Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J
Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the
BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.
Yokoyama, Akira; Yokoyama, Tetsuji; Matsui, Toshifumi; Mizukami, Takeshi; Kimura, Mitsuru; Matsushita, Sachio; Higuchi, Susumu; Maruyama, Katsuya
The life-time drinking profiles of Japanese alcoholics have shown that gastrectomy increases susceptibility to alcoholism. We investigated the trends in gastrectomy and alcohol dehydrogenase-1B (ADH1B) and aldehyde dehydrogenase-2 (ALDH2) genotypes and their interactions in alcoholics. This survey was conducted on 4879 Japanese alcoholic men 40 years of age or older who underwent routine gastrointestinal endoscopic screening during the period 1996-2010. ADH1B/ALDH2 genotyping was performed in 3702 patients. A history of gastrectomy was found in 508 (10.4%) patients. The reason for the gastrectomy was peptic ulcer in 317 patients and gastric cancer in 187 patients. The frequency of gastrectomy had gradually decreased from 13.3% in 1996-2000 to 10.5% in 2001-2005 and to 7.8% in 2006-2010 (P alcoholism-susceptibility genotypes, ADH1B*1/*1 and ALDH2*1/*1, modestly but significantly tended not to occur in the same individual (P = 0.026). The frequency of ADH1B*1/*1 decreased with ascending age groups. The high frequency of history of gastrectomy suggested that gastrectomy is still a risk factor for alcoholism, although the percentage decreased during the period. The alcoholism-susceptibility genotype ADH1B*1/*1 was less frequent in the gastrectomy group, suggesting a competitive gene-gastrectomy interaction for alcoholism. A gene-gene interaction and gene-age interactions regarding the ADH1B genotype were observed.
Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun
Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these
Full Text Available Abstract Background The ageing of the worldwide population means there is a growing need for research on the biology of ageing. DNA damage is likely a key contributor to the ageing process and elucidating the role of different DNA repair systems in ageing is of great interest. In this paper we propose a data mining approach, based on classification methods (decision trees and Naive Bayes, for analysing data about human DNA repair genes. The goal is to build classification models that allow us to discriminate between ageing-related and non-ageing-related DNA repair genes, in order to better understand their different properties. Results The main patterns discovered by the classification methods are as follows: (a the number of protein-protein interactions was a predictor of DNA repair proteins being ageing-related; (b the use of predictor attributes based on protein-protein interactions considerably increased predictive accuracy of attributes based on Gene Ontology (GO annotations; (c GO terms related to "response to stimulus" seem reasonably good predictors of ageing-relatedness for DNA repair genes; (d interaction with the XRCC5 (Ku80 protein is a strong predictor of ageing-relatedness for DNA repair genes; and (e DNA repair genes with a high expression in T lymphocytes are more likely to be ageing-related. Conclusions The above patterns are broadly integrated in an analysis discussing relations between Ku, the non-homologous end joining DNA repair pathway, ageing and lymphocyte development. These patterns and their analysis support non-homologous end joining double strand break repair as central to the ageing-relatedness of DNA repair genes. Our work also showcases the use of protein interaction partners to improve accuracy in data mining methods and our approach could be applied to other ageing-related pathways.
Faith, Myles S
This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.
Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong
Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.
Pyun, Jung-A; Kim, Sunshin; Cho, Nam H; Koh, InSong; Lee, Jong-Young; Shin, Chol; Kwack, KyuBum
The aim of this study was to identify polymorphisms and gene-gene interactions that are significantly associated with age at menarche and age at menopause in a Korean population. A total of 3,452 and 1,827 women participated in studies of age at menarche and age at natural menopause, respectively. Linear regression analyses adjusted for residence area were used to perform genome-wide association studies (GWAS), candidate gene association studies, and interactions between the candidate genes for age at menarche and age at natural menopause. In GWAS, four single nucleotide polymorphisms (SNPs; rs7528241, rs1324329, rs11597068, and rs6495785) were strongly associated with age at natural menopause (lowest P = 9.66 × 10). However, GWAS of age at menarche did not reveal any strong associations. In candidate gene association studies, SNPs with P menopause, there was a significant interaction between intronic SNPs on ADAM metallopeptidase with thrombospondin type I motif 9 (ADAMTS9) and SMAD family member 3 (SMAD3) genes (P = 9.52 × 10). For age at menarche, there were three significant interactions between three intronic SNPs on follicle-stimulating hormone receptor (FSHR) gene and one SNP located at the 3' flanking region of insulin-like growth factor 2 receptor (IGF2R) gene (lowest P = 1.95 × 10). Novel SNPs and synergistic interactions between candidate genes are significantly associated with age at menarche and age at natural menopause in a Korean population.
Yoshizaki, Kaichi; Furuse, Tamio; Kimura, Ryuichi; Tucci, Valter; Kaneda, Hideki; Wakana, Shigeharu; Osumi, Noriko
Neurodevelopmental disorders such as autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD) have increased over the last few decades. These neurodevelopmental disorders are characterized by a complex etiology, which involves multiple genes and gene-environmental interactions. Various genes that control specific properties of neural development exert pivotal roles in the occurrence and severity of phenotypes associated with neurodevelopmental disorders. Moreover, paternal aging has been reported as one of the factors that contribute to the risk of ASD and ADHD. Here we report, for the first time, that paternal aging has profound effects on the onset of behavioral abnormalities in mice carrying a mutation of Pax6, a gene with neurodevelopmental regulatory functions. We adopted an in vitro fertilization approach to restrict the influence of additional factors. Comprehensive behavioral analyses were performed in Sey/+ mice (i.e., Pax6 mutant heterozygotes) born from in vitro fertilization of sperm taken from young or aged Sey/+ fathers. No body weight changes were found in the four groups, i.e., Sey/+ and wild type (WT) mice born to young or aged father. However, we found important differences in maternal separation-induced ultrasonic vocalizations of Sey/+ mice born from young father and in the level of hyperactivity of Sey/+ mice born from aged fathers in the open-field test, respectively, compared to WT littermates. Phenotypes of anxiety were observed in both genotypes born from aged fathers compared with those born from young fathers. No significant difference was found in social behavior and sensorimotor gating among the four groups. These results indicate that mice with a single genetic risk factor can develop different phenotypes depending on the paternal age. Our study advocates for serious considerations on the role of paternal aging in breeding strategies for animal studies.
Full Text Available Neurodevelopmental disorders such as autism spectrum disorder (ASD and attention deficit and hyperactivity disorder (ADHD have increased over the last few decades. These neurodevelopmental disorders are characterized by a complex etiology, which involves multiple genes and gene-environmental interactions. Various genes that control specific properties of neural development exert pivotal roles in the occurrence and severity of phenotypes associated with neurodevelopmental disorders. Moreover, paternal aging has been reported as one of the factors that contribute to the risk of ASD and ADHD. Here we report, for the first time, that paternal aging has profound effects on the onset of behavioral abnormalities in mice carrying a mutation of Pax6, a gene with neurodevelopmental regulatory functions. We adopted an in vitro fertilization approach to restrict the influence of additional factors. Comprehensive behavioral analyses were performed in Sey/+ mice (i.e., Pax6 mutant heterozygotes born from in vitro fertilization of sperm taken from young or aged Sey/+ fathers. No body weight changes were found in the four groups, i.e., Sey/+ and wild type (WT mice born to young or aged father. However, we found important differences in maternal separation-induced ultrasonic vocalizations of Sey/+ mice born from young father and in the level of hyperactivity of Sey/+ mice born from aged fathers in the open-field test, respectively, compared to WT littermates. Phenotypes of anxiety were observed in both genotypes born from aged fathers compared with those born from young fathers. No significant difference was found in social behavior and sensorimotor gating among the four groups. These results indicate that mice with a single genetic risk factor can develop different phenotypes depending on the paternal age. Our study advocates for serious considerations on the role of paternal aging in breeding strategies for animal studies.
The idea of gerontogenes is in line with the evolutionary explanation of ageing as being an emergent phenomenon as a result of the imperfect maintenance and repair systems. Although evolutionary processes did not select for any specific ageing genes that restrict and determine the lifespan...... of an individual, the term ‘gerontogenes’ primarily refers to any genes that may seem to influence ageing and longevity, without being specifically selected for that role. Such genes can also be called ‘virtual gerontogenes’ by virtue of their indirect influence on the rate and process of ageing. More than 1000...... virtual gerontogenes have been associated with ageing and longevity in model organisms and humans. The ‘real’ genes, which do influence the essential lifespan of a species, and have been selected for in accordance with the evolutionary life history of the species, are known as the longevity assurance...
Kirchsteiger, C.; Patrik, M.
This paper describes the background and status of a new International Network on ''Incorporating Ageing Effects into Probabilistic Safety Assessment''. The Joint Research Centre (JRC) of the European Commission organized in September 2004 the kickoff meeting of this Network at JRC's Institute for Energy in Petten, Netherlands, with the aims to open the APSA Network, to start discussion of ageing issues in relation to incorporating ageing effects into PSA tools and to come to consensus on objectives and work packages of the Network, taking into account the specific expectations of potential Network partners. The presentations and discussions at the meeting confirmed the main conclusion from the previously organized PSAM 7 pre-conference workshop on ''Incorporating PSA into Ageing Management'', Budapest, June 2004, namely that incorporating ageing effects into PSA seems to be more and more a hot topic particularly for risk assessment and ageing management of nuclear power plants operating at advanced age (more than 25-30 years) and for the purpose of plant life extension. However, it also appeared that, especially regarding the situation in Europe, at present there are several on-going feasibility or full studies in this area, but not yet a completed Ageing PSA leading to applications. The project's working method is a NETWORK of operators, industry, research, academia and consultants with an active interest in the area (physical networking via a series of workshops and virtual networking via the Internet). The resulting knowledge should help PSA developers and users to incorporate the effects of equipment ageing into current PSA tools and models, to identify and/or develop most effective corresponding methods, to focus on dominant ageing contributors and components and to promote the use of PSA for ageing management of Nuclear Power Plants. (orig.)
Samantha A McAllery
Full Text Available While current antiretroviral therapy has significantly improved, challenges still remain in life-long targeting of HIV-1 reservoirs. Lentiviral gene therapy has the potential to deliver protective genes into the HIV-1 reservoir. However, inefficient reverse transcription (RT occurs in HIV-1 reservoirs during lentiviral gene delivery. The viral protein Vpx is capable of increasing lentiviral RT by antagonizing the restriction factor SAMHD1. Incorporating Vpx into lentiviral vectors could substantially increase gene delivery into the HIV-1 reservoir. The feasibility of this Vpx approach was tested in resting cell models utilizing macrophages and dendritic cells. Our results showed Vpx exposure led to increased permissiveness of cells over a period that exceeded 2 weeks. Consequently, significant lower potency of HIV-1 antiretrovirals inhibiting RT and integration was observed. When Vpx was incorporated with anti-HIV-1 genes inhibiting either pre-RT or post-RT stages of the viral life-cycle, transduction levels significantly increased. However, a stronger antiviral effect was only observed with constructs that inhibit pre-RT stages of the viral life cycle. In conclusion this study demonstrates a way to overcome the major delivery obstacle of gene delivery into HIV-1 reservoir cell types. Importantly, incorporating Vpx with pre-RT anti-HIV-1 genes, demonstrated the greatest protection against HIV-1 infection.
Full Text Available Onset of depressive symptoms after the age of 65, or late-life depression (LLD, is common and poses a significant burden on affected individuals, caretakers and society. Evidence suggests a unique biological basis for LLD, but current hypotheses do not account for its pathophysiological complexity. Here we propose a novel etiological framework for LLD, the age-by-disease biological interaction hypothesis, based on the observations that the subset of genes that undergoes lifelong progressive changes in expression is restricted to a specific set of biological processes, and that a disproportionate number of these age-dependent genes have been previously and similarly implicated in neurodegenerative and neuropsychiatric disorders, including depression. The age-by-disease biological interaction hypothesis posits that age-dependent biological processes (i are pushed in LLD-promoting directions by changes in gene expression naturally occurring during brain aging, which (ii directly contribute to pathophysiological mechanisms of LLD, and (iii that individual variability in rates of age-dependent changes determines risk or resiliency to develop age-related disorders, including LLD. We review observations supporting this hypothesis, including consistent and specific age-dependent changes in brain gene expression, and their overlap with neuropsychiatric and neurodegenerative disease pathways. We then review preliminary reports supporting the genetic component of this hypothesis. Other potential biological mediators of age-dependent gene changes are proposed. We speculate that studies examining the relative contribution of these mechanisms to age-dependent changes and related disease mechanisms will not only provide critical information on the biology of normal aging of the human brain, but will inform our understanding our age-dependent diseases, in time fostering the development of new interventions for prevention and treatment of age-dependent diseases
Samek, Diana R; Hicks, Brian M; Keyes, Margaret A; Iacono, William G; McGue, Matt
Gene × Environment interaction contributes to externalizing disorders in childhood and adolescence, but little is known about whether such effects are long lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a Gene × Environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This Gene × Environment interaction was not present for antisocial behavior symptoms after age 17, but it was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). The results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of Gene × Environment interaction may persist through young adulthood for substance use disorders, but it appears to be limited to adolescence for antisocial behavior.
Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Iacono, William G.; McGue, Matt
Gene × environment interaction contributes to externalizing disorders in adolescence, but little is known about whether such effects are long-lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a gene × environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This gene × environment interaction was not present for antisocial behavior symptoms after age 17, but was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). Results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of gene × environment interaction may persist through young adulthood for substance use disorders, but is limited to adolescence for antisocial behavior. PMID:27580681
Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying
Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.
Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.
Glass, Daniel; Viñuela, Ana; Davies, Matthew N; Ramasamy, Adaikalavan; Parts, Leopold; Knowles, David; Brown, Andrew A; Hedman, Asa K; Small, Kerrin S; Buil, Alfonso; Grundberg, Elin; Nica, Alexandra C; Di Meglio, Paola; Nestle, Frank O; Ryten, Mina; Durbin, Richard; McCarthy, Mark I; Deloukas, Panagiotis; Dermitzakis, Emmanouil T; Weale, Michael E; Bataille, Veronique; Spector, Tim D
Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age. Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues. Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.
Lin, Eugene; Kuo, Po-Hsiu; Liu, Yu-Li; Yang, Albert C; Kao, Chung-Feng; Tsai, Shih-Jen
Previous animal studies have indicated associations between circadian clock genes and cognitive impairment . In this study, we assessed whether 11 circadian clockgenes are associated with cognitive aging independently and/or through complex interactions in an old Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to evaluate cognitive function. Our data showed associations between cognitive aging and single nucleotide polymorphisms (SNPs) in 4 key circadian clock genes, CLOCK rs3749473 (p = 0.0017), NPAS2 rs17655330 (p = 0.0013), RORA rs13329238 (p = 0.0009), and RORB rs10781247 (p = 7.9 x 10-5). We also found that interactions between CLOCK rs3749473, NPAS2 rs17655330, RORA rs13329238, and RORB rs10781247 affected cognitive aging (p = 0.007). Finally, we investigated the influence of interactions between CLOCK rs3749473, RORA rs13329238, and RORB rs10781247 with environmental factors such as alcohol consumption, smoking status, physical activity, and social support on cognitive aging (p = 0.002 ~ 0.01). Our study indicates that circadian clock genes such as the CLOCK, NPAS2, RORA, and RORB genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-environment interactions.
Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.
Ho Joshua WK
Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of
Schmitz, Lauren; Conley, Dalton
This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.
Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu
Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.
Barrdahl, Myrto; Rudolph, Anja; Hopper, John L
.36, 95% CI: 1.16-1.59, pint = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10...... epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER......) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP
Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.
Kim, Kyoung-Nam; Lee, Mee-Ri; Lim, Youn-Hee; Hong, Yun-Chul
Homocysteine has been causally associated with various adverse health outcomes. Evidence supporting the relationship between lead and homocysteine levels has been accumulating, but most prior studies have not focused on the interaction with genetic polymorphisms. From a community-based prospective cohort, we analysed 386 participants (aged 41-71 years) with information regarding blood lead and plasma homocysteine levels. Blood lead levels were measured between 2001 and 2003, and plasma homocysteine levels were measured in 2007. Interactions of lead levels with 42 genotyped single-nucleotide polymorphisms (SNPs) in five genes ( TF , HFE , CBS , BHMT and MTR ) were assessed via a 2-degree of freedom (df) joint test and a 1-df interaction test. In secondary analyses using imputation, we further assessed 58 imputed SNPs in the TF and MTHFR genes. Blood lead concentrations were positively associated with plasma homocysteine levels (p=0.0276). Six SNPs in the TF and MTR genes were screened using the 2-df joint test, and among them, three SNPs in the TF gene showed interactions with lead with respect to homocysteine levels through the 1-df interaction test (plead levels. Blood lead levels were positively associated with plasma homocysteine levels measured 4-6 years later, and three SNPs in the TF gene modified the association. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Newton, Timothy; Allison, Rachel; Edgar, James R; Lumb, Jennifer H; Rodger, Catherine E; Manna, Paul T; Rizo, Tania; Kohl, Zacharias; Nygren, Anders O H; Arning, Larissa; Schüle, Rebecca; Depienne, Christel; Goldberg, Lisa; Frahm, Christiane; Stevanin, Giovanni; Durr, Alexandra; Schöls, Ludger; Winner, Beate; Beetz, Christian; Reid, Evan
Many genetic neurological disorders exhibit variable expression within affected families, often exemplified by variations in disease age at onset. Epistatic effects (i.e. effects of modifier genes on the disease gene) may underlie this variation, but the mechanistic basis for such epistatic interactions is rarely understood. Here we report a novel epistatic interaction between SPAST and the contiguous gene DPY30, which modifies age at onset in hereditary spastic paraplegia, a genetic axonopathy. We found that patients with hereditary spastic paraplegia caused by genomic deletions of SPAST that extended into DPY30 had a significantly younger age at onset. We show that, like spastin, the protein encoded by SPAST, the DPY30 protein controls endosomal tubule fission, traffic of mannose 6-phosphate receptors from endosomes to the Golgi, and lysosomal ultrastructural morphology. We propose that additive effects on this pathway explain the reduced age at onset of hereditary spastic paraplegia in patients who are haploinsufficient for both genes.
