying causal mechanisms, and because of the way knowledge is retrieved from human memory during the judgment process. Neuroimaging studies indicate that the brain distinguishes causal events from mere covariation, and between perceived and inferred causality. Areas involved in error prediction are also activated, implying automatic activation of possible exception cases during causal decision-making.
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Directory of Open Access Journals (Sweden)
Thomas eWidlok
2014-11-01
Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.
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Zhang, Q; Baldwin, V J; Acland, G M; Parshall, C J; Haskel, J; Aguirre, G D; Ray, K
1999-01-01
Photoreceptor dysplasia (pd) is one of a group of at least six distinct autosomal and one X-linked retinal disorders identified in dogs which are collectively known as progressive retinal atrophy (PRA). It is an early onset retinal disease identified in miniature schnauzer dogs, and pedigree analysis and breeding studies have established autosomal recessive inheritance of the disease. Using a gene-based approach, a number of retina-expressed genes, including some members of the phototransduction pathway, have been causally implicated in retinal diseases of humans and other animals. Here we examined seven such potential candidate genes (opsin, RDS/peripherin, ROM1, rod cGMP-gated cation channel alpha-subunit, and three subunits of transducin) for their causal association with the pd locus by testing segregation of intragenic markers with the disease locus, or, in the absence of informative polymorphisms, sequencing of the coding regions of the genes. Based on these results, we have conclusively excluded four photoreceptor-specific genes as candidates for pd by linkage analysis. For three other photoreceptor-specific genes, we did not find any mutation in the coding sequences of the genes and have excluded them provisionally. Formal exclusion would require investigation of the levels of expression of the candidate genes in pd-affected dogs relative to age-matched controls. At present we are building suitable informative pedigrees for the disease locus with a sufficient number of meiosis to be useful for genomewide screening. This should identify markers linked to the disease locus and eventually permit progress toward the identification of the photoreceptor dysplasia gene and the disease-causing mutation.
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Inference of Causal Relationships between Biomarkers and Outcomes in High Dimensions
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Felix Agakov
2011-12-01
Full Text Available We describe a unified computational framework for learning causal dependencies between genotypes, biomarkers, and phenotypic outcomes from large-scale data. In contrast to previous studies, our framework allows for noisy measurements, hidden confounders, missing data, and pleiotropic effects of genotypes on outcomes. The method exploits the use of genotypes as “instrumental variables” to infer causal associations between phenotypic biomarkers and outcomes, without requiring the assumption that genotypic effects are mediated only through the observed biomarkers. The framework builds on sparse linear methods developed in statistics and machine learning and modified here for inferring structures of richer networks with latent variables. Where the biomarkers are gene transcripts, the method can be used for fine mapping of quantitative trait loci (QTLs detected in genetic linkage studies. To demonstrate our method, we examined effects of gene transcript levels in the liver on plasma HDL cholesterol levels in a sample of 260 mice from a heterogeneous stock.
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Causal boundary for strongly causal spacetimes: Pt. 1
International Nuclear Information System (INIS)
Szabados, L.B.
1989-01-01
In a previous paper an analysis of the general structure of the causal boundary constructions and a new explicit identification rule, built up from elementary TIP-TIF gluings, were presented. In the present paper we complete our identification by incorporating TIP-TIP and TIF-TIF gluings as well. An asymptotic causality condition is found which, for physically important cases, ensures the uniqueness of the endpoints of the non-spacelike curves in the completed spacetime. (author)
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Structural Equations and Causal Explanations: Some Challenges for Causal SEM
Markus, Keith A.
2010-01-01
One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…
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Directory of Open Access Journals (Sweden)
Hong Zhu
Full Text Available Rheumatoid arthritis (RA is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations.Gene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects. For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected 'highly verified' genes were measured by ELISA among our in-house RA cases and controls.A total of 221 RA-associated genes were newly identified by gene-based association study, including 71'overlapped', 76 'European-specific' and 74 'Asian-specific' genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 'overlapped' (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA, 5 'European-specific' (PHTF1, RPS18, BAK1, TNFRSF14, SUOX and 4 'Asian-specific' (RNASET2, HFE, BTN2A2, MAPK13 genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02 and HLA-DMA (P value = 4.70E-02 in plasma were significantly different in our in-house samples.Our study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA
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THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...
CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc
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Finding the Cause: Verbal Framing Helps Children Extract Causal Evidence Embedded in a Complex Scene
Butler, Lucas P.; Markman, Ellen M.
2012-01-01
In making causal inferences, children must both identify a causal problem and selectively attend to meaningful evidence. Four experiments demonstrate that verbally framing an event ("Which animals make Lion laugh?") helps 4-year-olds extract evidence from a complex scene to make accurate causal inferences. Whereas framing was unnecessary when…
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Spatial Causality. An application to the Deforestation Process in Bolivia
Directory of Open Access Journals (Sweden)
Javier Aliaga
2011-01-01
Full Text Available This paper analyses the causes of deforestation for a representative set of Bolivian municipalities. The literature on environmental economics insists on the importance of physical and social factors. We focus on the last group of variables. Our objective is to identify causal mechanisms between these factors of risk and the problem of deforestation. To this end, we present a testing strategy for spatial causality, based on a sequence of Lagrange Multipliers. The results that we obtain for the Bolivian case confirm only partially the traditional view of the problem of deforestation. Indeed, we only find unequivocal signs of causality in relation to the structure of property rights.
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Identifying Candidate Reprogramming Genes in Mouse Induced Pluripotent Stem Cells.
Gao, Fang; Li, Jingyu; Zhang, Heng; Yang, Xu; An, Tiezhu
2017-08-01
Factor-based induced reprogramming approaches have tremendous potential for human regenerative medicine, but the efficiencies of these approaches are still low. In this study, we analyzed the global transcriptional profiles of mouse induced pluripotent stem cells (miPSCs) and mouse embryonic stem cells (mESCs) from seven different labs and present here the first successful clustering according to cell type, not by lab of origin. We identified 2131 different expression genes (DEs) as candidate pluripotency-associated genes by comparing mESCs/miPSCs with somatic cells and 720 DEs between miPSCs and mESCs. Interestingly, there was a significant overlap between the two DE sets. Therefore, we defined the overlap DEs as "consensus DEs" including 313 miPSC-specific genes expressed at a higher level in miPSCs versus mESCs and 184 mESC-specific genes in total and reasoned that these may contribute to the differences in pluripotency between mESCs and miPSCs. A classification of "consensus DEs" according to their different expression levels between somatic cells and mESCs/miPSCs shows that 86% of the miPSC-specific genes are more highly expressed in somatic cells, while 73% of mESC-specific genes are highly expressed in mESCs/miPSCs, indicating that the miPSCs have not efficiently silenced the expression pattern of the somatic cells from which they are derived and failed to completely induce the genes with high expression levels in mESCs. We further revealed a strong correlation between oocyte-enriched factors and insufficiently induced mESC-specific genes and identified 11 hub genes via network analysis. In light of these findings, we postulated that these key hub genes might not only drive somatic cell nuclear transfer (SCNT) reprogramming but also augment the efficiency and quality of miPSC reprogramming.
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Directory of Open Access Journals (Sweden)
Paules Richard S
2007-11-01
Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying
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Exome sequencing identifies three novel candidate genes implicated in intellectual disability.
Directory of Open Access Journals (Sweden)
Zehra Agha
Full Text Available Intellectual disability (ID is a major health problem mostly with an unknown etiology. Recently exome sequencing of individuals with ID identified novel genes implicated in the disease. Therefore the purpose of the present study was to identify the genetic cause of ID in one syndromic and two non-syndromic Pakistani families. Whole exome of three ID probands was sequenced. Missense variations in two plausible novel genes implicated in autosomal recessive ID were identified: lysine (K-specific methyltransferase 2B (KMT2B, zinc finger protein 589 (ZNF589, as well as hedgehog acyltransferase (HHAT with a de novo mutation with autosomal dominant mode of inheritance. The KMT2B recessive variant is the first report of recessive Kleefstra syndrome-like phenotype. Identification of plausible causative mutations for two recessive and a dominant type of ID, in genes not previously implicated in disease, underscores the large genetic heterogeneity of ID. These results also support the viewpoint that large number of ID genes converge on limited number of common networks i.e. ZNF589 belongs to KRAB-domain zinc-finger proteins previously implicated in ID, HHAT is predicted to affect sonic hedgehog, which is involved in several disorders with ID, KMT2B associated with syndromic ID fits the epigenetic module underlying the Kleefstra syndromic spectrum. The association of these novel genes in three different Pakistani ID families highlights the importance of screening these genes in more families with similar phenotypes from different populations to confirm the involvement of these genes in pathogenesis of ID.
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Causality discovery technology
Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.
2012-11-01
Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.
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Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.
Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella
2018-01-06
Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.
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Rehder, Bob
2017-01-01
This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…
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Identifying and Analyzing Novel Epilepsy-Related Genes Using Random Walk with Restart Algorithm
Directory of Open Access Journals (Sweden)
Wei Guo
2017-01-01
Full Text Available As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients’ personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases.
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The Use of Causal Mapping in the Design of Sustainability Performance Measurement Systems
DEFF Research Database (Denmark)
Parisi, Cristiana
2013-01-01
organisations’ strategic performance measurement systems (SPMSs). This study’s main contribution is the triangulation of multiple qualitative methods to enhance the reliability of causal maps. This innovative approach supports the use of causal mapping to extract managerial tacit knowledge in order to identify...
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A 6-gene signature identifies four molecular subgroups of neuroblastoma
2011-01-01
Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432
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Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei
2012-07-01
In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.
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Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G
2016-04-05
Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.
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Liu, Shao-Hsien; Ulbricht, Christine M; Chrysanthopoulou, Stavroula A; Lapane, Kate L
2016-07-20
Causal mediation analysis is often used to understand the impact of variables along the causal pathway of an occurrence relation. How well studies apply and report the elements of causal mediation analysis remains unknown. We systematically reviewed epidemiological studies published in 2015 that employed causal mediation analysis to estimate direct and indirect effects of observed associations between an exposure on an outcome. We identified potential epidemiological studies through conducting a citation search within Web of Science and a keyword search within PubMed. Two reviewers independently screened studies for eligibility. For eligible studies, one reviewer performed data extraction, and a senior epidemiologist confirmed the extracted information. Empirical application and methodological details of the technique were extracted and summarized. Thirteen studies were eligible for data extraction. While the majority of studies reported and identified the effects of measures, most studies lacked sufficient details on the extent to which identifiability assumptions were satisfied. Although most studies addressed issues of unmeasured confounders either from empirical approaches or sensitivity analyses, the majority did not examine the potential bias arising from the measurement error of the mediator. Some studies allowed for exposure-mediator interaction and only a few presented results from models both with and without interactions. Power calculations were scarce. Reporting of causal mediation analysis is varied and suboptimal. Given that the application of causal mediation analysis will likely continue to increase, developing standards of reporting of causal mediation analysis in epidemiological research would be prudent.
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Novel Myopia Genes and Pathways Identified From Syndromic Forms of Myopia
Loughman, James; Wildsoet, Christine F.; Williams, Cathy; Guggenheim, Jeremy A.
2018-01-01
Purpose To test the hypothesis that genes known to cause clinical syndromes featuring myopia also harbor polymorphisms contributing to nonsyndromic refractive errors. Methods Clinical phenotypes and syndromes that have refractive errors as a recognized feature were identified using the Online Mendelian Inheritance in Man (OMIM) database. One hundred fifty-four unique causative genes were identified, of which 119 were specifically linked with myopia and 114 represented syndromic myopia (i.e., myopia and at least one other clinical feature). Myopia was the only refractive error listed for 98 genes and hyperopia and the only refractive error noted for 28 genes, with the remaining 28 genes linked to phenotypes with multiple forms of refractive error. Pathway analysis was carried out to find biological processes overrepresented within these sets of genes. Genetic variants located within 50 kb of the 119 myopia-related genes were evaluated for involvement in refractive error by analysis of summary statistics from genome-wide association studies (GWAS) conducted by the CREAM Consortium and 23andMe, using both single-marker and gene-based tests. Results Pathway analysis identified several biological processes already implicated in refractive error development through prior GWAS analyses and animal studies, including extracellular matrix remodeling, focal adhesion, and axon guidance, supporting the research hypothesis. Novel pathways also implicated in myopia development included mannosylation, glycosylation, lens development, gliogenesis, and Schwann cell differentiation. Hyperopia was found to be linked to a different pattern of biological processes, mostly related to organogenesis. Comparison with GWAS findings further confirmed that syndromic myopia genes were enriched for genetic variants that influence refractive errors in the general population. Gene-based analyses implicated 21 novel candidate myopia genes (ADAMTS18, ADAMTS2, ADAMTSL4, AGK, ALDH18A1, ASXL1, COL4A1
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Structure and Strength in Causal Induction
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2005-01-01
We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…
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Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung
2018-03-19
With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.
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Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B
2017-06-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
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Regression to Causality : Regression-style presentation influences causal attribution
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
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Measures of Coupling between Neural Populations Based on Granger Causality Principle.
Kaminski, Maciej; Brzezicka, Aneta; Kaminski, Jan; Blinowska, Katarzyna J
2016-01-01
This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality) principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a "weak node." Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF) supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.
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Whole-Genome Sequencing of Sordaria macrospora Mutants Identifies Developmental Genes.
Nowrousian, Minou; Teichert, Ines; Masloff, Sandra; Kück, Ulrich
2012-02-01
The study of mutants to elucidate gene functions has a long and successful history; however, to discover causative mutations in mutants that were generated by random mutagenesis often takes years of laboratory work and requires previously generated genetic and/or physical markers, or resources like DNA libraries for complementation. Here, we present an alternative method to identify defective genes in developmental mutants of the filamentous fungus Sordaria macrospora through Illumina/Solexa whole-genome sequencing. We sequenced pooled DNA from progeny of crosses of three mutants and the wild type and were able to pinpoint the causative mutations in the mutant strains through bioinformatics analysis. One mutant is a spore color mutant, and the mutated gene encodes a melanin biosynthesis enzyme. The causative mutation is a G to A change in the first base of an intron, leading to a splice defect. The second mutant carries an allelic mutation in the pro41 gene encoding a protein essential for sexual development. In the mutant, we detected a complex pattern of deletion/rearrangements at the pro41 locus. In the third mutant, a point mutation in the stop codon of a transcription factor-encoding gene leads to the production of immature fruiting bodies. For all mutants, transformation with a wild type-copy of the affected gene restored the wild-type phenotype. Our data demonstrate that whole-genome sequencing of mutant strains is a rapid method to identify developmental genes in an organism that can be genetically crossed and where a reference genome sequence is available, even without prior mapping information.
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A general method for identifying major hybrid male sterility genes in Drosophila.
Zeng, L W; Singh, R S
1995-10-01
The genes responsible for hybrid male sterility in species crosses are usually identified by introgressing chromosome segments, monitored by visible markers, between closely related species by continuous backcrosses. This commonly used method, however, suffers from two problems. First, it relies on the availability of markers to monitor the introgressed regions and so the portion of the genome examined is limited to the marked regions. Secondly, the introgressed regions are usually large and it is impossible to tell if the effects of the introgressed regions are the result of single (or few) major genes or many minor genes (polygenes). Here we introduce a simple and general method for identifying putative major hybrid male sterility genes which is free of these problems. In this method, the actual hybrid male sterility genes (rather than markers), or tightly linked gene complexes with large effects, are selectively introgressed from one species into the background of another species by repeated backcrosses. This is performed by selectively backcrossing heterozygous (for hybrid male sterility gene or genes) females producing fertile and sterile sons in roughly equal proportions to males of either parental species. As no marker gene is required for this procedure, this method can be used with any species pairs that produce unisexual sterility. With the application of this method, a small X chromosome region of Drosophila mauritiana which produces complete hybrid male sterility (aspermic testes) in the background of D. simulans was identified. Recombination analysis reveals that this region contains a second major hybrid male sterility gene linked to the forked locus located at either 62.7 +/- 0.66 map units or at the centromere region of the X chromosome of D. mauritiana.
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Epidermal growth factor gene is a newly identified candidate gene for gout.
Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui
2016-08-10
Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67-0.88, Padjusted = 6.42 × 10(-3)). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations.
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Causality in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...
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Clustering approaches to identifying gene expression patterns from DNA microarray data.
Do, Jin Hwan; Choi, Dong-Kug
2008-04-30
The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.
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Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.
2018-01-01
Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000
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Directory of Open Access Journals (Sweden)
Malin Lando
2009-11-01
Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.
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International Nuclear Information System (INIS)
Novello, M.; Salim, J.M.; Torres, J.; Oliveira, H.P. de
1989-01-01
A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author) [pt
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Dynamics of Quantum Causal Structures
Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav
2018-01-01
It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
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Exome sequencing identifies ZNF644 mutations in high myopia.
Directory of Open Access Journals (Sweden)
Yi Shi
2011-06-01
Full Text Available Myopia is the most common ocular disorder worldwide, and high myopia in particular is one of the leading causes of blindness. Genetic factors play a critical role in the development of myopia, especially high myopia. Recently, the exome sequencing approach has been successfully used for the disease gene identification of Mendelian disorders. Here we show a successful application of exome sequencing to identify a gene for an autosomal dominant disorder, and we have identified a gene potentially responsible for high myopia in a monogenic form. We captured exomes of two affected individuals from a Han Chinese family with high myopia and performed sequencing analysis by a second-generation sequencer with a mean coverage of 30× and sufficient depth to call variants at ∼97% of each targeted exome. The shared genetic variants of these two affected individuals in the family being studied were filtered against the 1000 Genomes Project and the dbSNP131 database. A mutation A672G in zinc finger protein 644 isoform 1 (ZNF644 was identified as being related to the phenotype of this family. After we performed sequencing analysis of the exons in the ZNF644 gene in 300 sporadic cases of high myopia, we identified an additional five mutations (I587V, R680G, C699Y, 3'UTR+12 C>G, and 3'UTR+592 G>A in 11 different patients. All these mutations were absent in 600 normal controls. The ZNF644 gene was expressed in human retinal and retinal pigment epithelium (RPE. Given that ZNF644 is predicted to be a transcription factor that may regulate genes involved in eye development, mutation may cause the axial elongation of eyeball found in high myopia patients. Our results suggest that ZNF644 might be a causal gene for high myopia in a monogenic form.
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Causal inference based on counterfactuals
Directory of Open Access Journals (Sweden)
Höfler M
2005-09-01
Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.
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DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel
2017-02-01
We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.
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GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature
Directory of Open Access Journals (Sweden)
Ning Ye
2015-01-01
Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.
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The argumentative impact of causal relations
DEFF Research Database (Denmark)
Nielsen, Anne Ellerup
1996-01-01
such as causality, explanation and justification. In certain types of discourse, causal relations also imply an intentional element. This paper describes the way in which the semantic and pragmatic functions of causal markers can be accounted for in terms of linguistic and rhetorical theories of argumentation.......The semantic relations between and within utterances are marked by the use of connectors and adverbials. One type of semantic relations is causal relations expressed by causal markers such as because, therefore, so, for, etc. Some of these markers cover different types of causal relations...
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Occupational safety management: the role of causal attribution.
Gyekye, Seth Ayim
2010-12-01
The paper addresses the causal attribution theory, an old and well-established theme in social psychology which denotes the everyday, commonsense explanations that people use to explain events and the world around them. The attribution paradigm is considered one of the most appropriate analytical tools for exploratory and descriptive studies in social psychology and organizational literature. It affords the possibility of describing accident processes as objectively as possible and with as much detail as possible. Causal explanations are vital to the formal analysis of workplace hazards and accidents, as they determine how organizations act to prevent accident recurrence. Accordingly, they are regarded as fundamental and prerequisite elements for safety management policies. The paper focuses primarily on the role of causal attributions in occupational and industrial accident analyses and implementation of safety interventions. It thus serves as a review of the contribution of attribution theory to occupational and industrial accidents. It comprises six sections. The first section presents an introduction to the classic attribution theories, and the second an account of the various ways in which the attribution paradigm has been applied in organizational settings. The third and fourth sections review the literature on causal attributions and demographic and organizational variables respectively. The sources of attributional biases in social psychology and how they manifest and are identified in the causal explanations for industrial and occupational accidents are treated in the fifth section. Finally, conclusion and recommendations are presented. The recommendations are particularly important for the reduction of workplace accidents and associated costs. The paper touches on the need for unbiased causal analyses, belief in the preventability of accidents, and the imperative role of management in occupational safety management.
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Causality analysis in business performance measurement system using system dynamics methodology
Yusof, Zainuridah; Yusoff, Wan Fadzilah Wan; Maarof, Faridah
2014-07-01
One of the main components of the Balanced Scorecard (BSC) that differentiates it from any other performance measurement system (PMS) is the Strategy Map with its unidirectional causality feature. Despite its apparent popularity, criticisms on the causality have been rigorously discussed by earlier researchers. In seeking empirical evidence of causality, propositions based on the service profit chain theory were developed and tested using the econometrics analysis, Granger causality test on the 45 data points. However, the insufficiency of well-established causality models was found as only 40% of the causal linkages were supported by the data. Expert knowledge was suggested to be used in the situations of insufficiency of historical data. The Delphi method was selected and conducted in obtaining the consensus of the causality existence among the 15 selected expert persons by utilizing 3 rounds of questionnaires. Study revealed that only 20% of the propositions were not supported. The existences of bidirectional causality which demonstrate significant dynamic environmental complexity through interaction among measures were obtained from both methods. With that, a computer modeling and simulation using System Dynamics (SD) methodology was develop as an experimental platform to identify how policies impacting the business performance in such environments. The reproduction, sensitivity and extreme condition tests were conducted onto developed SD model to ensure their capability in mimic the reality, robustness and validity for causality analysis platform. This study applied a theoretical service management model within the BSC domain to a practical situation using SD methodology where very limited work has been done.
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Entropy for theories with indefinite causal structure
International Nuclear Information System (INIS)
Markes, Sonia; Hardy, Lucien
2011-01-01
Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.
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Energy consumption and economic growth: A causality analysis for Greece
International Nuclear Information System (INIS)
Tsani, Stela Z.
2010-01-01
This paper investigates the causal relationship between aggregated and disaggregated levels of energy consumption and economic growth for Greece for the period 1960-2006 through the application of a later development in the methodology of time series proposed by Toda and Yamamoto (1995). At aggregated levels of energy consumption empirical findings suggest the presence of a uni-directional causal relationship running from total energy consumption to real GDP. At disaggregated levels empirical evidence suggests that there is a bi-directional causal relationship between industrial and residential energy consumption to real GDP but this is not the case for the transport energy consumption with causal relationship being identified in neither direction. The importance of these findings lies on their policy implications and their adoption on structural policies affecting energy consumption in Greece suggesting that in order to address energy import dependence and environmental concerns without hindering economic growth emphasis should be put on the demand side and energy efficiency improvements.
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Examination of tetrahydrobiopterin pathway genes in autism.
Schnetz-Boutaud, N C; Anderson, B M; Brown, K D; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L
2009-11-01
Autism is a complex disorder with a high degree of heritability and significant phenotypic and genotypic heterogeneity. Although candidate gene studies and genome-wide screens have failed to identify major causal loci associated with autism, numerous studies have proposed association with several variations in genes in the dopaminergic and serotonergic pathways. Because tetrahydrobiopterin (BH4) is the essential cofactor in the synthesis of these two neurotransmitters, we genotyped 25 SNPs in nine genes of the BH4 pathway in a total of 403 families. Significant nominal association was detected in the gene for 6-pyruvoyl-tetrahydropterin synthase, PTS (chromosome 11), with P = 0.009; this result was not restricted to an affected male-only subset. Multilocus interaction was detected in the BH4 pathway alone, but not across the serotonin, dopamine and BH4 pathways.
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Epidermal growth factor gene is a newly identified candidate gene for gout
Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui
2016-01-01
Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295
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Causal reasoning and models of cognitive tasks for naval nuclear power plant operators
International Nuclear Information System (INIS)
Salazar-Ferrer, P.
1995-06-01
In complex industrial process control, causal reasoning appears as a major component in operators' cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs
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Causality and matter propagation in 3D spin foam quantum gravity
International Nuclear Information System (INIS)
Oriti, Daniele; Tlas, Tamer
2006-01-01
In this paper we tackle the issue of causality in quantum gravity, in the context of 3d spin foam models. We identify the correct procedure for implementing the causality/orientation dependence restriction that reduces the path integral for BF theory to that of quantum gravity in first order form. We construct explicitly the resulting causal spin foam model. We then add matter degrees of freedom to it and construct a causal spin foam model for 3d quantum gravity coupled to matter fields. Finally, we show that the corresponding spin foam amplitudes admit a natural approximation as the Feynman amplitudes of a noncommutative quantum field theory, with the appropriate Feynman propagators weighting the lines of propagation, and that this effective field theory reduces to the usual quantum field theory in flat space in the no-gravity limit
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Identifying the genes of unconventional high temperature superconductors.
Hu, Jiangping
We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d -orbitals of cations that participate in strong in-plane couplings to the p -orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.
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A 6-gene signature identifies four molecular subgroups of neuroblastoma
Directory of Open Access Journals (Sweden)
Kogner Per
2011-04-01
Full Text Available Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB; Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples. Four distinct clusters were identified by Principal Components Analysis (PCA in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.
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Dynamics of Quantum Causal Structures
Directory of Open Access Journals (Sweden)
Esteban Castro-Ruiz
2018-03-01
Full Text Available It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B. Here, we develop a framework for “dynamics of causal structures,” i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B, via superposition of causal orders, to a channel from B to A. We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
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Causal inference in public health.
Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M
2013-01-01
Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.
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Measures of coupling between neural populations based on Granger causality principle
Directory of Open Access Journals (Sweden)
Maciej Kaminski
2016-10-01
Full Text Available This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a weak node. Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.