Full Text Available A vast amount of literature has confirmed the role of gene-environment (G×E interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.
Howson, Joanna M M; Cooper, Jason D; Smyth, Deborah J
The common genetic loci that independently influence the risk of type 1 diabetes have largely been determined. Their interactions with age-at-diagnosis of type 1 diabetes, sex, or the major susceptibility locus, HLA class II, remain mostly unexplored. A large collection of more than 14,866 type 1...
Tarone, Aaron M; Foran, David R
Forensic entomologists use size and developmental stage to estimate blow fly age, and from those, a postmortem interval. Since such estimates are generally accurate but often lack precision, particularly in the older developmental stages, alternative aging methods would be advantageous. Presented here is a means of incorporating developmentally regulated gene expression levels into traditional stage and size data, with a goal of more precisely estimating developmental age of immature Lucilia sericata. Generalized additive models of development showed improved statistical support compared to models that did not include gene expression data, resulting in an increase in estimate precision, especially for postfeeding third instars and pupae. The models were then used to make blind estimates of development for 86 immature L. sericata raised on rat carcasses. Overall, inclusion of gene expression data resulted in increased precision in aging blow flies. © 2010 American Academy of Forensic Sciences.
Ryan, Veronica H; Primiani, Christopher T; Rao, Jagadeesh S; Ahn, Kwangmi; Rapoport, Stanley I; Blanchard, Helene
The polyunsaturated arachidonic and docosahexaenoic acids (AA and DHA) participate in cell membrane synthesis during neurodevelopment, neuroplasticity, and neurotransmission throughout life. Each is metabolized via coupled enzymatic reactions within separate but interacting metabolic cascades. AA and DHA pathway genes are coordinately expressed and underlie cascade interactions during human brain development and aging. The BrainCloud database for human non-pathological prefrontal cortex gene expression was used to quantify postnatal age changes in mRNA expression of 34 genes involved in AA and DHA metabolism. Expression patterns were split into Development (0 to 20 years) and Aging (21 to 78 years) intervals. Expression of genes for cytosolic phospholipases A2 (cPLA2), cyclooxygenases (COX)-1 and -2, and other AA cascade enzymes, correlated closely with age during Development, less so during Aging. Expression of DHA cascade enzymes was less inter-correlated in each period, but often changed in the opposite direction to expression of AA cascade genes. Except for the PLA2G4A (cPLA2 IVA) and PTGS2 (COX-2) genes at 1q25, highly inter-correlated genes were at distant chromosomal loci. Coordinated age-related gene expression during the brain Development and Aging intervals likely underlies coupled changes in enzymes of the AA and DHA cascades and largely occur through distant transcriptional regulation. Healthy brain aging does not show upregulation of PLA2G4 or PTGS2 expression, which was found in Alzheimer's disease.
Veronica H Ryan
Full Text Available The polyunsaturated arachidonic and docosahexaenoic acids (AA and DHA participate in cell membrane synthesis during neurodevelopment, neuroplasticity, and neurotransmission throughout life. Each is metabolized via coupled enzymatic reactions within separate but interacting metabolic cascades.AA and DHA pathway genes are coordinately expressed and underlie cascade interactions during human brain development and aging.The BrainCloud database for human non-pathological prefrontal cortex gene expression was used to quantify postnatal age changes in mRNA expression of 34 genes involved in AA and DHA metabolism.Expression patterns were split into Development (0 to 20 years and Aging (21 to 78 years intervals. Expression of genes for cytosolic phospholipases A2 (cPLA2, cyclooxygenases (COX-1 and -2, and other AA cascade enzymes, correlated closely with age during Development, less so during Aging. Expression of DHA cascade enzymes was less inter-correlated in each period, but often changed in the opposite direction to expression of AA cascade genes. Except for the PLA2G4A (cPLA2 IVA and PTGS2 (COX-2 genes at 1q25, highly inter-correlated genes were at distant chromosomal loci.Coordinated age-related gene expression during the brain Development and Aging intervals likely underlies coupled changes in enzymes of the AA and DHA cascades and largely occur through distant transcriptional regulation. Healthy brain aging does not show upregulation of PLA2G4 or PTGS2 expression, which was found in Alzheimer's disease.
Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar
We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.
Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin
Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.
The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...
Jonathan H. Young
Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.
Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle
A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.
Dressler, William W; Balieiro, Mauro C; Ferreira de Araújo, Luiza; Silva, Wilson A; Ernesto Dos Santos, José
Research on gene-environment interaction was facilitated by breakthroughs in molecular biology in the late 20th century, especially in the study of mental health. There is a reliable interaction between candidate genes for depression and childhood adversity in relation to mental health outcomes. The aim of this paper is to explore the role of culture in this process in an urban community in Brazil. The specific cultural factor examined is cultural consonance, or the degree to which individuals are able to successfully incorporate salient cultural models into their own beliefs and behaviors. It was hypothesized that cultural consonance in family life would mediate the interaction of genotype and childhood adversity. In a study of 402 adult Brazilians from diverse socioeconomic backgrounds, conducted from 2011 to 2014, the interaction of reported childhood adversity and a polymorphism in the 2A serotonin receptor was associated with higher depressive symptoms. Further analysis showed that the gene-environment interaction was mediated by cultural consonance in family life, and that these effects were more pronounced in lower social class neighborhoods. The findings reinforce the role of the serotonergic system in the regulation of stress response and learning and memory, and how these processes in turn interact with environmental events and circumstances. Furthermore, these results suggest that gene-environment interaction models should incorporate a wider range of environmental experience and more complex pathways to better understand how genes and the environment combine to influence mental health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bae, Sunwoong; Park, Seunghye; Kim, Jung; Choi, Jong Seob; Kim, Kyung Hoon; Kwon, Donguk; Jin, EonSeon; Park, Inkyu; Kim, Do Hyun; Seo, Tae Seok
Superior green algal cells showing high lipid production and rapid growth rate are considered as an alternative for the next generation green energy resources. To achieve the biomass based energy generation, transformed microalgae with superlative properties should be developed through genetic engineering. Contrary to the normal cells, microalgae have rigid cell walls, so that target gene delivery into cells is challengeable. In this study, we report a ZnO nanowire-incorporated microdevice for a high throughput microalgal transformation. The proposed microdevice was equipped with not only a ZnO nanowire in the microchannel for gene delivery into cells but also a pneumatic polydimethylsiloxane (PDMS) microvalve to modulate the cellular attachment and detachment from the nanowire. As a model, hygromycin B resistance gene cassette (Hyg3) was functionalized on the hydrothermally grown ZnO nanowires through a disulfide bond and released into green algal cells, Chlamydomonas reinhardtii, by reductive cleavage. During Hyg3 gene delivery, a monolithic PDMS membrane was bent down, so that algal cells were pushed down toward ZnO nanowires. The supply of vacuum in the pneumatic line made the PDMS membrane bend up, enabling the gene delivered algal cells to be recovered from the outlet of the microchannel. We successfully confirmed Hyg3 gene integrated in microalgae by amplifying the inserted gene through polymerase chain reaction (PCR) and DNA sequencing. The efficiency of the gene delivery to algal cells using the ZnO nanowire-incorporated microdevice was 6.52 × 10(4)- and 9.66 × 10(4)-fold higher than that of a traditional glass bead beating and electroporation.
Mielniczuk, Jan; Teisseyre, Paweł
Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.
Taye H Hamza; Honglei Chen; Erin M Hill-Burns; Shannon L Rhodes; Jennifer Montimurro; Denise M Kay; Albert Tenesa; Victoria I Kusel; Patricia Sheehan; Muthukrishnan Eaaswarkhanth; Dora Yearout; Ali Samii; John W Roberts; Pinky Agarwal; Yvette Bordelon
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal compo...
Ayhan, Yavuz; Sawa, Akira; Ross, Christopher A; Pletnikov, Mikhail V
The pathogenesis of schizophrenia and related mental illnesses likely involves multiple interactions between susceptibility genes of small effects and environmental factors. Gene-environment interactions occur across different stages of neurodevelopment to produce heterogeneous clinical and pathological manifestations of the disease. The main obstacle for mechanistic studies of gene-environment interplay has been the paucity of appropriate experimental systems for elucidating the molecular pathways that mediate gene-environment interactions relevant to schizophrenia. Recent advances in psychiatric genetics and a plethora of experimental data from animal studies allow us to suggest a new approach to gene-environment interactions in schizophrenia. We propose that animal models based on identified genetic mutations and measurable environment factors will help advance studies of the molecular mechanisms of gene-environment interplay.
Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong
With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.
Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud
BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric
Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung
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.
Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins
Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.
Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed
Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
Ching Lee Koo
Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza
Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.
Full Text Available The influenza A virus genome comprises eight negative-sense viral RNAs (vRNAs that form individual ribonucleoprotein (RNP complexes. In order to incorporate a complete set of each of these vRNAs, the virus uses a selective packaging mechanism that facilitates co-packaging of specific gene segments but whose molecular basis is still not fully understood. Recently, we used a competitive transfection model where plasmids encoding the A/Puerto Rico/8/34 (PR8 and A/Udorn/307/72 (Udorn PB1 gene segments were competed to show that the Udorn PB1 gene segment is preferentially co-packaged into progeny virions with the Udorn NA gene segment. Here we created chimeric PB1 genes combining both Udorn and PR8 PB1 sequences to further define the location within the Udorn PB1 gene that drives co-segregation of these genes and show that nucleotides 1776–2070 of the PB1 gene are crucial for preferential selection. In vitro assays examining specific interactions between Udorn NA vRNA and purified vRNAs transcribed from chimeric PB1 genes also supported the importance of this region in the PB1-NA interaction. Hence, this work identifies an association between viral genes that are co-selected during packaging. It also reveals a region potentially important in the RNP-RNP interactions within the supramolecular complex that is predicted to form prior to budding to allow one of each segment to be packaged in the viral progeny. Our study lays the foundation to understand the co-selection of specific genes, which may be critical to the emergence of new viruses with pandemic potential.
Full Text Available The lack of knowledge about the earliest events in disease development is due to the multi-factorial nature of disease risk. This information gap is the consequence of the lack of appreciation for the fact that most diseases arise from the complex interactions between genes and the environment as a function of the age or stage of development of the individual. Whether an environmental exposure causes illness or not is dependent on the efficiency of the so-called Ã¢Â€Âœenvironmental response machineryÃ¢Â€Â (i.e., the complex of metabolic pathways that can modulate response to environmental perturbations that one has inherited. Thus, elucidating the causes of most chronic diseases will require an understanding of both the genetic and environmental contribution to their etiology. Unfortunately, the exploration of the relationship between genes and the environment has been hampered in the past by the limited knowledge of the human genome, and by the inclination of scientists to study disease development using experimental models that consider exposure to a single environmental agent. Rarely in the past were interactions between multiple genes or between genes and environmental agents considered in studies of human disease etiology. The most critical issue is how to relate exposure-disease association studies to pathways and mechanisms. To understand how genes and environmental factors interact to perturb biological pathways to cause injury or disease, scientists will need tools with the capacity to monitor the global expression of thousands of genes, proteins and metabolites simultaneously. The generation of such data in multiple species can be used to identify conserved and functionally significant genes and pathways involved in geneenvironment interactions. Ultimately, it is this knowledge that will be used to guide agencies such as the U.S. Department of Health and Human Services in decisions regarding biomedical research funding
Bagshaw, Andrew T M; Horwood, L John; Fergusson, David M; Gemmell, Neil J; Kennedy, Martin A
The genetic and environmental influences on human personality and behaviour are a complex matter of ongoing debate. Accumulating evidence indicates that short tandem repeats (STRs) in regulatory regions are good candidates to explain heritability not accessed by genome-wide association studies. We tested for associations between the genotypes of four selected repeats and 18 traits relating to personality, behaviour, cognitive ability and mental health in a well-studied longitudinal birth cohort (n = 458-589) using one way analysis of variance. The repeats were a highly conserved poly-AC microsatellite in the upstream promoter region of the T-box brain 1 (TBR1) gene and three previously studied STRs in the activating enhancer-binding protein 2-beta (AP2-β) and androgen receptor (AR) genes. Where significance was found we used multiple regression to assess the influence of confounding factors. Carriers of the shorter, most common, allele of the AR gene's GGN microsatellite polymorphism had fewer anxiety-related symptoms, which was consistent with previous studies, but in our study this was not significant following Bonferroni correction. No associations with two repeats in the AP2-β gene withstood this correction. A novel finding was that carriers of the minor allele of the TBR1 AC microsatellite were at higher risk of conduct problems in childhood at age 7-9 (p = 0.0007, which did pass Bonferroni correction). Including maternal smoking during pregnancy (MSDP) in models controlling for potentially confounding influences showed that an interaction between TBR1 genotype and MSDP was a significant predictor of conduct problems in childhood and adolescence (p behaviour up to age 25 years (p ≤ 0.02). This interaction remained significant after controlling for possible confounders including maternal age at birth, socio-economic status and education, and offspring birth weight. The potential functional importance of the TBR1 gene's promoter microsatellite
Peter J Castaldi
Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.
Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.
Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621
Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C
Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.
Maurya, Shashank Kumar; Mishra, Rajnikant
The Pax6, a transcriptional regulator and multifunctional protein, has been found critical for neurogenesis, neuro-degeneration, mental retardation, neuroendocrine tumors, glioblastoma and astrocytomas. The age-associated alteration in the expression of Pax6 in neuron and glia has also been observed in the immunologically privileged brain. Therefore, it is presumed that Pax6 may modulate brain immunity by activation of microglia either directly interacting with genes or proteins of microglia or indirectly though inflammation associated with neurodegeneration. This report describes evaluation of expression, co-localization and interactions of Pax6 with Ionized binding protein1 (Iba1) in brain of aging mice by Immunohistochemistry, Chromatin Immuno-precipitation (ChIP) and Co-immunoprecipitation (Co-IP), respectively. The co-localization of Pax6 with Iba1 was observed in the cerebellum, cerebral cortex, hippocampus, midbrain and olfactory lobe. The Pax6 and Iba1 also interact physically. The age-dependent alteration in their expression and co-localization were also observed in mice. Results indicate Pax6-dependent activities of Iba1 in the remodelling of microglia during immunological surveillance of the brain. Copyright © 2017 Elsevier B.V. All rights reserved.
Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif
Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.
Wade, Mark; Hoffmann, Thomas J; Jenkins, Jennifer M
Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behavior--two widely studied factors in ToM development-interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers' cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children's ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene-environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. © The Author (2015). Published by Oxford University Press. For Permissions, please email: firstname.lastname@example.org.
Dorra Hmida-Ben Brahim
Full Text Available Huntington’s disease (HD is an autosomal dominant neurodegenerative disorder. The causative mutation is an expansion of more than 36 CAG repeats in the first exon of IT15 gene. Many studies have shown that the IT15 interacts with several modifier genes to regulate the age at onset (AO of HD. Our study aims to investigate the implication of CAG expansion and 9 modifiers in the age at onset variance of 15 HD Tunisian patients and to establish the correlation between these modifiers genes and the AO of this disease. Despite the small number of studied patients, this report consists of the first North African study in Huntington disease patients. Our results approve a specific effect of modifiers genes in each population.
Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon
Larson, Nicholas B; Schaid, Daniel J
Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.
Jia, Bin; Wang, Xiaodong
: The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.
Full Text Available Severe mental illness is a broad category that includes schizophrenia, bipolar disorder and severe depression. Both genetic disposition and environmental exposures play important roles in the development of severe mental illness. Multiple lines of evidence suggest that the roles of genetic and environmental depend on each other. Gene-environment interactions may underlie the paradox of strong environmental factors for highly heritable disorders, the low estimates of shared environmental influences in twin studies of severe mental illness and the heritability gap between twin and molecular heritability estimates. Sons and daughters of parents with severe mental illness are more vulnerable to the effects of prenatal and postnatal environmental exposures, suggesting that the expression of genetic liability depends on environment. In the last decade, gene-environment interactions involving specific molecular variants in candidate genes have been identified. Replicated findings include an interaction between a polymorphism in the AKT1 gene and cannabis use in the development of psychosis and an interaction between the length polymorphism of the serotonin transporter gene and childhood maltreatment in the development of persistent depressive disorder. Bipolar disorder has been underinvestigated, with only a single study showing an interaction between a functional polymorphism in BDNF and stressful life events triggering bipolar depressive episodes. The first systematic search for gene-environment interactions has found that a polymorphism in CTNNA3 may sensitise the developing brain to the pathogenic effect of cytomegalovirus in utero, leading to schizophrenia in adulthood. Strategies for genome-wide investigations will likely include coordination between epidemiological and genetic research efforts, systematic assessment of multiple environmental factors in large samples, and prioritization of genetic variants.
Fraser, Hunter B.; Khaitovich, Philipp; Plotkin, Joshua B.; Paabo, Svante; Eisen, Michael B.
It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.
Hunter B Fraser
Full Text Available It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.
Tindale, Lauren C; Leach, Stephen; Spinelli, John J; Brooks-Wilson, Angela R
Several studies have found that long-lived individuals do not appear to carry lower numbers of common disease-associated variants than ordinary people; it has been hypothesized that they may instead carry protective variants. An intriguing type of protective variant is buffering variants that protect against variants that have deleterious effects. We genotyped 18 variants in 15 genes related to longevity or healthy aging that had been previously reported as having a gene-gene interaction or buffering effect. We compared a group of 446 healthy oldest-old 'Super-Seniors' (individuals 85 or older who have never been diagnosed with cancer, cardiovascular disease, dementia, diabetes or major pulmonary disease) to 421 random population-based midlife controls. Cases and controls were of European ancestry. Association tests of individual SNPs showed that Super-Seniors were less likely than controls to carry an APOEε4 allele or a haptoglobin HP2 allele. Interactions between APOE/FOXO3, APOE/CRYL1, and LPA/CRYL1 did not remain significant after multiple testing correction. In a network analysis of the candidate genes, lipid and cholesterol metabolism was a common theme. APOE, HP, and CRYL1 have all been associated with Alzheimer's Disease, the pathology of which involves lipid and cholesterol pathways. Age-related changes in lipid and cholesterol maintenance, particularly in the brain, may be central to healthy aging and longevity.
Jacob M Zahn
Full Text Available We present the AGEMAP (Atlas of Gene Expression in Mouse Aging Project gene expression database, which is a resource that catalogs changes in gene expression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1 a pattern common to neural tissues, (2 a pattern for vascular tissues, and (3 a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different.
Goljanek-Whysall, Katarzyna; Iwanejko, Lesley A; Vasilaki, Aphrodite; Pekovic-Vaughan, Vanja; McDonagh, Brian
Ageing is associated with a progressive loss of skeletal muscle mass, quality and function-sarcopenia, associated with reduced independence and quality of life in older generations. A better understanding of the mechanisms, both genetic and epigenetic, underlying this process would help develop therapeutic interventions to prevent, slow down or reverse muscle wasting associated with ageing. Currently, exercise is the only known effective intervention to delay the progression of sarcopenia. The cellular responses that occur in muscle fibres following exercise provide valuable clues to the molecular mechanisms regulating muscle homoeostasis and potentially the progression of sarcopenia. Redox signalling, as a result of endogenous generation of ROS/RNS in response to muscle contractions, has been identified as a crucial regulator for the adaptive responses to exercise, highlighting the redox environment as a potentially core therapeutic approach to maintain muscle homoeostasis during ageing. Further novel and attractive candidates include the manipulation of microRNA expression. MicroRNAs are potent gene regulators involved in the control of healthy and disease-associated biological processes and their therapeutic potential has been researched in the context of various disorders, including ageing-associated muscle wasting. Finally, we discuss the impact of the circadian clock on the regulation of gene expression in skeletal muscle and whether disruption of the peripheral muscle clock affects sarcopenia and altered responses to exercise. Interventions that include modifying altered redox signalling with age and incorporating genetic mechanisms such as circadian- and microRNA-based gene regulation, may offer potential effective treatments against age-associated sarcopenia.
Li, Ting; Du, Jiang; Yu, Shunying; Jiang, Haifeng; Fu, Yingmei; Wang, Dongxiang; Sun, Haiming; Chen, Hanhui; Zhao, Min
The interaction of the association of dopamine genes, impulsivity and childhood trauma with substance abuse remains unclear. To clarify the impacts and the interactions of the Catechol -O-methyltransferase (COMT) gene, impulsivity and childhood trauma on the age of onset of heroin use among heroin dependent patients in China. 202 male and 248 female inpatients who meet DSM-IV criteria of heroin dependence were enrolled. Impulsivity and childhood trauma were measured using BIS-11 (Barratt Impulsiveness Scale-11) and ETISR-SF (Early Trauma Inventory Self Report-Short Form). The single nucleotide polymorphism (SNP) rs737866 on the COMT gene-which has previously been associated with heroin abuse, was genotyped using a DNA sequence detection system. Structural equations model was used to assess the interaction paths between these factors and the age of onset of heroin use. Chi-square test indicated the individuals with TT allele have earlier age of onset of heroin use than those with CT or CC allele. In the correlation analysis, the severity of childhood trauma was positively correlated to impulsive score, but both of them were negatively related to the age of onset of heroin use. In structure equation model, both the COMT gene and childhood trauma had impacts on the age of onset of heroin use directly or via impulsive personality. Our findings indicated that the COMT gene, impulsive personality traits and childhood trauma experience were interacted to impact the age of onset of heroin use, which play a critical role in the development of heroin dependence. The impact of environmental factor was greater than the COMT gene in the development of heroin dependence.
Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.
Hur, Junguk; Özgür, Arzucan; He, Yongqun
Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of
Full Text Available Interactions between proteins and genes are considered essential in the description of biomolecular phenomena, and networks of interactions are applied in a system's biology approach. Recently, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for improving the detection of gene interactions. In particular, syntactic relations among linguistic information are good for detecting gene interactions. However, previous systems give a reasonably good precision but poor recall. To improve recall without sacrificing precision, this paper proposes a three-phase method for detecting gene interactions based on syntactic relations. In the first phase, we retrieve syntactic encapsulation categories for each candidate agent and target. In the second phase, we construct a verb list that indicates the nature of the interaction between pairs of genes. In the last phase, we determine direction rules to detect which of two genes is the agent or target. Even without biomolecular knowledge, our method performs reasonably well using a small training dataset. While the first phase contributes to improve recall, the second and third phases contribute to improve precision. In the experimental results using ICML 05 Workshop on Learning Language in Logic (LLL05 data, our proposed method gave an F-measure of 67.2% for the test data, significantly outperforming previous methods. We also describe the contribution of each phase to the performance.
Full Text Available Prostate cancer (PCa is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI, smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs = 1.79–4.41. GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032 and 5.33 (p = 0.046, respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007 and 3.11 (p = 0.024, respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041. These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.
Zhao, Wei; Ware, Erin B; He, Zihuai; Kardia, Sharon L R; Faul, Jessica D; Smith, Jennifer A
Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).
Full Text Available Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index-associated genetic loci identified through large-scale genome-wide association studies (GWAS only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS. In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS. Childhood socioeconomic status (parental education was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488 by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA (p = 0.07.
Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.
Hooiveld, MHW; Morgan, R; Rieden, PID; Houtzager, E; Pannese, M; Damen, K; Boncinelli, E; Durston, AJ
Understanding why metazoan Hox/HOM-C genes are expressed in spatiotemporal sequences showing colinearity with their genomic sequence is a central challenge in developmental biology. Here, we studied the consequences of ectopically expressing Hox genes to investigate whether Hox-Hox interactions
Mostafavi, Sara; Morris, Quaid
In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Full Text Available Persisters comprise a group of phenotypically heterogeneous metabolically quiescent bacteria with multidrug tolerance and contribute to the recalcitrance of chronic infections. Although recent work has shown that toxin-antitoxin (TA system HipAB depends on stringent response effector (pppGppin persister formation, whether other persister pathways are also dependent on stringent response has not been explored. Here we examined the relationship of (pppGpp with 15 common persister genes (dnaK, clpB, rpoS, pspF, tnaA, sucB, ssrA, smpB, recA, umuD, uvrA, hipA, mqsR, relE, dinJ using Escherichia coli as a model. By comparing the persister levels of wild type with their single gene knockout and double knockout mutants with relA, we divided their interactions into five types, namely A “dependent” (dnaK, recA, B “positive reinforcement” (rpoS, pspF, ssrA, recA, C “antagonistic” (clpB, sucB, umuD, uvrA, hipA, mqsR, relE, dinJ, D “epistasis” (clpB, rpoS, tnaA, ssrA, smpB, hipA, and E “irrelevant” (dnaK, clpB, rpoS, tnaA, sucB, smpB, umuD, uvrA, hipA, mqsR, relE, dinJ. We found that the persister gene interactions are intimately dependent on bacterial culture age, cell concentrations (diluted versus undiluted culture, and drug classifications, where the same gene may belong to different groups with varying antibiotics, culture age or cell concentrations. Together, this study represents the first attempt to systematically characterize the intricate relationships among the different mechanisms of persistence and as such provide new insights into the complexity of the persistence phenomenon at the level of persister gene network interactions.
Ren, Yu-Yu; Koch, Lauren G; Britton, Steven L; Qi, Nathan R; Treutelaar, Mary K; Burant, Charles F; Li, Jun Z
Intrinsic aerobic exercise capacity can influence many complex traits including obesity and aging. To study this connection we established two rat lines by divergent selection of untrained aerobic capacity. After 32 generations the high capacity runners (HCR) and low capacity runners (LCR) differed in endurance running distance and body fat, blood glucose, other health indicators, and natural life span. To understand the interplay among genetic differences, chronological age, and acute exercise we performed microarray-based gene expression analyses in skeletal muscle with a 2×2×2 design to simultaneously compare HCR and LCR, old and young animals, and rest and exhaustion. Transcripts for mitochondrial function are expressed higher in HCRs than LCRs at both rest and exhaustion and for both age groups. Expression of cell adhesion and extracellular matrix genes tend to decrease with age. This and other age effects are more prominent in LCRs than HCRs, suggesting that HCRs have a slower aging process and this may be partly due to their better metabolic health. Strenuous exercise mainly affects transcription regulation and cellular response. The effects of any one factor often depend on the other two. For example, there are ∼140 and ∼110 line-exercise "interacting" genes for old and young animals, respectively. Many genes highlighted in our study are consistent with prior reports, but many others are novel. The gene- and pathway-level statistics for the main effects, either overall or stratified, and for all possible interactions, represent a rich reference dataset for understanding the interdependence among lines, aging, and exercise. Copyright © 2016 the American Physiological Society.
Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.
Bønnelykke, Klaus; Ober, Carole
, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs......Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also...... heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes...
Full Text Available Abstract Background The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. Results We have developed MINER (Microarray Interactive Network Exploration and Representation, an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Conclusion Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.
Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the signiﬁcant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratiﬁcation. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.
Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung
Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Catherine E Dana
Full Text Available Genome sequencing has revealed examples of horizontally transferred genes, but we still know little about how such genes are incorporated into their host genomes. We have previously reported the identification of a gene (flp that appears to have entered the Hydra genome through horizontal transfer. Here we provide additional evidence in support of our original hypothesis that the transfer was from a unicellular organism, and we show that the transfer occurred in an ancestor of two medusozoan cnidarian species. In addition we show that the gene is part of a bicistronic operon in the Hydra genome. These findings identify a new animal phylum in which trans-spliced leader addition has led to the formation of operons, and define the requirements for evolution of an operon in Hydra. The identification of operons in Hydra also provides a tool that can be exploited in the construction of transgenic Hydra strains.
Yang, Cheng-Hong; Chang, Hsueh-Wei
Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer. PMID:24895547
Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis
Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.
Mohan, Adith; Mather, Karen A; Thalamuthu, Anbupalam; Baune, Bernhard T; Sachdev, Perminder S
The review aims to provide a summary of recent developments in the study of gene expression in the aging human brain. Profiling differentially expressed genes or 'transcripts' in the human brain over the course of normal aging has provided valuable insights into the biological pathways that appear activated or suppressed in late life. Genes mediating neuroinflammation and immune system activation in particular, show significant age-related upregulation creating a state of vulnerability to neurodegenerative and neuropsychiatric disease in the aging brain. Cellular ionic dyshomeostasis and age-related decline in a host of molecular influences on synaptic efficacy may underlie neurocognitive decline in later life. Critically, these investigations have also shed light on the mobilization of protective genetic responses within the aging human brain that help determine health and disease trajectories in older age. There is growing interest in the study of pre and posttranscriptional regulators of gene expression, and the role of noncoding RNAs in particular, as mediators of the phenotypic diversity that characterizes human brain aging. Gene expression studies in healthy brain aging offer an opportunity to unravel the intricately regulated cellular underpinnings of neurocognitive aging as well as disease risk and resiliency in late life. In doing so, new avenues for early intervention in age-related neurodegenerative disease could be investigated with potentially significant implications for the development of disease-modifying therapies.
Wallace Helen M
Full Text Available Abstract Background The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis, gene-environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. Method A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918 assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top-down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. Conclusion The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis
Full Text Available Aging is accompanied by considerable heterogeneity with possible co-expression of differentiation pathways. The present study investigates the interplay between crucial myogenic, adipogenic and Wnt-related genes orchestrating aged myogenic progenitor differentiation (AMPD using clonal gene expression profiling in conjunction with Bayesian structure learning (BSL techniques. The expression of three myogenic regulatory factor genes (Myogenin, Myf-5, MyoD1, four genes involved in regulating adipogenic potential (C/EBPα, DDIT3, FoxC2, PPARγ, and two genes in the Wnt-signaling pathway (Lrp5, Wnt5a known to influence both differentiation programs were determined across thirty-four clones by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR. Three control genes were used for normalization of the clonal expression data (18S, GAPDH and B2M. Constraint-based BSL techniques, namely (a PC Algorithm, (b Grow-shrink algorithm (GS, and (c Incremental Association Markov Blanket (IAMB were used to model the functional relationships (FRs in the form of acyclic networks from the clonal expression profiles. A novel resampling approach that obviates the need for a user-defined confidence threshold is proposed to identify statistically significant FRs at small sample sizes. Interestingly, the resulting acyclic network consisted of FRs corresponding to myogenic, adipogenic, Wnt-related genes and their interaction. A significant number of these FRs were robust to normalization across the three house-keeping genes and the choice of the BSL technique. The results presented elucidate the delicate balance between differentiation pathways (i.e. myogenic as well as adipogenic and possible cross-talk between pathways in AMPD.
Oskari Kilpeläinen, Tuomas; Franks, Paul W
to an equal bout of physical activity. Individuals with specific genetic profiles are also expected to be more responsive to the beneficial effects of physical activity in the prevention of type 2 diabetes. Identification of such gene-physical activity interactions could give new insights into the biological...... the reader to the recent advances in the genetics of type 2 diabetes, summarize the current evidence on gene-physical activity interactions in relation to type 2 diabetes, and outline how information on gene-physical activity interactions might help improve the prevention and treatment of type 2 diabetes....... Finally, we will discuss the existing and emerging strategies that might enhance our ability to identify and exploit gene-physical activity interactions in the etiology of type 2 diabetes. © 2014 S. Karger AG, Basel....
Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.
Notzon, S; Domschke, K; Holitschke, K; Ziegler, C; Arolt, V; Pauli, P; Reif, A; Deckert, J; Zwanzger, P
Social anxiety has been suggested to be promoted by an insecure attachment style. Oxytocin is discussed as a mediator of trust and social bonding as well as a modulator of social anxiety. Applying a gene-environment (G × E) interaction approach, in the present pilot study the main and interactive effects of attachment styles and oxytocin receptor (OXTR) gene variation were probed in a combined risk factor model of social anxiety in healthy probands. Participants (N = 388; 219 females, 169 males; age 24.7 ± 4.7 years) were assessed for anxiety in social situations (Social Phobia and Anxiety Inventory) depending on attachment style (Adult Attachment Scale, AAS) and OXTR rs53576 A/G genotype. A less secure attachment style was significantly associated with higher social anxiety. This association was partly modulated by OXTR genotype, with a stronger negative influence of a less secure attachment style on social anxiety in A allele carriers as compared to GG homozygotes. The present pilot data point to a strong association of less secure attachment and social anxiety as well as to a gene-environment interaction effect of OXTR rs53576 genotype and attachment style on social anxiety possibly constituting a targetable combined risk marker of social anxiety disorder.
Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.
Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai
Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923
Maria João Soares Rodrigues de Sousa Fernandes
Full Text Available With the aging population and the natural increase of nursing care within gerontology, there is increasing interest in how the nurse interacts with the aged person and utilizes their role to protect and promote successful aging behaviors. The goal lies in understanding the nurse−aged person interaction process. This is a naturalistic study of qualitative paradigm and inductive reasoning, developed in the context of primary health care. We observed the interaction process between nurse and older person in various Health Centers and Day/Socializing Centers and supplemented the information with an interview. The grounded theory analysis method of Corbin & Strauss was used, which provides the triangulation of data and uses theoretical sampling. The nurse−aged person interaction is established in a joint process of recreation of the gerontologic care predisposing, fostering and strengthening knowledge about the essence of life. The elderly person who is the object of nurse care, builds their lived experience by aiming towards integrity, establishing individual and social interaction and enhancing experiences. From this whole interaction process, a central concept emerges: clarification of the aged person’s lived experience.
Szentágotai-Tătar, Aurora; Chiș, Adina; Vulturar, Romana; Dobrean, Anca; Cândea, Diana Mirela; Miu, Andrei C
Rooted in people's preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology.