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Putting a cap on causality violations in causal dynamical triangulations
International Nuclear Information System (INIS)
Ambjoern, Jan; Loll, Renate; Westra, Willem; Zohren, Stefan
2007-01-01
The formalism of causal dynamical triangulations (CDT) provides us with a non-perturbatively defined model of quantum gravity, where the sum over histories includes only causal space-time histories. Path integrals of CDT and their continuum limits have been studied in two, three and four dimensions. Here we investigate a generalization of the two-dimensional CDT model, where the causality constraint is partially lifted by introducing branching points with a weight g s , and demonstrate that the system can be solved analytically in the genus-zero sector. The solution is analytic in a neighborhood around weight g s = 0 and cannot be analytically continued to g s = ∞, where the branching is entirely geometric and where one would formally recover standard Euclidean two-dimensional quantum gravity defined via dynamical triangulations or Liouville theory
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Directory of Open Access Journals (Sweden)
Martin Poot
2011-05-01
Full Text Available Understanding complex networks that modulate development in humans is hampered by genetic and phenotypic heterogeneity within and between populations. Here we present a method that exploits natural variation in highly diverse mouse genetic reference panels in which genetic and environmental factors can be tightly controlled. The aim of our study is to test a cross-species genetic mapping strategy, which compares data of gene mapping in human patients with functional data obtained by QTL mapping in recombinant inbred mouse strains in order to prioritize human disease candidate genes.We exploit evolutionary conservation of developmental phenotypes to discover gene variants that influence brain development in humans. We studied corpus callosum volume in a recombinant inbred mouse panel (C57BL/6J×DBA/2J, BXD strains using high-field strength MRI technology. We aligned mouse mapping results for this neuro-anatomical phenotype with genetic data from patients with abnormal corpus callosum (ACC development.From the 61 syndromes which involve an ACC, 51 human candidate genes have been identified. Through interval mapping, we identified a single significant QTL on mouse chromosome 7 for corpus callosum volume with a QTL peak located between 25.5 and 26.7 Mb. Comparing the genes in this mouse QTL region with those associated with human syndromes (involving ACC and those covered by copy number variations (CNV yielded a single overlap, namely HNRPU in humans and Hnrpul1 in mice. Further analysis of corpus callosum volume in BXD strains revealed that the corpus callosum was significantly larger in BXD mice with a B genotype at the Hnrpul1 locus than in BXD mice with a D genotype at Hnrpul1 (F = 22.48, p<9.87*10(-5.This approach that exploits highly diverse mouse strains provides an efficient and effective translational bridge to study the etiology of human developmental disorders, such as autism and schizophrenia.
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Geisheker, Madeleine R.; Heymann, Gabriel; Wang, Tianyun; Coe, Bradley P.; Turner, Tychele N.; Stessman, Holly A.F.; Hoekzema, Kendra; Kvarnung, Malin; Shaw, Marie; Friend, Kathryn; Liebelt, Jan; Barnett, Christopher; Thompson, Elizabeth M.; Haan, Eric; Guo, Hui; Anderlid, Britt-Marie; Nordgren, Ann; Lindstrand, Anna; Vandeweyer, Geert; Alberti, Antonino; Avola, Emanuela; Vinci, Mirella; Giusto, Stefania; Pramparo, Tiziano; Pierce, Karen; Nalabolu, Srinivasa; Michaelson, Jacob J.; Sedlacek, Zdenek; Santen, Gijs W.E.; Peeters, Hilde; Hakonarson, Hakon; Courchesne, Eric; Romano, Corrado; Kooy, R. Frank; Bernier, Raphael A.; Nordenskjöld, Magnus; Gecz, Jozef; Xia, Kun; Zweifel, Larry S.; Eichler, Evan E.
2017-01-01
Although de novo missense mutations have been predicted to account for more cases of autism than gene-truncating mutations, most research has focused on the latter. We identified the properties of de novo missense mutations in patients with neurodevelopmental disorders (NDDs) and highlight 35 genes with excess missense mutations. Additionally, 40 amino acid sites were recurrently mutated in 36 genes, and targeted sequencing of 20 sites in 17,689 NDD patients identified 21 new patients with identical missense mutations. One recurrent site (p.Ala636Thr) occurs in a glutamate receptor subunit, GRIA1. This same amino acid substitution in the homologous but distinct mouse glutamate receptor subunit Grid2 is associated with Lurcher ataxia. Phenotypic follow-up in five individuals with GRIA1 mutations shows evidence of specific learning disabilities and autism. Overall, we find significant clustering of de novo mutations in 200 genes, highlighting specific functional domains and synaptic candidate genes important in NDD pathology. PMID:28628100
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Allman, Elizabeth S; Degnan, James H; Rhodes, John A
2011-06-01
Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.
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Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.
Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J
2016-01-01
Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.
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Causality Statistical Perspectives and Applications
Berzuini, Carlo; Bernardinell, Luisa
2012-01-01
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr
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A multivariate analysis of the causal flow between renewable energy consumption and GDP in Tunisia
Ben Salha, Ousama; Sebri, Maamar
2013-01-01
This paper examines the causality linkages between economic growth, renewable energy consumption, CO2 emissions and domestic investment in Tunisia between 1971 and 2010. Using the ARDL bounds testing approach to cointegration, long-run relationships between the variables are identified. On the other hand, the Granger causality analysis indicates that there is bi-directional causality between renewable energy consumption and economic growth, which supports the validity of the feedback hypothes...
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A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems
Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik
2003-01-01
The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method
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Waaijenborg, S.; Zwinderman, A.H.
2009-01-01
ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the
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Identifying genes that mediate anthracyline toxicity in immune cells
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Amber eFrick
2015-04-01
Full Text Available The role of the immune system in response to chemotherapeutic agents remains elusive. The interpatient variability observed in immune and chemotherapeutic cytotoxic responses is likely, at least in part, due to complex genetic differences. Through the use of a panel of genetically diverse mouse inbred strains, we developed a drug screening platform aimed at identifying genes underlying these chemotherapeutic cytotoxic effects on immune cells. Using genome-wide association studies (GWAS, we identified four genome-wide significant quantitative trait loci (QTL that contributed to the sensitivity of doxorubicin and idarubicin in immune cells. Of particular interest, a locus on chromosome 16 was significantly associated with cell viability following idarubicin administration (p = 5.01x10-8. Within this QTL lies App, which encodes amyloid beta precursor protein. Comparison of dose-response curves verified that T-cells in App knockout mice were more sensitive to idarubicin than those of C57BL/6J control mice (p < 0.05.In conclusion, the cellular screening approach coupled with GWAS led to the identification and subsequent validation of a gene involved in T-cell viability after idarubicin treatment. Previous studies have suggested a role for App in in vitro and in vivo cytotoxicity to anticancer agents; the overexpression of App enhances resistance, while the knockdown of this gene is deleterious to cell viability. Thus, further investigations should include performing mechanistic studies, validating additional genes from the GWAS, including Ppfia1 and Ppfibp1, and ultimately translating the findings to in vivo and human studies.
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Characterization of the MLO gene family in Rosaceae and gene expression analysis in Malus domestica.
Pessina, Stefano; Pavan, Stefano; Catalano, Domenico; Gallotta, Alessandra; Visser, Richard G F; Bai, Yuling; Malnoy, Mickael; Schouten, Henk J
2014-07-22
Powdery mildew (PM) is a major fungal disease of thousands of plant species, including many cultivated Rosaceae. PM pathogenesis is associated with up-regulation of MLO genes during early stages of infection, causing down-regulation of plant defense pathways. Specific members of the MLO gene family act as PM-susceptibility genes, as their loss-of-function mutations grant durable and broad-spectrum resistance. We carried out a genome-wide characterization of the MLO gene family in apple, peach and strawberry, and we isolated apricot MLO homologs through a PCR-approach. Evolutionary relationships between MLO homologs were studied and syntenic blocks constructed. Homologs that are candidates for being PM susceptibility genes were inferred by phylogenetic relationships with functionally characterized MLO genes and, in apple, by monitoring their expression following inoculation with the PM causal pathogen Podosphaera leucotricha. Genomic tools available for Rosaceae were exploited in order to characterize the MLO gene family. Candidate MLO susceptibility genes were identified. In follow-up studies it can be investigated whether silencing or a loss-of-function mutations in one or more of these candidate genes leads to PM resistance.
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The Functions of Danish Causal Conjunctions
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Rita Therkelsen
2004-01-01
Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.
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Space and time in perceptual causality
Directory of Open Access Journals (Sweden)
Benjamin Straube
2010-04-01
Full Text Available Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte’s view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.
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Confounding factors in determining causal soil moisture-precipitation feedback
Tuttle, Samuel E.; Salvucci, Guido D.
2017-07-01
Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.
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Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.
Lawrenson, Kate; Iversen, Edwin S; Tyrer, Jonathan; Weber, Rachel Palmieri; Concannon, Patrick; Hazelett, Dennis J; Li, Qiyuan; Marks, Jeffrey R; Berchuck, Andrew; Lee, Janet M; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Bandera, Elisa V; Bean, Yukie; Beckmann, Matthias W; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Plisiecka-Halasa, Joanna; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Eccles, Diana; Easton, Douglas T; Edwards, Robert P; Eilber, Ursula; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Gronwald, Jacek; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Jakubowska, Anna; Paul, James; Jensen, Allan; Karlan, Beth Y; Kjaer, Susanne Kruger; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph L; Kiemeney, Lambertus A; Krakstad, Camilla; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Cannioto, Rikki; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Nevanlinna, Heli; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Noor Azmi, Mat Adenan; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Budzilowska, Agnieszka; Sellers, Thomas A; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston, Lara; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Coetzee, Gerhard A; Freedman, Matthew L; Monteiro, Alvaro N A; Moes-Sosnowska, Joanna; Kupryjanczyk, Jolanta; Pharoah, Paul D; Gayther, Simon A; Schildkraut, Joellen M
2015-11-01
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Is There a Causal Effect of High School Math on Labor Market Outcomes?
Joensen, Juanna Schroter; Nielsen, Helena Skyt
2009-01-01
In this paper, we exploit a high school pilot scheme to identify the causal effect of advanced high school math on labor market outcomes. The pilot scheme reduced the costs of choosing advanced math because it allowed for a more flexible combination of math with other courses. We find clear evidence of a causal relationship between math and…
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Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng
2017-08-01
Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.
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A cross-study gene set enrichment analysis identifies critical pathways in endometriosis
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Bai Chunyan
2009-09-01
Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.
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A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.
Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C
2017-10-01
Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.
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Civetta, Alberto
2016-05-01
Understanding the origin of species is of interest to biologist in general and evolutionary biologist in particular. Hybrid male sterility (HMS) has been a focus in studies of speciation because sterility imposes a barrier to free gene flow between organisms, thus effectively isolating them as distinct species. In this review, I focus on the role of differential gene expression in HMS and speciation. Microarray and qPCR assays have established associations between misregulation of gene expression and sterility in hybrids between closely related species. These studies originally proposed disrupted expression of spermatogenesis genes as a causative of sterility. Alternatively, rapid genetic divergence of regulatory elements, particularly as they relate to the male sex (fast-male evolution), can drive the misregulation of sperm developmental genes in the absence of sterility. The use of fertile hybrids (both backcross and F1 progeny) as controls has lent support to this alternative explanation. Differences in gene expression between fertile and sterile hybrids can also be influenced by a pattern of faster evolution of the sex chromosome (fast-X evolution) than autosomes. In particular, it would be desirable to establish whether known X-chromosome sterility factors can act as trans-regulatory drivers of genome-wide patterns of misregulation. Genome-wide expression studies coupled with assays of proxies of sterility in F1 and BC progeny have identified candidate HMS genes but functional assays, and a better phenotypic characterization of sterility phenotypes, are needed to rigorously test how these genes might contribute to HMS.
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Nelson-Coffey, SK; Fritz, MM; Lyubomirsky, S; Cole, SW
2017-01-01
Prosocial behavior is linked to longevity, but few studies have experimentally manipulated prosocial behavior to identify the causal mechanisms underlying this association. One possible mediating pathway involves changes in gene expression that may subsequently influence disease development or resistance.In the current study, we examined changes in a leukocyte gene expression profile known as the Conserved Transcriptional Response to Adversity (CTRA) in 159 adults who were randomly assigned f...
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MethylMix 2.0: an R package for identifying DNA methylation genes.
Cedoz, Pierre-Louis; Prunello, Marcos; Brennan, Kevin; Gevaert, Olivier
2018-04-14
DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes. Here we present a new version of MethylMix that automates the construction of DNA-methylation and gene expression datasets from The Cancer Genome Atlas (TCGA). More precisely, MethylMix 2.0 incorporates two major updates: the automated downloading of DNA methylation and gene expression datasets from TCGA and the automated preprocessing of such datasets: value imputation, batch correction and CpG sites clustering within each gene. The resulting datasets can subsequently be analyzed with MethylMix to identify transcriptionally predictive methylation states. We show that the Differential Methylation Values created by MethylMix can be used for cancer subtyping. olivier.gevaert@stanford.edu. https://bioconductor.org/packages/release/bioc/manuals/MethylMix/man/MethylMix.pdf. MethylMix 2.0 was implemented as an R package and is available in bioconductor.
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A large-scale RNA interference screen identifies genes that regulate autophagy at different stages.
Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man; He, Bin; Zhang, Liqing; Varmark, Hanne; Green, Michael R; Sheng, Zhi
2018-02-12
Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.
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Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B.; Kim, Jung-Hyun; Ang, J. Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P.; Andrews, Brenda; Boerkoel, Cornelius F.; Hieter, Philip
2016-01-01
Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1. Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064
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Paradoxical Behavior of Granger Causality
Witt, Annette; Battaglia, Demian; Gail, Alexander
2013-03-01
Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen
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On causality of extreme events
Directory of Open Access Journals (Sweden)
Massimiliano Zanin
2016-06-01
Full Text Available Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.
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Integrating mean and variance heterogeneities to identify differentially expressed genes.
Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen
2016-12-06
In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment
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Type 1 Diabetes Candidate Genes Linked to Pancreatic Islet Cell Inflammation and Beta-Cell Apoptosis
DEFF Research Database (Denmark)
Størling, Joachim; Pociot, Flemming
2017-01-01
(GWAS) have identified more than 50 genetic regions that affect the risk of developing T1D. Most of these susceptibility loci, however, harbor several genes, and the causal variant(s) and gene(s) for most of the loci remain to be established. A significant part of the genes located in the T1D...... susceptibility loci are expressed in human islets and β cells and mounting evidence suggests that some of these genes modulate the β-cell response to the immune system and viral infection and regulate apoptotic β-cell death. Here, we discuss the current status of T1D susceptibility loci and candidate genes...
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International Nuclear Information System (INIS)
Zulfiqar, Asma; Paulose, Bibin; Chhikara, Sudesh; Dhankher, Om Parkash
2011-01-01
Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: → Molecular mechanism of Cr uptake and detoxification in plants is not well known. → We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. → 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. → Pathways linked to stress, ion transport, and sulfur assimilation were affected. → This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.
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Energy Technology Data Exchange (ETDEWEB)
Zulfiqar, Asma, E-mail: asmazulfiqar08@yahoo.com [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Paulose, Bibin, E-mail: bpaulose@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Chhikara, Sudesh, E-mail: sudesh@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States); Dhankher, Om Parkash, E-mail: parkash@psis.umass.edu [Department of Plant, Soil, and Insect Sciences, 270 Stockbridge Road, University of Massachusetts Amherst, MA 01003 (United States)
2011-10-15
Chromium pollution is a serious environmental problem with few cost-effective remediation strategies available. Crambe abyssinica (a member of Brassicaseae), a non-food, fast growing high biomass crop, is an ideal candidate for phytoremediation of heavy metals contaminated soils. The present study used a PCR-Select Suppression Subtraction Hybridization approach in C. abyssinica to isolate differentially expressed genes in response to Cr exposure. A total of 72 differentially expressed subtracted cDNAs were sequenced and found to represent 43 genes. The subtracted cDNAs suggest that Cr stress significantly affects pathways related to stress/defense, ion transporters, sulfur assimilation, cell signaling, protein degradation, photosynthesis and cell metabolism. The regulation of these genes in response to Cr exposure was further confirmed by semi-quantitative RT-PCR. Characterization of these differentially expressed genes may enable the engineering of non-food, high-biomass plants, including C. abyssinica, for phytoremediation of Cr-contaminated soils and sediments. - Highlights: > Molecular mechanism of Cr uptake and detoxification in plants is not well known. > We identified differentially regulated genes upon Cr exposure in Crambe abyssinica. > 72 Cr-induced subtracted cDNAs were sequenced and found to represent 43 genes. > Pathways linked to stress, ion transport, and sulfur assimilation were affected. > This is the first Cr transcriptome study in a crop with phytoremediation potential. - This study describes the identification and isolation of differentially expressed genes involved in chromium metabolism and detoxification in a non-food industrial oil crop Crambe abyssinica.
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Systems Genetics Analysis to Identify the Genetic Modulation of a Glaucoma-Associated Gene.
Chintalapudi, Sumana R; Jablonski, Monica M
2017-01-01
Loss of retinal ganglion cells (RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Recently, γ-synuclein (SNCG) was shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the regulation of Sncg in RGCs, we used a systems genetics approach to identify a gene that modulates the expression of Sncg, followed by confirmatory studies in both healthy and diseased retinas. We found that chromosome 1 harbors an eQTL that modulates the expression of Sncg in the mouse retina and identified Pfdn2 as the candidate upstream modulator of Sncg expression. Downregulation of Pfdn2 in enriched RGCs causes a concomitant reduction in Sncg. In this chapter, we describe our strategy and methods for identifying and confirming a genetic modulation of a glaucoma-associated gene. A similar method can be applied to other genes expressed in other tissues.
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2018-01-01
One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520
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Olafsson, Gestur; Helgason, Sigurdur
1996-01-01
This book is intended to introduce researchers and graduate students to the concepts of causal symmetric spaces. To date, results of recent studies considered standard by specialists have not been widely published. This book seeks to bring this information to students and researchers in geometry and analysis on causal symmetric spaces.Includes the newest results in harmonic analysis including Spherical functions on ordered symmetric space and the holmorphic discrete series and Hardy spaces on compactly casual symmetric spacesDeals with the infinitesimal situation, coverings of symmetric spaces, classification of causal symmetric pairs and invariant cone fieldsPresents basic geometric properties of semi-simple symmetric spacesIncludes appendices on Lie algebras and Lie groups, Bounded symmetric domains (Cayley transforms), Antiholomorphic Involutions on Bounded Domains and Para-Hermitian Symmetric Spaces
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Directory of Open Access Journals (Sweden)
Mao Yu
2009-07-01
Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From
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You've gotta be lucky: Coverage and the elusive gene-gene interaction.
Reimherr, Matthew; Nicolae, Dan L
2011-01-01
Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.
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Directory of Open Access Journals (Sweden)
Petr Volkov
Full Text Available Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI, lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL, hemoglobin A1c (HbA1c and homeostatic model assessment of insulin resistance (HOMA-IR via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dysmetabolic traits associated with the development of
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Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis
2017-01-01
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
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Triantafillou, Sofia
2017-09-29
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
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Zhong, Chao; Sun, Suli; Li, Yinping; Duan, Canxing; Zhu, Zhendong
2018-03-01
A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F 2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.
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A 6-gene signature identifies four molecular subgroups of neuroblastoma
LENUS (Irish Health Repository)
Abel, Frida
2011-04-14
Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and\\/or dead of disease, p < 0.05, Fisher\\'s exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group\\'s specific characteristics.
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International Nuclear Information System (INIS)
Thomassen, Mads; Tan, Qihua; Kruse, Torben A
2008-01-01
Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may
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Zhang, Tianxiao; Hou, Liping; Chen, David T; McMahon, Francis J; Wang, Jen-Chyong; Rice, John P
2018-03-01
Bipolar disorder is a mental illness with lifetime prevalence of about 1%. Previous genetic studies have identified multiple chromosomal linkage regions and candidate genes that might be associated with bipolar disorder. The present study aimed to identify potential susceptibility variants for bipolar disorder using 6 related case samples from a four-generation family. A combination of exome sequencing and linkage analysis was performed to identify potential susceptibility variants for bipolar disorder. Our study identified a list of five potential candidate genes for bipolar disorder. Among these five genes, GRID1(Glutamate Receptor Delta-1 Subunit), which was previously reported to be associated with several psychiatric disorders and brain related traits, is particularly interesting. Variants with functional significance in this gene were identified from two cousins in our bipolar disorder pedigree. Our findings suggest a potential role for these genes and the related rare variants in the onset and development of bipolar disorder in this one family. Additional research is needed to replicate these findings and evaluate their patho-biological significance. Copyright © 2017 Elsevier B.V. All rights reserved.
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Gutiérrez, Rodrigo A; Stokes, Trevor L; Thum, Karen; Xu, Xiaodong; Obertello, Mariana; Katari, Manpreet S; Tanurdzic, Milos; Dean, Alexis; Nero, Damion C; McClung, C Robertson; Coruzzi, Gloria M
2008-03-25
Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N) assimilation such as glutamate (Glu) or glutamine (Gln) might serve as signals of organic N status that in turn regulate gene expression. To identify genome-wide responses to such organic N signals, Arabidopsis seedlings were transiently treated with ammonium nitrate in the presence or absence of MSX, an inhibitor of glutamine synthetase, resulting in a block of Glu/Gln synthesis. Genes that responded to organic N were identified as those whose response to ammonium nitrate treatment was blocked in the presence of MSX. We showed that some genes previously identified to be regulated by nitrate are under the control of an organic N-metabolite. Using an integrated network model of molecular interactions, we uncovered a subnetwork regulated by organic N that included CCA1 and target genes involved in N-assimilation. We validated some of the predicted interactions and showed that regulation of the master clock control gene CCA1 by Glu or a Glu-derived metabolite in turn regulates the expression of key N-assimilatory genes. Phase response curve analysis shows that distinct N-metabolites can advance or delay the CCA1 phase. Regulation of CCA1 by organic N signals may represent a novel input mechanism for N-nutrients to affect plant circadian clock function.
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Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini
2012-09-01
Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
David G Ashbrook
2015-07-01
Full Text Available Bipolar disorder (BD is a significant neuropsychiatric disorder with a lifetime prevalence of ~1%. To identify genetic variants underlying BD genome-wide association studies (GWAS have been carried out. While many variants of small effect associated with BD have been identified few have yet been confirmed, partly because of the low power of GWAS due to multiple comparisons being made. Complementary mapping studies using murine models have identified genetic variants for behavioral traits linked to BD, often with high power, but these identified regions often contain too many genes for clear identification of candidate genes. In the current study we have aligned human BD GWAS results and mouse linkage studies to help define and evaluate candidate genes linked to BD, seeking to use the power of the mouse mapping with the precision of GWAS. We use quantitative trait mapping for open field test and elevated zero maze data in the largest mammalian model system, the BXD recombinant inbred mouse population, to identify genomic regions associated with these BD-like phenotypes. We then investigate these regions in whole genome data from the Psychiatric Genomics Consortium’s bipolar disorder GWAS to identify candidate genes associated with BD. Finally we establish the biological relevance and pathways of these genes in a comprehensive systems genetics analysis.We identify four genes associated with both mouse anxiety and human BD. While TNR is a novel candidate for BD, we can confirm previously suggested associations with CMYA5, MCTP1 and RXRG. A cross-species, systems genetics analysis shows that MCTP1, RXRG and TNR coexpress with genes linked to psychiatric disorders and identify the striatum as a potential site of action. CMYA5, MCTP1, RXRG and TNR are associated with mouse anxiety and human BD. We hypothesize that MCTP1, RXRG and TNR influence intercellular signaling in the striatum.
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A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets
DEFF Research Database (Denmark)
Taneera, Jalal; Lang, Stefan; Sharma, Amitabh
2012-01-01
Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability. In an attempt to identify additional T2D genes, we analyzed global gene expression in human islets from 63 donors. Using 48 genes located near T2D risk variants, we identified ...
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Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng
2017-11-13
The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly
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Ward, Lucas D; Kellis, Manolis
2016-01-04
More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Informational and Causal Architecture of Discrete-Time Renewal Processes
Directory of Open Access Journals (Sweden)
Sarah E. Marzen
2015-07-01
Full Text Available Renewal processes are broadly used to model stochastic behavior consisting of isolated events separated by periods of quiescence, whose durations are specified by a given probability law. Here, we identify the minimal sufficient statistic for their prediction (the set of causal states, calculate the historical memory capacity required to store those states (statistical complexity, delineate what information is predictable (excess entropy, and decompose the entropy of a single measurement into that shared with the past, future, or both. The causal state equivalence relation defines a new subclass of renewal processes with a finite number of causal states despite having an unbounded interevent count distribution. We use the resulting formulae to analyze the output of the parametrized Simple Nonunifilar Source, generated by a simple two-state hidden Markov model, but with an infinite-state ϵ-machine presentation. All in all, the results lay the groundwork for analyzing more complex processes with infinite statistical complexity and infinite excess entropy.
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Principal stratification in causal inference.
Frangakis, Constantine E; Rubin, Donald B
2002-03-01
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.
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Johnston, Iain G; Williams, Ben P
2016-02-24
Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.
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Causal Set Generator and Action Computer
Cunningham, William; Krioukov, Dmitri
2017-01-01
The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...
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'Omics' approaches in tomato aimed at identifying candidate genes ...
African Journals Online (AJOL)
adriana
2013-12-04
Dec 4, 2013 ... approaches could be combined in order to identify candidate genes for the genetic control of ascorbic ..... applied to other traits under the complex control of many ... Engineering increased vitamin C levels in ... Chem. Biol. 13:532–538. Giovannucci E, Rimm EB, Liu Y, Stampfer MJ, Willett WC (2002). A.