Background Susceptibility to atopy originates from effects of the environment on genes. Birth order has been identified as a risk factor for atopy and evidence for some candidate genes has been accumulated; however no study has yet assessed a birth order-gene interaction. Objective To investigate the interaction of IL13 polymorphisms with birth order on allergic sensitization at ages 4, 10 and 18 years. Methods Mother-infant dyads were recruited antenatally and followed prospectively to age 18 years. Questionnaire data (at birth, age 4, 10, 18); skin prick test (SPT) at ages 4, 10, 18; total serum IgE and specific inhalant screen at age 10; and genotyping for IL13 were collected. Three SNPs were selected from IL13: rs20541 (exon 4, nonsynonymous SNP), rs1800925 (promoter region) and rs2066960 (intron 1). Analysis included multivariable log-linear regression analyses using repeated measurements to estimate prevalence ratios (PRs). Results Of the 1456 participants, birth order information was available for 83.2% (1212/1456); SPT was performed on 67.4% at age 4, 71.2% at age 10 and 58.0% at age 18. The prevalence of atopy (sensitization to one or more food or aeroallergens) increased from 19.7% at age 4, to 26.7% at 10 and 41.1% at age 18. Repeated measurement analysis indicated interaction between rs20541 and birth order on SPT. The stratified analyses demonstrated that the effect of IL13 on SPT was restricted only to first-born children (p = 0.007; adjusted PR = 1.35; 95%CI = 1.09, 1.69). Similar findings were noted for firstborns regarding elevated total serum IgE at age 10 (p = 0.007; PR = 1.73; 1.16, 2.57) and specific inhalant screen (p = 0.034; PR = 1.48; 1.03, 2.13). Conclusions This is the first study to show an interaction between birth order and IL13 polymorphisms on allergic sensitization. Future functional genetic research need to determine whether or not birth order is related to altered expression and methylation of the IL13 gene. PMID:20403202
Ogbuanu Ikechukwu U
Full Text Available Abstract Background Susceptibility to atopy originates from effects of the environment on genes. Birth order has been identified as a risk factor for atopy and evidence for some candidate genes has been accumulated; however no study has yet assessed a birth order-gene interaction. Objective To investigate the interaction of IL13 polymorphisms with birth order on allergic sensitization at ages 4, 10 and 18 years. Methods Mother-infant dyads were recruited antenatally and followed prospectively to age 18 years. Questionnaire data (at birth, age 4, 10, 18; skin prick test (SPT at ages 4, 10, 18; total serum IgE and specific inhalant screen at age 10; and genotyping for IL13 were collected. Three SNPs were selected from IL13: rs20541 (exon 4, nonsynonymous SNP, rs1800925 (promoter region and rs2066960 (intron 1. Analysis included multivariable log-linear regression analyses using repeated measurements to estimate prevalence ratios (PRs. Results Of the 1456 participants, birth order information was available for 83.2% (1212/1456; SPT was performed on 67.4% at age 4, 71.2% at age 10 and 58.0% at age 18. The prevalence of atopy (sensitization to one or more food or aeroallergens increased from 19.7% at age 4, to 26.7% at 10 and 41.1% at age 18. Repeated measurement analysis indicated interaction between rs20541 and birth order on SPT. The stratified analyses demonstrated that the effect of IL13 on SPT was restricted only to first-born children (p = 0.007; adjusted PR = 1.35; 95%CI = 1.09, 1.69. Similar findings were noted for firstborns regarding elevated total serum IgE at age 10 (p = 0.007; PR = 1.73; 1.16, 2.57 and specific inhalant screen (p = 0.034; PR = 1.48; 1.03, 2.13. Conclusions This is the first study to show an interaction between birth order and IL13 polymorphisms on allergic sensitization. Future functional genetic research need to determine whether or not birth order is related to altered expression and methylation of the IL13 gene.
Full Text Available Abstract Background Gene-environment interactions are likely to explain some of the heterogeneity in childhood asthma. Here, we describe the methodology and experiences in establishing a database for childhood asthma designed to study gene-environment interactions (PAGES - Paediatric Asthma Gene Environment Study. Methods Children with asthma and under the care of a respiratory paediatrician are being recruited from 15 hospitals between 2008 and 2011. An asthma questionnaire is completed and returned by post. At a routine clinic visit saliva is collected for DNA extraction. Detailed phenotyping in a proportion of children includes spirometry, bronchodilator response (BDR, skin prick reactivity, exhaled nitric oxide and salivary cotinine. Dietary and quality of life questionnaires are completed. Data are entered onto a purpose-built database. Results To date 1045 children have been invited to participate and data collected in 501 (48%. The mean age (SD of participants is 8.6 (3.9 years, 57% male. DNA has been collected in 436 children. Spirometry has been obtained in 172 children, mean % predicted (SD FEV1 97% (15 and median (IQR BDR is 5% (2, 9. There were differences in age, socioeconomic status, severity and %FEV1 between the different centres (p≤0.024. Reasons for non-participation included parents not having time to take part, children not attending clinics and, in a small proportion, refusal to take part. Conclusions It is feasible to establish a national database to study gene-environment interactions within an asthmatic paediatric population; there are barriers to participation and some different characteristics in individuals recruited from different centres. Recruitment to our study continues and is anticipated to extend current understanding of asthma heterogeneity.
Luecke-Huhle, Christine; Ehrfeld, Angelika; Rau, Waltraud
Simian Virus 40-transformed Chinese hamster embryo cells (Co631) contain 5 viral copies integrated per cell genome. These SV40 sequences were used as an endogenous indicator gene to study response of mammalian cells to radiation at gene level. Cells were internally irradiated by Auger electrons emitted by Iodine-125 which was incorporated in cell DNA in form of 5-[ 125 I] iododeoxyuridine ( 125 IdU). An increase in gene copy number was measured using dispersed cell blotting and Southern analysis in combination with highly sensitive DNA hybridization. A 13-fold amplification of the SV40 sequences and a 2-fold amplification of two cellular oncogenes of the ras family were found. Other cellular genes, like the α-actin gene, are not amplified and no variation in gene copy number was observed after incubation of cells with cold IdU. Thus, specific gene amplification seems to be the consequence of radiation-induced DNA damage and the resulting cell cycle arrest. (author)
Matura, Silke; Prvulovic, David; Hartmann, Daniel; Scheibe, Monika; Sepanski, Beate; Butz, Marius; Oertel-Knöchel, Viola; Knöchel, Christian; Karakaya, Tarik; Fußer, Fabian; Hattingen, Elke; Pantel, Johannes
The apolipoprotein E (ApoE) ɛ4 allele is a well-established genetic risk factor for sporadic Alzheimer's disease. Some evidence suggests a negative role of the ApoE ɛ4 allele for cognitive performance in late life, while beneficial effects on cognition have been shown in young age. We investigated age-related effects of the ApoE gene on brain function by assessing cognitive performance, as well as functional activation patterns during retrieval of Face-Name pairs in a group of young (n = 50; age 26.4±4.6 years, 25 ɛ4 carriers) and old (n = 40; age 66.1±7.0 years, 20 ɛ4 carriers) participants. A cross-sectional factorial design was used to examine the effects of age, ApoE genotype, and their interaction on both cognitive performance and the blood oxygenation level dependent (BOLD) brain response during retrieval of Face-Name pairs. While there were no genotype-related differences in cognitive performance, we found a significant interaction of age and ApoE genotype on task-related activation bilaterally in anterior cingulate gyrus and superior frontal gyrus, as well as left and right insula. Old age was associated with increased activity in ɛ4 carriers. The increased BOLD response in old ɛ4 carriers during retrieval could indicate a neurocognitive disadvantage associated with the ɛ4 allele with increasing age. Furthermore, recruitment of neuronal resources resulted in enhanced memory performance in young ɛ4 carriers, pointing to a better neurofunctional capacity associated with the ApoE4 genotype in young age.
Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming
In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.
Full Text Available BACKGROUND/OBJECTIVE: Gene-gene interactions in the reverse cholesterol transport system for high-density lipoprotein-cholesterol (HDL-C are poorly understood. The present study observed gene-gene combination effect and interactions between single nucleotide polymorphisms (SNPs in ABCA1, APOA1, SR-B1, and CETP in serum HDL-C from a cross-sectional study in the Japanese population. METHODS: The study population comprised 1,535 men and 1,515 women aged 35-69 years who were enrolled in the Japan Multi-Institutional Collaborative Cohort (J-MICC Study. We selected 13 SNPs in the ABCA1, APOA1, CETP, and SR-B1 genes in the reverse cholesterol transport system. The effects of genetic and environmental factors were assessed using general linear and logistic regression models after adjusting for age, sex, and region. PRINCIPAL FINDINGS: Alcohol consumption and daily activity were positively associated with HDL-C levels, whereas smoking had a negative relationship. The T allele of CETP, rs3764261, was correlated with higher HDL-C levels and had the highest coefficient (2.93 mg/dL/allele among the 13 SNPs, which was statistically significant after applying the Bonferroni correction (p<0.001. Gene-gene combination analysis revealed that CETP rs3764261 was associated with high HDL-C levels with any combination of SNPs from ABCA1, APOA1, and SR-B1, although no gene-gene interaction was apparent. An increasing trend for serum HDL-C was also observed with an increasing number of alleles (p<0.001. CONCLUSIONS: The present study identified a multiplier effect from a polymorphism in CETP with ABCA1, APOA1, and SR-B1, as well as a dose-dependence according to the number of alleles present.
Sarup, Pernille Merete
and longevity selected lines. Among the latter genes we found a clear overrepresentation of genes involved in immune functions supporting the hypothesis of the life shortening effect of an overactive immune system (inflammaging). Eighty-four genes were differentially expressed at the same physiological age...... between control and longevity selected lines, and the overlap between the same chronological and physiological age gene lists counted 40 candidate genes for increased longevity. Among these were genes with functions in starvation resistance, a regulator of immune responses and several genes which have...... We have investigated how the gene-expression profile of longevity selected lines of Drosophila melanogaster differed from control lines in young, middle-aged and old male flies. 530 genes were differentially expressed between selected and control flies at the same chronological age. We used...
Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B
A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app email@example.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.
Observed parenting behaviors interact with a polymorphism of the brain-derived neurotrophic factor gene to predict the emergence of oppositional defiant and callous-unemotional behaviors at age 3 years.
Willoughby, Michael T; Mills-Koonce, Roger; Propper, Cathi B; Waschbusch, Daniel A
Using the Durham Child Health and Development Study, this study (N = 171) tested whether observed parenting behaviors in infancy (6 and 12 months) and toddlerhood/preschool (24 and 36 months) interacted with a child polymorphism of the brain-derived neurotrophic factor gene to predict oppositional defiant disorder (ODD) and callous-unemotional (CU) behaviors at age 3 years. Child genotype interacted with observed harsh and intrusive (but not sensitive) parenting to predict ODD and CU behaviors. Harsh-intrusive parenting was more strongly associated with ODD and CU for children with a methionine allele of the brain-derived neurotrophic factor gene. CU behaviors were uniquely predicted by harsh-intrusive parenting in infancy, whereas ODD behaviors were predicted by harsh-intrusive parenting in both infancy and toddlerhood/preschool. The results are discussed from the perspective of the contributions of caregiving behaviors as contributing to distinct aspects of early onset disruptive behavior.
Dong Ling Tong
Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.
Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill
Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.
van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Lagou, Vasiliki
Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.
Pardo, Joaquín; Abba, Martin C; Lacunza, Ezequiel; Ogundele, Olalekan M; Paiva, Isabel; Morel, Gustavo R; Outeiro, Tiago F; Goya, Rodolfo G
In rats, learning and memory performance decline during normal aging, which makes this rodent species a suitable model to evaluate therapeutic strategies. In aging rats, insulin-like growth factor-I (IGF-I), is known to significantly improve spatial memory accuracy as compared to control counterparts. A constellation of gene expression changes underlie the hippocampal phenotype of aging but no studies on the effects of IGF-I on the hippocampal transcriptome of old rodents have been documented. Here, we assessed the effects of IGF-I gene therapy on spatial memory performance in old female rats and compared them with changes in the hippocampal transcriptome. In the Barnes maze test, experimental rats showed a significantly higher exploratory frequency of the goal hole than controls. Hippocampal RNA-sequencing showed that 219 genes are differentially expressed in 28-month-old rats intracerebroventricularly injected with an adenovector expressing rat IGF-I as compared with placebo adenovector-injected counterparts. From the differentially expressed genes, 81 were down and 138 upregulated. From those genes, a list of functionally relevant genes, concerning hippocampal IGF-I expression, synaptic plasticity as well as neuronal function was identified. Our results provide an initial glimpse at the molecular mechanisms underlying the neuroprotective actions of IGF-I in the aging brain.
Greene Casey S
Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be
Fatimah L.C. Jackson
Full Text Available The synergistic effects of genes and the environment on health are explored in three case studies: adult lactase persistence, autism spectrum disorders, and the metabolic syndrome, providing examples of the interactive complexities underlying these phenotypes. Since the phenotypes are the initial targets of evolutionary processes, understanding the specific environmental contexts of the genetic, epigenetic, and proteomic changes associated with these phenotypes is essential in predicting their health implications. Robust databases must be developed on the local scale to deconstruct both the population substructure and the unique components of the environment that stimulate geographically-specific changes in gene expression patterns. To produce these databases and make valid predictions, new, locally-focused and information-dense models are needed that incorporate data on evolutionary ecology, environmental complexity, local geographic patterns of gene expression, and population substructure.
Rachel A Kohman
Full Text Available Normal aging alters expression of numerous genes within the brain. Some of these transcription changes likely contribute to age-associated cognitive decline, reduced neural plasticity, and the higher incidence of neuropathology. Identifying factors that modulate brain aging is crucial for improving quality of life. One promising intervention to counteract negative effects of aging is aerobic exercise. Aged subjects that exercise show enhanced cognitive performance and increased hippocampal neurogenesis and synaptic plasticity. Currently, the mechanisms behind the anti-aging effects of exercise are not understood. The present study conducted a microarray on whole hippocampal samples from adult (3.5-month-old and aged (18-month-old male BALB/c mice that were individually housed with or without running wheels for 8 weeks. Results showed that aging altered genes related to chromatin remodeling, cell growth, immune activity, and synapse organization compared to adult mice. Exercise was found to modulate many of the genes altered by aging, but in the opposite direction. For example, wheel running increased expression of genes related to cell growth and attenuated expression of genes involved in immune function and chromatin remodeling. Collectively, findings show that even late-onset exercise may attenuate age-related changes in gene expression and identifies possible pathways through which exercise may exert its beneficial effects.
Reimherr, Matthew; Nicolae, Dan L
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.
Charruau, Pauline; Johnston, Rachel A.; Stahler, Daniel R.; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W.; vonHoldt, Bridgett M.; Cole, Steven W.; Tung, Jenny; Wayne, Robert K.
Abstract Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566
A multilevel prediction of physiological response to challenge: Interactions among child maltreatment, neighborhood crime, endothelial nitric oxide synthase gene (eNOS), and GABA(A) receptor subunit alpha-6 gene (GABRA6).
Lynch, Michael; Manly, Jody Todd; Cicchetti, Dante
Physiological response to stress has been linked to a variety of healthy and pathological conditions. The current study conducted a multilevel examination of interactions among environmental toxins (i.e., neighborhood crime and child maltreatment) and specific genetic polymorphisms of the endothelial nitric oxide synthase gene (eNOS) and GABA(A) receptor subunit alpha-6 gene (GABRA6). One hundred eighty-six children were recruited at age 4. The presence or absence of child maltreatment as well as the amount of crime that occurred in their neighborhood during the previous year were determined at that time. At age 9, the children were brought to the lab, where their physiological response to a cognitive challenge (i.e., change in the amplitude of the respiratory sinus arrhythmia) was assessed and DNA samples were collected for subsequent genotyping. The results confirmed that complex Gene × Gene, Environment × Environment, and Gene × Environment interactions were associated with different patterns of respiratory sinus arrhythmia reactivity. The implications for future research and evidence-based intervention are discussed.
Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.
Philip J. Lupo
Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.
Kleeberger, Steven R.; Ohtsuka, Yoshinori
Inter-individual variation in human responses to air pollutants suggests that some subpopulations are at increased risk to the detrimental effects of pollutant exposure. Extrinsic factors such as previous exposure and nutritional status may influence individual susceptibility. Intrinsic (host) factors that determine susceptibility include age, gender, and pre-existing disease (e.g., asthma), and it is becoming clear that genetic background also contributes to individual susceptibility. Environmental exposures to particulates and genetic factors associated with disease risk likely interact in a complex fashion that varies from one population and one individual to another. The relationships between genetic background and disease risk and severity are often evaluated through traditional family-based linkage studies and positional cloning techniques. However, case-control studies based on association of disease or disease subphenotypes with candidate genes have advantages over family pedigree studies for complex disease phenotypes. This is based in part on continued development of quantitative analysis and the discovery and availability of simple sequence repeats and single nucleotide polymorphisms. Linkage analyses with genetically standardized animal models also provide a useful tool to identify genetic determinants of responses to environmental pollutants. These approaches have identified significant susceptibility quantitative trait loci on mouse chromosomes 1, 6, 11, and 17. Physical mapping and comparative mapping between human and mouse genomes will yield candidate susceptibility genes that may be tested by association studies in human subjects. Human studies and mouse modeling will provide important insight to understanding genetic factors that contribute to differential susceptibility to air pollutants
Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.
Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi
The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.
Chung, Sun Ju; Armasu, Sebastian M; Anderson, Kari J; Biernacka, Joanna M; Lesnick, Timothy G; Rider, David N; Cunningham, Julie M; Ahlskog, J Eric; Frigerio, Roberta; Maraganore, Demetrius M
Prior studies causally linked mutations in SNCA, MAPT, and LRRK2 genes with familial Parkinsonism. Genome-wide association studies have demonstrated association of single nucleotide polymorphisms (SNPs) in those three genes with sporadic Parkinson's disease (PD) susceptibility worldwide. Here we investigated the interactions between SNPs in those three susceptibility genes and environmental exposures (pesticides application, tobacco smoking, coffee drinking, and alcohol drinking) also associated with PD susceptibility. Pairwise interactions between environmental exposures and 18 variants (16 SNPs and two variable number tandem repeats, or "VNTRs") in SNCA, MAPT and LRRK2, were investigated using data from 1098 PD cases from the upper Midwest, USA and 1098 matched controls. Environmental exposures were assessed using a validated telephone interview script. Five pairwise interactions had uncorrected P-values coffee drinking × MAPT H1/H2 haplotype or MAPT rs16940806, and alcohol drinking × MAPT rs2435211. None of these interactions remained significant after Bonferroni correction. Secondary analyses in strata defined by type of control (sibling or unrelated), sex, or age at onset of the case also did not identify significant interactions after Bonferroni correction. This study documented limited pairwise interactions between established genetic and environmental risk factors for PD; however, the associations were not significant after correction for multiple testing. Copyright © 2013 Elsevier Ltd. All rights reserved.
Van Bel, Michiel; Coppens, Frederik
Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .
Coombes, Brandon; Basu, Saonli; McGue, Matt
Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.
Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.
The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to
Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan
Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.
Schuck, Nicolas W; Petok, Jessica R; Meeter, Martijn; Schjeide, Brit-Maren M; Schröder, Julia; Bertram, Lars; Gluck, Mark A; Li, Shu-Chen
Probabilistic category learning involves complex interactions between the hippocampus and striatum that may depend on whether acquisition occurs via feedback or observation. Little is known about how healthy aging affects these processes. We tested whether age-related behavioral differences in probabilistic category learning from feedback or observation depend on a genetic factor known to influence individual differences in hippocampal function, the KIBRA gene (single nucleotide polymorphism rs17070145). Results showed comparable age-related performance impairments in observational as well as feedback-based learning. Moreover, genetic analyses indicated an age-related interactive effect of KIBRA on learning: among older adults, the beneficial T-allele was positively associated with learning from feedback, but negatively with learning from observation. In younger adults, no effects of KIBRA were found. Our results add behavioral genetic evidence to emerging data showing age-related differences in how neural resources relate to memory functions, namely that hippocampal and striatal contributions to probabilistic category learning may vary with age. Our findings highlight the effects genetic factors can have on differential age-related decline of different memory functions. Copyright © 2017 Elsevier Inc. All rights reserved.
Cardinale, S; Cambray, G
The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content
Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.
Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio
A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.
Pepe, J; Bonnet, N; Herrmann, F R; Biver, E; Rizzoli, R; Chevalley, T; Ferrari, S L
We investigated the interaction between periostin SNPs and the SNPs of the genes assumed to modulate serum periostin levels and bone microstructure in a cohort of postmenopausal women. We identified an interaction between LRP5 SNP rs648438 and periostin SNP rs9547970 on serum periostin levels and on radial cortical porosity. The purpose of this study is to investigate the interaction between periostin gene polymorphisms (SNPs) and other genes potentially responsible for modulating serum periostin levels and bone microstructure in a cohort of postmenopausal women. In 648 postmenopausal women from the Geneva Retirees Cohort, we analyzed 6 periostin SNPs and another 149 SNPs in 14 genes, namely BMP2, CTNNB1, ESR1, ESR2, LRP5, LRP6, PTH, SPTBN1, SOST, TGFb1, TNFRSF11A, TNFSF11, TNFRSF11B and WNT16. Volumetric BMD and bone microstructure were measured by high-resolution peripheral quantitative computed tomography at the distal radius and tibia. Serum periostin levels were associated with radial cortical porosity, including after adjustment for age, BMI, and years since menopause (p = 0.036). Sixteen SNPs in the ESR1, LRP5, TNFRSF11A, SOST, SPTBN1, TNFRSF11B and TNFSF11 genes were associated with serum periostin levels (p range 0.03-0.001) whereas 26 SNPs in 9 genes were associated with cortical porosity at the radius and/or at the tibia. WNT 16 was the gene with the highest number of SNPs associated with both trabecular and cortical microstructure. The periostin SNP rs9547970 was also associated with cortical porosity (p = 0.04). In particular, SNPs in LRP5, ESR1 and near the TNFRSF11A gene were associated with both cortical porosity and serum periostin levels. Eventually, we identified an interaction between LRP5 SNP rs648438 and periostin SNP rs9547970 on serum periostin levels (interaction p = 0.01) and on radial cortical porosity (interaction p = 0.005). These results suggest that periostin expression is genetically modulated, particularly by polymorphisms
A. K. PARIHAR
explaining the manifestation of complex traits such as yield. ... interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. ... Keywords. grass pea; scaling test; gene interactions; gene effects; heritability; Lathyrus sativus.
Brahe, Lena Kirchner; Angquist, Lars; Larsen, Lesli Hingstrup
Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene-diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile ...
Full Text Available Age-related macular degeneration (AMD is a progressive neurodegenerative disease that affects approximately 8.7% of elderly people worldwide (>55 years old. AMD is characterized by a multifactorial aetiology that involves several genetic and environmental risk factors (genes, ageing, smoking, family history, dietary habits, oxidative stress, and hypertension. In particular, ageing and cigarette smoking (including oxidative compounds and reactive oxygen species have been shown to significantly increase susceptibility to the disease. Furthermore, different genes (CFH, CFI, C2, C3, IL-6, IL-8, and ARMS2 that play a crucial role in the inflammatory pathway have been associated with AMD risk. Several genetic and molecular studies have indicated the participation of inflammatory molecules (cytokines and chemokines, immune cells (macrophages, and complement proteins in the development and progression of the disease. Taking into consideration the genetic and molecular background, this review highlights the genetic role of inflammatory genes involved in AMD pathogenesis and progression.
Liu, Gang; Lee, Seunggeun; Lee, Alice W
test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides power gain compared to the standard logistic regression analysis and better control of Type I error when compared to the analysis......There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances the power for testing multiplicative interaction in case......-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated Type I error in the corresponding tests can occur. This paper extends the empirical Bayes (EB) approach previously developed for multiplicative interaction that trades off between bias and efficiency...
Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny
Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812
Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.
Pilling, Luke C; Joehanes, Roby; Melzer, David; Harries, Lorna W; Henley, William; Dupuis, Josée; Lin, Honghuang; Mitchell, Marcus; Hernandez, Dena; Ying, Sai-Xia; Lunetta, Kathryn L; Benjamin, Emelia J; Singleton, Andrew; Levy, Daniel; Munson, Peter; Murabito, Joanne M; Ferrucci, Luigi
Chronically elevated circulating inflammatory markers are common in older persons but mechanisms are unclear. Many blood transcripts (>800 genes) are associated with interleukin-6 protein levels (IL6) independent of age. We aimed to identify gene transcripts statistically mediating, as drivers or responders, the increasing levels of IL6 protein in blood at older ages. Blood derived in-vivo RNA from the Framingham Heart Study (FHS, n=2422, ages 40-92 yrs) and InCHIANTI study (n=694, ages 30-104 yrs), with Affymetrix and Illumina expression arrays respectively (>17,000 genes tested), were tested for statistical mediation of the age-IL6 association using resampling techniques, adjusted for confounders and multiple testing. In FHS, IL6 expression was not associated with IL6 protein levels in blood. 102 genes (0.6% of 17,324 expressed) statistically mediated the age-IL6 association of which 25 replicated in InCHIANTI (including 5 of the 10 largest effect genes). The largest effect gene (SLC4A10, coding for NCBE, a sodium bicarbonate transporter) mediated 19% (adjusted CI 8.9 to 34.1%) and replicated by PCR in InCHIANTI (n=194, 35.6% mediated, p=0.01). Other replicated mediators included PRF1 (perforin, a cytolytic protein in cytotoxic T lymphocytes and NK cells) and IL1B (Interleukin 1 beta): few other cytokines were significant mediators. This transcriptome-wide study on human blood identified a small distinct set of genes that statistically mediate the age-IL6 association. Findings are robust across two cohorts and different expression technologies. Raised IL6 levels may not derive from circulating white cells in age related inflammation. Published by Elsevier Inc.
Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in
Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.
Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…
Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.
Van Yper, Lindsey N; Vermeire, Katrien; De Vel, Eddy F J; Beynon, Andy J; Dhooge, Ingeborg J M
Age-related hearing loss hampers the ability to understand speech in adverse listening conditions. This is attributed to a complex interaction of changes in the peripheral and central auditory system. One aspect that may deteriorate across the lifespan is binaural interaction. The present study investigates binaural interaction at the level of the auditory brainstem. It is hypothesized that brainstem binaural interaction deteriorates with advancing age. Forty-two subjects of various age participated in the study. Auditory brainstem responses (ABRs) were recorded using clicks and 500 Hz tone-bursts. ABRs were elicited by monaural right, monaural left, and binaural stimulation. Binaural interaction was investigated in two ways. First, grand averages of the binaural interaction component were computed for each age group. Second, wave V characteristics of the binaural ABR were compared with those of the summed left and right ABRs. Binaural interaction in the click ABR was demonstrated by shorter latencies and smaller amplitudes in the binaural compared with the summed monaural responses. For 500 Hz tone-burst ABR, no latency differences were found. However, amplitudes were significantly smaller in the binaural than summed monaural condition. An age-effect was found for 500 Hz tone-burst, but not for click ABR. Brainstem binaural interaction seems to decline with age. Interestingly, these changes seem to be stimulus-dependent.
Current dietary guidelines for fat intake have not taken into consideration the possible genetic differences underlying the individual variability in responsiveness to dietary components. Genetic variability has been identified in humans for all the known lipid metabolism-related genes resulting in a plethora of candidate genes and genetic variants to examine in diet-gene interaction studies focused on fat consumption. Some examples of fat-gene interaction are reviewed. These include: the interaction between total intake and the 14C/T in the hepatic lipase gene promoter in determining high-density lipoprotein cholesterol (HDL-C) metabolism; the interaction between polyunsaturated fatty acids (PUFA) and the 5G/A polymorphism in the APOA1 gene plasma HDL-C concentrations; the interaction between PUFA and the L162V polymorphism in the PPARA gene in determining triglycerides and APOC3 concentrations; and the interaction between PUFA intake and the -1131T>C in the APOA5 gene in determining triglyceride metabolism. Although hundreds of diet-gene interaction studies in lipid metabolism have been published, the level of evidence to make specific nutritional recommendations to the population is still low and more research in nutrigenetics has to be undertaken. (Author) 31 refs.
Age-dependent interaction of apolipoprotein E gene with eastern birthplace in Finland affects severity of coronary atherosclerosis and risk of fatal myocardial infarction--Helsinki Sudden Death Study.
Tyynelä, Petri; Goebeler, Sirkka; Ilveskoski, Erkki; Mikkelsson, Jussi; Perola, Markus; Lehtimäki, Terho; Karhunen, Pekka J
Mortality from coronary heart disease (CHD) has been constantly higher in eastern late settlement regions compared to western early settlements in Finland, unrelated to classical risk factors. In line with this, eastern birthplace was an age-dependent predictor of severe coronary atherosclerosis and pre-hospital sudden coronary death among male residents of Helsinki. We investigated a possible interaction of apolipoprotein E (APOE) gene with birthplace on the risk of myocardial infarction (MI) and coronary atherosclerosis. APOE genotypes were analyzed in the Helsinki Sudden Death Study series comprising out-of-hospital deaths among males aged 33-70 years (n = 577), who were born in high (east, n = 273) or low (west, n = 304) CHD mortality area. Eastern-born men ≤ 55 years carried 30% more often (P = 0.017) and older men 40% less often (P = 0.022) the APOE ϵ4 allele compared to western-born men (P = 0.003 for birthplace-by-age interaction). In multivariate analysis, the ϵ4 allele associated with the risk of out-of-hospital MI (odds ratio 2.58; 95% CI 1.20-5.55; P = 0.016) only in eastern-born men and with advanced atherosclerosis in both regions of origin, respectively. Birthplace-bound risk of CHD was age-dependently modified by APOE ϵ4 allele, suggesting genetic differences in CHD susceptibility between early and late settlement regions in Finland and providing one explanation for the eastern high mortality.
Pan, David Z; Garske, Kristina M; Alvarez, Marcus; Bhagat, Yash V; Boocock, James; Nikkola, Elina; Miao, Zong; Raulerson, Chelsea K; Cantor, Rita M; Civelek, Mete; Glastonbury, Craig A; Small, Kerrin S; Boehnke, Michael; Lusis, Aldons J; Sinsheimer, Janet S; Mohlke, Karen L; Laakso, Markku; Pajukanta, Päivi; Ko, Arthur
Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi-C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis-eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5, which we further confirm by EMSA, and highlights 38 additional candidate genes.
Age-related macular degeneration (AMD) is a prevalent blinding disease, accounting for roughly 50% of blindness in developed nations. Very significant advances have been made in terms of discovering genetic susceptibilities to AMD as well as dietary risk factors. To date, nutritional supplementation...
Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M
Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and ......Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome...
Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P
and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...
Meng, Guofeng; Zhong, Xiaoyan; Mei, Hongkang
Aging, as a complex biological process, is accompanied by the accumulation of functional loses at different levels, which makes age to be the biggest risk factor to many neurological diseases. Even following decades of investigation, the process of aging is still far from being fully understood, especially at a systematic level. In this study, we identified aging related genes in brain by collecting the ones with sustained and consistent gene expression or DNA methylation changes in the aging process. Functional analysis with Gene Ontology to these genes suggested transcriptional regulators to be the most affected genes in the aging process. Transcription regulation analysis found some transcription factors, especially Specificity Protein 1 (SP1), to play important roles in regulating aging related gene expression. Module-based functional analysis indicated these genes to be associated with many well-known aging related pathways, supporting the validity of our approach to select aging related genes. Finally, we investigated the roles of aging related genes on Alzheimer's Disease (AD). We found that aging and AD related genes both involved some common pathways, which provided a possible explanation why aging made the brain more vulnerable to Alzheimer's Disease.
Roecklein, Kathryn A; Wong, Patricia M; Franzen, Peter L; Hasler, Brant P; Wood-Vasey, W Michael; Nimgaonkar, Vishwajit L; Miller, Megan A; Kepreos, Kyle M; Ferrell, Robert E; Manuck, Stephen B
The human melanopsin gene has been reported to mediate risk for seasonal affective disorder (SAD), which is hypothesized to be caused by decreased photic input during winter when light levels fall below threshold, resulting in differences in circadian phase and/or sleep. However, it is unclear if melanopsin increases risk of SAD by causing differences in sleep or circadian phase, or if those differences are symptoms of the mood disorder. To determine if melanopsin sequence variations are associated with differences in sleep-wake behavior among those not suffering from a mood disorder, the authors tested associations between melanopsin gene polymorphisms and self-reported sleep timing (sleep onset and wake time) in a community sample (N = 234) of non-Hispanic Caucasian participants (age 30-54 yrs) with no history of psychological, neurological, or sleep disorders. The authors also tested the effect of melanopsin variations on differences in preferred sleep and activity timing (i.e., chronotype), which may reflect differences in circadian phase, sleep homeostasis, or both. Daylength on the day of assessment was measured and included in analyses. DNA samples were genotyped for melanopsin gene polymorphisms using fluorescence polarization. P10L genotype interacted with daylength to predict self-reported sleep onset (interaction p sleep onset among those with the TT genotype was later in the day when individuals were assessed on longer days and earlier in the day on shorter days, whereas individuals in the other genotype groups (i.e., CC and CT) did not show this interaction effect. P10L genotype also interacted in an analogous way with daylength to predict self-reported morningness (interaction p sleep onset and chronotype as a function of daylength, whereas other genotypes at P10L do not seem to have effects that vary by daylength. A better understanding of how melanopsin confers heightened responsivity to daylength may improve our understanding of a broad range of
Kim, Theresa H M; Connolly, Jennifer A; Rotondi, Michael; Tamim, Hala
Positive-interaction parenting early in childhood is encouraged due to its association with behavioural development later in life. The objective of this study was to examine if the level of positive-interaction parenting style differs among teen, optimal age, and advanced age mothers in Canada, and to identify the characteristics associated with positive-interaction parenting style separately for each age group. This was a cross-sectional secondary analysis of the National Longitudinal Survey of Children and Youth. First-time mothers with children 0-23 months were grouped into: teen (15-19 years, N = 53,409), optimal age (20-34 years, N = 790,960), and advanced age (35 years and older, N = 106,536). The outcome was positive-interaction parenting style (Parenting Practices Scale); maternal socio-demographics, health, social, and child characteristics were considered for backward stepwise multiple linear regression modeling, stratified for each of the age groups. Teen, optimal age, and advanced age mothers reported similar levels of positive- interaction parenting style. Covariates differed across the three age groups. Among optimal age mothers, being an ever-landed immigrant, childcare use, and being devoted to religion were found to decrease positive-interaction parenting style, whereas, higher education was found to increase positive-interaction parenting style. Teen mothers were not found to have any characteristics uniquely associated with positive-interaction parenting. Among advanced age mothers, social support was uniquely associated with an increase in positive-interaction parenting. Very good/excellent health was found to be positively associated with parenting in teens but negatively associated with parenting in advanced age mothers. Characteristics associated with positive-interaction parenting varied among the three age groups. Findings may have public health implications through information dissemination to first-time mothers, clinicians
AlShahrani, Mona; Hoehndorf, Robert
In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.
In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.
Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A
Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of
Kim, Kyung Mok; Chung, Ki Wung; Jeong, Hyeong Oh; Lee, Bonggi; Kim, Dae Hyun; Park, June Whoun; Kim, Seong Min; Yu, Byung Pal; Chung, Hae Young
Age-associated renal fibrosis is related with renal function decline during aging. Imbalance between accumulation and degradation of extracellular matrix is key feature of fibrosis. In this study, RNA-sequencing (RNA-Seq) results based on next-generation sequencing (NGS) data were analyzed to identify key proteins that change during aging and calorie restriction (CR). Among the changed genes, A2M and MMP2, which are known to interact, exhibited the highest between centrality (BC) and degree values when analyzed by protein–protein interaction (PPI). Both mRNA and protein levels of MMP2 and A2M were increased during aging. Furthermore, the interaction between MMP2 and A2M was verified by immunoprecipitation and immunohistochemistry. MMP2 activity was further measured under the presence or absence of A2M-MMP2 interaction. MMP2 activity, which was increased under the absence of A2M-MMP2 interaction, was significantly decreased under the presence of interactions in aged kidney. We further hypothesized that the interaction between A2M-MMP2 played a role in the inactivation of MMP2 leading to accumulation of ECM including collagen type I and IV. Aged kidney showed highly accumulated MMP2 substrate proteins despite of increased MMP2 protein expression and CR blunted these accumulation. Additional in vivo analysis revealed that the signal transducer and activator of transcription (STAT) 3 transcriptional factor was significantly increased thus increasing A2M expression during aging. STAT3 activating cytokines were also highly increased in aged kidney. In conclusion, the results of the present study indicate that A2M-MMP2 interaction has a role in age-associated renal ECM accumulation and in the suppression such fibrosis by CR. PMID:29464020
Berchtold, Nicole C.; Cribbs, David H.; Coleman, Paul D.; Rogers, Joseph; Head, Elizabeth; Kim, Ronald; Beach, Tom; Miller, Carol; Troncoso, Juan; Trojanowski, John Q.; Zielke, H. Ronald; Cotman, Carl W.
Gene expression profiles were assessed in the hippocampus, entorhinal cortex, superior-frontal gyrus, and postcentral gyrus across the lifespan of 55 cognitively intact individuals aged 20–99 years. Perspectives on global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age in the superior-frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the sixth to seventh decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with down-regulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with proportionally greater activation in the female brain. These data open opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain and suggest that this balance is set differently in males and females, an intriguing idea. PMID:18832152
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.
Full Text Available Tomato fruit firmness is a polygenetic trait and depends on firmness components pericarp thickness, firmness of epidermis and firmness of flash. The accumulation of favourable traits ratio for each component (towards the increase of expression the fruit firmness can be increased. This paper deals with aspects of increasing fruit firmness by increasing firmness of epidermis and thickness of pericarp. By using genotypes with rin (ripening inhibitor gene, we were able to accomplish great firmness of fruits, especially firmness of flash. The expression of these traits cause the asynchronization of maturing process so the fruits do not over mature or soften. Genetic effects have been evaluated by researching the average values of fruit firmness in six diallel parent lines (D-150, S-49, S-35, H-52, Kg-z and SP-109 and progeny (P1, P2, F1, F2, BC1 and BC2 by applying additive dominant model with three and six parameters (Mather and Jinks, 1982. Mean values of fruit firmness for parents and progeny were significantly different. Firmness of fruits is a trait influenced first of all by additive gene since they were found in all researched combinations. Epystatic gene effect was important in inheriting process for all three two-gene interactions. The stabile duplicate type of epystsase was found, which in this case reduces the unfavourable effects of dominant genes of parents with soft fruits. .
Full Text Available The etiology of the sporadic form of Alzheimer's disease (AD remains largely unknown. Recent evidence has suggested that gene-environment interactions (GxE may play a crucial role in its development and progression. Whereas various susceptibility loci have been identified, like the apolipoprotein E4 allele, these cannot fully explain the increasing prevalence of AD observed with aging. In addition to such genetic risk factors, various environmental factors have been proposed to alter the risk of developing AD as well as to affect the rate of cognitive decline in AD patients. Nevertheless, aside from the independent effects of genetic and environmental risk factors, their synergistic participation in increasing the risk of developing AD has been sparsely investigated, even though evidence points towards such a direction. Advances in the genetic manipulation of mice, modeling various aspects of the AD pathology, have provided an excellent tool to dissect the effects of genes, environment, and their interactions. In this paper we present several environmental factors implicated in the etiology of AD that have been tested in transgenic animal models of the disease. The focus lies on the concept of GxE and its importance in a multifactorial disease like AD. Additionally, possible mediating mechanisms and future challenges are discussed.
Full Text Available Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55% were clean reads. Five differentially expressed genes with an adjusted P value 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.
Full Text Available Abstract Background The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources. Results Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes. Conclusion We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for
Ashapkin, V V; Linkova, N S; Khavinson, V Kh; Vanyushin, B F
Expression levels of genes encoding specific transcription factors and other functionally important proteins vary upon aging of pancreatic and bronchial epithelium cell cultures. The peptides KEDW and AEDL tissue-specifically affect gene expression in pancreatic and bronchial cell cultures, respectively. It is established in this work that the DNA methylation patterns of the PDX1, PAX6, NGN3, NKX2-1, and SCGB1A1 gene promoter regions change upon aging in pancreatic and bronchial cell cultures in correlation with variations in their expression levels. Thus, stable changes in gene expression upon aging of cell cultures could be caused by changes in their promoter methylation patterns. The methylation patterns of the PAX4 gene in pancreatic cells as well as those of the FOXA1, SCGB3A2, and SFTPA1 genes in bronchial cells do not change upon aging and are unaffected by peptides, whereas their expression levels change in both cases. The promoter region of the FOXA2 gene in pancreatic cells contains a small number of methylated CpG sites, their methylation levels being affected by cell culture aging and KEDW, though without any correlation with gene expression levels. The promoter region of the FOXA2 gene is completely unmethylated in bronchial cells irrespective of cell culture age and AEDL action. Changes in promoter methylation might be the cause of age- and peptide-induced variations in expression levels of the PDX1, PAX6, and NGN3 genes in pancreatic cells and NKX2-1 and SCGB1A1 genes in bronchial cells. Expression levels of the PAX4 and FOXA2 genes in pancreatic cells and FOXA1, FOXA2, SCGB3A2, and SFTPA1 genes in bronchial cells seem to be controlled by some other mechanisms.
Altshuler, Ianina; McLeod, Anne M; Colbourne, John K; Yan, Norman D; Cristescu, Melania E
Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.
Full Text Available Thearticlepresentsthe results of studies of the phenomenon empirical inter-age manipulation in the pedagogical interaction. Inter-age manipulation is considered a form of manipulation carried out on the basis of an appeal to the participants in the interaction age roles. Based on the results of a survey 109 teenagers 13-15 years, using a questionnaire, color test of relations and projective drawing shows that inter-age manipulation is a common way to impact on the students, elected teacher. Teachers are the subjects of inter-age manipulation more often than students. It was revealed that the effectiveness of inter-age manipulation in pedagogical interaction increases if it is meaningful is consistent with the normative content of age roles, as well as «inter-age distance" between the teacher and the students. The greatest effectiveness of have inter-age manipulation undertaken for older teachers, and manipulation "from below" from young teachers
To understand mechanisms of neurotoxicity in susceptible populations, we examined age-related changes in constitutive gene expression in the retinas of young (4mos), middle-aged (11 mos) and aged (23 mos) male Long Evans rats. Derived from a pouch of the forebrain during develop...
Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.
Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao
To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright Â© 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Full Text Available Abstract Background Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS, a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte
Zeng, Yi; Chen, Huashuai; Ni, Ting
Logistic regression analysis based on data from 822 Han Chinese oldest old aged 92+ demonstrated that interactions between carrying FOXO1A-266 or FOXO3-310 or FOXO3-292 and tea drinking at around age 60 or at present time were significantly associated with lower risk of cognitive disability...... at advanced ages. Associations between tea drinking and reduced cognitive disability were much stronger among carriers of the genotypes of FOXO1A-266 or FOXO3-310 or FOXO3-292 compared with noncarriers, and it was reconfirmed by analysis of three-way interactions across FOXO genotypes, tea drinking at around...... age 60, and at present time. Based on prior findings from animal and human cell models, we postulate that intake of tea compounds may activate FOXO gene expression, which in turn may positively affect cognitive function in the oldest old population. Our empirical findings imply that the health...
Manuella Nóbrega Dourado
Full Text Available Bacteria from the genus Methylobacterium interact symbiotically (endophytically and epiphytically with different plant species. These interactions can promote plant growth or induce systemic resistance, increasing plant fitness. The plant colonization is guided by molecular communication between bacteria-bacteria and bacteria-plants, where the bacteria recognize specific exuded compounds by other bacteria (e.g. homoserine molecules and/or by the plant roots (e.g. flavonoids, ethanol and methanol, respectively. In this context, the aim of this study was to evaluate the effect of quorum sensing molecules (N-acyl-homoserine lactones and plant exudates (including ethanol in the expression of a series of bacterial genes involved in Methylobacterium-plant interaction. The selected genes are related to bacterial metabolism (mxaF, adaptation to stressful environment (crtI, phoU and sss, to interactions with plant metabolism compounds (acdS and pathogenicity (patatin and phoU. Under in vitro conditions, our results showed the differential expression of some important genes related to metabolism, stress and pathogenesis, thereby AHL molecules up-regulate all tested genes, except phoU, while plant exudates induce only mxaF gene expression. In the presence of plant exudates there is a lower bacterial density (due the endophytic and epiphytic colonization, which produce less AHL, leading to down regulation of genes when compared to the control. Therefore, bacterial density, more than plant exudate, influences the expression of genes related to plant-bacteria interaction.
Wang, Cecilia; Yolitz, Jason; Alberico, Thomas; Laslo, Mara; Sun, Yaning; Wheeler, Charles T; Sun, Xiaoping; Zou, Sige
Botanicals possess numerous bioactivities, and some promote healthy aging. Dietary macronutrients are major determinants of life span. The interaction between botanicals and macronutrients that modulates life span is not well understood. Here, we investigated the effect of a cranberry-containing botanical on life span and the influence of macronutrients on the longevity-related effect of cranberry in Drosophila. Flies were supplemented with cranberry on three dietary conditions: standard, high sugar-low protein, and low sugar-high protein diets. We found that cranberry slightly extended life span in males fed with the low sugar-high protein diet but not with other diets. Cranberry extended life span in females fed with the standard diet and more prominently the high sugar-low protein diet but not with the low sugar-high protein diet. Life-span extension was associated with increased reproduction and higher expression of oxidative stress and heat shock response genes. Moreover, cranberry improved survival of sod1 knockdown and dfoxo mutant flies but did not increase wild-type fly's resistance to acute oxidative stress. Cranberry slightly extended life span in flies fed with a high-fat diet. These findings suggest that cranberry promotes healthy aging by increasing stress responsiveness. Our study reveals an interaction of cranberry with dietary macronutrients and stresses the importance of considering diet composition in designing interventions for promoting healthy aging. Published by Oxford University Press on behalf of the Gerontological Society of America 2013.
Brett A McKinney
Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to
Galan-Chilet, Inmaculada; Grau-Perez, Maria; De Marco, Griselda; Guallar, Eliseo; Martin-Escudero, Juan Carlos; Dominguez-Lucas, Alejandro; Gonzalez-Manzano, Isabel; Lopez-Izquierdo, Raul; Briongos-Figuero, Laisa Socorro; Redon, Josep; Chaves, Felipe Javier; Tellez-Plaza, Maria
Selenium and single-nucleotide-polymorphisms in selenoprotein genes have been associated to diabetes. However, the interaction of selenium with genetic variation in diabetes and oxidative stress-related genes has not been evaluated as a potential determinant of diabetes risk. We evaluated the cross-sectional and prospective associations of plasma selenium concentrations with type 2 diabetes, and the interaction of selenium concentrations with genetic variation in candidate polymorphisms, in a representative sample of 1452 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.2µg/L. 120 participants had diabetes at baseline. Among diabetes-free participants who were not lost during the follow-up (N=1234), 75 developed diabetes over time. The multivariable adjusted odds ratios (95% confidence interval) for diabetes prevalence comparing the second and third to the first tertiles of plasma selenium levels were 1.80 (1.03, 3.14) and 1.97 (1.14, 3.41), respectively. The corresponding hazard ratios (95% CI) for diabetes incidence were 1.76 (0.96, 3.22) and 1.80 (0.98, 3.31), respectively. In addition, we observed significant interactions between selenium and polymorphisms in PPARGC1A, and in genes encoding mitochondrial proteins, such as BCS1L and SDHA, and suggestive interactions of selenium with other genes related to selenoproteins and redox metabolism. Plasma selenium was positively associated with prevalent and incident diabetes. While the statistical interactions of selenium with polymorphisms involved in regulation of redox and insulin signaling pathways provide biological plausibility to the positive associations of selenium with diabetes, further research is needed to elucidate the causal pathways underlying these associations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Gokarn, Rahul; Solon-Biet, Samantha M; Cogger, Victoria C; Cooney, Gregory J; Wahl, Devin; McMahon, Aisling C; Mitchell, James R; Mitchell, Sarah J; Hine, Christopher; de Cabo, Rafael; Raubenheimer, David; Simpson, Stephen J; Le Couteur, David G
Nutrition influences both hepatic function and aging, but mechanisms are poorly understood. Here, the effects of lifelong, ad libitum-fed diets varying in macronutrients and energy on hepatic gene expression were studied. Gene expression was measured using Affymetrix mouse arrays in livers of 46 mice aged 15 months fed one of 25 diets varying in protein, carbohydrates, fat, and energy density from 3 weeks of age. Gene expression was almost entirely influenced by protein intake. Carbohydrate and fat intake had few effects on gene expression compared with protein. Pathways and processes associated with protein intake included those involved with mitochondrial function, metabolic signaling (PI3K-Akt, AMPK, mTOR) and metabolism of protein and amino acids. Protein intake had variable effects on genes associated with regulation of longevity and influenced by caloric restriction. Among the genes of interest with expression that were significantly associated with protein intake are Cth, Gls2, Igf1, and Nnmt, which were increased with higher protein intake, and Igf2bp2, Fgf21, Prkab2, and Mtor, which were increased with lower protein intake. Dietary protein has a powerful impact on hepatic gene expression in older mice, with some overlap with genes previously reported to be involved with regulation of longevity or caloric restriction.
Gupta, Arpana; Labus, Jennifer; Kilpatrick, Lisa A; Bonyadi, Mariam; Ashe-McNalley, Cody; Heendeniya, Nuwanthi; Bradesi, Sylvie; Chang, Lin; Mayer, Emeran A
Early adverse life events (EALs) have been associated with regional thinning of the subgenual cingulate cortex (sgACC), a brain region implicated in the development of disorders of mood and affect, and often comorbid functional pain disorders, such as irritable bowel syndrome (IBS). Regional neuroinflammation related to chronic stress system activation has been suggested as a possible mechanism underlying these neuroplastic changes. However, the interaction of genetic and environmental factors in these changes is poorly understood. The current study aimed to evaluate the interactions of EALs and candidate gene polymorphisms in influencing thickness of the sgACC. 210 female subjects (137 healthy controls; 73 IBS) were genotyped for stress and inflammation-related gene polymorphisms. Genetic variation with EALs, and diagnosis on sgACC thickness was examined, while controlling for race, age, and total brain volume. Compared to HCs, IBS had significantly reduced sgACC thickness (p = 0.03). Regardless of disease group (IBS vs. HC), thinning of the left sgACC was associated with a significant gene-gene environment interaction between the IL-1β genotype, the NR3C1 haplotype, and a history of EALs (p = 0.05). Reduced sgACC thickness in women with the minor IL-1β allele, was associated with EAL total scores regardless of NR3C1 haplotype status (p = 0.02). In subjects homozygous for the major IL-1β allele, reduced sgACC with increasing levels of EALs was seen only with the less common NR3C1 haplotype (p = 0.02). These findings support an interaction between polymorphisms related to stress and inflammation and early adverse life events in modulating a key region of the emotion arousal circuit.
Aging is as a result of dysfunction of the body mechanisms due to failure of one organelle, tissue, component or the other. In man there is a pointer towards gene loss as a primary cause of ageing. In this paper we develop a mathematical model describing changes in gene efficiency or gene failure. This model is used to ...