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Spectral dimension in causal set quantum gravity
International Nuclear Information System (INIS)
Eichhorn, Astrid; Mizera, Sebastian
2014-01-01
We evaluate the spectral dimension in causal set quantum gravity by simulating random walks on causal sets. In contrast to other approaches to quantum gravity, we find an increasing spectral dimension at small scales. This observation can be connected to the nonlocality of causal set theory that is deeply rooted in its fundamentally Lorentzian nature. Based on its large-scale behaviour, we conjecture that the spectral dimension can serve as a tool to distinguish causal sets that approximate manifolds from those that do not. As a new tool to probe quantum spacetime in different quantum gravity approaches, we introduce a novel dimensional estimator, the causal spectral dimension, based on the meeting probability of two random walkers, which respect the causal structure of the quantum spacetime. We discuss a causal-set example, where the spectral dimension and the causal spectral dimension differ, due to the existence of a preferred foliation. (paper)
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The causal link between energy and output growth: Evidence from Markov switching Granger causality
International Nuclear Information System (INIS)
Kandemir Kocaaslan, Ozge
2013-01-01
In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s
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Coalitional game theory as a promising approach to identify candidate autism genes.
Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul
2018-01-01
Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.
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¿CONFIEREN PODERES CAUSALES LOS UNIVERSALES TRASCENDENTES?
Directory of Open Access Journals (Sweden)
José Tomás Alvarado Marambio
2013-11-01
Full Text Available This work discusses the so-called ‘Eleatic’ argument against the existence of transcendent universals, i. e. universals which does not require instantiation for its existence. The Eleatic Principle states that everything produces a difference in the causal powers of something. As transcendent universals seem not to produce such a difference, transcendent universals seem not to exist. The argument depends crucially on the justification and the interpretation of the Eleatic Principle. It is argued, first, that it is not very clear that the principle is justified, and, second, that there are several alternatives for its interpretation, in relation with the different theories one can endorse about modality or causality. Anti-realist theories of modality or causality are not very appropriate for the understanding of what should be a ‘causal power’. Neither does a realist theory of causality conjoined with a combinatorial theory of possible worlds. A ‘causal power’ seems to be better understood in connection with a realist –non-reductionist– theory of causality and a causal theory of modality. Taken in this way the Eleatic Principle, nonetheless, it is argued that transcendent universals do ‘produce’ a difference in causal powers, for every causal connection requires such universals for its existence.
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DEFF Research Database (Denmark)
Hasselbalch, Hans Carl; Skov, Vibe; Stauffer Larsen, Thomas
2014-01-01
Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were...
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Friederich, Simon
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the
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Hammarlöf, Disa L; Canals, Rocío; Hinton, Jay C D
2013-10-01
The availability of thousands of genome sequences of bacterial pathogens poses a particular challenge because each genome contains hundreds of genes of unknown function (FUN). How can we easily discover which FUN genes encode important virulence factors? One solution is to combine two different functional genomic approaches. First, transcriptomics identifies bacterial FUN genes that show differential expression during the process of mammalian infection. Second, global mutagenesis identifies individual FUN genes that the pathogen requires to cause disease. The intersection of these datasets can reveal a small set of candidate genes most likely to encode novel virulence attributes. We demonstrate this approach with the Salmonella infection model, and propose that a similar strategy could be used for other bacterial pathogens. Copyright © 2013 Elsevier Ltd. All rights reserved.
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mediation: R package for causal mediation analysis
Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke
2012-01-01
In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting su...
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A powerful score-based test statistic for detecting gene-gene co-association.
Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun
2016-01-29
The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.
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A Hierarchical Causal Taxonomy of Psychopathology across the Life Span
Lahey, Benjamin B.; Krueger, Robert F.; Rathouz, Paul J.; Waldman, Irwin D.; Zald, David H.
2016-01-01
We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the three levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. PMID:28004947
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Gene expression signature analysis identifies vorinostat as a candidate therapy for gastric cancer.
Directory of Open Access Journals (Sweden)
Sofie Claerhout
Full Text Available Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future.Using microarray technology, we generated a gene expression profile of human gastric cancer-specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern.We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment.
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Directory of Open Access Journals (Sweden)
Cielito C Reyes-Gibby
Full Text Available Mucositis is a complex, dose-limiting toxicity of chemotherapy or radiotherapy that leads to painful mouth ulcers, difficulty eating or swallowing, gastrointestinal distress, and reduced quality of life for patients with cancer. Mucositis is most common for those undergoing high-dose chemotherapy and hematopoietic stem cell transplantation and for those being treated for malignancies of the head and neck. Treatment and management of mucositis remain challenging. It is expected that multiple genes are involved in the formation, severity, and persistence of mucositis. We used Ingenuity Pathway Analysis (IPA, a novel network-based approach that integrates complex intracellular and intercellular interactions involved in diseases, to systematically explore the molecular complexity of mucositis. As a first step, we searched the literature to identify genes that harbor or are close to the genetic variants significantly associated with mucositis. Our literature review identified 27 candidate genes, of which ERCC1, XRCC1, and MTHFR were the most frequently studied for mucositis. On the basis of this 27-gene list, we used IPA to generate gene networks for mucositis. The most biologically significant novel molecules identified through IPA analyses included TP53, CTNNB1, MYC, RB1, P38 MAPK, and EP300. Additionally, uracil degradation II (reductive and thymine degradation pathways (p = 1.06-08 were most significant. Finally, utilizing 66 SNPs within the 8 most connected IPA-derived candidate molecules, we conducted a genetic association study for oral mucositis in the head and neck cancer patients who were treated using chemotherapy and/or radiation therapy (186 head and neck cancer patients with oral mucositis vs. 699 head and neck cancer patients without oral mucositis. The top ranked gene identified through this association analysis was RB1 (rs2227311, p-value = 0.034, odds ratio = 0.67. In conclusion, gene network analysis identified novel molecules and
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Reyes-Gibby, Cielito C; Melkonian, Stephanie C; Wang, Jian; Yu, Robert K; Shelburne, Samuel A; Lu, Charles; Gunn, Gary Brandon; Chambers, Mark S; Hanna, Ehab Y; Yeung, Sai-Ching J; Shete, Sanjay
2017-01-01
Mucositis is a complex, dose-limiting toxicity of chemotherapy or radiotherapy that leads to painful mouth ulcers, difficulty eating or swallowing, gastrointestinal distress, and reduced quality of life for patients with cancer. Mucositis is most common for those undergoing high-dose chemotherapy and hematopoietic stem cell transplantation and for those being treated for malignancies of the head and neck. Treatment and management of mucositis remain challenging. It is expected that multiple genes are involved in the formation, severity, and persistence of mucositis. We used Ingenuity Pathway Analysis (IPA), a novel network-based approach that integrates complex intracellular and intercellular interactions involved in diseases, to systematically explore the molecular complexity of mucositis. As a first step, we searched the literature to identify genes that harbor or are close to the genetic variants significantly associated with mucositis. Our literature review identified 27 candidate genes, of which ERCC1, XRCC1, and MTHFR were the most frequently studied for mucositis. On the basis of this 27-gene list, we used IPA to generate gene networks for mucositis. The most biologically significant novel molecules identified through IPA analyses included TP53, CTNNB1, MYC, RB1, P38 MAPK, and EP300. Additionally, uracil degradation II (reductive) and thymine degradation pathways (p = 1.06-08) were most significant. Finally, utilizing 66 SNPs within the 8 most connected IPA-derived candidate molecules, we conducted a genetic association study for oral mucositis in the head and neck cancer patients who were treated using chemotherapy and/or radiation therapy (186 head and neck cancer patients with oral mucositis vs. 699 head and neck cancer patients without oral mucositis). The top ranked gene identified through this association analysis was RB1 (rs2227311, p-value = 0.034, odds ratio = 0.67). In conclusion, gene network analysis identified novel molecules and biological
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Using reporter gene assays to identify cis regulatory differences between humans and chimpanzees.
Chabot, Adrien; Shrit, Ralla A; Blekhman, Ran; Gilad, Yoav
2007-08-01
Most phenotypic differences between human and chimpanzee are likely to result from differences in gene regulation, rather than changes to protein-coding regions. To date, however, only a handful of human-chimpanzee nucleotide differences leading to changes in gene regulation have been identified. To hone in on differences in regulatory elements between human and chimpanzee, we focused on 10 genes that were previously found to be differentially expressed between the two species. We then designed reporter gene assays for the putative human and chimpanzee promoters of the 10 genes. Of seven promoters that we found to be active in human liver cell lines, human and chimpanzee promoters had significantly different activity in four cases, three of which recapitulated the gene expression difference seen in the microarray experiment. For these three genes, we were therefore able to demonstrate that a change in cis influences expression differences between humans and chimpanzees. Moreover, using site-directed mutagenesis on one construct, the promoter for the DDA3 gene, we were able to identify three nucleotides that together lead to a cis regulatory difference between the species. High-throughput application of this approach can provide a map of regulatory element differences between humans and our close evolutionary relatives.
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Directory of Open Access Journals (Sweden)
Na Liu
2016-07-01
Full Text Available Kernel starch content is an important trait in maize (Zea mays L. as it accounts for 65% to 75% of the dry kernel weight and positively correlates with seed yield. A number of starch synthesis-related genes have been identified in maize in recent years. However, many loci underlying variation in starch content among maize inbred lines still remain to be identified. The current study is a genome-wide association study that used a set of 263 maize inbred lines. In this panel, the average kernel starch content was 66.99%, ranging from 60.60% to 71.58% over the three study years. These inbred lines were genotyped with the SNP50 BeadChip maize array, which is comprised of 56,110 evenly spaced, random SNPs. Population structure was controlled by a mixed linear model (MLM as implemented in the software package TASSEL. After the statistical analyses, four SNPs were identified as significantly associated with starch content (P ≤ 0.0001, among which one each are located on chromosomes 1 and 5 and two are on chromosome 2. Furthermore, 77 candidate genes associated with starch synthesis were found within the 100-kb intervals containing these four QTLs, and four highly associated genes were within 20-kb intervals of the associated SNPs. Among the four genes, Glucose-1-phosphate adenylyltransferase (APS1; Gene ID GRMZM2G163437 is known as an important regulator of kernel starch content. The identified SNPs, QTLs, and candidate genes may not only be readily used for germplasm improvement by marker-assisted selection in breeding, but can also elucidate the genetic basis of starch content. Further studies on these identified candidate genes may help determine the molecular mechanisms regulating kernel starch content in maize and other important cereal crops.
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Causal knowledge and the development of inductive reasoning.
Bright, Aimée K; Feeney, Aidan
2014-06-01
We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.
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Causal Diagrams for Empirical Research
Pearl, Judea
1994-01-01
The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...
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Nakayama, Akiyoshi; Nakaoka, Hirofumi; Yamamoto, Ken; Sakiyama, Masayuki; Shaukat, Amara; Toyoda, Yu; Okada, Yukinori; Kamatani, Yoichiro; Nakamura, Takahiro; Takada, Tappei; Inoue, Katsuhisa; Yasujima, Tomoya; Yuasa, Hiroaki; Shirahama, Yuko; Nakashima, Hiroshi
2016-01-01
Objective A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. Methods Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were replicated with 1396 cases and 1268 controls using a custom chip of 1961 single nucleotide polymorphisms (SNPs). We also first conducted GWASs of gout subtypes. Replication with Caucasian and New Zeala...
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Understanding environmental contributions to autism: Causal concepts and the state of science.
Hertz-Picciotto, Irva; Schmidt, Rebecca J; Krakowiak, Paula
2018-04-01
The complexity of neurodevelopment, the rapidity of early neurogenesis, and over 100 years of research identifying environmental influences on neurodevelopment serve as backdrop to understanding factors that influence risk and severity of autism spectrum disorder (ASD). This Keynote Lecture, delivered at the May 2016 annual meeting of the International Society for Autism Research, describes concepts of causation, outlines the trajectory of research on nongenetic factors beginning in the 1960s, and briefly reviews the current state of this science. Causal concepts are introduced, including root causes; pitfalls in interpreting time trends as clues to etiologic factors; susceptible time windows for exposure; and implications of a multi-factorial model of ASD. An historical background presents early research into the origins of ASD. The epidemiologic literature from the last fifteen years is briefly but critically reviewed for potential roles of, for example, air pollution, pesticides, plastics, prenatal vitamins, lifestyle and family factors, and maternal obstetric and metabolic conditions during her pregnancy. Three examples from the case-control CHildhood Autism Risks from Genes and the Environment Study are probed to illustrate methodological approaches to central challenges in observational studies: capturing environmental exposure; causal inference when a randomized controlled clinical trial is either unethical or infeasible; and the integration of genetic, epigenetic, and environmental influences on development. We conclude with reflections on future directions, including exposomics, new technologies, the microbiome, gene-by-environment interaction in the era of -omics, and epigenetics as the interface of those two. As the environment is malleable, this research advances the goal of a productive and fulfilling life for all children, teen-agers and adults. Autism Res 2018, 11: 554-586. © 2018 International Society for Autism Research, Wiley Periodicals, Inc
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What Causal Forces Shape Internet Connectivity at the AS-level?
National Research Council Canada - National Science Library
Chang, Hyunseok; Jamin, Sugih; Willinger, Walter
2003-01-01
...." By focusing on the AS subgraph ASpc whose links represent provider-customer relationships, we present an empirical study that identifies three crucial causal forces at work in the design of AS connectivity: (i) AS-geography, i.e...
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CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.
Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua
2018-03-01
In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and
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An Empirical Investigation into Causality of Unsafe Act and Recovery during EOP Simulation
Energy Technology Data Exchange (ETDEWEB)
Choi, Sun Yeong; Jung, Won Dea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-08-15
A data collection worksheet and guideline to collect HRA (Human Reliability Analysis) data with simulator data sources were developed for the HRA data handbook project by KAERI. Using the data worksheet, simulator data were collected and analyzed for an HRA qualitative database. The purpose of this paper is to define the causalities of operators' UAs (Unsafe Acts) ending in an inappropriate component manipulation and recovery during an EOP (Emergency Operating Procedure) operation, and to show some results for the causality from a case study. The reason we suggest the causality of an UA is because an inappropriate manipulation during an EOP operation can be resulted by the causality among operators in an MCR (Main Control Room). Therefore, a 'causality' data field was inserted into the data worksheet to identify the real initiator, and related operators for an inappropriate component manipulation. With this 'causality' data field, an HRA analyzer can establish who caused an UA (or a recovery) and who was involved in the process. They can also calculate the HEP (Human Error Probability) grouped by the initiator if they are interested in the HEP by the initiator.
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Directory of Open Access Journals (Sweden)
John Patrick Mpindi
Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is
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The selective power of causality on memory errors.
Marsh, Jessecae K; Kulkofsky, Sarah
2015-01-01
We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.
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Rate-Agnostic (Causal) Structure Learning.
Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince
2015-12-01
Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a "rate-agnostic" manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling.
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Directory of Open Access Journals (Sweden)
Dhir Rajiv
2004-08-01
Full Text Available Abstract Background Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. Results Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using
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A large-scale RNA interference screen identifies genes that regulate autophagy at different stages
DEFF Research Database (Denmark)
Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man
2018-01-01
Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed...... with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes...... have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays...
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Causality and analyticity in optics
International Nuclear Information System (INIS)
Nussenzveig, H.M.
In order to provide an overall picture of the broad range of optical phenomena that are directly linked with the concepts of causality and analyticity, the following topics are briefly reviewed, emphasizing recent developments: 1) Derivation of dispersion relations for the optical constants of general linear media from causality. Application to the theory of natural optical activity. 2) Derivation of sum rules for the optical constants from causality and from the short-time response function (asymptotic high-frequency behavior). Average spectral behavior of optical media. Applications. 3) Role of spectral conditions. Analytic properties of coherence functions in quantum optics. Reconstruction theorem.4) Phase retrieval problems. 5) Inverse scattering problems. 6) Solution of nonlinear evolution equations in optics by inverse scattering methods. Application to self-induced transparency. Causality in nonlinear wave propagation. 7) Analytic continuation in frequency and angular momentum. Complex singularities. Resonances and natural-mode expansions. Regge poles. 8) Wigner's causal inequality. Time delay. Spatial displacements in total reflection. 9) Analyticity in diffraction theory. Complex angular momentum theory of Mie scattering. Diffraction as a barrier tunnelling effect. Complex trajectories in optics. (Author) [pt
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mediation: R Package for Causal Mediation Analysis
Directory of Open Access Journals (Sweden)
Dustin Tingley
2014-09-01
Full Text Available In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.
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Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Farzana, Jasmine; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul
2013-12-01
Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.
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Neural theory for the perception of causal actions.
Fleischer, Falk; Christensen, Andrea; Caggiano, Vittorio; Thier, Peter; Giese, Martin A
2012-07-01
The efficient prediction of the behavior of others requires the recognition of their actions and an understanding of their action goals. In humans, this process is fast and extremely robust, as demonstrated by classical experiments showing that human observers reliably judge causal relationships and attribute interactive social behavior to strongly simplified stimuli consisting of simple moving geometrical shapes. While psychophysical experiments have identified critical visual features that determine the perception of causality and agency from such stimuli, the underlying detailed neural mechanisms remain largely unclear, and it is an open question why humans developed this advanced visual capability at all. We created pairs of naturalistic and abstract stimuli of hand actions that were exactly matched in terms of their motion parameters. We show that varying critical stimulus parameters for both stimulus types leads to very similar modulations of the perception of causality. However, the additional form information about the hand shape and its relationship with the object supports more fine-grained distinctions for the naturalistic stimuli. Moreover, we show that a physiologically plausible model for the recognition of goal-directed hand actions reproduces the observed dependencies of causality perception on critical stimulus parameters. These results support the hypothesis that selectivity for abstract action stimuli might emerge from the same neural mechanisms that underlie the visual processing of natural goal-directed action stimuli. Furthermore, the model proposes specific detailed neural circuits underlying this visual function, which can be evaluated in future experiments.
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Yang, Lawrence H.; Wonpat-Borja, Ahtoy J.
2011-01-01
Identifying factors that facilitate treatment for psychotic disorders among Chinese-immigrants is crucial due to delayed treatment use. Identifying causal beliefs held by relatives that might predict identification of ‘mental illness’ as opposed to other ‘indigenous labels’ may promote more effective mental health service use. We examine what effects beliefs of ‘physical causes’ and other non-biomedical causal beliefs (‘general social causes’, and ‘indigenous Chinese beliefs’ or culture-speci...
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Causal asymmetry across cultures: Assigning causal roles in symmetric physical settings
Directory of Open Access Journals (Sweden)
Andrea eBender
2011-09-01
Full Text Available In the cognitive sciences, causal cognition in the physical domain has featured as a core research topic, but the impact of culture has been rarely ever explored. One case in point for a topic on which this neglect is pronounced is the pervasive tendency of people to consider one of two (equally important entities as more important for bringing about an effect. In order to scrutinize how robust such tendencies are across cultures, we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content. This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also subject to culture-specific concepts. Moreover, the asymmetries were found to be modulated by figure-ground relations, but not by marking agency.
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Entanglement, non-Markovianity, and causal non-separability
Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan
2018-03-01
Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.
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How causal analysis can reveal autonomy in models of biological systems
Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa
2017-11-01
Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.
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Reconstructing Causal Biological Networks through Active Learning.
Directory of Open Access Journals (Sweden)
Hyunghoon Cho
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
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X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes.
Hu, H; Haas, S A; Chelly, J; Van Esch, H; Raynaud, M; de Brouwer, A P M; Weinert, S; Froyen, G; Frints, S G M; Laumonnier, F; Zemojtel, T; Love, M I; Richard, H; Emde, A-K; Bienek, M; Jensen, C; Hambrock, M; Fischer, U; Langnick, C; Feldkamp, M; Wissink-Lindhout, W; Lebrun, N; Castelnau, L; Rucci, J; Montjean, R; Dorseuil, O; Billuart, P; Stuhlmann, T; Shaw, M; Corbett, M A; Gardner, A; Willis-Owen, S; Tan, C; Friend, K L; Belet, S; van Roozendaal, K E P; Jimenez-Pocquet, M; Moizard, M-P; Ronce, N; Sun, R; O'Keeffe, S; Chenna, R; van Bömmel, A; Göke, J; Hackett, A; Field, M; Christie, L; Boyle, J; Haan, E; Nelson, J; Turner, G; Baynam, G; Gillessen-Kaesbach, G; Müller, U; Steinberger, D; Budny, B; Badura-Stronka, M; Latos-Bieleńska, A; Ousager, L B; Wieacker, P; Rodríguez Criado, G; Bondeson, M-L; Annerén, G; Dufke, A; Cohen, M; Van Maldergem, L; Vincent-Delorme, C; Echenne, B; Simon-Bouy, B; Kleefstra, T; Willemsen, M; Fryns, J-P; Devriendt, K; Ullmann, R; Vingron, M; Wrogemann, K; Wienker, T F; Tzschach, A; van Bokhoven, H; Gecz, J; Jentsch, T J; Chen, W; Ropers, H-H; Kalscheuer, V M
2016-01-01
X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or loci are yet to be identified. Here, we have investigated 405 unresolved families with XLID. We employed massively parallel sequencing of all X-chromosome exons in the index males. The majority of these males were previously tested negative for copy number variations and for mutations in a subset of known XLID genes by Sanger sequencing. In total, 745 X-chromosomal genes were screened. After stringent filtering, a total of 1297 non-recurrent exonic variants remained for prioritization. Co-segregation analysis of potential clinically relevant changes revealed that 80 families (20%) carried pathogenic variants in established XLID genes. In 19 families, we detected likely causative protein truncating and missense variants in 7 novel and validated XLID genes (CLCN4, CNKSR2, FRMPD4, KLHL15, LAS1L, RLIM and USP27X) and potentially deleterious variants in 2 novel candidate XLID genes (CDK16 and TAF1). We show that the CLCN4 and CNKSR2 variants impair protein functions as indicated by electrophysiological studies and altered differentiation of cultured primary neurons from Clcn4(-/-) mice or after mRNA knock-down. The newly identified and candidate XLID proteins belong to pathways and networks with established roles in cognitive function and intellectual disability in particular. We suggest that systematic sequencing of all X-chromosomal genes in a cohort of patients with genetic evidence for X-chromosome locus involvement may resolve up to 58% of Fragile X-negative cases.
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International Nuclear Information System (INIS)
Bombelli, L.; Lee, J.; Meyer, D.; Sorkin, R.D.
1987-01-01
We propose that space-time at the smallest scales is in reality a causal set: a locally finite set of elements endowed with a partial order corresponding to the macroscopic relation that defines past and future. We explore how a Lorentzian manifold can approximate a causal set, noting in particular that the thereby defined effective dimensionality of a given causal set can vary with length scale. Finally, we speculate briefly on the quantum dynamics of causal sets, indicating why an appropriate choice of action can reproduce general relativity in the classical limit
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Shungin, Dmitry; Cornelis, Marilyn C; Divaris, Kimon; Holtfreter, Birte; Shaffer, John R; Yu, Yau-Hua; Barros, Silvana P; Beck, James D; Biffar, Reiner; Boerwinkle, Eric A; Crout, Richard J.; Ganna, Andrea; Hallmans, Goran; Hindy, George; Hu, Frank B; Kraft, Peter; McNeil, Daniel W; Melander, Olle; Moss, Kevin L; North, Kari E; Orho-Melander, Marju; Pedersen, Nancy L; Ridker, Paul M; Rimm, Eric B; Rose, Lynda M; Rukh, Gull; Teumer, Alexander; Weyant, Robert J; Chasman, Daniel I; Joshipura, Kaumudi; Kocher, Thomas; Magnusson, Patrik KE; Marazita, Mary L; Nilsson, Peter; Offenbacher, Steve; Davey Smith, George; Lundberg, Pernilla; Palmer, Tom M; Timpson, Nicholas J; Johansson, Ingegerd; Franks, Paul W
2015-01-01
Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis. Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide
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Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer
Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong
2011-01-01
Background Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. Methodology/Principal Findings Using microarray technology, we generated a gene expression profile of human gastric cancer–specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A) whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. Conclusions/Significance We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment. PMID:21931799
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X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes
Hu, H.; Haas, S.A.; Chelly, J.; Van Esch, H.; Raynaud, M.; de Brouwer, A.P.M.; Weinert, S.; Froyen, G.; Frints, S.G.M.; Laumonnier, F.; Zemojtel, T.; Love, M.I.; Richard, H.; Emde, A.K.; Bienek, M.
2016-01-01
X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or loci are yet to be identified. Here, we have investigated 405 unresolved families with XLID. We employed massively parallel sequencing of all X-chromosome exons in the index males. The majority of ...
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Representing Personal Determinants in Causal Structures.
Bandura, Albert
1984-01-01
Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…
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Identifying candidate driver genes by integrative ovarian cancer genomics data
Lu, Xinguo; Lu, Jibo
2017-08-01
Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.
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Repeated Causal Decision Making
Hagmayer, York; Meder, Bjorn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…
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Causality in Classical Electrodynamics
Savage, Craig
2012-01-01
Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…
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Shen, K A; Meyers, B C; Islam-Faridi, M N; Chin, D B; Stelly, D M; Michelmore, R W
1998-08-01
The recent cloning of genes for resistance against diverse pathogens from a variety of plants has revealed that many share conserved sequence motifs. This provides the possibility of isolating numerous additional resistance genes by polymerase chain reaction (PCR) with degenerate oligonucleotide primers. We amplified resistance gene candidates (RGCs) from lettuce with multiple combinations of primers with low degeneracy designed from motifs in the nucleotide binding sites (NBSs) of RPS2 of Arabidopsis thaliana and N of tobacco. Genomic DNA, cDNA, and bacterial artificial chromosome (BAC) clones were successfully used as templates. Four families of sequences were identified that had the same similarity to each other as to resistance genes from other species. The relationship of the amplified products to resistance genes was evaluated by several sequence and genetic criteria. The amplified products contained open reading frames with additional sequences characteristic of NBSs. Hybridization of RGCs to genomic DNA and to BAC clones revealed large numbers of related sequences. Genetic analysis demonstrated the existence of clustered multigene families for each of the four RGC sequences. This parallels classical genetic data on clustering of disease resistance genes. Two of the four families mapped to known clusters of resistance genes; these two families were therefore studied in greater detail. Additional evidence that these RGCs could be resistance genes was gained by the identification of leucine-rich repeat (LRR) regions in sequences adjoining the NBS similar to those in RPM1 and RPS2 of A. thaliana. Fluorescent in situ hybridization confirmed the clustered genomic distribution of these sequences. The use of PCR with degenerate oligonucleotide primers is therefore an efficient method to identify numerous RGCs in plants.
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Gene-environment interaction involving recently identified colorectal cancer susceptibility loci
Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily
2014-01-01
BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789
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LGscore: A method to identify disease-related genes using biological literature and Google data.
Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun
2015-04-01
Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.
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Kant on causal laws and powers.
Henschen, Tobias
2014-12-01
The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.
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An assessment of predominant causal factors of pilot deviations that contribute to runway incursions
Campbell, Denado M.
The aim of this study was to identify predominant causal factors of pilot deviations in runway incursions over a two-year period. Runway incursion reports were obtained from NASA's Aviation Safety Reporting System (ASRS), and a qualitative method was used by classifying and coding each report to a specific causal factor(s). The causal factors that were used were substantiated by research from the Aircraft Owner's and Pilot's Association that found that these causal factors were the most common in runway incursion incidents and accidents. An additional causal factor was also utilized to determine the significance of pilot training in relation to runway incursions. From the reports examined, it was found that miscommunication and situational awareness have the greatest impact on pilots and are most often the major causes of runway incursions. This data can be used to assist airports, airlines, and the FAA to understand trends in pilot deviations, and to find solutions for specific problem areas in runway incursion incidents.
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Detecting dynamic causal inference in nonlinear two-phase fracture flow
Faybishenko, Boris
2017-08-01
Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.
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Directory of Open Access Journals (Sweden)
Hans Carl Hasselbalch
Full Text Available Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were selectively and highly deregulated in myelofibrosis patients. Gene expression microarray studies have been performed on whole blood from 69 patients with myeloproliferative neoplasms. Amongst the top-20 of the most upregulated genes in PMF compared to controls, we identified 5 genes (DEFA4, ELA2, OLFM4, CTSG, and AZU1, which were highly significantly deregulated in PMF only. None of these genes were significantly regulated in ET and PV patients. However, hierarchical cluster analysis showed that these genes were also highly expressed in a subset of patients with ET (n = 1 and PV (n = 4 transforming towards myelofibrosis and/or being featured by an aggressive phenotype. We have identified a simple 5-gene signature, which is uniquely and highly significantly deregulated in patients in transitional stages of ET and PV towards myelofibrosis and in patients with PMF only. Some of these genes are considered to be responsible for the derangement of bone marrow stroma in myelofibrosis. Accordingly, this gene-signature may reflect key processes in the pathogenesis and pathophysiology of myelofibrosis development.
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New Mutation Identified in the SRY Gene High Mobility Group (HMG
Directory of Open Access Journals (Sweden)
Feride İffet Şahin
2013-06-01
Full Text Available Mutations in the SRY gene prevent the differentiation of the fetal gonads to testes and cause developing female phenotype, and as a result sex reversal and pure gonadal dysgenesis (Swyer syndrome can be developed. Different types of mutations identified in the SRY gene are responsible for 15% of the gonadal dysgenesis. In this study, we report a new mutation (R132P in the High Mobility Group (HMG region of SRY gene was detected in a patient with primary amenorrhea who has 46,XY karyotype. This mutation leads to replacement of the polar and basic arginine with a nonpolar hydrophobic proline residue at aminoacid 132 in the nuclear localization signal region of the protein. With this case report we want to emphasize the genetic approach to the patients with gonadal dysgenesis. If Y chromosome is detected during cytogenetic analysis, revealing the presence of the SRY gene and identification of mutations in this gene by sequencing analysis is become important in.
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Directory of Open Access Journals (Sweden)
Jan E Aagaard
Full Text Available Understanding the genetic basis of reproductive isolation promises insight into speciation and the origins of biological diversity. While progress has been made in identifying genes underlying barriers to reproduction that function after fertilization (post-zygotic isolation, we know much less about earlier acting pre-zygotic barriers. Of particular interest are barriers involved in mating and fertilization that can evolve extremely rapidly under sexual selection, suggesting they may play a prominent role in the initial stages of reproductive isolation. A significant challenge to the field of speciation genetics is developing new approaches for identification of candidate genes underlying these barriers, particularly among non-traditional model systems. We employ powerful proteomic and genomic strategies to study the genetic basis of conspecific pollen precedence, an important component of pre-zygotic reproductive isolation among yellow monkeyflowers (Mimulus spp. resulting from male pollen competition. We use isotopic labeling in combination with shotgun proteomics to identify more than 2,000 male function (pollen tube proteins within maternal reproductive structures (styles of M. guttatus flowers where pollen competition occurs. We then sequence array-captured pollen tube exomes from a large outcrossing population of M. guttatus, and identify those genes with evidence of selective sweeps or balancing selection consistent with their role in pollen competition. We also test for evidence of positive selection on these genes more broadly across yellow monkeyflowers, because a signal of adaptive divergence is a common feature of genes causing reproductive isolation. Together the molecular evolution studies identify 159 pollen tube proteins that are candidate genes for conspecific pollen precedence. Our work demonstrates how powerful proteomic and genomic tools can be readily adapted to non-traditional model systems, allowing for genome-wide screens
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Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim
2011-11-11
To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets. We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray
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Directory of Open Access Journals (Sweden)
Dunja Knapp
Full Text Available Understanding how the limb blastema is established after the initial wound healing response is an important aspect of regeneration research. Here we performed parallel expression profile time courses of healing lateral wounds versus amputated limbs in axolotl. This comparison between wound healing and regeneration allowed us to identify amputation-specific genes. By clustering the expression profiles of these samples, we could detect three distinguishable phases of gene expression - early wound healing followed by a transition-phase leading to establishment of the limb development program, which correspond to the three phases of limb regeneration that had been defined by morphological criteria. By focusing on the transition-phase, we identified 93 strictly amputation-associated genes many of which are implicated in oxidative-stress response, chromatin modification, epithelial development or limb development. We further classified the genes based on whether they were or were not significantly expressed in the developing limb bud. The specific localization of 53 selected candidates within the blastema was investigated by in situ hybridization. In summary, we identified a set of genes that are expressed specifically during regeneration and are therefore, likely candidates for the regulation of blastema formation.
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Directory of Open Access Journals (Sweden)
Gian Andri Thun
Full Text Available Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD. The role of more common SERPINA1 single nucleotide polymorphisms (SNPs in respiratory health remains poorly understood. We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS in 1392 individuals of the SAPALDIA cohort. Five common SNPs, defined by showing minor allele frequencies (MAFs >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = -0.068 g/L per minor allele (P = 1.20*10(-12. But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410, suggested that AAT serum level is causally determined at this locus by rare (MAF<1% and low-frequent (MAF 1-5% variants only, in particular by the well-documented protein inhibitor S and Z (PI S, PI Z variants. Replication of the association of rs4905179 with AAT serum levels in the Copenhagen City Heart Study (N = 8273 was successful (P<0.0001, as was the replication of its synthetic nature (the effect disappeared after adjusting for PI S and Z, P = 0.57. Extending the analysis to lung function revealed a more complex situation. Only in individuals with severely compromised pulmonary health (N = 397, associations of common SNPs at this locus with lung function were driven by rarer PI S or Z variants. Overall, our meta-analysis of lung function in ever-smokers does not support a functional role of common SNPs in the SERPINA gene
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Repair of Partly Misspecified Causal Diagrams.
Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B
2017-07-01
Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.
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Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash
2016-01-01
Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499
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Directory of Open Access Journals (Sweden)
Kelsey E. Grinde
2017-09-01
Full Text Available To date, gene-based rare variant testing approaches have focused on aggregating information across sets of variants to maximize statistical power in identifying genes showing significant association with diseases. Beyond identifying genes that are associated with diseases, the identification of causal variant(s in those genes and estimation of their effect is crucial for planning replication studies and characterizing the genetic architecture of the locus. However, we illustrate that straightforward single-marker association statistics can suffer from substantial bias introduced by conditioning on gene-based test significance, due to the phenomenon often referred to as “winner's curse.” We illustrate the ramifications of this bias on variant effect size estimation and variant prioritization/ranking approaches, outline parameters of genetic architecture that affect this bias, and propose a bootstrap resampling method to correct for this bias. We find that our correction method significantly reduces the bias due to winner's curse (average two-fold decrease in bias, p < 2.2 × 10−6 and, consequently, substantially improves mean squared error and variant prioritization/ranking. The method is particularly helpful in adjustment for winner's curse effects when the initial gene-based test has low power and for relatively more common, non-causal variants. Adjustment for winner's curse is recommended for all post-hoc estimation and ranking of variants after a gene-based test. Further work is necessary to continue seeking ways to reduce bias and improve inference in post-hoc analysis of gene-based tests under a wide variety of genetic architectures.
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Functional equations with causal operators
Corduneanu, C
2003-01-01
Functional equations encompass most of the equations used in applied science and engineering: ordinary differential equations, integral equations of the Volterra type, equations with delayed argument, and integro-differential equations of the Volterra type. The basic theory of functional equations includes functional differential equations with causal operators. Functional Equations with Causal Operators explains the connection between equations with causal operators and the classical types of functional equations encountered by mathematicians and engineers. It details the fundamentals of linear equations and stability theory and provides several applications and examples.
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Classical planning and causal implicatures
DEFF Research Database (Denmark)
Blackburn, Patrick Rowan; Benotti, Luciana
In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important...... to generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate...
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Causal beliefs about obesity and associated health behaviors: results from a population-based survey
Directory of Open Access Journals (Sweden)
Coups Elliot J
2010-03-01
Full Text Available Abstract Background Several genetic variants are associated with obesity risk. Promoting the notion of genes as a cause for obesity may increase genetically deterministic beliefs and decrease motivation to engage in healthy lifestyle behaviors. Little is known about whether causal beliefs about obesity are associated with lifestyle behaviors. Study objectives were as follows: 1 to document the prevalence of various causal beliefs about obesity (i.e., genes versus lifestyle behaviors, and 2 to determine the association between obesity causal beliefs and self-reported dietary and physical activity behaviors. Methods The study data were drawn from the 2007 Health Information National Trends Survey (HINTS. A total of 3,534 individuals were included in the present study. Results Overall, 72% of respondents endorsed the belief that lifestyle behaviors have 'a lot' to do with causing obesity, whereas 19% indicated that inheritance has 'a lot' to do with causing obesity. Multinomial logistic regression analyses indicated that the belief that obesity is inherited was associated with lower reported levels of physical activity (OR = 0.87, 95% CI: 0.77-0.99 and fruit and vegetable consumption (OR = 0.87, 95% CI: 0.76-0.99. In contrast, the belief that obesity is caused by lifestyle behaviors was associated with greater reported levels of physical activity (OR = 1.29, 95% CI: 1.03-1.62, but was not associated with fruit and vegetable intake (OR = 1.07, 95% CI: 0.90-1.28. Conclusions Causal beliefs about obesity are associated with some lifestyle behaviors. Additional research is needed to determine whether promoting awareness of the genetic determinants of obesity will decrease the extent to which individuals will engage in the lifestyle behaviors essential to healthy weight management.
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Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.
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Directory of Open Access Journals (Sweden)
Frank Barning
2016-01-01
Full Text Available A total of 1,263 adults from Newfoundland and Labrador were studied in the research. Body mass index (BMI and percent trunk fat (PTF were analyzed as biomarkers for obesity. The Mendelian randomization (MR approach with two single-nucleotide polymorphisms in the fat-mass and obesity (FTO gene as instruments was employed to assess the causal effect. In both genders, increasing physical activity significantly reduced BMI and PTF when adjusted for age and the FTO gene. The effect of physical activity was stronger on PTF than BMI. Direct observational analyses showed significant increase in BMI/PTF when physical activity decreased. A similar association in MR analyses was not significant. The association between physical activity and BMI/PTF could be due to reversed causality or common confounding factors. Our study provides insights into the causal contributions of obesity to physical activity in adults. Health intervention strategies to increase physical activity among adults should include some other plans such as improving diet for reducing obesity.
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The Causality of Evolution on Different Fitness Landscapes
Vyawahare, Saurabh; Austin, Robert; Zhang, Qiucen; Kim, Hyunsung; Bestoso, John
2013-03-01
Evolution of antibiotic resistance is a growing problem. One major reason why most antibiotics fail is because of mutations on drug targets (e.g. essential enzymes). Sequencing of clinically resistant isolates have shown that multiple mutational-hotspots exist in coding regions, which could potentially prohibit the binding of drugs. However, it is not clear whether the appearance of each mutation is random or influenced by other factors. In this paper, we compare evolution of resistance to ciprofloxacin from two distinct but well characterized genetic backgrounds. By combining our recently developed evolution reactor and deep whole-genome sequencing, we show different alleles of σs factor lead to fixation of different mutations in gyrA gene that confer ciprofloxacin resistance to bacteria Escherichia coli. Such causality of evolution in different genes provides an opportunity to control the evolution of antibiotic resistance. Sponsored by the NCI/NIH Physical Sciences Oncology Centers
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Zirlinger, M.; Kreiman, Gabriel; Anderson, D. J.
2001-01-01
Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions...
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X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes
Hu, H; Haas, S.A.; Chelly, J.; Esch, H. Van; Raynaud, M.; Brouwer, A.P. de; Weinert, S.; Froyen, G.; Frints, S.G.; Laumonnier, F.; Zemojtel, T.; Love, M.I.; Richard, H.; Emde, A.K.; Bienek, M.; Jensen, C.; Hambrock, M.; Fischer, U.; Langnick, C.; Feldkamp, M.; Wissink-Lindhout, W.; Lebrun, N.; Castelnau, L.; Rucci, J.; Montjean, R.; Dorseuil, O.; Billuart, P.; Stuhlmann, T.; Shaw, M.; Corbett, M.A.; Gardner, A.; Willis-Owen, S.; Tan, C.; Friend, K.L.; Belet, S.; Roozendaal, K.E. van; Jimenez-Pocquet, M.; Moizard, M.P.; Ronce, N.; Sun, R.; O'Keeffe, S.; Chenna, R.; Bommel, A. van; Goke, J.; Hackett, A.; Field, M.; Christie, L.; Boyle, J.; Haan, E.; Nelson, J.; Turner, G.; Baynam, G.; Gillessen-Kaesbach, G.; Muller, U.; Steinberger, D.; Budny, B.; Badura-Stronka, M.; Latos-Bielenska, A.; Ousager, L.B.; Wieacker, P.; Rodriguez Criado, G.; Bondeson, M.L.; Anneren, G.; Dufke, A.; Cohen, M.; Maldergem, L. Van; Vincent-Delorme, C.; Echenne, B.; Simon-Bouy, B.; Kleefstra, T.; Willemsen, M.H.; Fryns, J.P.; Devriendt, K.; Ullmann, R.; Vingron, M.; Wrogemann, K.; Wienker, T.F.; Tzschach, A.; Bokhoven, H. van; Gecz, J.; Jentsch, T.J.; Chen, W.; Ropers, H.H.; Kalscheuer, V.M.
2016-01-01
X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or
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X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes
DEFF Research Database (Denmark)
Hu, H; Haas, S A; Chelly, J
2016-01-01
X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes...
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Interactions of information transfer along separable causal paths
Jiang, Peishi; Kumar, Praveen
2018-04-01
Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.
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Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.
Iliev, Rumen; Axelrod, Robert
2016-05-01
The vast majority of the work on culture and cognition has focused on cross-cultural comparisons, largely ignoring the dynamic aspects of culture. In this article, we provide a diachronic analysis of causal cognition over time. We hypothesized that the increased role of education, science, and technology in Western societies should be accompanied by greater attention to causal connections. To test this hypothesis, we compared word frequencies in English texts from different time periods and found an increase in the use of causal language of about 40% over the past two centuries. The observed increase was not attributable to general language effects or to changing semantics of causal words. We also found that there was a consistent difference between the 19th and the 20th centuries, and that the increase happened mainly in the 20th century. © The Author(s) 2016.
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Li, Qili; Bu, Junyan; Yu, Zhihe; Tang, Lihua; Huang, Suiping; Guo, Tangxun; Mo, Jianyou; Hsiang, Tom
2018-02-22
Here, we present a draft genome sequence of isolate 15060 of Colletotrichum fructicola , a causal agent of mango anthracnose. The final assembly consists of 1,048 scaffolds totaling 56,493,063 bp (G+C content, 53.38%) and 15,180 predicted genes. Copyright © 2018 Li et al.
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Causality, spin, and equal-time commutators
International Nuclear Information System (INIS)
Abdel-Rahman, A.M.
1975-01-01
We study the causality constraints on the structure of the Lorentz-antisymmetric component of the commutator of two conserved isovector currents between fermion states of equal momenta. We discuss the sum rules that follow from causality and scaling, using the recently introduced refined infinite-momentum technique. The complete set of sum rules is found to include the spin-dependent fixed-mass sum rules obtained from light-cone commutators. The causality and scaling restrictions on the structure of the electromagnetic equal-time commutators are discussed, and it is found, in particular, that causality requires the spin-dependent part of the matrix element for the time-space electromagnetic equal-time commutator to vanish identically. It is also shown, in comparison with the electromagnetic case, that the corresponding matrix element for the time-space isovector current equal-time commutator is required, by causality, to have isospin-antisymmetric tensor and scalar operator Schwinger terms
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Causal inference, probability theory, and graphical insights.
Baker, Stuart G
2013-11-10
Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.
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Directory of Open Access Journals (Sweden)
Hongfeng Peng
2016-03-01
Full Text Available Using a sample of province-level panel data, this paper investigates the Granger causality associations among economic growth (GDP, foreign direct investment (FDI and CO2 emissions in China. By applying the bootstrap Granger panel causality approach (Kónya, 2006, we consider both cross-sectional dependence and homogeneity of different regions in China. The empirical results support that the causality direction not only works in a single direction either from GDP to FDI (in Yunnan or from FDI to GDP (in Beijing, Neimenggu, Jilin, Shanxi and Gansu, but it also works in both directions (in Henan. Moreover, we document that GDP is Granger-causing CO2 emissions in Neimenggu, Hubei, Guangxi and Gansu while there is bidirectional causality between these two variables in Shanxi. In the end, we identify the unidirectional causality from FDI to CO2 emissions in Beijing, Henan, Guizhou and Shanxi, and the bidirectional causality between FDI and CO2 emissions in Neimenggu.
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Two novel antimicrobial defensins from rice identified by gene coexpression network analyses.
Tantong, Supaluk; Pringsulaka, Onanong; Weerawanich, Kamonwan; Meeprasert, Arthitaya; Rungrotmongkol, Thanyada; Sarnthima, Rakrudee; Roytrakul, Sittiruk; Sirikantaramas, Supaart
2016-10-01
Defensins form an antimicrobial peptides (AMP) family, and have been widely studied in various plants because of their considerable inhibitory functions. However, their roles in rice (Oryza sativa L.) have not been characterized, even though rice is one of the most important staple crops that is susceptible to damaging infections. Additionally, a previous study identified 598 rice genes encoding cysteine-rich peptides, suggesting there are several uncharacterized AMPs in rice. We performed in silico gene expression and coexpression network analyses of all genes encoding defensin and defensin-like peptides, and determined that OsDEF7 and OsDEF8 are coexpressed with pathogen-responsive genes. Recombinant OsDEF7 and OsDEF8 could form homodimers. They inhibited the growth of the bacteria Xanthomonas oryzae pv. oryzae, X. oryzae pv. oryzicola, and Erwinia carotovora subsp. atroseptica with minimum inhibitory concentration (MIC) ranging from 0.6 to 63μg/mL. However, these OsDEFs are weakly active against the phytopathogenic fungi Helminthosporium oryzae and Fusarium oxysporum f.sp. cubense. This study describes a useful method for identifying potential plant AMPs with biological activities. Copyright © 2016 Elsevier Inc. All rights reserved.
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A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs
Karabatsos, George; Walker, Stephen G.
2013-01-01
The regression discontinuity (RD) design (Thistlewaite & Campbell, 1960; Cook, 2008) provides a framework to identify and estimate causal effects from a non-randomized design. Each subject of a RD design is assigned to the treatment (versus assignment to a non-treatment) whenever her/his observed value of the assignment variable equals or…
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K-causality and degenerate spacetimes
Dowker, H. F.; Garcia, R. S.; Surya, S.
2000-11-01
The causal relation K+ was introduced by Sorkin and Woolgar to extend the standard causal analysis of C2 spacetimes to those that are only C0. Most of their results also hold true in the case of metrics with degeneracies which are C0 but vanish at isolated points. In this paper we seek to examine K+ explicitly in the case of topology-changing `Morse histories' which contain degeneracies. We first demonstrate some interesting features of this relation in globally Lorentzian spacetimes. In particular, we show that K+ is robust and the Hawking and Sachs characterization of causal continuity translates into a natural condition in terms of K+. We then examine K+ in topology-changing Morse spacetimes with the degenerate points excised and then for the Morse histories in which the degenerate points are reinstated. We find further characterizations of causal continuity in these cases.
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Causal inference in econometrics
Kreinovich, Vladik; Sriboonchitta, Songsak
2016-01-01
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
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Jazayeri, Roshanak; Hu, Hao; Fattahi, Zohreh; Musante, Luciana; Abedini, Seyedeh Sedigheh; Hosseini, Masoumeh; Wienker, Thomas F; Ropers, Hans Hilger; Najmabadi, Hossein; Kahrizi, Kimia
2015-10-01
Intellectual disability (ID) is a neuro-developmental disorder which causes considerable socio-economic problems. Some ID individuals are also affected by ataxia, and the condition includes different mutations affecting several genes. We used whole exome sequencing (WES) in combination with homozygosity mapping (HM) to identify the genetic defects in five consanguineous families among our cohort study, with two affected children with ID and ataxia as major clinical symptoms. We identified three novel candidate genes, RIPPLY1, MRPL10, SNX14, and a new mutation in known gene SURF1. All are autosomal genes, except RIPPLY1, which is located on the X chromosome. Two are housekeeping genes, implicated in transcription and translation regulation and intracellular trafficking, and two encode mitochondrial proteins. The pathogenesis of these variants was evaluated by mutation classification, bioinformatic methods, review of medical and biological relevance, co-segregation studies in the particular family, and a normal population study. Linkage analysis and exome sequencing of a small number of affected family members is a powerful new technique which can be used to decrease the number of candidate genes in heterogenic disorders such as ID, and may even identify the responsible gene(s).
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Hu, Hao; Wienker, Thomas F; Musante, Luciana; Kalscheuer, Vera M; Kahrizi, Kimia; Najmabadi, Hossein; Ropers, H Hilger
2014-12-01
Next-generation sequencing has greatly accelerated the search for disease-causing defects, but even for experts the data analysis can be a major challenge. To facilitate the data processing in a clinical setting, we have developed a novel medical resequencing analysis pipeline (MERAP). MERAP assesses the quality of sequencing, and has optimized capacity for calling variants, including single-nucleotide variants, insertions and deletions, copy-number variation, and other structural variants. MERAP identifies polymorphic and known causal variants by filtering against public domain databases, and flags nonsynonymous and splice-site changes. MERAP uses a logistic model to estimate the causal likelihood of a given missense variant. MERAP considers the relevant information such as phenotype and interaction with known disease-causing genes. MERAP compares favorably with GATK, one of the widely used tools, because of its higher sensitivity for detecting indels, its easy installation, and its economical use of computational resources. Upon testing more than 1,200 individuals with mutations in known and novel disease genes, MERAP proved highly reliable, as illustrated here for five families with disease-causing variants. We believe that the clinical implementation of MERAP will expedite the diagnostic process of many disease-causing defects. © 2014 WILEY PERIODICALS, INC.
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Kassir, Yona
2017-01-01
Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.
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Causal localizations in relativistic quantum mechanics
Castrigiano, Domenico P. L.; Leiseifer, Andreas D.
2015-07-01
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac's localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.
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González-Plaza, Juan J; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R
2016-01-01
Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species.
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El-Sharkawy, Islam; Liang, Dong; Xu, Kenong
2015-12-01
Using RNA-seq, this study analysed an apple (Malus×domestica) anthocyanin-deficient yellow-skin somatic mutant 'Blondee' (BLO) and its red-skin parent 'Kidd's D-8' (KID), the original name of 'Gala', to understand the molecular mechanisms underlying the mutation. A total of 3299 differentially expressed genes (DEGs) were identified between BLO and KID at four developmental stages and/or between two adjacent stages within BLO and/or KID. A weighted gene co-expression network analysis (WGCNA) of the DEGs uncovered a network module of 34 genes highly correlated (r=0.95, P=9.0×10(-13)) with anthocyanin contents. Although 12 of the 34 genes in the WGCNA module were characterized and known of roles in anthocyanin, the remainder 22 appear to be novel. Examining the expression of ten representative genes in the module in 14 diverse apples revealed that at least eight were significantly correlated with anthocyanin variation. MdMYB10 (MDP0000259614) and MdGST (MDP0000252292) were among the most suppressed module member genes in BLO despite being undistinguishable in their corresponding sequences between BLO and KID. Methylation assay of MdMYB10 and MdGST in fruit skin revealed that two regions (MR3 and MR7) in the MdMYB10 promoter exhibited remarkable differences between BLO and KID. In particular, methylation was high and progressively increased alongside fruit development in BLO while was correspondingly low and constant in KID. The methylation levels in both MR3 and MR7 were negatively correlated with anthocyanin content as well as the expression of MdMYB10 and MdGST. Clearly, the collective repression of the 34 genes explains the loss-of-colour in BLO while the methylation in MdMYB10 promoter is likely causal for the mutation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.