Erokhin, Maksim; Davydova, Anna; Kyrchanova, Olga; Parshikov, Alexander; Georgiev, Pavel; Chetverina, Darya
Chromatin insulators are regulatory elements involved in the modulation of enhancer-promoter communication. The 1A2 and Wari insulators are located immediately downstream of the Drosophila yellow and white genes, respectively. Using an assay based on the yeast GAL4 activator, we have found that both insulators are able to interact with their target promoters in transgenic lines, forming gene loops. The existence of an insulator-promoter loop is confirmed by the fact that insulator proteins could be detected on the promoter only in the presence of an insulator in the transgene. The upstream promoter regions, which are required for long-distance stimulation by enhancers, are not essential for promoter-insulator interactions. Both insulators support basal activity of the yellow and white promoters in eyes. Thus, the ability of insulators to interact with promoters might play an important role in the regulation of basal gene transcription.
Sameith, Katrin; Amini, Saman; Groot Koerkamp, Marian J A; van Leenen, Dik; Brok, Mariel; Brabers, Nathalie; Lijnzaad, Philip; van Hooff, Sander R; Benschop, Joris J; Lenstra, Tineke L; Apweiler, Eva; van Wageningen, Sake; Snel, Berend; Holstege, Frank C P; Kemmeren, Patrick
Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering pathway organization and understanding the relationship between genotype, phenotype and disease. To investigate the nature of genetic interactions between gene-specific transcription factors (GSTFs) in Saccharomyces cerevisiae, we systematically analyzed 72 GSTF pairs by gene expression profiling double and single deletion mutants. These pairs were selected through previously published growth-based genetic interactions as well as through similarity in DNA binding properties. The result is a high-resolution atlas of gene expression-based genetic interactions that provides systems-level insight into GSTF epistasis. The atlas confirms known genetic interactions and exposes new ones. Importantly, the data can be used to investigate mechanisms that underlie individual genetic interactions. Two molecular mechanisms are proposed, "buffering by induced dependency" and "alleviation by derepression". These mechanisms indicate how negative genetic interactions can occur between seemingly unrelated parallel pathways and how positive genetic interactions can indirectly expose parallel rather than same-pathway relationships. The focus on GSTFs is important for understanding the transcription regulatory network of yeast as it uncovers details behind many redundancy relationships, some of which are completely new. In addition, the study provides general insight into the complex nature of epistasis and proposes mechanistic models for genetic interactions, the majority of which do not fall into easily recognizable within- or between-pathway relationships.
Irizar, Haritz; Goñi, Joaquín; Alzualde, Ainhoa; Castillo-Triviño, Tamara; Olascoaga, Javier; Lopez de Munain, Adolfo; Otaegui, David
Both cellular senescence and organismic aging are known to be dynamic processes that start early in life and progress constantly during the whole life of the individual. In this work, with the objective of identifying signatures of age-related progressive change at the transcriptomic level, we have performed a whole-genome gene expression analysis of peripheral blood leukocytes in a group of healthy individuals with ages ranging from 14 to 93 years. A set of genes with progressively changing gene expression (either increase or decrease with age) has been identified and contextualized in a coexpression network. A modularity analysis has been performed on this network and biological-term and pathway enrichment analyses have been used for biological interpretation of each module. In summary, the results of the present work reveal the existence of a transcriptomic component that shows progressive expression changes associated to age in peripheral blood leukocytes, highlighting both the dynamic nature of the process and the need to complement young vs. elder studies with longitudinal studies that include middle aged individuals. From the transcriptional point of view, immunosenescence seems to be occurring from a relatively early age, at least from the late 20s/early 30s, and the 49-56 year old age-range appears to be critical. In general, the genes that, according to our results, show progressive expression changes with aging are involved in pathogenic/cellular processes that have classically been linked to aging in humans: cancer, immune processes and cellular growth vs. maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.
Moran, Paula; Stokes, Jennifer; Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John; O'Tuathaigh, Colm
The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.
Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John
The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886
Yang, Chunxia; Sun, Ning; Liu, Zhifen; Li, Xinrong; Xu, Yong; Zhang, Kerang
Major depressive disorder (MDD) is a mental disorder that results from complex interplay between multiple and partially overlapping sets of susceptibility genes and environmental factors. The brain derived neurotrophic factor (BDNF) and Protein kinase C gamma type (PRKCG) are logical candidate genes in MDD. Among diverse environmental factors, negative life events have been suggested to exert a crucial impact on brain development. In the present study, we hypothesized that interactions between genetic variants in BDNF and PRKCG and negative life events may play an important role in the development of MDD. We recruited a total of 406 patients with MDD and 391 age- and gender-matched control subjects. Gene-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Under a dominant model, we observed a significant three-way interaction among BDNF rs6265, PRKCG rs3745406, and negative life events. The gene-environment combination of PRKCG rs3745406 C allele, BDNF rs6265 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 5.97; 95% CI, 2.71-13.15). To our knowledge, this is the first report of evidence that the BDNF-PRKCG interaction may modify the relationship between negative life events and MDD in the Chinese population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Dang, J; Shan, S; Li, J; Zhao, H; Xin, Q; Liu, Y; Bian, X; Liu, Q
Interferon (IFN) activation signaling and T helper 17 (Th17)-cell/B-cell regulation play a critical role in the pathogenesis of systemic lupus erythematosus (SLE). Several studies have provided convincing evidence that polymorphisms in IRF5, STAT4, IKZF1 and ETS1 from these pathways may be involved in SLE by affecting gene expression or epistasis. We analyzed the genetic interaction in known SLE susceptibility loci from the four genes in northern Han Chinese. A total of 946 northern Han Chinese participated in this study (370 unrelated SLE patients and 576 healthy controls). Subjects underwent genotyping for the single-nucleotide polymorphisms (SNPs) rs2004640 in IRF5, rs7574865 in STAT4, rs4917014 in IKZF1 and rs1128334 in ETS1 by use of a TaqMan SNP genotyping assay and direct sequencing. Gene-gene interaction analysis involved direct counting, multifactor dimensionality reduction (MDR) and linear regression analysis. SLE patients and controls differed in allele frequencies of rs7574865, rs1128334 (P < 0.001) and rs4917014 (P < 0.01). Direct counting revealed that the frequency of risk homozygote combinations was higher for SLE patients than controls (P < 0.01). Furthermore, 2-, 3- and 4-way gene-gene epistasis in SLE was confirmed by parametric methods and MDR analysis. Gene expression analysis partially supported the findings. Our study confirmed the association of the IFN pathway or Th17/B-cells and the pathogenesis of SLE, and gene-gene interaction in this pathway may increase the risk of SLE. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Nigg, Joel; Nikolas, Molly; Burt, S. Alexandra
Objective: To summarize and evaluate the state of knowledge regarding the role of measured gene-by-environment interactions in relation to attention-deficit/hyperactivity disorder. Method: A selective review of methodologic issues was followed by a systematic search for relevant articles on measured gene-by-environment interactions; the search…
Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. Thi...
Liu, Dongjing; Schwender, Holger; Wang, Mengying; Wang, Hong; Wang, Ping; Zhu, Hongping; Zhou, Zhibo; Li, Jing; Wu, Tao; Beaty, Terri H
Small ubiquitin-like modification, also known as sumoylation, is a crucial post-translational regulatory mechanisms involved in development of the lip and palate. Recent studies reported two sumoylation target genes, MSX1 and TP63, to have achieved genome-wide level significance in tests of association with nonsyndromic clefts. Here, we performed a candidate gene analysis considering gene-gene and gene-environment interaction for SUMO1, MSX1, and TP63 to further explore the etiology of nonsyndromic cleft lip with or without cleft palate (NSCL/P). A total of 130 single-nucleotide polymorphisms (SNPs) in or near SUMO1, MSX1, and TP63 was analyzed among 1,038 Asian NSCL/P trios ascertained through an international consortium. Conditional logistic regression models were used to explore gene-gene (G × G) and gene-environment (G × E) interaction involving maternal environmental tobacco smoke and multivitamin supplementation. Bonferroni correction was used for G × E analysis and permutation tests were used for G × G analysis. While transmission disequilibrium tests and gene-environment interaction analysis showed no significant results, we did find signals of gene-gene interaction between SNPs near MSX1 and TP63. Three pairwise interactions yielded significant p values in permutation tests (rs884690 and rs9290890 with p = 9.34 × 10 -5 and empirical p = 1.00 × 10 -4 , rs1022136 and rs4687098 with p = 2.41 × 10 -4 and empirical p = 2.95 × 10 -4 , rs6819546 and rs9681004 with p = 5.15 × 10 -4 and empirical p = 3.02 × 10 -4 ). Gene-gene interaction between MSX1 and TP63 may influence the risk of NSCL/P in Asian populations. Our study provided additional understanding of the genetic etiology of NSCL/P and underlined the importance of considering gene-gene interaction in the etiology of this common craniofacial malformation. © 2018 Wiley Periodicals, Inc.
Daniel Victor Guebel
Full Text Available Motivation: In the brain of elderly-healthy individuals, the effects of sexual dimorphism and those due to normal ageing appear overlapped. Discrimination of these two dimensions would powerfully contribute to a better understanding of the aetiology of some neurodegenerative diseases, such as sporadic Alzheimer. Methods: Following a system biology approach, top-down and bottom-up strategies were combined. First, public transcriptome data corresponding to the transition from adulthood to the ageing stage in normal, human hippocampus were analysed through an optimized microarray post-processing (Q-GDEMAR method together with a proper experimental design (full factorial analysis. Second, the identified genes were placed in context by building compatible networks. The subsequent ontology analyses carried out on these networks clarify the main functionalities involved. Results: Noticeably we could identify large sets of genes according to three groups: those that exclusively depend on the sex, those that exclusively depend on the age, and those that depend on the particular combinations of sex and age (interaction. The genes identified were validated against three independent sources (a proteomic study of ageing, a senescence database, and a mitochondrial genetic database. We arrived to several new inferences about the biological functions compromised during ageing in two ways: by taking into account the sex-independent effects of ageing, and considering the interaction between age and sex where pertinent. In particular, we discuss the impact of our findings on the functions of mitochondria, autophagy, mitophagia, and microRNAs.Conclusions: The evidence obtained herein supports the occurrence of significant neurobiological differences in the hippocampus, not only between adult and elderly individuals, but between old-healthy women and old-healthy men. Hence, to obtain realistic results in further analysis of the transition from the normal ageing to
Marcelo R. Luizon
Full Text Available Hypertension is a leading cause of cardiovascular mortality, but only about half of patients on antihypertensive therapy achieve blood pressure control. Preeclampsia is defined as pregnancy-induced hypertension and proteinuria, and is associated with increased maternal and perinatal mortality and morbidity. Similarly, a large number of patients with preeclampsia are non-responsive to antihypertensive therapy. Pharmacogenomics may help to guide the personalized treatment for non-responsive hypertensive patients. There is evidence for the association of genetic variants with variable response to the most commonly used antihypertensive drugs. However, further replication is needed to confirm these associations in different populations. The failure to replicate findings from single-locus association studies has prompted the search for novel statistical methods for data analysis, which are required to detect the complex effects from multiple genes to drug response phenotypes. Notably, gene–gene interaction analyses have been applied to pharmacogenetic studies, including antihypertensive drug response. In this perspective article, we present advances of considering the interactions among genetic polymorphisms of different candidate genes within pathways relevant to antihypertensive drug response, and we highlight recent findings related to gene–gene interactions on pharmacogenetics of hypertension and preeclampsia. Finally, we discuss the future directions that are needed to unravel additional genes and variants involved in the responsiveness to antihypertensive drugs.
Full Text Available The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.
Full Text Available Cotton plants engineered for resistance to the herbicides, glyphosate or glufosinate have made a considerable impact on the production of the crop worldwide. In this work, embryogenic cell cultures derived from Gossypium hirsutum L. cv Coker 312 hypocotyl callus were transformed via Agrobacterium tumefaciens with the rice cytochrome P450 gene, CYP81A6 (bel. In rice, bel has been shown to confer resistance to both bentazon and sulfanylurea herbicides. Transformed cells were selected on a liquid medium supplemented alternately or simultaneously with kanamycin (50mg/L and bentazon (4.2 µmol. A total of 17 transgenic cotton lines were recovered, based on the initial resistance to bentazon and on PCR detection of the bel transgene. Bel integration into the cotton genome was confirmed by Southern blot and expression of the transgene was verified by RT-PCR. In greenhouse and experimental plot trials, herbicide (bentazon tolerance of up to 1250 mg/L was demonstrated in the transgenic plants. Transgenic lines with a single copy of the bel gene showed normal Mendelian inheritance of the characteristic. Importantly, resistance to bentazon was shown to be stably incorporated in the T1, T2 and T3 generations of self-fertilised descendents and in plants outcrossed to another upland cotton cultivar. Engineering resistance to bentazon in cotton through the heterologous expression of bel opens the possibility of incorporating this trait into elite cultivars, a strategy that would give growers a more flexible alternative to weed management in cotton crops.
Declerck, Ken; Remy, Sylvie; Wohlfahrt-Veje, Christine
BACKGROUND: Prenatal environmental conditions may influence disease risk in later life. We previously found a gene-environment interaction between the paraoxonase 1 (PON1) Q192R genotype and prenatal pesticide exposure leading to an adverse cardio-metabolic risk profile at school age. However...... was observed in prenatally pesticide exposed children carrying the PON1 192R-allele. Differentially methylated genes were enriched in several neuroendocrine signaling pathways including dopamine-DARPP32 feedback (appetite, reward pathways), corticotrophin releasing hormone signaling, nNOS, neuregulin signaling...
Full Text Available Aging-associated alterations of cellular functions have been implicated in various disorders including cancers. Due to difficulties in identifying aging cells in living tissues, most studies have focused on aging-associated changes in whole tissues or certain cell pools. Thus, it remains unclear what kinds of alterations accumulate in each cell during aging. While analyzing several mouse lines expressing fluorescent proteins (FPs, we found that expression of FPs is gradually silenced in the intestinal epithelium during aging in units of single crypt composed of clonal stem cell progeny. The cells with low FP expression retained the wild-type Apc allele and the tissues composed of them did not exhibit any histological abnormality. Notably, the silencing of FPs was also observed in intestinal adenomas and the surrounding normal mucosae of Apc-mutant mice, and mediated by DNA methylation of the upstream promoter. Our genome-wide analysis then showed that the silencing of FPs reflects specific gene expression alterations during aging, and that these alterations occur in not only mouse adenomas but also human sporadic and hereditary (familial adenomatous polyposis adenomas. Importantly, pharmacological inhibition of DNA methylation, which suppresses adenoma development in Apc-mutant mice, reverted the aging-associated silencing of FPs and gene expression alterations. These results identify aging-associated gene expression signatures that are heterogeneously induced by DNA methylation and precede intestinal tumorigenesis triggered by Apc inactivation, and suggest that pharmacological inhibition of the signature genes could be a novel strategy for the prevention and treatment of intestinal tumors.
Full Text Available Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.
Bisgaard, Hans; Simpson, Angela; Palmer, Colin N A
BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether there is an int......BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether...... there is an interaction between FLG loss-of-function mutations with environmental exposures (pets and dust mites) in relation to the development of eczema. METHODS AND FINDINGS: We used data obtained in early life in a high-risk birth cohort in Denmark and replicated the findings in an unselected birth cohort...... in the United Kingdom. Primary outcome was age of onset of eczema; environmental exposures included pet ownership and mite and pet allergen levels. In Copenhagen (n = 379), FLG mutation increased the risk of eczema during the first year of life (hazard ratio [HR] 2.26, 95% confidence interval [CI] 1.27-4.00, p...
Ko, Lauren N; Rana, Jasmine; Burgin, Susan
In the current digital age, medical education has slowly evolved from the largely lecture-based teaching style of the past to incorporate more interactive pedagogical techniques, including use of social media. Already used readily by millennial trainees and clinicians, social media can also be used in innovative ways to teach trainees and facilitate continuing education among practicing clinicians. In this commentary, we discuss many learning benefits of social media and review potential pitfalls of employing social media in both trainee and physician dermatological education.