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Next-generation sequencing identifies transportin 3 as the causative gene for LGMD1F.
Directory of Open Access Journals (Sweden)
Annalaura Torella
Full Text Available Limb-girdle muscular dystrophies (LGMD are genetically and clinically heterogeneous conditions. We investigated a large family with autosomal dominant transmission pattern, previously classified as LGMD1F and mapped to chromosome 7q32. Affected members are characterized by muscle weakness affecting earlier the pelvic girdle and the ileopsoas muscles. We sequenced the whole exome of four family members and identified a shared heterozygous frame-shift variant in the Transportin 3 (TNPO3 gene, encoding a member of the importin-β super-family. The TNPO3 gene is mapped within the LGMD1F critical interval and its 923-amino acid human gene product is also expressed in skeletal muscle. In addition, we identified an isolated case of LGMD with a new missense mutation in the same gene. We localized the mutant TNPO3 around the nucleus, but not inside. The involvement of gene related to the nuclear transport suggests a novel disease mechanism leading to muscular dystrophy.
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Bayesian networks improve causal environmental ...
Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value
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van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B
2015-01-01
Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.
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Dynamics and causality constraints
International Nuclear Information System (INIS)
Sousa, Manoelito M. de
2001-04-01
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)
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Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong
2013-10-18
Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be
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de Jong, Simone; Vidler, Lewis R; Mokrab, Younes; Collier, David A; Breen, Gerome
2016-08-01
Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the 'drug pathways' most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected pneratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy. © The Author(s) 2016.
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Identifying Genes Controlling Ferulate Cross-Linking Formation in Grass Cell Walls
Energy Technology Data Exchange (ETDEWEB)
de O. Buanafina, Marcia Maria [Pennsylvania State Univ., University Park, PA (United States)
2013-10-16
This proposal focuses on cell wall feruloylation and our long term goal is to identify and isolate novel genes controlling feruloylation and to characterize the phenotype of mutants in this pathway, with a spotlight on cell wall properties.
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Causal uncertainty, claimed and behavioural self-handicapping.
Thompson, Ted; Hepburn, Jonathan
2003-06-01
Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.
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A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy
DEFF Research Database (Denmark)
Bruhn, Sören; Fang, Yu; Barrenäs, Fredrik
2014-01-01
The identification of diagnostic markers and therapeutic candidate genes in common diseases is complicated by the involvement of thousands of genes. We hypothesized that genes co-regulated with a key gene in allergy, IL13, would form a module that could help to identify candidate genes. We identi...
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Causal knowledge and reasoning in decision making
Hagmayer, Y.; Witteman, C.L.M.
2017-01-01
Normative causal decision theories argue that people should use their causal knowledge in decision making. Based on these ideas, we argue that causal knowledge and reasoning may support and thereby potentially improve decision making based on expected outcomes, narratives, and even cues. We will
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Expert Causal Reasoning and Explanation.
Kuipers, Benjamin
The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…
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Utility and Limitations of Using Gene Expression Data to Identify Functional Associations.
Directory of Open Access Journals (Sweden)
Sahra Uygun
2016-12-01
Full Text Available Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets.
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Directory of Open Access Journals (Sweden)
Simone de Jong
Full Text Available Despite large-scale genome-wide association studies (GWAS, the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1, is located in, and regulated by the major histocompatibility (MHC complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.
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Davarniya, Behzad; Hu, Hao; Kahrizi, Kimia; Musante, Luciana; Fattahi, Zohreh; Hosseini, Masoumeh; Maqsoud, Fariba; Farajollahi, Reza; Wienker, Thomas F; Ropers, H Hilger; Najmabadi, Hossein
2015-01-01
Cognitive impairment or intellectual disability (ID) is a widespread neurodevelopmental disorder characterized by low IQ (below 70). ID is genetically heterogeneous and is estimated to affect 1-3% of the world's population. In affected children from consanguineous families, autosomal recessive inheritance is common, and identifying the underlying genetic cause is an important issue in clinical genetics. In the framework of a larger project, aimed at identifying candidate genes for autosomal recessive intellectual disorder (ARID), we recently carried out single nucleotide polymorphism-based genome-wide linkage analysis in several families from Ardabil province in Iran. The identification of homozygosity-by-descent loci in these families, in combination with whole exome sequencing, led us to identify possible causative homozygous changes in two families. In the first family, a missense variant was found in GRM1 gene, while in the second family, a frameshift alteration was identified in TRMT1, both of which were found to co-segregate with the disease. GRM1, a known causal gene for autosomal recessive spinocerebellar ataxia (SCAR13, MIM#614831), encodes the metabotropic glutamate receptor1 (mGluR1). This gene plays an important role in synaptic plasticity and cerebellar development. Conversely, the TRMT1 gene encodes a tRNA methyltransferase that dimethylates a single guanine residue at position 26 of most tRNAs using S-adenosyl methionine as the methyl group donor. We recently presented TRMT1 as a candidate gene for ARID in a consanguineous Iranian family (Najmabadi et al., 2011). We believe that this second Iranian family with a biallelic loss-of-function mutation in TRMT1 gene supports the idea that this gene likely has function in development of the disorder.
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Gene Network for Identifying the Entropy Changes of Different Modules in Pediatric Sepsis
Directory of Open Access Journals (Sweden)
Jing Yang
2016-12-01
Full Text Available Background/Aims: Pediatric sepsis is a disease that threatens life of children. The incidence of pediatric sepsis is higher in developing countries due to various reasons, such as insufficient immunization and nutrition, water and air pollution, etc. Exploring the potential genes via different methods is of significance for the prevention and treatment of pediatric sepsis. This study aimed to identify potential genes associated with pediatric sepsis utilizing analysis of gene network and entropy. Methods: The mRNA expression in the blood samples collected from 20 septic children and 30 healthy controls was quantified by using Affymetrix HG-U133A microarray. Two condition-specific protein-protein interaction networks (PINs, one for the healthy control and the other one for the children with sepsis, were deduced by combining the fundamental human PINs with gene expression profiles in the two phenotypes. Subsequently, distinct modules from the two conditional networks were extracted by adopting a maximal clique-merging approach. Delta entropy (ΔS was calculated between sepsis and control modules. Results: Then, key genes displaying changes in gene composition were identified by matching the control and sepsis modules. Two objective modules were obtained, in which ribosomal protein RPL4 and RPL9 as well as TOP2A were probably considered as the key genes differentiating sepsis from healthy controls. Conclusion: According to previous reports and this work, TOP2A is the potential gene therapy target for pediatric sepsis. The relationship between pediatric sepsis and RPL4 and RPL9 needs further investigation.
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Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
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Hagmayer, York; Engelmann, Neele
2014-01-01
Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...
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Search for missing schizophrenia genes will require a new ...
Indian Academy of Sciences (India)
2013-08-06
Aug 6, 2013 ... causal gene(s)?. The successful search for disease genes is based on a ..... 2010 Mobile interspersed repeats are major structural variants in ... Petronis A., Paterson A. D. and Kennedy J. L. 1999 Schizophrenia: an epigenetic ...
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2018-01-01
Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181
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Illness causal beliefs in Turkish immigrants
Directory of Open Access Journals (Sweden)
Klimidis Steven
2007-07-01
Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes
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Illness causal beliefs in Turkish immigrants.
Minas, Harry; Klimidis, Steven; Tuncer, Can
2007-07-24
People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different
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Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival
DEFF Research Database (Denmark)
Thomassen, Mads; Jochumsen, Kirsten M; Mogensen, Ole
2009-01-01
the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1...... using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways....
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Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
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Directory of Open Access Journals (Sweden)
Jesús Lascorz
2011-01-01
Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.
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Exploring Individual Differences in Preschoolers' Causal Stance
Alvarez, Aubry; Booth, Amy E.
2016-01-01
Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…
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Uncertainty, causality and decision: The case of social risks and nuclear risk in particular
International Nuclear Information System (INIS)
Lahidji, R.
2012-01-01
Probability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area. When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequences and are causally interconnected. The model provides a causal interpretation of Savage's conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem's causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a
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Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah
2017-01-01
The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network
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The Causal Pattern of Mobile Phone Ownership and Implications for ...
African Journals Online (AJOL)
This paper examined a number of predictors of mobile phone ownership amongst fish and vegetable sellers in Yola Metropolis, Nigeria. Using regression path analysis, it identified the causal pattern of mobile phone ownership for Male and Female in the study area. Although there were few significant differences between ...
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Candidate Essential Genes in Burkholderia cenocepacia J2315 Identified by Genome-Wide TraDIS
Wong, Yee-Chin
2016-08-22
Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing) as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.
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Candidate Essential Genes in Burkholderia cenocepacia J2315 Identified by Genome-Wide TraDIS
Wong, Yee-Chin; Abd El Ghany, Moataz; Naeem, Raeece; Lee, Kok-Wei; Tan, Yung-Chie; Pain, Arnab; Nathan, Sheila
2016-01-01
Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing) as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.
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Candidate essential genes in Burkholderia cenocepacia J2315 identified by genome-wide TraDIS
Directory of Open Access Journals (Sweden)
Yee-Chin Wong
2016-08-01
Full Text Available Burkholderia cenocepacia infection often leads to fatal cepacia syndrome in cystic fibrosis patients. However, antibiotic therapy rarely results in complete eradication of the pathogen due to its intrinsic resistance to many clinically available antibiotics. Recent attention has turned to the identification of essential genes as the proteins encoded by these genes may serve as potential targets for development of novel antimicrobials. In this study, we utilized TraDIS (Transposon Directed Insertion-site Sequencing as a genome-wide screening tool to facilitate the identification of B. cenocepacia genes essential for its growth and viability. A transposon mutant pool consisting of approximately 500,000 mutants was successfully constructed, with more than 400,000 unique transposon insertion sites identified by computational analysis of TraDIS datasets. The saturated library allowed for the identification of 383 genes that were predicted to be essential in B. cenocepacia. We extended the application of TraDIS to identify conditionally essential genes required for in vitro growth and revealed an additional repertoire of 439 genes to be crucial for B. cenocepacia growth under nutrient-depleted conditions. The library of B. cenocepacia mutants can subsequently be subjected to various biologically related conditions to facilitate the discovery of genes involved in niche adaptation as well as pathogenicity and virulence.
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Kusunoki, Kazutaka; Nakano, Yuki; Tanaka, Keisuke; Sakata, Yoichi; Koyama, Hiroyuki; Kobayashi, Yuriko
2017-02-01
Differences in the expression levels of aluminium (Al) tolerance genes are a known determinant of Al tolerance among plant varieties. We combined transcriptomic analysis of six Arabidopsis thaliana accessions with contrasting Al tolerance and a reverse genetic approach to identify Al-tolerance genes responsible for differences in Al tolerance between accession groups. Gene expression variation increased in the signal transduction process under Al stress and in growth-related processes in the absence of stress. Co-expression analysis and promoter single nucleotide polymorphism searching suggested that both trans-acting polymorphisms of Al signal transduction pathway and cis-acting polymorphisms in the promoter sequences caused the variations in gene expression associated with Al tolerance. Compared with the wild type, Al sensitivity increased in T-DNA knockout (KO) lines for five genes, including TARGET OF AVRB OPERATION1 (TAO1) and an unannotated gene (At5g22530). These were identified from 53 Al-inducible genes showing significantly higher expression in tolerant accessions than in sensitive accessions. These results indicate that the difference in transcriptional signalling is partly associated with the natural variation in Al tolerance in Arabidopsis. Our study also demonstrates the feasibility of comparative transcriptome analysis by using natural genetic variation for the identification of genes responsible for Al stress tolerance. © 2016 John Wiley & Sons Ltd.
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Freytag, Virginie; Probst, Sabine; Hadziselimovic, Nils; Boglari, Csaba; Hauser, Yannick; Peter, Fabian; Gabor Fenyves, Bank; Milnik, Annette; Demougin, Philippe; Vukojevic, Vanja; de Quervain, Dominique J-F; Papassotiropoulos, Andreas; Stetak, Attila
2017-07-12
The identification of genes related to encoding, storage, and retrieval of memories is a major interest in neuroscience. In the current study, we analyzed the temporal gene expression changes in a neuronal mRNA pool during an olfactory long-term associative memory (LTAM) in Caenorhabditis elegans hermaphrodites. Here, we identified a core set of 712 (538 upregulated and 174 downregulated) genes that follows three distinct temporal peaks demonstrating multiple gene regulation waves in LTAM. Compared with the previously published positive LTAM gene set (Lakhina et al., 2015), 50% of the identified upregulated genes here overlap with the previous dataset, possibly representing stimulus-independent memory-related genes. On the other hand, the remaining genes were not previously identified in positive associative memory and may specifically regulate aversive LTAM. Our results suggest a multistep gene activation process during the formation and retrieval of long-term memory and define general memory-implicated genes as well as conditioning-type-dependent gene sets. SIGNIFICANCE STATEMENT The identification of genes regulating different steps of memory is of major interest in neuroscience. Identification of common memory genes across different learning paradigms and the temporal activation of the genes are poorly studied. Here, we investigated the temporal aspects of Caenorhabditis elegans gene expression changes using aversive olfactory associative long-term memory (LTAM) and identified three major gene activation waves. Like in previous studies, aversive LTAM is also CREB dependent, and CREB activity is necessary immediately after training. Finally, we define a list of memory paradigm-independent core gene sets as well as conditioning-dependent genes. Copyright © 2017 the authors 0270-6474/17/376661-12$15.00/0.
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Directory of Open Access Journals (Sweden)
Ling-Yun Dai
2017-01-01
Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.
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Directory of Open Access Journals (Sweden)
Tung Shu-Yun
2011-04-01
Full Text Available Abstract Background Orchids comprise one of the largest families of flowering plants and generate commercially important flowers. However, model plants, such as Arabidopsis thaliana do not contain all plant genes, and agronomic and horticulturally important genera and species must be individually studied. Results Several molecular biology tools were used to isolate flower-specific gene promoters from Oncidium 'Gower Ramsey' (Onc. GR. A cDNA library of reproductive tissues was used to construct a microarray in order to compare gene expression in flowers and leaves. Five genes were highly expressed in flower tissues, and the subcellular locations of the corresponding proteins were identified using lip transient transformation with fluorescent protein-fusion constructs. BAC clones of the 5 genes, together with 7 previously published flower- and reproductive growth-specific genes in Onc. GR, were identified for cloning of their promoter regions. Interestingly, 3 of the 5 novel flower-abundant genes were putative trypsin inhibitor (TI genes (OnTI1, OnTI2 and OnTI3, which were tandemly duplicated in the same BAC clone. Their promoters were identified using transient GUS reporter gene transformation and stable A. thaliana transformation analyses. Conclusions By combining cDNA microarray, BAC library, and bombardment assay techniques, we successfully identified flower-directed orchid genes and promoters.
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Eby, Lillian T; Butts, Marcus M; Hoffman, Brian J; Sauer, Julia B
2015-07-01
Although mentoring has documented relationships with employee attitudes and outcomes of interest to organizations, neither the causal direction nor boundary conditions of the relationship between mentoring and organizational citizenship behaviors (OCBs) has been fully explored. On the basis of Social Learning Theory (SLT; Bandura, 1977, 1986), we predicted that mentoring received by supervisors would causally precede OCBs, rather than employee OCBs resulting in the receipt of more mentoring from supervisors. Results from cross-lagged data collected at 2 points in time from 190 intact supervisor-employee dyads supported our predictions; however, only for OCBs directed at individuals (OCB-Is) and not for OCBs directed at the organization (OCB-Os). Further supporting our theoretical rationale for expecting mentoring to precede OCBs, we found that coworker support operates as a substitute for mentoring in predicting OCB-Is. By contrast, no moderating effects were found for perceived organizational support. The results are discussed in terms of theoretical implications for mentoring and OCB research, as well as practical suggestions for enhancing employee citizenship behaviors. (c) 2015 APA, all rights reserved).
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Behavioural Pattern of Causality Parameter of Autoregressive ...
African Journals Online (AJOL)
In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...
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Candidate gene linkage approach to identify DNA variants that predispose to preterm birth
DEFF Research Database (Denmark)
Bream, Elise N A; Leppellere, Cara R; Cooper, Margaret E
2013-01-01
Background:The aim of this study was to identify genetic variants contributing to preterm birth (PTB) using a linkage candidate gene approach.Methods:We studied 99 single-nucleotide polymorphisms (SNPs) for 33 genes in 257 families with PTBs segregating. Nonparametric and parametric analyses were...... through the infant and/or the mother in the etiology of PTB....
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International Nuclear Information System (INIS)
Maund, J.B.
1979-01-01
Although the existence of tachyons is not ruled out by special relativity, it appears that causal paradoxes will arise if there are tachyons. The usual solutions to these paradoxes employ some form of the reinterpretation principle. In this paper it is argued first that, the principle is incoherent, second, that even if it is not, some causal paradoxes remain, and third, the most plausible ''solution,'' which appeals to boundary conditions of the universe, will conflict with special relativity
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DEFF Research Database (Denmark)
Kaczkowski, Bogumil; Tanaka, Yuji; Kawaji, Hideya
2016-01-01
Genes that are commonly deregulated in cancer are clinically attractive as candidate pan-diagnostic markers and therapeutic targets. To globally identify such targets, we compared Cap Analysis of Gene Expression (CAGE) profiles from 225 different cancer cell lines and 339 corresponding primary cell...
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Directory of Open Access Journals (Sweden)
York eHagmayer
2014-11-01
Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.
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Exploring causal associations between alcohol and coronary heart disease risk factors
DEFF Research Database (Denmark)
Lawlor, Debbie A; Nordestgaard, Børge G; Benn, Marianne
2013-01-01
association with triglycerides [-14.9% (-25.6, -4.3)] in IV analyses; P = 0.006 and 0.01, respectively, for difference between the two. Alcohol was not associated with non-HDLc or glucose.ConclusionOur results show adverse effects of long-term alcohol consumption on BP and BMI. We also found novel evidence......AimsTo explore the causal effect of long-term alcohol consumption on coronary heart disease risk factors.Methods and resultsWe used variants in ADH1B and ADH1C genes as instrumental variables (IV) to estimate the causal effect of long-term alcohol consumption on body mass index (BMI), blood...... pressure (BP), lipids, fibrinogen, and glucose. Analyses were undertaken in 54 604 Danes (mean age 56 years). Both confounder-adjusted multivariable and IV analyses suggested that a greater alcohol consumption among those who drank any alcohol resulted in a higher BP [mean difference in SBP per doubling...
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Directory of Open Access Journals (Sweden)
Candy M Taylor
Full Text Available Quantitative Reverse Transcription PCR (qRT-PCR is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC, Helicase (HEL, and Polypyrimidine tract-binding protein (PTB] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other
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DEFF Research Database (Denmark)
Day, Felix R; Thompson, Deborah J; Helgason, Hannes
2017-01-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P ... pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare...... variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women...
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Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
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[Antibibiotic resistance by nosocomial infections' causal agents].
Salazar-Holguín, Héctor Daniel; Cisneros-Robledo, María Elena
2016-01-01
The antibibiotic resistance by nosocomial infections (NI) causal agents constitutes a seriously global problematic that involves the Mexican Institute of Social Security's Regional General Hospital 1 in Chihuahua, Mexico; although with special features that required to be specified and evaluated, in order to concrete an effective therapy. Observational, descriptive and prospective study; by means of active vigilance all along 2014 in order to detect the nosocomial infections, for epidemiologic study, culture and antibiogram to identify its causal agents and antibiotics resistance and sensitivity. Among 13527 hospital discharges, 1079 displayed NI (8 %), standed out: the related on vascular lines, of surgical site, pneumonia and urinal track; they added up two thirds of the total. We carried out culture and antibiogram about 300 of them (27.8 %); identifying 31 bacterian species, mainly seven of those (77.9 %): Escherichia coli, Staphylococcus aureus and epidermidis, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Enterobacter cloacae; showing multiresistance to 34 tested antibiotics, except in seven with low or without resistance at all: vancomycin, teicoplanin, linezolid, quinupristin-dalfopristin, piperacilin-tazobactam, amikacin and carbapenems. When we contrasted those results with the recommendations in the clinical practice guides, it aroused several contradictions; so they must be taken with reserves and has to be tested in each hospital, by means of cultures and antibiograms in practically every case of nosocomial infection.
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Identity, causality, and pronoun ambiguity.
Sagi, Eyal; Rips, Lance J
2014-10-01
This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs. Copyright © 2014 Cognitive Science Society, Inc.
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Uddin, Raihan; Singh, Shiva M
2017-01-01
As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they
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Jackson, Belinda M; Abete-Luzi, Patricia; Krause, Michael W; Eisenmann, David M
2014-04-16
The Wnt signaling pathway plays a fundamental role during metazoan development, where it regulates diverse processes, including cell fate specification, cell migration, and stem cell renewal. Activation of the beta-catenin-dependent/canonical Wnt pathway up-regulates expression of Wnt target genes to mediate a cellular response. In the nematode Caenorhabditis elegans, a canonical Wnt signaling pathway regulates several processes during larval development; however, few target genes of this pathway have been identified. To address this deficit, we used a novel approach of conditionally activated Wnt signaling during a defined stage of larval life by overexpressing an activated beta-catenin protein, then used microarray analysis to identify genes showing altered expression compared with control animals. We identified 166 differentially expressed genes, of which 104 were up-regulated. A subset of the up-regulated genes was shown to have altered expression in mutants with decreased or increased Wnt signaling; we consider these genes to be bona fide C. elegans Wnt pathway targets. Among these was a group of six genes, including the cuticular collagen genes, bli-1 col-38, col-49, and col-71. These genes show a peak of expression in the mid L4 stage during normal development, suggesting a role in adult cuticle formation. Consistent with this finding, reduction of function for several of the genes causes phenotypes suggestive of defects in cuticle function or integrity. Therefore, this work has identified a large number of putative Wnt pathway target genes during larval life, including a small subset of Wnt-regulated collagen genes that may function in synthesis of the adult cuticle.
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2009-07-28
further referred to as normative models of causation. A second type of model, which are based on Pavlovian classical conditioning, is associative...covariation detection and causal judgment literature including fertilizers and plant growth; gene expression and physical traits; drug administration...Allergy Food C Reaction 4 Food Allergy Food D Reaction 1 Experimental Drug Drug A Pain Relief 2 Experimental Drug
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Directory of Open Access Journals (Sweden)
José Tomás Alvarado
2009-08-01
Full Text Available This work presents a causal conception of metaphysical modality in which a state of affairs is metaphysically possible if and only if it can be caused (in the past, the present or the future by current entities. The conception is contrasted with what is called the “combinatorial” conception of modality, in which everything can co-exist with anything else. This work explains how the notion of ‘causality’ should be construed in the causal theory, what difference exists between modalities thus defined from nomological modality, how accessibility relations between possible worlds should be interpreted, and what is the relation between the causal conception and the necessity of origin.
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Causal reasoning with mental models
Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N.
2014-01-01
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398
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Causal reasoning with mental models.
Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N
2014-01-01
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
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Causal reasoning with mental models
Directory of Open Access Journals (Sweden)
Sangeet eKhemlani
2014-10-01
Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
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Foundational perspectives on causality in large-scale brain networks
Mannino, Michael; Bressler, Steven L.
2015-12-01
A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical
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Mondal, M; Sengupta, M; Samanta, S; Sil, A; Ray, K
2012-12-15
Albinism represents a group of genetic disorders with a broad spectrum of hypopigmentary phenotypes dependent on the genetic background of the patients. Oculocutaneous albinism (OCA) patients have little or no pigment in their eyes, skin and hair, whereas ocular albinism (OA) primarily presents the ocular symptoms, and the skin and hair color may vary from near normal to very fair. Mutations in genes directly or indirectly regulating melanin production are responsible for different forms of albinism with overlapping clinical features. In this study, 27 albinistic individuals from 24 families were screened for causal variants by a PCR-sequencing based approach. TYR, OCA2, TYRP1, SLC45A2, SLC24A5, TYRP2 and SILV were selected as candidate genes. We identified 5 TYR and 3 OCA2 mutations, majority in homozygous state, in 8 unrelated patients including a case of autosomal recessive ocular albinism (AROA). A homozygous 4-nucleotide novel insertion in SLC24A5 was detected in a person showing with extreme cutaneous hypopigmentation. A potential causal variant was identified in the TYRP2 gene in a single patient. Haplotype analyses in the patients carrying homozygous mutations in the classical OCA genes suggested founder effect. This is the first report of an Indian AROA patient harboring a mutation in OCA2. Our results also reveal for the first time that mutations in SLC24A5 could contribute to extreme hypopigmentation in humans. Copyright © 2012 Elsevier B.V. All rights reserved.
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International Nuclear Information System (INIS)
Lenburg, Marc E; Liou, Louis S; Gerry, Norman P; Frampton, Garrett M; Cohen, Herbert T; Christman, Michael F
2003-01-01
Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell
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Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia
2015-01-01
With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.
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Baltussen, Tim J H; Coolen, Jordy P M; Zoll, Jan; Verweij, Paul E; Melchers, Willem J G
2018-04-26
Aspergillus fumigatus is a saprophytic fungus that extensively produces conidia. These microscopic asexually reproductive structures are small enough to reach the lungs. Germination of conidia followed by hyphal growth inside human lungs is a key step in the establishment of infection in immunocompromised patients. RNA-Seq was used to analyze the transcriptome of dormant and germinating A. fumigatus conidia. Construction of a gene co-expression network revealed four gene clusters (modules) correlated with a growth phase (dormant, isotropic growth, polarized growth). Transcripts levels of genes encoding for secondary metabolites were high in dormant conidia. During isotropic growth, transcript levels of genes involved in cell wall modifications increased. Two modules encoding for growth and cell cycle/DNA processing were associated with polarized growth. In addition, the co-expression network was used to identify highly connected intermodular hub genes. These genes may have a pivotal role in the respective module and could therefore be compelling therapeutic targets. Generally, cell wall remodeling is an important process during isotropic and polarized growth, characterized by an increase of transcripts coding for hyphal growth and cell cycle/DNA processing when polarized growth is initiated. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Use of tiling array data and RNA secondary structure predictions to identify noncoding RNA genes
DEFF Research Database (Denmark)
Weile, Christian; Gardner, Paul P; Hedegaard, Mads M
2007-01-01
neuroblastoma cell line SK-N-AS. Using this strategy, we identify thousands of human candidate RNA genes. To further verify the expression of these genes, we focused on candidate genes that had a stable hairpin structures or a high level of covariance. Using northern blotting, we verify the expression of 2 out...
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Sequence-Based Introgression Mapping Identifies Candidate White Mold Tolerance Genes in Common Bean
Directory of Open Access Journals (Sweden)
Sujan Mamidi
2016-07-01
Full Text Available White mold, caused by the necrotrophic fungus (Lib. de Bary, is a major disease of common bean ( L.. WM7.1 and WM8.3 are two quantitative trait loci (QTL with major effects on tolerance to the pathogen. Advanced backcross populations segregating individually for either of the two QTL, and a recombinant inbred (RI population segregating for both QTL were used to fine map and confirm the genetic location of the QTL. The QTL intervals were physically mapped using the reference common bean genome sequence, and the physical intervals for each QTL were further confirmed by sequence-based introgression mapping. Using whole-genome sequence data from susceptible and tolerant DNA pools, introgressed regions were identified as those with significantly higher numbers of single-nucleotide polymorphisms (SNPs relative to the whole genome. By combining the QTL and SNP data, WM7.1 was located to a 660-kb region that contained 41 gene models on the proximal end of chromosome Pv07, while the WM8.3 introgression was narrowed to a 1.36-Mb region containing 70 gene models. The most polymorphic candidate gene in the WM7.1 region encodes a BEACH-domain protein associated with apoptosis. Within the WM8.3 interval, a receptor-like protein with the potential to recognize pathogen effectors was the most polymorphic gene. The use of gene and sequence-based mapping identified two candidate genes whose putative functions are consistent with the current model of pathogenicity.
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DEFF Research Database (Denmark)
Kuhnert, Barbara; Lindner, Felix; Bentzen, Martin Mose
We introduce causal agency models as a modeling technique for representing and reasoning about ethical dilemmas. We find that ethical dilemmas, although they look similar on the surface, have very different causal structures. Based on their structural properties, as identified by the causal agency...... models, we cluster a set of dilemmas in Type 1 and Type 2 dilemmas. We observe that for Type 2 dilemmas but not for Type 1 dilemmas a utilitarian action dominates the possibility of refraining from action. Hence, we hypothesize, based on the model, that Type 2 dilemmas are perceived as less difficult...
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Heterogeneous Causal Effects and Sample Selection Bias
DEFF Research Database (Denmark)
Breen, Richard; Choi, Seongsoo; Holm, Anders
2015-01-01
The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...
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Fischer, Martin; Grossmann, Patrick; Padi, Megha; DeCaprio, James A
2016-07-27
Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Directory of Open Access Journals (Sweden)
Miranda van Uitert
Full Text Available Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite and protein-protein associations (STRING. This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome. The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300 and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.
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Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...
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Guo, Yuan; Qiu, Caisheng; Long, Songhua; Chen, Ping; Hao, Dongmei; Preisner, Marta; Wang, Hui; Wang, Yufu
2017-08-30
To better understand the molecular mechanisms and gene expression characteristics associated with development of bast fiber cell within flax stem phloem, the gene expression profiling of flax stem peels and leaves were screened, using Illumina's Digital Gene Expression (DGE) analysis. Four DGE libraries (2 for stem peel and 2 for leaf), ranging from 6.7 to 9.2 million clean reads were obtained, which produced 7.0 million and 6.8 million mapped reads for flax stem peel and leave, respectively. By differential gene expression analysis, a total of 975 genes, of which 708 (73%) genes have protein-coding annotation, were identified as phloem enriched genes putatively involved in the processes of polysaccharide and cell wall metabolism. Differential expression genes (DEGs) was validated using quantitative RT-PCR, the expression pattern of all nine genes determined by qRT-PCR fitted in well with that obtained by sequencing analysis. Cluster and Gene Ontology (GO) analysis revealed that a large number of genes related to metabolic process, catalytic activity and binding category were expressed predominantly in the stem peels. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the phloem enriched genes suggested approximately 111 biological pathways. The large number of genes and pathways produced from DGE sequencing will expand our understanding of the complex molecular and cellular events in flax bast fiber development and provide a foundation for future studies on fiber development in other bast fiber crops. Copyright © 2017 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
Jibril Hirbo
Full Text Available Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB, a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23-34% are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.
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Expert elicitation on ultrafine particles: likelihood of health effects and causal pathways
Directory of Open Access Journals (Sweden)
Brunekreef Bert
2009-07-01
Full Text Available Abstract Background Exposure to fine ambient particulate matter (PM has consistently been associated with increased morbidity and mortality. The relationship between exposure to ultrafine particles (UFP and health effects is less firmly established. If UFP cause health effects independently from coarser fractions, this could affect health impact assessment of air pollution, which would possibly lead to alternative policy options to be considered to reduce the disease burden of PM. Therefore, we organized an expert elicitation workshop to assess the evidence for a causal relationship between exposure to UFP and health endpoints. Methods An expert elicitation on the health effects of ambient ultrafine particle exposure was carried out, focusing on: 1 the likelihood of causal relationships with key health endpoints, and 2 the likelihood of potential causal pathways for cardiac events. Based on a systematic peer-nomination procedure, fourteen European experts (epidemiologists, toxicologists and clinicians were selected, of whom twelve attended. They were provided with a briefing book containing key literature. After a group discussion, individual expert judgments in the form of ratings of the likelihood of causal relationships and pathways were obtained using a confidence scheme adapted from the one used by the Intergovernmental Panel on Climate Change. Results The likelihood of an independent causal relationship between increased short-term UFP exposure and increased all-cause mortality, hospital admissions for cardiovascular and respiratory diseases, aggravation of asthma symptoms and lung function decrements was rated medium to high by most experts. The likelihood for long-term UFP exposure to be causally related to all cause mortality, cardiovascular and respiratory morbidity and lung cancer was rated slightly lower, mostly medium. The experts rated the likelihood of each of the six identified possible causal pathways separately. Out of these
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Entanglement entropy in causal set theory
Sorkin, Rafael D.; Yazdi, Yasaman K.
2018-04-01
Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1 + 1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.
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Comparative Transcriptomics to Identify Novel Genes and Pathways in Dinoflagellates
Ryan, D.
2016-02-01
The unarmored dinoflagellate Karenia brevis is among the most prominent harmful, bloom-forming phytoplankton species in the Gulf of Mexico. During blooms, the polyketides PbTx-1 and PbTx-2 (brevetoxins) are produced by K. brevis. Brevetoxins negatively impact human health and the Gulf shellfish harvest. However, the genes underlying brevetoxin synthesis are currently unknown. Because the K. brevis genome is extremely large ( 1 × 1011 base pairs long), and with a high proportion of repetitive, non-coding DNA, it has not been sequenced. In fact, large, repetitive genomes are common among the dinoflagellate group. High-throughput RNA sequencing technology enabled us to assemble Karenia transcriptomes de novo and investigate potential genes in the brevetoxin pathway through comparative transcriptomics. The brevetoxin profile varies among K. brevis clonal cultures. For example, well-documented Wilson-CCFWC268 typically produces 8-10 pg PbTx per cell, whereas SP1 produces differences in gene expression. Of the 85,000 transcripts in the K. brevis transcriptome, 4,600 transcripts, including novel unannotated orthologs and putative polyketide synthases (PKSs), were only expressed by brevetoxin-producing K. brevis and K. papilionacea, not K. mikimotoi. Examination of gene expression between the typical- and low-toxin Wilson clones identified about 3,500 genes with significantly different expression levels, including 2 putative PKSs. One of the 2 PKSs was only found in the brevetoxin-producing Karenia species. These transcriptomes could not have been characterized without high-throughput RNA sequencing.
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Directory of Open Access Journals (Sweden)
Yanara Marincevic-Zuniga
2017-08-01
Full Text Available Abstract Background Structural chromosomal rearrangements that lead to expressed fusion genes are a hallmark of acute lymphoblastic leukemia (ALL. In this study, we performed transcriptome sequencing of 134 primary ALL patient samples to comprehensively detect fusion transcripts. Methods We combined fusion gene detection with genome-wide DNA methylation analysis, gene expression profiling, and targeted sequencing to determine molecular signatures of emerging ALL subtypes. Results We identified 64 unique fusion events distributed among 80 individual patients, of which over 50% have not previously been reported in ALL. Although the majority of the fusion genes were found only in a single patient, we identified several recurrent fusion gene families defined by promiscuous fusion gene partners, such as ETV6, RUNX1, PAX5, and ZNF384, or recurrent fusion genes, such as DUX4-IGH. Our data show that patients harboring these fusion genes displayed characteristic genome-wide DNA methylation and gene expression signatures in addition to distinct patterns in single nucleotide variants and recurrent copy number alterations. Conclusion Our study delineates the fusion gene landscape in pediatric ALL, including both known and novel fusion genes, and highlights fusion gene families with shared molecular etiologies, which may provide additional information for prognosis and therapeutic options in the future.
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Common mutations identified in the MLH1 gene in familial Lynch syndrome
Directory of Open Access Journals (Sweden)
Jisha Elias
2017-12-01
In this study we identified three families with Lynch syndrome from a rural cancer center in western India (KCHRC, Goraj, Gujarat, where 70-75 CRC patients are seen annually. DNA isolated from the blood of consented family members of all three families (8-10 members/family was subjected to NGS sequencing methods on an Illumina HiSeq 4000 platform. We identified unique mutations in the MLH1 gene in all three HNPCC family members. Two of the three unrelated families shared a common mutation (154delA and 156delA. Total 8 members of a family were identified as carriers for 156delA mutation of which 5 members were unaffected while 3 were affected (age of onset: 1 member <30yrs & 2 were>40yr. The family with 154delA mutation showed 2 affected members (>40yr carrying the mutations.LYS618DEL mutation found in 8 members of the third family showed that both affected and unaffected carried the mutation. Thus the common mutations identified in the MLH1 gene in two unrelated families had a high risk for lynch syndrome especially above the age of 40.
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Causal Relationships Among Time Series of the Lange Bramke Catchment (Harz Mountains, Germany)
Aufgebauer, Britta; Hauhs, Michael; Bogner, Christina; Meesenburg, Henning; Lange, Holger
2016-04-01
Convergent Cross Mapping (CCM) has recently been introduced by Sugihara et al. for the identification and quantification of causal relationships among ecosystem variables. In particular, the method allows to decide on the direction of causality; in some cases, the causality might be bidirectional, indicating a network structure. We extend this approach by introducing a method of surrogate data to obtain confidence intervals for CCM results. We then apply this method to time series from stream water chemistry. Specifically, we analyze a set of eight dissolved major ions from three different catchments belonging to the hydrological monitoring system at the Bramke valley in the Harz Mountains, Germany. Our results demonstrate the potentials and limits of CCM as a monitoring instrument in forestry and hydrology or as a tool to identify processes in ecosystem research. While some networks of causally linked ions can be associated with simple physical and chemical processes, other results illustrate peculiarities of the three studied catchments, which are explained in the context of their special history.
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Preschoolers prefer to learn causal information
Directory of Open Access Journals (Sweden)
Aubry eAlvarez
2015-02-01
Full Text Available Young children, in general, appear to have a strong drive to explore the environment in ways that reveal its underlying causal structure. But are they really attuned specifically to casual information in this quest for understanding, or do they show equal interest in other types of non-obvious information about the world? To answer this question, we introduced 20 three-year-old children to two puppets who were anxious to tell the child about a set of novel artifacts and animals. One puppet consistently described causal properties of the items while the other puppet consistently described carefully matched non-causal properties of the same items. After a familiarization period in which children learned which type of information to expect from each informant, children were given the opportunity to choose which they wanted to hear describe each of eight pictured test items. On average, children chose to hear from the informant that provided causal descriptions on 72% of the trials. This preference for causal information has important implications for explaining the role of conceptual information in supporting early learning and may suggest means for maximizing interest and motivation in young children.
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Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman
2013-01-01
Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.
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Tamplin, Owen J; Cox, Brian J; Rossant, Janet
2011-12-15
The node and notochord are key tissues required for patterning of the vertebrate body plan. Understanding the gene regulatory network that drives their formation and function is therefore important. Foxa2 is a key transcription factor at the top of this genetic hierarchy and finding its targets will help us to better understand node and notochord development. We performed an extensive microarray-based gene expression screen using sorted embryonic notochord cells to identify early notochord-enriched genes. We validated their specificity to the node and notochord by whole mount in situ hybridization. This provides the largest available resource of notochord-expressed genes, and therefore candidate Foxa2 target genes in the notochord. Using existing Foxa2 ChIP-seq data from adult liver, we were able to identify a set of genes expressed in the notochord that had associated regions of Foxa2-bound chromatin. Given that Foxa2 is a pioneer transcription factor, we reasoned that these sites might represent notochord-specific enhancers. Candidate Foxa2-bound regions were tested for notochord specific enhancer function in a zebrafish reporter assay and 7 novel notochord enhancers were identified. Importantly, sequence conservation or predictive models could not have readily identified these regions. Mutation of putative Foxa2 binding elements in two of these novel enhancers abrogated reporter expression and confirmed their Foxa2 dependence. The combination of highly specific gene expression profiling and genome-wide ChIP analysis is a powerful means of understanding developmental pathways, even for small cell populations such as the notochord. Copyright © 2011 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Feixiong Cheng
2016-09-01
Full Text Available Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase. Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline that may be potential for antiviral indication (e.g. anti-Ebola. In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.
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Directory of Open Access Journals (Sweden)
Behzad Davarniya
Full Text Available Cognitive impairment or intellectual disability (ID is a widespread neurodevelopmental disorder characterized by low IQ (below 70. ID is genetically heterogeneous and is estimated to affect 1-3% of the world's population. In affected children from consanguineous families, autosomal recessive inheritance is common, and identifying the underlying genetic cause is an important issue in clinical genetics. In the framework of a larger project, aimed at identifying candidate genes for autosomal recessive intellectual disorder (ARID, we recently carried out single nucleotide polymorphism-based genome-wide linkage analysis in several families from Ardabil province in Iran. The identification of homozygosity-by-descent loci in these families, in combination with whole exome sequencing, led us to identify possible causative homozygous changes in two families. In the first family, a missense variant was found in GRM1 gene, while in the second family, a frameshift alteration was identified in TRMT1, both of which were found to co-segregate with the disease. GRM1, a known causal gene for autosomal recessive spinocerebellar ataxia (SCAR13, MIM#614831, encodes the metabotropic glutamate receptor1 (mGluR1. This gene plays an important role in synaptic plasticity and cerebellar development. Conversely, the TRMT1 gene encodes a tRNA methyltransferase that dimethylates a single guanine residue at position 26 of most tRNAs using S-adenosyl methionine as the methyl group donor. We recently presented TRMT1 as a candidate gene for ARID in a consanguineous Iranian family (Najmabadi et al., 2011. We believe that this second Iranian family with a biallelic loss-of-function mutation in TRMT1 gene supports the idea that this gene likely has function in development of the disorder.
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Kahrizi, Kimia; Musante, Luciana; Fattahi, Zohreh; Hosseini, Masoumeh; Maqsoud, Fariba; Farajollahi, Reza; Wienker, Thomas F.; Ropers, H. Hilger; Najmabadi, Hossein
2015-01-01
Cognitive impairment or intellectual disability (ID) is a widespread neurodevelopmental disorder characterized by low IQ (below 70). ID is genetically heterogeneous and is estimated to affect 1–3% of the world’s population. In affected children from consanguineous families, autosomal recessive inheritance is common, and identifying the underlying genetic cause is an important issue in clinical genetics. In the framework of a larger project, aimed at identifying candidate genes for autosomal recessive intellectual disorder (ARID), we recently carried out single nucleotide polymorphism-based genome-wide linkage analysis in several families from Ardabil province in Iran. The identification of homozygosity-by-descent loci in these families, in combination with whole exome sequencing, led us to identify possible causative homozygous changes in two families. In the first family, a missense variant was found in GRM1 gene, while in the second family, a frameshift alteration was identified in TRMT1, both of which were found to co-segregate with the disease. GRM1, a known causal gene for autosomal recessive spinocerebellar ataxia (SCAR13, MIM#614831), encodes the metabotropic glutamate receptor1 (mGluR1). This gene plays an important role in synaptic plasticity and cerebellar development. Conversely, the TRMT1 gene encodes a tRNA methyltransferase that dimethylates a single guanine residue at position 26 of most tRNAs using S-adenosyl methionine as the methyl group donor. We recently presented TRMT1 as a candidate gene for ARID in a consanguineous Iranian family (Najmabadi et al., 2011). We believe that this second Iranian family with a biallelic loss-of-function mutation in TRMT1 gene supports the idea that this gene likely has function in development of the disorder. PMID:26308914
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Mathematical implications of Einstein-Weyl causality
International Nuclear Information System (INIS)
Borchers, H.J.; Sen, R.N.
2006-01-01
The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics. (orig.)
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Is there a Causal Effect of High School Math on Labor Market Outcomes?
DEFF Research Database (Denmark)
Joensen, E. Juanna Schröter; Nielsen, Helena Skyt
2009-01-01
In this paper, we exploit a high school pilot scheme to identify the causal effect of advanced high school math on labor market outcomes. The pilot scheme reduced the costs of choosing advanced math because it allowed for a more flexible combination of math with other courses. We find clear...... evidence of a causal relationship between math and earnings for students who are induced to choose math after being exposed to the pilot scheme. The effect partly stems from the fact that these students end up with a higher education....
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Introductive remarks on causal inference
Directory of Open Access Journals (Sweden)
Silvana A. Romio
2013-05-01
Full Text Available One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treatment weight procedure.
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An Integrative Analysis to Identify Driver Genes in Esophageal Squamous Cell Carcinoma.
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Genta Sawada
Full Text Available Few driver genes have been well established in esophageal squamous cell carcinoma (ESCC. Identification of the genomic aberrations that contribute to changes in gene expression profiles can be used to predict driver genes.We searched for driver genes in ESCC by integrative analysis of gene expression microarray profiles and copy number data. To narrow down candidate genes, we performed survival analysis on expression data and tested the genetic vulnerability of each genes using public RNAi screening data. We confirmed the results by performing RNAi experiments and evaluating the clinical relevance of candidate genes in an independent ESCC cohort.We found 10 significantly recurrent copy number alterations accompanying gene expression changes, including loci 11q13.2, 7p11.2, 3q26.33, and 17q12, which harbored CCND1, EGFR, SOX2, and ERBB2, respectively. Analysis of survival data and RNAi screening data suggested that GRB7, located on 17q12, was a driver gene in ESCC. In ESCC cell lines harboring 17q12 amplification, knockdown of GRB7 reduced the proliferation, migration, and invasion capacities of cells. Moreover, siRNA targeting GRB7 had a synergistic inhibitory effect when combined with trastuzumab, an anti-ERBB2 antibody. Survival analysis of the independent cohort also showed that high GRB7 expression was associated with poor prognosis in ESCC.Our integrative analysis provided important insights into ESCC pathogenesis. We identified GRB7 as a novel ESCC driver gene and potential new therapeutic target.
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Zhang, Yunhua; Dai, Li; Liu, Ying; Zhang, YuHang; Wang, ShaoPeng
2017-01-01
Fruit is essential for plant reproduction and is responsible for protection and dispersal of seeds. The development and maturation of fruit is tightly regulated by numerous genetic factors that respond to environmental and internal stimulation. In this study, we attempted to identify novel fruit-related genes in a model organism, Arabidopsis thaliana, using a computational method. Based on validated fruit-related genes, the random walk with restart (RWR) algorithm was applied on a protein-protein interaction (PPI) network using these genes as seeds. The identified genes with high probabilities were filtered by the permutation test and linkage tests. In the permutation test, the genes that were selected due to the structure of the PPI network were discarded. In the linkage tests, the importance of each candidate gene was measured from two aspects: (1) its functional associations with validated genes and (2) its similarity with validated genes on gene ontology (GO) terms and KEGG pathways. Finally, 255 inferred genes were obtained, subsequent extensive analysis of important genes revealed that they mainly contribute to ubiquitination (UBQ9, UBQ8, UBQ11, UBQ10), serine hydroxymethyl transfer (SHM7, SHM5, SHM6) or glycol-metabolism (HXKL2_ARATH, CSY5, GAPCP1), suggesting essential roles during the development and maturation of fruit in Arabidopsis thaliana.
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Seo, Heewon; Kwon, Eun Jin; You, Young-Ah; Park, Yoomi; Min, Byung Joo; Yoo, Kyunghun; Hwang, Han-Sung; Kim, Ju Han; Kim, Young Ju
2018-01-24
Ritodrine is a commonly used tocolytic to prevent preterm labour. However, it can cause unexpected serious adverse reactions, such as pulmonary oedema, pulmonary congestion, and tachycardia. It is unknown whether such adverse reactions are associated with pharmacogenomic variants in patients. Whole-exome sequencing of 13 subjects with serious ritodrine-induced cardiac and pulmonary side-effects was performed to identify causal genes and variants. The deleterious impact of nonsynonymous substitutions for all genes was computed and compared between cases (n = 13) and controls (n = 30). The significant genes were annotated with Gene Ontology (GO), and the associated disease terms were categorised into four functional classes for functional enrichment tests. To assess the impact of distributed rare variants in cases with side effects, we carried out rare variant association tests with a minor allele frequency ≤ 1% using the burden test, the sequence Kernel association test (SKAT), and optimised SKAT. We identified 28 genes that showed significantly lower gene-wise deleteriousness scores in cases than in controls. Three of the identified genes-CYP1A1, CYP8B1, and SERPINA7-are pharmacokinetic genes. The significantly identified genes were categorized into four functional classes: ion binding, ATP binding, Ca 2+ -related, and ciliopathies-related. These four classes were significantly enriched with ciliary genes according to SYSCILIA Gold Standard genes (P side effects may be associated with deleterious genetic variants in ciliary and pharmacokinetic genes.
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Quasi-Experimental Designs for Causal Inference
Kim, Yongnam; Steiner, Peter
2016-01-01
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
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International Nuclear Information System (INIS)
Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt
2007-01-01
Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome
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Gravity and matter in causal set theory
International Nuclear Information System (INIS)
Sverdlov, Roman; Bombelli, Luca
2009-01-01
The goal of this paper is to propose an approach to the formulation of dynamics for causal sets and coupled matter fields. We start from the continuum version of the action for a Klein-Gordon field coupled to gravity, and rewrite it first using quantities that have a direct correspondent in the case of a causal set, namely volumes, causal relations and timelike lengths, as variables to describe the geometry. In this step, the local Lagrangian density L(f;x) for a set of fields f is recast into a quasilocal expression L 0 (f;p,q) that depends on pairs of causally related points pprq and is a function of the values of f in the Alexandrov set defined by those points, and whose limit as p and q approach a common point x is L(f;x). We then describe how to discretize L 0 (f;p,q) and use it to define a causal-set-based action.
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Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network
Directory of Open Access Journals (Sweden)
Baoman Wang
2015-01-01
Full Text Available Apoptosis is the process of programmed cell death (PCD that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature.
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Causal theory in (2+1)-dimensional Qed
International Nuclear Information System (INIS)
Scharf, G.; Wreszinski, W.F.
1994-01-01
The program of constructing the S-matrix by means of causality in quantum field theory goes back to Stueckelberg and Bogoliubov. Epstein and Glaser proposed an axiomatic construct where ultraviolet divergences do not appear, leading directly to the renormalized perturbation series. They have shown that in the causal theory the UV problem is a consequence of incorrect distribution splitting. This paper studies the causal theory in (2+1)D Qed
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How multiple causes combine: independence constraints on causal inference.
Liljeholm, Mimi
2015-01-01
According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.
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Directory of Open Access Journals (Sweden)
Fatou K. Ndiaye
2017-06-01
Full Text Available Objectives: Genome-wide association studies (GWAS have identified >100 loci independently contributing to type 2 diabetes (T2D risk. However, translational implications for precision medicine and for the development of novel treatments have been disappointing, due to poor knowledge of how these loci impact T2D pathophysiology. Here, we aimed to measure the expression of genes located nearby T2D associated signals and to assess their effect on insulin secretion from pancreatic beta cells. Methods: The expression of 104 candidate T2D susceptibility genes was measured in a human multi-tissue panel, through PCR-free expression assay. The effects of the knockdown of beta-cell enriched genes were next investigated on insulin secretion from the human EndoC-βH1 beta-cell line. Finally, we performed RNA-sequencing (RNA-seq so as to assess the pathways affected by the knockdown of the new genes impacting insulin secretion from EndoC-βH1, and we analyzed the expression of the new genes in mouse models with altered pancreatic beta-cell function. Results: We found that the candidate T2D susceptibility genes' expression is significantly enriched in pancreatic beta cells obtained by laser capture microdissection or sorted by flow cytometry and in EndoC-βH1 cells, but not in insulin sensitive tissues. Furthermore, the knockdown of seven T2D-susceptibility genes (CDKN2A, GCK, HNF4A, KCNK16, SLC30A8, TBC1D4, and TCF19 with already known expression and/or function in beta cells changed insulin secretion, supporting our functional approach. We showed first evidence for a role in insulin secretion of four candidate T2D-susceptibility genes (PRC1, SRR, ZFAND3, and ZFAND6 with no previous knowledge of presence and function in beta cells. RNA-seq in EndoC-βH1 cells with decreased expression of PRC1, SRR, ZFAND6, or ZFAND3 identified specific gene networks related to T2D pathophysiology. Finally, a positive correlation between the expression of Ins2 and the
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Causal factors in accidents of high-speed craft and conventional ocean-going vessels
International Nuclear Information System (INIS)
Antao, Pedro; Guedes Soares, C.
2008-01-01
An analysis of 40 ocean-going commercial vessel accidents is compared with the study of a similar number of high-speed crafts (HSCs) accidents, using in both cases a methodology that highlights the sequence of events leading to the accident and identifies the associated latent or causal factors. The main objective of this study was to identify and understand the difference in the pattern of causal factors associated with HSC accidents, as compared with the more traditional ocean-going ships. From the analysis one can see that the HSC accidents are mainly related to bridge personnel and operations, where the human element is the key factor identified as being responsible for the majority of the accidents. When compared with ocean-going commercial vessels, it is clear that navigational equipment and procedures have a larger preponderance in terms of the occurrence of accidents of HSC and particular attention should be given to these issues
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The mistake of the causal relationship
Directory of Open Access Journals (Sweden)
О. Д. Комаров
2015-03-01
Full Text Available The article deals with issues of the mistake of the causal relationship. The modern criminal law science approaches to the content of the mistake of the causal relationship and its significance to the qualification of the crime are described. It is proved that in cases of dolus generalis different mental attitude of the guilty person to two separate acts of his conduct exist. Consequently, in mentioned above cases mistake of the causal relationship does not have place. The rules of qualification of the crimes commited with the mistake of causation and in cases of dolus generalis are proposed .
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A genome scale RNAi screen identifies GLI1 as a novel gene regulating vorinostat sensitivity.
Falkenberg, K J; Newbold, A; Gould, C M; Luu, J; Trapani, J A; Matthews, G M; Simpson, K J; Johnstone, R W
2016-07-01
Vorinostat is an FDA-approved histone deacetylase inhibitor (HDACi) that has proven clinical success in some patients; however, it remains unclear why certain patients remain unresponsive to this agent and other HDACis. Constitutive STAT (signal transducer and activator of transcription) activation, overexpression of prosurvival Bcl-2 proteins and loss of HR23B have been identified as potential biomarkers of HDACi resistance; however, none have yet been used to aid the clinical utility of HDACi. Herein, we aimed to further elucidate vorinostat-resistance mechanisms through a functional genomics screen to identify novel genes that when knocked down by RNA interference (RNAi) sensitized cells to vorinostat-induced apoptosis. A synthetic lethal functional screen using a whole-genome protein-coding RNAi library was used to identify genes that when knocked down cooperated with vorinostat to induce tumor cell apoptosis in otherwise resistant cells. Through iterative screening, we identified 10 vorinostat-resistance candidate genes that sensitized specifically to vorinostat. One of these vorinostat-resistance genes was GLI1, an oncogene not previously known to regulate the activity of HDACi. Treatment of vorinostat-resistant cells with the GLI1 small-molecule inhibitor, GANT61, phenocopied the effect of GLI1 knockdown. The mechanism by which GLI1 loss of function sensitized tumor cells to vorinostat-induced apoptosis is at least in part through interactions with vorinostat to alter gene expression in a manner that favored apoptosis. Upon GLI1 knockdown and vorinostat treatment, BCL2L1 expression was repressed and overexpression of BCL2L1 inhibited GLI1-knockdown-mediated vorinostat sensitization. Taken together, we present the identification and characterization of GLI1 as a new HDACi resistance gene, providing a strong rationale for development of GLI1 inhibitors for clinical use in combination with HDACi therapy.
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Taguchi, Y-H
2017-12-21
Although post-traumatic stress disorder (PTSD) is primarily a mental disorder, it can cause additional symptoms that do not seem to be directly related to the central nervous system, which PTSD is assumed to directly affect. PTSD-mediated heart diseases are some of such secondary disorders. In spite of the significant correlations between PTSD and heart diseases, spatial separation between the heart and brain (where PTSD is primarily active) prevents researchers from elucidating the mechanisms that bridge the two disorders. Our purpose was to identify genes linking PTSD and heart diseases. In this study, gene expression profiles of various murine tissues observed under various types of stress or without stress were analyzed in an integrated manner using tensor decomposition (TD). Based upon the obtained features, ∼ 400 genes were identified as candidate genes that may mediate heart diseases associated with PTSD. Various gene enrichment analyses supported biological reliability of the identified genes. Ten genes encoding protein-, DNA-, or mRNA-interacting proteins-ILF2, ILF3, ESR1, ESR2, RAD21, HTT, ATF2, NR3C1, TP53, and TP63-were found to be likely to regulate expression of most of these ∼ 400 genes and therefore are candidate primary genes that cause PTSD-mediated heart diseases. Approximately 400 genes in the heart were also found to be strongly affected by various drugs whose known adverse effects are related to heart diseases and/or fear memory conditioning; these data support the reliability of our findings. TD-based unsupervised feature extraction turned out to be a useful method for gene selection and successfully identified possible genes causing PTSD-mediated heart diseases.
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International Nuclear Information System (INIS)
Wesseh, Presley K.; Zoumara, Babette
2012-01-01
This contribution investigates causal interdependence between energy consumption and economic growth in Liberia and proposes application of a bootstrap methodology. To better reflect causality, employment is incorporated as additional variable. The study demonstrates evidence of distinct bidirectional Granger causality between energy consumption and economic growth. Additionally, the results show that employment in Liberia Granger causes economic growth and apply irrespective of the short-run or long-run. Evidence from a Monte Carlo experiment reveals that the asymptotic Granger causality test suffers size distortion problem for Liberian data, suggesting that the bootstrap technique employed in this study is more appropriate. Given the empirical results, implications are that energy expansion policies like energy subsidy or low energy tariff for instance, would be necessary to cope with demand exerted as a result of economic growth in Liberia. Furthermore, Liberia might have the performance of its employment generation on the economy partly determined by adequate energy. Therefore, it seems fully justified that a quick shift towards energy production based on clean energy sources may significantly slow down economic growth in Liberia. Hence, the government’s target to implement a long-term strategy to make Liberia a carbon neutral country, and eventually less carbon dependent by 2050 is understandable. - Highlights: ► Causality between energy consumption and economic growth in Liberia investigated. ► There is bidirectional causality between energy consumption and economic growth. ► Energy expansion policies are necessary to cope with demand from economic growth. ► Asymptotic Granger causality test suffers size distortion problem for Liberian data. ► The bootstrap methodology employed in our study is more appropriate.
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Investigating Driver Fatigue versus Alertness Using the Granger Causality Network
Directory of Open Access Journals (Sweden)
Wanzeng Kong
2015-08-01
Full Text Available Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies.
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Wang, Ying; Ding, Jia-tong; Yang, Hai-ming; Yan, Zheng-jie; Cao, Wei; Li, Yang-bai
2015-01-01
Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp) were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species. PMID:26599806
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Directory of Open Access Journals (Sweden)
Ying Wang
Full Text Available Monochromatic light is widely applied to promote poultry reproductive performance, yet little is currently known regarding the mechanism by which light wavelengths affect pigeon reproduction. Recently, high-throughput sequencing technologies have been used to provide genomic information for solving this problem. In this study, we employed Illumina Hiseq 2000 to identify differentially expressed genes in ovary tissue from pigeons under blue and white light conditions and de novo transcriptome assembly to construct a comprehensive sequence database containing information on the mechanisms of follicle development. A total of 157,774 unigenes (mean length: 790 bp were obtained by the Trinity program, and 35.83% of these unigenes were matched to genes in a non-redundant protein database. Gene description, gene ontology, and the clustering of orthologous group terms were performed to annotate the transcriptome assembly. Differentially expressed genes between blue and white light conditions included those related to oocyte maturation, hormone biosynthesis, and circadian rhythm. Furthermore, 17,574 SSRs and 533,887 potential SNPs were identified in this transcriptome assembly. This work is the first transcriptome analysis of the Columba ovary using Illumina technology, and the resulting transcriptome and differentially expressed gene data can facilitate further investigations into the molecular mechanism of the effect of blue light on follicle development and reproduction in pigeons and other bird species.
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Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.
Noar, Roslyn D; Daub, Margaret E
2016-01-01
Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode
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Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.
Directory of Open Access Journals (Sweden)
Roslyn D Noar
Full Text Available Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that
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A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.
Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L
2016-03-01
Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015
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Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification
Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei
2013-01-01
Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724
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On minimizers of causal variational principles
International Nuclear Information System (INIS)
Schiefeneder, Daniela
2011-01-01
Causal variational principles are a class of nonlinear minimization problems which arise in a formulation of relativistic quantum theory referred to as the fermionic projector approach. This thesis is devoted to a numerical and analytic study of the minimizers of a general class of causal variational principles. We begin with a numerical investigation of variational principles for the fermionic projector in discrete space-time. It is shown that for sufficiently many space-time points, the minimizing fermionic projector induces non-trivial causal relations on the space-time points. We then generalize the setting by introducing a class of causal variational principles for measures on a compact manifold. In our main result we prove under general assumptions that the support of a minimizing measure is either completely timelike, or it is singular in the sense that its interior is empty. In the examples of the circle, the sphere and certain flag manifolds, the general results are supplemented by a more detailed analysis of the minimizers. (orig.)
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Energy Technology Data Exchange (ETDEWEB)
Hong, R. L., Hamaguchi, L., Busch, M. A., and Weigel, D.
2003-06-01
OAK-B135 In Arabidopsis thaliana, cis-regulatory sequences of the floral homeotic gene AGAMOUS (AG) are located in the second intron. This 3 kb intron contains binding sites for two direct activators of AG, LEAFY (LFY) and WUSCHEL (WUS), along with other putative regulatory elements. We have used phylogenetic footprinting and the related technique of phylogenetic shadowing to identify putative cis-regulatory elements in this intron. Among 29 Brassicaceae, several other motifs, but not the LFY and WUS binding sites previously identified, are largely invariant. Using reporter gene analyses, we tested six of these motifs and found that they are all functionally important for activity of AG regulatory sequences in A. thaliana. Although there is little obvious sequence similarity outside the Brassicaceae, the intron from cucumber AG has at least partial activity in A. thaliana. Our studies underscore the value of the comparative approach as a tool that complements gene-by-gene promoter dissection, but also highlight that sequence-based studies alone are insufficient for a complete identification of cis-regulatory sites.
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Yang, Lawrence H; Wonpat-Borja, Ahtoy J
2012-08-01
Identifying factors that facilitate treatment for psychotic disorders among Chinese-immigrants is crucial due to delayed treatment use. Identifying causal beliefs held by relatives that might predict identification of 'mental illness' as opposed to other 'indigenous labels' may promote more effective mental health service use. We examine what effects beliefs of 'physical causes' and other non-biomedical causal beliefs ('general social causes', and 'indigenous Chinese beliefs' or culture-specific epistemologies of illness) might have on mental illness identification. Forty-nine relatives of Chinese-immigrant consumers with psychosis were sampled. Higher endorsement of 'physical causes' was associated with mental illness labeling. However among the non-biomedical causal beliefs, 'general social causes' demonstrated no relationship with mental illness identification, while endorsement of 'indigenous Chinese beliefs' showed a negative relationship. Effective treatment- and community-based psychoeducation, in addition to emphasizing biomedical models, might integrate indigenous Chinese epistemologies of illness to facilitate rapid identification of psychotic disorders and promote treatment use.
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Consciousness and the "Causal Paradox"
Velmans, Max
1996-01-01
Viewed from a first-person perspective consciousness appears to be necessary for complex, novel human activity - but viewed from a third-person perspective consciousness appears to play no role in the activity of brains, producing a "causal paradox". To resolve this paradox one needs to distinguish consciousness of processing from consciousness accompanying processing or causing processing. Accounts of consciousness/brain causal interactions switch between first- and third-person perspectives...
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Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer
DEFF Research Database (Denmark)
Lawrenson, Kate; Iversen, Edwin S; Tyrer, Jonathan
2015-01-01
genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association......, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest...... that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene....
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Directory of Open Access Journals (Sweden)
Ian M Willis
2008-07-01
Full Text Available Transcriptional repression of ribosomal components and tRNAs is coordinately regulated in response to a wide variety of environmental stresses. Part of this response involves the convergence of different nutritional and stress signaling pathways on Maf1, a protein that is essential for repressing transcription by RNA polymerase (pol III in Saccharomyces cerevisiae. Here we identify the functions buffering yeast cells that are unable to down-regulate transcription by RNA pol III. MAF1 genetic interactions identified in screens of non-essential gene-deletions and conditionally expressed essential genes reveal a highly interconnected network of 64 genes involved in ribosome biogenesis, RNA pol II transcription, tRNA modification, ubiquitin-dependent proteolysis and other processes. A survey of non-essential MAF1 synthetic sick/lethal (SSL genes identified six gene-deletions that are defective in transcriptional repression of ribosomal protein (RP genes following rapamycin treatment. This subset of MAF1 SSL genes included MED20 which encodes a head module subunit of the RNA pol II Mediator complex. Genetic interactions between MAF1 and subunits in each structural module of Mediator were investigated to examine the functional relationship between these transcriptional regulators. Gene expression profiling identified a prominent and highly selective role for Med20 in the repression of RP gene transcription under multiple conditions. In addition, attenuated repression of RP genes by rapamycin was observed in a strain deleted for the Mediator tail module subunit Med16. The data suggest that Mediator and Maf1 function in parallel pathways to negatively regulate RP mRNA and tRNA synthesis.
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Directory of Open Access Journals (Sweden)
Paiva Renata T
2012-06-01
Full Text Available Abstract Background Thalidomide is an anti-inflammatory and anti-angiogenic drug currently used for the treatment of several diseases, including erythema nodosum leprosum, which occurs in patients with lepromatous leprosy. In this research, we use DNA microarray analysis to identify the impact of thalidomide on gene expression responses in human cells after lipopolysaccharide (LPS stimulation. We employed a two-stage framework. Initially, we identified 1584 altered genes in response to LPS. Modulation of this set of genes was then analyzed in the LPS stimulated cells treated with thalidomide. Results We identified 64 genes with altered expression induced by thalidomide using the rank product method. In addition, the lists of up-regulated and down-regulated genes were investigated by means of bioinformatics functional analysis, which allowed for the identification of biological processes affected by thalidomide. Confirmatory analysis was done in five of the identified genes using real time PCR. Conclusions The results showed some genes that can further our understanding of the biological mechanisms in the action of thalidomide. Of the five genes evaluated with real time PCR, three were down regulated and two were up regulated confirming the initial results of the microarray analysis.
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A mutation in the MATP gene causes the cream coat colour in the horse
Directory of Open Access Journals (Sweden)
Guérin Gérard
2003-01-01
Full Text Available Abstract In horses, basic colours such as bay or chestnut may be partially diluted to buckskin and palomino, or extremely diluted to cream, a nearly white colour with pink skin and blue eyes. This dilution is expected to be controlled by one gene and we used both candidate gene and positional cloning strategies to identify the "cream mutation". A horse panel including reference colours was established and typed for different markers within or in the neighbourhood of two candidate genes. Our data suggest that the causal mutation, a G to A transition, is localised in exon 2 of the MATP gene leading to an aspartic acid to asparagine substitution in the encoded protein. This conserved mutation was also described in mice and humans, but not in medaka.
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Challenges to inferring causality from viral information dispersion in dynamic social networks
Ternovski, John
2014-06-01
Understanding the mechanism behind large-scale information dispersion through complex networks has important implications for a variety of industries ranging from cyber-security to public health. With the unprecedented availability of public data from online social networks (OSNs) and the low cost nature of most OSN outreach, randomized controlled experiments, the "gold standard" of causal inference methodologies, have been used with increasing regularity to study viral information dispersion. And while these studies have dramatically furthered our understanding of how information disseminates through social networks by isolating causal mechanisms, there are still major methodological concerns that need to be addressed in future research. This paper delineates why modern OSNs are markedly different from traditional sociological social networks and why these differences present unique challenges to experimentalists and data scientists. The dynamic nature of OSNs is particularly troublesome for researchers implementing experimental designs, so this paper identifies major sources of bias arising from network mutability and suggests strategies to circumvent and adjust for these biases. This paper also discusses the practical considerations of data quality and collection, which may adversely impact the efficiency of the estimator. The major experimental methodologies used in the current literature on virality are assessed at length, and their strengths and limits identified. Other, as-yetunsolved threats to the efficiency and unbiasedness of causal estimators--such as missing data--are also discussed. This paper integrates methodologies and learnings from a variety of fields under an experimental and data science framework in order to systematically consolidate and identify current methodological limitations of randomized controlled experiments conducted in OSNs.
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Ariyarathna, H A Chandima K; Oldach, Klaus H; Francki, Michael G
2016-01-19
Although the HKT transporter genes ascertain some of the key determinants of crop salt tolerance mechanisms, the diversity and functional role of group II HKT genes are not clearly understood in bread wheat. The advanced knowledge on rice HKT and whole genome sequence was, therefore, used in comparative gene analysis to identify orthologous wheat group II HKT genes and their role in trait variation under different saline environments. The four group II HKTs in rice identified two orthologous gene families from bread wheat, including the known TaHKT2;1 gene family and a new distinctly different gene family designated as TaHKT2;2. A single copy of TaHKT2;2 was found on each homeologous chromosome arm 7AL, 7BL and 7DL and each gene was expressed in leaf blade, sheath and root tissues under non-stressed and at 200 mM salt stressed conditions. The proteins encoded by genes of the TaHKT2;2 family revealed more than 93% amino acid sequence identity but ≤52% amino acid identity compared to the proteins encoded by TaHKT2;1 family. Specifically, variations in known critical domains predicted functional differences between the two protein families. Similar to orthologous rice genes on chromosome 6L, TaHKT2;1 and TaHKT2;2 genes were located approximately 3 kb apart on wheat chromosomes 7AL, 7BL and 7DL, forming a static syntenic block in the two species. The chromosomal region on 7AL containing TaHKT2;1 7AL-1 co-located with QTL for shoot Na(+) concentration and yield in some saline environments. The differences in copy number, genes sequences and encoded proteins between TaHKT2;2 homeologous genes and other group II HKT gene families within and across species likely reflect functional diversity for ion selectivity and transport in plants. Evidence indicated that neither TaHKT2;2 nor TaHKT2;1 were associated with primary root Na(+) uptake but TaHKT2;1 may be associated with trait variation for Na(+) exclusion and yield in some but not all saline environments.
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Frewen, Paul A; Schmittmann, Verena D; Bringmann, Laura F; Borsboom, Denny
2013-01-01
Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. The present study utilized Perceived Causal Relations (PCR) scaling in order to assess participants' own attributions concerning whether and to what degree these co-occurring problems may be causally interrelated. 288 young adults rated the frequency and respective PCR scores associating their symptoms of posttraumatic reexperiencing, depression, anxiety, and guilt-shame. PCR scores were found to moderate associations between the frequency of posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame. Network analyses showed that the number of feedback loops between PCR scores was positively associated with symptom frequencies. Results tentatively support the interpretation of PCR scores as moderators of the association between different psychological problems, and lend support to the hypothesis that increased symptom frequencies are observed in the presence of an increased number of causal feedback loops between symptoms. Additionally, a perceived causal role for the reexperiencing of traumatic memories in exacerbating emotional disturbance was identified.
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Directory of Open Access Journals (Sweden)
Paul A. Frewen
2013-08-01
Full Text Available Background: Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. Objectives: The present study utilized Perceived Causal Relations (PCR scaling in order to assess participants’ own attributions concerning whether and to what degree these co-occurring problems may be causally interrelated. Methods: 288 young adults rated the frequency and respective PCR scores associating their symptoms of posttraumatic reexperiencing, depression, anxiety, and guilt-shame. Results: PCR scores were found to moderate associations between the frequency of posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame. Network analyses showed that the number of feedback loops between PCR scores was positively associated with symptom frequencies. Conclusion: Results tentatively support the interpretation of PCR scores as moderators of the association between different psychological problems, and lend support to the hypothesis that increased symptom frequencies are observed in the presence of an increased number of causal feedback loops between symptoms. Additionally, a perceived causal role for the reexperiencing of traumatic memories in exacerbating emotional disturbance was identified.
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A Morpholino-based screen to identify novel genes involved in craniofacial morphogenesis
Melvin, Vida Senkus; Feng, Weiguo; Hernandez-Lagunas, Laura; Artinger, Kristin Bruk; Williams, Trevor
2014-01-01
BACKGROUND The regulatory mechanisms underpinning facial development are conserved between diverse species. Therefore, results from model systems provide insight into the genetic causes of human craniofacial defects. Previously, we generated a comprehensive dataset examining gene expression during development and fusion of the mouse facial prominences. Here, we used this resource to identify genes that have dynamic expression patterns in the facial prominences, but for which only limited information exists concerning developmental function. RESULTS This set of ~80 genes was used for a high throughput functional analysis in the zebrafish system using Morpholino gene knockdown technology. This screen revealed three classes of cranial cartilage phenotypes depending upon whether knockdown of the gene affected the neurocranium, viscerocranium, or both. The targeted genes that produced consistent phenotypes encoded proteins linked to transcription (meis1, meis2a, tshz2, vgll4l), signaling (pkdcc, vlk, macc1, wu:fb16h09), and extracellular matrix function (smoc2). The majority of these phenotypes were not altered by reduction of p53 levels, demonstrating that both p53 dependent and independent mechanisms were involved in the craniofacial abnormalities. CONCLUSIONS This Morpholino-based screen highlights new genes involved in development of the zebrafish craniofacial skeleton with wider relevance to formation of the face in other species, particularly mouse and human. PMID:23559552
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Bayesian nonparametric generative models for causal inference with missing at random covariates.
Roy, Jason; Lum, Kirsten J; Zeldow, Bret; Dworkin, Jordan D; Re, Vincent Lo; Daniels, Michael J
2018-03-26
We propose a general Bayesian nonparametric (BNP) approach to causal inference in the point treatment setting. The joint distribution of the observed data (outcome, treatment, and confounders) is modeled using an enriched Dirichlet process. The combination of the observed data model and causal assumptions allows us to identify any type of causal effect-differences, ratios, or quantile effects, either marginally or for subpopulations of interest. The proposed BNP model is well-suited for causal inference problems, as it does not require parametric assumptions about the distribution of confounders and naturally leads to a computationally efficient Gibbs sampling algorithm. By flexibly modeling the joint distribution, we are also able to impute (via data augmentation) values for missing covariates within the algorithm under an assumption of ignorable missingness, obviating the need to create separate imputed data sets. This approach for imputing the missing covariates has the additional advantage of guaranteeing congeniality between the imputation model and the analysis model, and because we use a BNP approach, parametric models are avoided for imputation. The performance of the method is assessed using simulation studies. The method is applied to data from a cohort study of human immunodeficiency virus/hepatitis C virus co-infected patients. © 2018, The International Biometric Society.
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Time-varying causal network of the Korean financial system based on firm-specific risk premiums
Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin
2016-09-01
The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.
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Testing the Causal Direction of Mediation Effects in Randomized Intervention Studies.
Wiedermann, Wolfgang; Li, Xintong; von Eye, Alexander
2018-05-21
In a recent update of the standards for evidence in research on prevention interventions, the Society of Prevention Research emphasizes the importance of evaluating and testing the causal mechanism through which an intervention is expected to have an effect on an outcome. Mediation analysis is commonly applied to study such causal processes. However, these analytic tools are limited in their potential to fully understand the role of theorized mediators. For example, in a design where the treatment x is randomized and the mediator (m) and the outcome (y) are measured cross-sectionally, the causal direction of the hypothesized mediator-outcome relation is not uniquely identified. That is, both mediation models, x → m → y or x → y → m, may be plausible candidates to describe the underlying intervention theory. As a third explanation, unobserved confounders can still be responsible for the mediator-outcome association. The present study introduces principles of direction dependence which can be used to empirically evaluate these competing explanatory theories. We show that, under certain conditions, third higher moments of variables (i.e., skewness and co-skewness) can be used to uniquely identify the direction of a mediator-outcome relation. Significance procedures compatible with direction dependence are introduced and results of a simulation study are reported that demonstrate the performance of the tests. An empirical example is given for illustrative purposes and a software implementation of the proposed method is provided in SPSS.
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Guo, Xingyi; Shi, Jiajun; Cai, Qiuyin; Shu, Xiao-Ou; He, Jing; Wen, Wanqing; Allen, Jamie; Pharoah, Paul; Dunning, Alison; Hunter, David J; Kraft, Peter; Easton, Douglas F; Zheng, Wei; Long, Jirong
2018-03-01
Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.
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Resting-state brain networks revealed by granger causal connectivity in frogs.
Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong
2016-10-15
Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
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Al-sbou, Mohammed
2012-06-01
This study was conducted to identify mutations in the homogentisate 1,2 dioxygenase gene (HGD) in alkaptonuria patients among Jordanian population. Blood samples were collected from four alkaptonuria patients, four carriers, and two healthy volunteers. DNA was isolated from peripheral blood. All 14 exons of the HGD gene were amplified using the polymerase chain reaction (PCR) technique. The PCR products were then purified and analyzed by sequencing. Five mutations were identified in our samples. Four of them were novel C1273A, T1046G, 551-552insG, T533G and had not been previously reported, and one mutation T847C has been described before. The types of mutations identified were two missense mutations, one splice site mutation, one frameshift mutation, and one polymorphism. We present the first molecular study of the HGD gene in Jordanian alkaptonuria patients. This study provides valuable information about the molecular basis of alkaptonuria in Jordanian population.
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International Nuclear Information System (INIS)
Golubovskaya, Vita M.; Ho, Baotran; Conroy, Jeffrey; Liu, Song; Wang, Dan; Cance, William G.
2014-01-01
Focal Adhesion Kinase (FAK) is a non-receptor kinase that plays an important role in many cellular processes: adhesion, proliferation, invasion, angiogenesis, metastasis and survival. Recently, we have shown that Roslin 2 or R2 (1-benzyl-15,3,5,7-tetraazatricyclo[3.3.1.1~3,7~]decane) compound disrupts FAK and p53 proteins, activates p53 transcriptional activity, and blocks tumor growth. In this report we performed a microarray gene expression analysis of R2-treated HCT116 p53 +/+ and p53 −/− cells and detected 1484 genes that were significantly up- or down-regulated (p < 0.05) in HCT116 p53 +/+ cells but not in p53 −/− cells. Among up-regulated genes in HCT p53 +/+ cells we detected critical p53 targets: Mdm-2, Noxa-1, and RIP1. Among down-regulated genes, Met, PLK2, KIF14, BIRC2 and other genes were identified. In addition, a combination of R2 compound with M13 compound that disrupts FAK and Mmd-2 complex or R2 and Nutlin-1 that disrupts Mdm-2 and p53 decreased clonogenicity of HCT116 p53 +/+ colon cancer cells more significantly than each agent alone in a p53-dependent manner. Thus, the report detects gene expression profile in response to R2 treatment and demonstrates that the combination of drugs targeting FAK, Mdm-2, and p53 can be a novel therapy approach
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Expression profiles of variation integration genes in bladder urothelial carcinoma.
Wang, J M; Wang, Y Q; Gao, Z L; Wu, J T; Shi, B K; Yu, C C
2014-04-30
Bladder cancer is a common cancer worldwide and its incidence continues to increase. There are approximately 261,000 cases of bladder cancer resulting in 115,000 deaths annually. This study aimed to integrate bladder cancer genome copy number variation information and bladder cancer gene transcription level expression data to construct a causal-target module network of the range of bladder cancer-related genomes. Here, we explored the control mechanism underlying bladder cancer phenotype expression regulation by the major bladder cancer genes. We selected 22 modules as the initial module network to expand the search to screen more networks. After bootstrapping 100 times, we obtained 16 key regulators. These 16 key candidate regulatory genes were further expanded to identify the expression changes of 11,676 genes in 275 modules, which may all have the same regulation. In conclusion, a series of modules associated with the terms 'cancer' or 'bladder' were considered to constitute a potential network.
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Directory of Open Access Journals (Sweden)
Sarah Rousseau
Full Text Available Among farm animals, pigs are known to show XX sex-reversal. In such cases the individuals are genetically female but exhibit a hermaphroditism, or a male phenotype. While the frequency of this congenital disease is quite low (less than 1%, the economic losses are significant for pig breeders. These losses result from sterility, urogenital infections and the carcasses being downgraded because of the risk of boar taint. It has been clearly demonstrated that the SRY gene is not involved in most cases of sex-reversal in pigs, and that autosomal recessive mutations remain to be discovered. A whole-genome scan analysis was performed in the French Large-White population to identify candidate genes: 38 families comprising the two non-affected parents and 1 to 11 sex-reversed full-sib piglets were genotyped with the PorcineSNP60 BeadChip. A Transmission Disequilibrium Test revealed a highly significant candidate region on SSC12 (most significant p-value<4.65.10(-10 containing the SOX9 gene. SOX9, one of the master genes involved in testis differentiation, was sequenced together with one of its main regulatory region Tesco. However, no causal mutations could be identified in either of the two sequenced regions. Further haplotype analyses did not identify a shared homozygous segment between the affected pigs, suggesting either a lack of power due to the SNP properties of the chip, or a second causative locus. Together with information from humans and mice, this study in pigs adds to the field of knowledge, which will lead to characterization of novel molecular mechanisms regulating sexual differentiation and dysregulation in cases of sex reversal.
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Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize.
Kelley, Rowena Y; Gresham, Cathy; Harper, Jonathan; Bridges, Susan M; Warburton, Marilyn L; Hawkins, Leigh K; Pechanova, Olga; Peethambaran, Bela; Pechan, Tibor; Luthe, Dawn S; Mylroie, J E; Ankala, Arunkanth; Ozkan, Seval; Henry, W B; Williams, W P
2010-10-07
Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database
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Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis.
Directory of Open Access Journals (Sweden)
Nigel P S Crawford
2007-11-01
Full Text Available A novel candidate metastasis modifier, ribosomal RNA processing 1 homolog B (Rrp1b, was identified through two independent approaches. First, yeast two-hybrid, immunoprecipitation, and functional assays demonstrated a physical and functional interaction between Rrp1b and the previous identified metastasis modifier Sipa1. In parallel, using mouse and human metastasis gene expression data it was observed that extracellular matrix (ECM genes are common components of metastasis predictive signatures, suggesting that ECM genes are either important markers or causal factors in metastasis. To investigate the relationship between ECM genes and poor prognosis in breast cancer, expression quantitative trait locus analysis of polyoma middle-T transgene-induced mammary tumor was performed. ECM gene expression was found to be consistently associated with Rrp1b expression. In vitro expression of Rrp1b significantly altered ECM gene expression, tumor growth, and dissemination in metastasis assays. Furthermore, a gene signature induced by ectopic expression of Rrp1b in tumor cells predicted survival in a human breast cancer gene expression dataset. Finally, constitutional polymorphism within RRP1B was found to be significantly associated with tumor progression in two independent breast cancer cohorts. These data suggest that RRP1B may be a novel susceptibility gene for breast cancer progression and metastasis.
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A general, multivariate definition of causal effects in epidemiology.
Flanders, W Dana; Klein, Mitchel
2015-07-01
Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias.
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Exome sequencing in 53 sporadic cases of schizophrenia identifies 18 putative candidate genes.
Directory of Open Access Journals (Sweden)
Michel Guipponi
Full Text Available Schizophrenia (SCZ is a severe, debilitating mental illness which has a significant genetic component. The identification of genetic factors related to SCZ has been challenging and these factors remain largely unknown. To evaluate the contribution of de novo variants (DNVs to SCZ, we sequenced the exomes of 53 individuals with sporadic SCZ and of their non-affected parents. We identified 49 DNVs, 18 of which were predicted to alter gene function, including 13 damaging missense mutations, 2 conserved splice site mutations, 2 nonsense mutations, and 1 frameshift deletion. The average number of exonic DNV per proband was 0.88, which corresponds to an exonic point mutation rate of 1.7×10(-8 per nucleotide per generation. The non-synonymous-to-synonymous mutation ratio of 2.06 did not differ from neutral expectations. Overall, this study provides a list of 18 putative candidate genes for sporadic SCZ, and when combined with the results of similar reports, identifies a second proband carrying a non-synonymous DNV in the RGS12 gene.
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Information causality from an entropic and a probabilistic perspective
International Nuclear Information System (INIS)
Al-Safi, Sabri W.; Short, Anthony J.
2011-01-01
The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.
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Causal Modeling of Secondary Science Students' Intentions to Enroll in Physics.
Crawley, Frank E.; Black, Carolyn B.
1992-01-01
Reports a study using the causal modeling method to verify underlying causes of student interest in enrolling in physics as predicted by the theory of planned behavior. Families were identified as major referents in the social support system for physics enrollment. Course and extracurricular conflicts and fear of failure were primary beliefs…
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Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik
2014-01-01
Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994
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Causal Mediation Analysis: Warning! Assumptions Ahead
Keele, Luke
2015-01-01
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…
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How to Be Causal: Time, Spacetime and Spectra
Kinsler, Paul
2011-01-01
I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers-Kronig relations. The specification of causality in terms of temporal differential equations then shows us the way to write down dynamical models so that their causal nature "in the sense used here" should be obvious to all. To extend existing…
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Fusco, Dahlene N; Brisac, Cynthia; John, Sinu P; Huang, Yi-Wen; Chin, Christopher R; Xie, Tiao; Zhao, Hong; Jilg, Nikolaus; Zhang, Leiliang; Chevaliez, Stephane; Wambua, Daniel; Lin, Wenyu; Peng, Lee; Chung, Raymond T; Brass, Abraham L
2013-06-01
Hepatitis C virus (HCV) infection is a leading cause of end-stage liver disease. Interferon-α (IFNα) is an important component of anti-HCV therapy; it up-regulates transcription of IFN-stimulated genes, many of which have been investigated for their antiviral effects. However, all of the genes required for the antiviral function of IFNα (IFN effector genes [IEGs]) are not known. IEGs include not only IFN-stimulated genes, but other nontranscriptionally induced genes that are required for the antiviral effect of IFNα. In contrast to candidate approaches based on analyses of messenger RNA (mRNA) expression, identification of IEGs requires a broad functional approach. We performed an unbiased genome-wide small interfering RNA screen to identify IEGs that inhibit HCV. Huh7.5.1 hepatoma cells were transfected with small interfering RNAs incubated with IFNα and then infected with JFH1 HCV. Cells were stained using HCV core antibody, imaged, and analyzed to determine the percent infection. Candidate IEGs detected in the screen were validated and analyzed further. The screen identified 120 previously unreported IEGs. From these, we more fully evaluated the following: asparagine-linked glycosylation 10 homolog (yeast, α-1,2-glucosyltransferase); butyrylcholinesterase; dipeptidyl-peptidase 4 (CD26, adenosine deaminase complexing protein 2); glucokinase (hexokinase 4) regulator; guanylate cyclase 1, soluble, β 3; MYST histone acetyltransferase 1; protein phosphatase 3 (formerly 2B), catalytic subunit, β isoform; peroxisomal proliferator-activated receptor-γ-DBD-interacting protein 1; and solute carrier family 27 (fatty acid transporter), member 2; and demonstrated that they enabled IFNα-mediated suppression of HCV at multiple steps of its life cycle. Expression of these genes had more potent effects against flaviviridae because a subset was required for IFNα to suppress dengue virus but not influenza A virus. In addition, many of the host genes detected in this
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Markovits, Henry
2014-12-01
Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Ning Zhao
2017-08-01
Full Text Available Non-target-site resistance (NTSR to herbicides is a worldwide concern for weed control. However, as the dominant NTSR mechanism in weeds, metabolic resistance is not yet well-characterized at the genetic level. For this study, we have identified a shortawn foxtail (Alopecurus aequalis Sobol. population displaying both TSR and NTSR to mesosulfuron-methyl and fenoxaprop-P-ethyl, yet the molecular basis for this NTSR remains unclear. To investigate the mechanisms of metabolic resistance, an RNA-Seq transcriptome analysis was used to find candidate genes that may confer metabolic resistance to the herbicide mesosulfuron-methyl in this plant population. The RNA-Seq libraries generated 831,846,736 clean reads. The de novo transcriptome assembly yielded 95,479 unigenes (averaging 944 bp in length that were assigned putative annotations. Among these, a total of 29,889 unigenes were assigned to 67 GO terms that contained three main categories, and 14,246 unigenes assigned to 32 predicted KEGG metabolic pathways. Global gene expression was measured using the reads generated from the untreated control (CK, water-only control (WCK, and mesosulfuron-methyl treatment (T of R and susceptible (S. Contigs that showed expression differences between mesosulfuron-methyl-treated R and S biotypes, and between mesosulfuron-methyl-treated, water-treated and untreated R plants were selected for further quantitative real-time PCR (qRT-PCR validation analyses. Seventeen contigs were consistently highly expressed in the resistant A. aequalis plants, including four cytochrome P450 monooxygenase (CytP450 genes, two glutathione S-transferase (GST genes, two glucosyltransferase (GT genes, two ATP-binding cassette (ABC transporter genes, and seven additional contigs with functional annotations related to oxidation, hydrolysis, and plant stress physiology. These 17 contigs could serve as major candidate genes for contributing to metabolic mesosulfuron-methyl resistance; hence
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Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella
2018-01-01
Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723
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Knowles, Emma E M; Carless, Melanie A; de Almeida, Marcio A A; Curran, Joanne E; McKay, D Reese; Sprooten, Emma; Dyer, Thomas D; Göring, Harald H; Olvera, Rene; Fox, Peter; Almasy, Laura; Duggirala, Ravi; Kent, Jack W; Blangero, John; Glahn, David C
2014-01-01
It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis. © 2013 Wiley Periodicals, Inc.
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Directory of Open Access Journals (Sweden)
Bordeaux John M
2011-05-01
Full Text Available Abstract Background Global transcriptional analysis of loblolly pine (Pinus taeda L. is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes. Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01. Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs including those with significant homology (E-values ≤ 2 × 10-30 to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in
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2011-01-01
Background Global transcriptional analysis of loblolly pine (Pinus taeda L.) is challenging due to limited molecular tools. PtGen2, a 26,496 feature cDNA microarray, was fabricated and used to assess drought-induced gene expression in loblolly pine propagule roots. Statistical analysis of differential expression and weighted gene correlation network analysis were used to identify drought-responsive genes and further characterize the molecular basis of drought tolerance in loblolly pine. Results Microarrays were used to interrogate root cDNA populations obtained from 12 genotype × treatment combinations (four genotypes, three watering regimes). Comparison of drought-stressed roots with roots from the control treatment identified 2445 genes displaying at least a 1.5-fold expression difference (false discovery rate = 0.01). Genes commonly associated with drought response in pine and other plant species, as well as a number of abiotic and biotic stress-related genes, were up-regulated in drought-stressed roots. Only 76 genes were identified as differentially expressed in drought-recovered roots, indicating that the transcript population can return to the pre-drought state within 48 hours. Gene correlation analysis predicts a scale-free network topology and identifies eleven co-expression modules that ranged in size from 34 to 938 members. Network topological parameters identified a number of central nodes (hubs) including those with significant homology (E-values ≤ 2 × 10-30) to 9-cis-epoxycarotenoid dioxygenase, zeatin O-glucosyltransferase, and ABA-responsive protein. Identified hubs also include genes that have been associated previously with osmotic stress, phytohormones, enzymes that detoxify reactive oxygen species, and several genes of unknown function. Conclusion PtGen2 was used to evaluate transcriptome responses in loblolly pine and was leveraged to identify 2445 differentially expressed genes responding to severe drought stress in roots. Many of the
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Ramirez-Córdova, Jesús; Drnevich, Jenny; Madrigal-Pulido, Jaime Alberto; Arrizon, Javier; Allen, Kirk; Martínez-Velázquez, Moisés; Alvarez-Maya, Ikuri
2012-08-01
During ethanol fermentation, yeast cells are exposed to stress due to the accumulation of ethanol, cell growth is altered and the output of the target product is reduced. For Agave beverages, like tequila, no reports have been published on the global gene expression under ethanol stress. In this work, we used microarray analysis to identify Saccharomyces cerevisiae genes involved in the ethanol response. Gene expression of a tequila yeast strain of S. cerevisiae (AR5) was explored by comparing global gene expression with that of laboratory strain S288C, both after ethanol exposure. Additionally, we used two different culture conditions, cells grown in Agave tequilana juice as a natural fermentation media or grown in yeast-extract peptone dextrose as artificial media. Of the 6368 S. cerevisiae genes in the microarray, 657 genes were identified that had different expression responses to ethanol stress due to strain and/or media. A cluster of 28 genes was found over-expressed specifically in the AR5 tequila strain that could be involved in the adaptation to tequila yeast fermentation, 14 of which are unknown such as yor343c, ylr162w, ygr182c, ymr265c, yer053c-a or ydr415c. These could be the most suitable genes for transforming tequila yeast to increase ethanol tolerance in the tequila fermentation process. Other genes involved in response to stress (RFC4, TSA1, MLH1, PAU3, RAD53) or transport (CYB2, TIP20, QCR9) were expressed in the same cluster. Unknown genes could be good candidates for the development of recombinant yeasts with ethanol tolerance for use in industrial tequila fermentation.
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DEFF Research Database (Denmark)
Husemoen, LL; Toft, U.; Fenger, Mogens
2006-01-01
BACKGROUND: Deficiency of folate has been associated with several disorders characterized by enhanced activation of the cellular immune system (non-allergic th1 type immune response). Whether folate status is also associated with atopic disease (allergic th2 type immune response) is unknown. We....../CT individuals [odds ratio 1.76, 95% confidence interval (95% CI) 1.19-2.60]. Additionally, gene-diet interaction effects were identified. Dietary markers were negatively associated with risk of atopy in persons with the TT genotype. Total homocysteine was not related to atopy (odds ratio per 5 mumol/l = 1.......12, 95% CI 0.98-1.29). CONCLUSIONS: The results suggest that an impaired folate metabolism may be causally related to the development of atopy....
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Wright, Robin; Parrish, Mark L; Cadera, Emily; Larson, Lynnelle; Matson, Clinton K; Garrett-Engele, Philip; Armour, Chris; Lum, Pek Yee; Shoemaker, Daniel D
2003-07-30
Increased levels of HMG-CoA reductase induce cell type- and isozyme-specific proliferation of the endoplasmic reticulum. In yeast, the ER proliferations induced by Hmg1p consist of nuclear-associated stacks of smooth ER membranes known as karmellae. To identify genes required for karmellae assembly, we compared the composition of populations of homozygous diploid S. cerevisiae deletion mutants following 20 generations of growth with and without karmellae. Using an initial population of 1,557 deletion mutants, 120 potential mutants were identified as a result of three independent experiments. Each experiment produced a largely non-overlapping set of potential mutants, suggesting that differences in specific growth conditions could be used to maximize the comprehensiveness of similar parallel analysis screens. Only two genes, UBC7 and YAL011W, were identified in all three experiments. Subsequent analysis of individual mutant strains confirmed that each experiment was identifying valid mutations, based on the mutant's sensitivity to elevated HMG-CoA reductase and inability to assemble normal karmellae. The largest class of HMG-CoA reductase-sensitive mutations was a subset of genes that are involved in chromatin structure and transcriptional regulation, suggesting that karmellae assembly requires changes in transcription or that the presence of karmellae may interfere with normal transcriptional regulation. Copyright 2003 John Wiley & Sons, Ltd.
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BOLD Granger causality reflects vascular anatomy.
Directory of Open Access Journals (Sweden)
J Taylor Webb
Full Text Available A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group, as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.
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Capturing cognitive causal paths in human reliability analysis with Bayesian network models
International Nuclear Information System (INIS)
Zwirglmaier, Kilian; Straub, Daniel; Groth, Katrina M.
2017-01-01
reIn the last decade, Bayesian networks (BNs) have been identified as a powerful tool for human reliability analysis (HRA), with multiple advantages over traditional HRA methods. In this paper we illustrate how BNs can be used to include additional, qualitative causal paths to provide traceability. The proposed framework provides the foundation to resolve several needs frequently expressed by the HRA community. First, the developed extended BN structure reflects the causal paths found in cognitive psychology literature, thereby addressing the need for causal traceability and strong scientific basis in HRA. Secondly, the use of node reduction algorithms allows the BN to be condensed to a level of detail at which quantification is as straightforward as the techniques used in existing HRA. We illustrate the framework by developing a BN version of the critical data misperceived crew failure mode in the IDHEAS HRA method, which is currently under development at the US NRC . We illustrate how the model could be quantified with a combination of expert-probabilities and information from operator performance databases such as SACADA. This paper lays the foundations necessary to expand the cognitive and quantitative foundations of HRA. - Highlights: • A framework for building traceable BNs for HRA, based on cognitive causal paths. • A qualitative BN structure, directly showing these causal paths is developed. • Node reduction algorithms are used for making the BN structure quantifiable. • BN quantified through expert estimates and observed data (Bayesian updating). • The framework is illustrated for a crew failure mode of IDHEAS.
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Gene discovery by chemical mutagenesis and whole-genome sequencing in Dictyostelium.
Li, Cheng-Lin Frank; Santhanam, Balaji; Webb, Amanda Nicole; Zupan, Blaž; Shaulsky, Gad
2016-09-01
Whole-genome sequencing is a useful approach for identification of chemical-induced lesions, but previous applications involved tedious genetic mapping to pinpoint the causative mutations. We propose that saturation mutagenesis under low mutagenic loads, followed by whole-genome sequencing, should allow direct implication of genes by identifying multiple independent alleles of each relevant gene. We tested the hypothesis by performing three genetic screens with chemical mutagenesis in the social soil amoeba Dictyostelium discoideum Through genome sequencing, we successfully identified mutant genes with multiple alleles in near-saturation screens, including resistance to intense illumination and strong suppressors of defects in an allorecognition pathway. We tested the causality of the mutations by comparison to published data and by direct complementation tests, finding both dominant and recessive causative mutations. Therefore, our strategy provides a cost- and time-efficient approach to gene discovery by integrating chemical mutagenesis and whole-genome sequencing. The method should be applicable to many microbial systems, and it is expected to revolutionize the field of functional genomics in Dictyostelium by greatly expanding the mutation spectrum relative to other common mutagenesis methods. © 2016 Li et al.; Published by Cold Spring Harbor Laboratory Press.
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Veturi, Yogasudha; Ritchie, Marylyn D
2018-01-01
Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each
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The causal structure of utility conditionals.
Bonnefon, Jean-François; Sloman, Steven A
2013-01-01
The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.
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Marenholz, Ingo; Grosche, Sarah; Kalb, Birgit; Rüschendorf, Franz; Blümchen, Katharina; Schlags, Rupert; Harandi, Neda; Price, Mareike; Hansen, Gesine; Seidenberg, Jürgen; Röblitz, Holger; Yürek, Songül; Tschirner, Sebastian; Hong, Xiumei; Wang, Xiaobin; Homuth, Georg; Schmidt, Carsten O; Nöthen, Markus M; Hübner, Norbert; Niggemann, Bodo; Beyer, Kirsten; Lee, Young-Ae
2017-10-20
Genetic factors and mechanisms underlying food allergy are largely unknown. Due to heterogeneity of symptoms a reliable diagnosis is often difficult to make. Here, we report a genome-wide association study on food allergy diagnosed by oral food challenge in 497 cases and 2387 controls. We identify five loci at genome-wide significance, the clade B serpin (SERPINB) gene cluster at 18q21.3, the cytokine gene cluster at 5q31.1, the filaggrin gene, the C11orf30/LRRC32 locus, and the human leukocyte antigen (HLA) region. Stratifying the results for the causative food demonstrates that association of the HLA locus is peanut allergy-specific whereas the other four loci increase the risk for any food allergy. Variants in the SERPINB gene cluster are associated with SERPINB10 expression in leukocytes. Moreover, SERPINB genes are highly expressed in the esophagus. All identified loci are involved in immunological regulation or epithelial barrier function, emphasizing the role of both mechanisms in food allergy.
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Kimaru, S K; Monda, E; Cheruiyot, R C; Mbaka, J; Alakonya, A
2018-01-01
Anthracnose disease of avocado contributes to a huge loss of avocado fruits due to postharvest rot in Kenya. The causal agent of this disease has not been clear but presumed to be Colletotrichum gloeosporioides as reported in other regions where avocado is grown. The fungus mainly infects fruits causing symptoms such as small blackish spots, "pepper spots," and black spots with raised margin which coalesce as infection progresses. Due to economic losses associated with the disease and emerging information of other species of fungi as causal agents of the disease, this study was aimed at identifying causal agent(s) of the disease. A total of 80 fungal isolates were collected from diseased avocado fruits in Murang'a County, the main avocado growing region in Kenya. Forty-six isolates were morphologically identified as Colletotrichum spp. based on their cultural characteristics, mainly whitish, greyish, and creamish colour and cottony/velvety mycelia on the top side of the culture and greyish cream with concentric zonation on the reverse side. Their spores were straight with rounded end and nonseptate. Thirty-four isolates were identified as Pestalotiopsis spp. based on their cultural characteristics: whitish grey mycelium with black fruiting structure on the upper side and greyish black one on the lower side and septate spores with 3-4 septa and 2 or 3 appendages at one end. Further molecular studies using ITS indicated Colletotrichum gloeosporioides , Colletotrichum boninense , and Pestalotiopsis microspora as the causal agents of anthracnose disease in avocado. However, with this being the first report, there is a need to conduct further studies to establish whether there is coinfection or any interaction thereof.
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Directory of Open Access Journals (Sweden)
S. K. Kimaru
2018-01-01
Full Text Available Anthracnose disease of avocado contributes to a huge loss of avocado fruits due to postharvest rot in Kenya. The causal agent of this disease has not been clear but presumed to be Colletotrichum gloeosporioides as reported in other regions where avocado is grown. The fungus mainly infects fruits causing symptoms such as small blackish spots, “pepper spots,” and black spots with raised margin which coalesce as infection progresses. Due to economic losses associated with the disease and emerging information of other species of fungi as causal agents of the disease, this study was aimed at identifying causal agent(s of the disease. A total of 80 fungal isolates were collected from diseased avocado fruits in Murang’a County, the main avocado growing region in Kenya. Forty-six isolates were morphologically identified as Colletotrichum spp. based on their cultural characteristics, mainly whitish, greyish, and creamish colour and cottony/velvety mycelia on the top side of the culture and greyish cream with concentric zonation on the reverse side. Their spores were straight with rounded end and nonseptate. Thirty-four isolates were identified as Pestalotiopsis spp. based on their cultural characteristics: whitish grey mycelium with black fruiting structure on the upper side and greyish black one on the lower side and septate spores with 3-4 septa and 2 or 3 appendages at one end. Further molecular studies using ITS indicated Colletotrichum gloeosporioides, Colletotrichum boninense, and Pestalotiopsis microspora as the causal agents of anthracnose disease in avocado. However, with this being the first report, there is a need to conduct further studies to establish whether there is coinfection or any interaction thereof.
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Dual Causality and the Autonomy of Biology.
Bock, Walter J
2017-03-01
Ernst Mayr's concept of dual causality in biology with the two forms of causes (proximate and ultimate) continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional (=proximate) and evolutionary (=ultimate) causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical sciences.