Zhaoyang, Ruixue; Sliwinski, Martin J; Martire, Lynn M; Smyth, Joshua M
Prevailing research has suggested that social relationships get better with age, but this evidence has been largely based on studies with lengthy reporting intervals. Using an ecological momentary assessment approach, the present study examined age differences in several characteristics of social interactions as reported in near-real time: the frequency, quality, and partner type. Participants (N = 173) ages 20-79 years reported their social interactions at 5 random times throughout the day for 1 week. Results revealed that age was associated with higher frequency of interacting with family and lower frequency of interacting with peripheral partners. These age effects, however, became nonsignificant after accounting for contextual factors such as race, gender, education, employment status, family structure, and living arrangement. In contrast, a curvilinear relationship best characterized age differences in both positive and negative ratings of daily social interaction quality, with middle-aged adults reporting the lowest positive ratings and older adults reporting the lowest negative ratings among all ages. Contextual factors did not account for these patterns of age differences in interaction quality. Furthermore, the intraindividual variability of interaction frequency with peripheral partners, partner diversity, and interaction quality (positivity and negativity) was lower among older adults than among younger adults. Findings from the present study portray a nuanced picture of social interactions in daily life and advance the understanding of social interactions across the life span. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Struwe, Ellen; Berzl, Gabriele M; Schild, Ralf L; Dötsch, Jörg
Fetal growth restriction is associated with an increased risk for metabolic and cardiovascular disease in later life. To further elucidate mechanisms that might be involved in the process of prenatal programming, we measured the adipokines leptin, resistin, and adiponectin and the GH-releasing hormone ghrelin in the placenta of small for gestational age (SGA) neonates. The control group included 24 placentas of appropriate for gestational age (AGA) newborns, in the study group were 16 placentas of SGA neonates. Gene expression of leptin, resistin, adiponectin, and ghrelin was examined. For hormones showing alterations in gene regulation placental protein expression was measured by Western blot. Placental mRNA expression of leptin was significantly increased in SGA placentas (p=0.0035, related to beta-actin). Protein concentration was increased, as well. There were no differences in placental resistin, adiponectin, or ghrelin gene expressions between SGA neonates and controls. Leptin was the only hormone to demonstrate a significant inverse correlation with birth weight (r=-0.44, p=0.01). Adiponectin correlated significantly with leptin (r=0.53, p=0.0023) and ghrelin (r=0.50, p=0.0045). Placental leptin gene expression and protein concentration showed the expected increase in the SGA group. Leptin was inversely correlated with birth weight. Positive correlation of adiponectin with leptin and ghrelin expression suggests an interaction between these hormones in the placenta. However, the unchanged expression of resistin, adiponectin, and ghrelin in SGA placentas and the absence of correlation with birth weight cast doubt whether these hormones produced in the placenta play a key role in fetal programming.
Willard M. Freeman
Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.
Kim, Sangkyu; Myers, Leann; Ravussin, Eric; Cherry, Katie E; Jazwinski, S Michal
Energy expenditure decreases with age, but in the oldest-old, energy demand for maintenance of body functions increases with declining health. Uncoupling proteins have profound impact on mitochondrial metabolic processes; therefore, we focused attention on mitochondrial uncoupling protein genes. Alongside resting metabolic rate (RMR), two SNPs in the promoter region of UCP2 were associated with healthy aging. These SNPs mark potential binding sites for several transcription factors; thus, they may affect expression of the gene. A third SNP in the 3'-UTR of UCP3 interacted with RMR. This UCP3 SNP is known to impact UCP3 expression in tissue culture cells, and it has been associated with body weight and mitochondrial energy metabolism. The significant main effects of the UCP2 SNPs and the interaction effect of the UCP3 SNP were also observed after controlling for fat-free mass (FFM) and physical-activity related energy consumption. The association of UCP2/3 with healthy aging was not found in males. Thus, our study provides evidence that the genetic risk factors for healthy aging differ in males and females, as expected from the differences in the phenotypes associated with healthy aging between the two sexes. It also has implications for how mitochondrial function changes during aging.
Full Text Available Abstract Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.
Hougaard Christensen, Mette Marie; Pedersen, Rasmus Steen; Stage, Tore Bjerregaard
The aim of this study was to determine the association between the renal clearance (CL(renal)) of metformin in healthy Caucasian volunteers and the single-nucleotide polymorphism (SNP) c.808G>T (rs316019) in OCT2 as well as the relevance of the gene-gene interactions between this SNP and (a) the ...
Håkansson, Anna; Westberg, Lars; Nilsson, Staffan; Buervenich, Silvia; Carmine, Andrea; Holmberg, Björn; Sydow, Olof; Olson, Lars; Johnels, Bo; Eriksson, Elias; Nissbrandt, Hans
The multifunctional cytokine interleukin-6 (IL-6) is involved in inflammatory processes in the central nervous system and increased levels of IL-6 have been found in patients with Parkinson's disease (PD). It is known that estrogen inhibits the production of IL-6, via action on estrogen receptors, thereby pointing to an important influence of estrogen on IL-6. In a previous study, we reported an association between a G/A single nucleotide polymorphism (SNP) at position 1730 in the gene coding for estrogen receptor beta (ERbeta) and age of onset of PD. To investigate the influence of a G/C SNP at position 174 in the promoter of the IL-6 gene, and the possible interaction of this SNP and the ERbeta G-1730A SNP on the risk for PD, the G-174C SNP was genotyped, by pyrosequencing, in 258 patients with PD and 308 controls. A significantly elevated frequency of the GG genotype of the IL-6 SNP was found in the patient group and this was most obvious among patients with an early age of onset (=50 years) of PD. When the GG genotypes of the IL-6 and ERbeta SNPs were combined, the combination was much more robustly associated with PD, and especially with PD with an early age of onset, than respective GG genotype when analyzed separately. Our results indicate that the G-174C SNP in the IL-6 promoter may influence the risk for developing PD, particularly regarding early age of onset PD, and that the effect is modified by interaction of the G-1730A SNP in the ERbeta gene. (c) 2004 Wiley-Liss, Inc.
Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun
Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). firstname.lastname@example.org. Supplementary data are available at Bioinformatics online.
Kim, Theresa H. M.; Connolly, Jennifer A.; Rotondi, Michael; Tamim, Hala
Background Positive-interaction parenting early in childhood is encouraged due to its association with behavioural development later in life. The objective of this study was to examine if the level of positive-interaction parenting style differs among teen, optimal age, and advanced age mothers in Canada, and to identify the characteristics associated with positive-interaction parenting style separately for each age group. Methods This was a cross-sectional secondary analysis of the National ...
Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A
Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same
Kristyn Alissa Bates
Full Text Available Alzheimer's disease (AD, the most common neurodegenerative disease worldwide, ranks as one of the most feared diseases in the world. Similarly, recent studies suggest that AD may be the third leading cause of death in the United States, behind heart disease and cancer. In the absence of a cure or effective treatment, strategies to prevent or delay the onset and progression of the disease are desperately needed. Decades of research have identified key risk and protective factors including genetic polymorphism in the APOE gene, age and lifestyle factors. Physical activity (PA is emerging as an attractive primary prevention strategy. This review will summarise the latest findings supporting the role of physical activity in the prevention of AD, including possible mechanisms and the influence of genetics on disease prevention. Given that AD and other dementias are recognised as a world health priority, public health strategies are needed to incorporate promoting the health benefits of physical activity across the lifespan.
Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan
Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.
Siegal Gene P
Full Text Available Abstract Background Human adenovirus serotype 5 (Ad5 has been widely explored as a gene delivery vector for a variety of diseases. Many target cells, however, express low levels of Ad5 native receptor, the Coxsackie-Adenovirus Receptor (CAR, and thus are resistant to Ad5 infection. The Protein Transduction Domain of the HIV Tat protein, namely PTDtat, has been shown to mediate protein transduction in a wide range of cells. We hypothesize that re-targeting Ad5 vector via the PTDtat motif would improve the efficacy of Ad5-mediated gene delivery. Results In this study, we genetically incorporated the PTDtat motif into the knob domain of Ad5 fiber, and rescued the resultant viral vector, Ad5.PTDtat. Our data showed the modification did not interfere with Ad5 binding to its native receptor CAR, suggesting Ad5 infection via the CAR pathway is retained. In addition, we found that Ad5.PTDtat exhibited enhanced gene transfer efficacy in all of the cell lines that we have tested, which included both low-CAR and high-CAR decorated cells. Competitive inhibition assays suggested the enhanced infectivity of Ad5.PTDtat was mediated by binding of the positively charged PTDtat peptide to the negatively charged epitopes on the cells' surface. Furthermore, we investigated in vivo gene delivery efficacy of Ad5.PTDtat using subcutaneous tumor models established with U118MG glioma cells, and found that Ad5.PTDtat exhibited enhanced gene transfer efficacy compared to unmodified Ad5 vector as analyzed by a non-invasive fluorescence imaging technique. Conclusion Genetic incorporation of the PTDtat motif into Ad5 fiber allowed Ad5 vectors to infect cells via an alternative PTDtat targeting motif while retaining the native CAR-mediated infection pathway. The enhanced infectivity was demonstrated in both cultured cells and in in vivo tumor models. Taken together, our study identifies a novel tropism expanded Ad5 vector that may be useful for clinical gene therapy
Di Ruscio, Annalisa; Ebralidze, Alexander K.; Benoukraf, Touati; Amabile, Giovanni; Goff, Loyal A.; Terragni, Joylon; Figueroa, Maria Eugenia; De Figureido Pontes, Lorena Lobo; Alberich-Jorda, Meritxell; Zhang, Pu; Wu, Mengchu; D’Alò, Francesco; Melnick, Ari; Leone, Giuseppe; Ebralidze, Konstantin K.; Pradhan, Sriharsa; Rinn, John L.; Tenen, Daniel G.
Summary DNA methylation was described almost a century ago. However, the rules governing its establishment and maintenance remain elusive. Here, we present data demonstrating that active transcription regulates levels of genomic methylation. We identified a novel RNA arising from the CEBPA gene locus critical in regulating the local DNA methylation profile. This RNA binds to DNMT1 and prevents CEBPA gene locus methylation. Deep sequencing of transcripts associated with DNMT1 combined with genome-scale methylation and expression profiling extended the generality of this finding to numerous gene loci. Collectively, these results delineate the nature of DNMT1-RNA interactions and suggest strategies for gene selective demethylation of therapeutic targets in disease. PMID:24107992
Cicchetti, Dante; Rogosch, Fred A.
In this investigation, gene-environment interaction effects in predicting resilience in adaptive functioning among maltreated and nonmaltreated low-income children (N = 595) were examined. A multi-component index of resilient functioning was derived and levels of resilient functioning were identified. Variants in four genes, 5-HTTLPR, CRHR1, DRD4 -521C/T, and OXTR, were investigated. In a series of ANCOVAs, child maltreatment demonstrated a strong negative main effect on children’s resilient functioning, whereas no main effects for any of the genotypes of the respective genes were found. However, gene-environment interactions involving genotypes of each of the respective genes and maltreatment status were obtained. For each respective gene, among children with a specific genotype, the relative advantage in resilient functioning of nonmaltreated compared to maltreated children was stronger than was the case for nonmaltreated and maltreated children with other genotypes of the respective gene. Across the four genes, a composite of the genotypes that more strongly differentiated resilient functioning between nonmaltreated and maltreated children provided further evidence of genetic variations influencing resilient functioning in nonmaltreated children, whereas genetic variation had a negligible effect on promoting resilience among maltreated children. Additional effects were observed for children based on the number of subtypes of maltreatment children experienced, as well as for abuse and neglect subgroups. Finally, maltreated and nonmaltreated children with high levels of resilience differed in their average number of differentiating genotypes. These results suggest that differential resilient outcomes are based on the interaction between genes and developmental experiences. PMID:22559122
Uddin, Raihan; Singh, Shiva M
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
Ma, Qiang; Huang, Hui; Sun, Long; Zhou, Tong; Zhu, Jingyuan; Cheng, Xuemin; Duan, Lijv; Li, Zhiyuan; Cui, Liuxin; Ba, Yue
The occurrence of endemic fluorosis is derived from high fluoride levels in drinking water and industrial fumes or dust. Reproductive disruption is also a major harm caused by fluoride exposure besides dental and skeletal lesions. However, few studies focus on the mechanism of fluoride exposure on male reproductive function, especially the possible interaction of fluoride exposure and gene polymorphism on male reproductive hormones. Therefore, we conducted a cross-sectional study in rural areas of Henan province in China to explore the interaction between the estrogen receptor alpha (ERα) gene and fluoride exposure on reproductive hormone levels in male farmers living in the endemic fluorosis villages. The results showed that fluoride exposure significantly increased the serum level of estradiol in the hypothalamic-pituitary-testicular (HPT) axis in male farmers. Moreover, the observations indicated that fluoride exposure and genetic markers had an interaction on serum concentration of follicle-stimulating hormone and estradiol, and the interaction among different loci of the ERα gene could impact the serum testosterone level. Findings in the present work suggest that chronic fluoride exposure in drinking water could modulate the levels of reproductive hormones in males living in endemic fluorosis areas, and the interaction between fluoride exposure and ERα polymorphisms might affect the serum levels of hormones in the HPT axis in male farmers. Copyright © 2017 Elsevier Ltd. All rights reserved.
Full Text Available Abstract Background Codon usage may vary significantly between different organisms and between genes within the same organism. Several evolutionary processes have been postulated to be the predominant determinants of codon usage: selection, mutation, and genetic drift. However, the relative contribution of each of these factors in different species remains debatable. The availability of complete genomes for tens of multicellular organisms provides an opportunity to inspect the relationship between codon usage and the evolutionary age of genes. Results We assign an evolutionary age to a gene based on the relative positions of its identified homologues in a standard phylogenetic tree. This yields a classification of all genes in a genome to several evolutionary age classes. The present study starts from the observation that each age class of genes has a unique codon usage and proceeds to provide a quantitative analysis of the codon usage in these classes. This observation is made for the genomes of Homo sapiens, Mus musculus, and Drosophila melanogaster. It is even more remarkable that the differences between codon usages in different age groups exhibit similar and consistent behavior in various organisms. While we find that GC content and gene length are also associated with the evolutionary age of genes, they can provide only a partial explanation for the observed codon usage. Conclusion While factors such as GC content, mutational bias, and selection shape the codon usage in a genome, the evolutionary history of an organism over hundreds of millions of years is an overlooked property that is strongly linked to GC content, protein length, and, even more significantly, to the codon usage of metazoan genomes.
Gregory, Alice M.; Lau, Jennifer Y. F.; Eley, Thalia C.
Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G × E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G × Es for phobias. In addition to the careful concep...
Andreassi, Maria Grazia, E-mail: email@example.com [CNR Institute of Clinical Physiology, G. Pasquinucci Hospital, Via Aurelia Sud, Massa (Italy)
Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.
Andreassi, Maria Grazia
Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.
Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh
Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.
Tornow, Sabine; Mewes, H W
Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.
Mezlini, Aziz M; Goldenberg, Anna
Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations. We introduce a Bayesian framework, Conflux, to find disease associated genes from exome sequencing data using networks as a prior. There are two main advantages to using networks within a probabilistic graphical model. First, networks are noisy and incomplete, a substantial impediment to gene discovery. Incorporating networks into the structure of a probabilistic models for gene inference has less impact on the solution than relying on the noisy network structure directly. Second, using a Bayesian framework we can keep track of the uncertainty of each gene being associated with the phenotype rather than returning a fixed list of genes. We first show that using networks clearly improves gene detection compared to individual gene testing. We then show consistently improved performance of Conflux compared to the state-of-the-art diffusion network-based method Hotnet2 and a variety of other network and variant aggregation methods, using randomly generated and literature-reported gene sets. We test Hotnet2 and Conflux on several network configurations to reveal biases and patterns of false positives and false negatives in each case. Our experiments show that our novel Bayesian framework Conflux incorporates many of the advantages of the current state-of-the-art methods, while offering more flexibility and improved power in many gene-disease association scenarios.
. Finally, using literature-based interaction discovery methods, we use the set of longevity genes, buffering genes, and their age-related target disease genes to construct the underlying subnetwork of interacting genes that is expected to be responsible for longevity. Genome wide, high-throughput hypothesis-free analyses are currently being utilized to elucidate unknown genetic pathways in many model organisms, linking observed phenotypes to their underlying genetic mechanisms. The longevity phenotype and its genetic mechanisms, such as our buffering hypothesis, are similar; thus, the experimental corroboration of our hypothesis provides a proof of concept for the utility of high-throughput methods for elucidating such mechanisms. It also provides a framework for developing strategies to prevent some age-related diseases by intervention at the appropriate level.
Pei, Lijun; Zhu, Huiping; Ye, Rongwei; Wu, Jilei; Liu, Jianmeng; Ren, Aiguo; Li, Zhiwen; Zheng, Xiaoying
Many studies have indicated that the reduced folate carrier gene (SLC19A1) is associated with an increased risk of neural tube defects (NTDs). However, the interaction between the SLC19A1 gene variant and maternal fever exposure and NTD risk remains unknown. The aim of this study was to investigate whether the risk for NTDs was influenced by the interactions between the SLC19A1 (rs1051266) variant and maternal first trimester fever. We investigated the potential interaction between maternal first trimester fever and maternal or offspring SLC19A1 polymorphism through a population-based case-control study. One hundred and four nuclear families with NTDs and 100 control families with nonmal newborns were included in the study. SLC19A1 polymorphism was determined using polymerase chain reaction-restricted fragment length polymorphism. Mothers who had the GG/GA genotype and first trimester fever had an elevated risk of NTDs (adjusted odds ratio, 11.73; 95% confidence interval, 3.02-45.58) as compared to absence of maternal first trimester fever and AA genotype after adjusting for maternal education, paternal education, and age, and had a significant interactive coefficient (γ = 3.17) between maternal GG/GA genotype and first trimester fever. However, there was no interaction between offspring's GG/GA genotype and maternal first trimester fever (the interactive coefficient γ = 0.97) after adjusting for confounding factors. Our findings suggested that the risk of NTDs was potentially influenced by a gene-environment interaction between maternal SLC19A1 rs1051266 GG/GA genotype and first trimester fever. Maternal GG/GA genotype may strengthen the effect of maternal fever exposure on NTD risk in this Chinese population. © 2014 Wiley Periodicals, Inc.
Braberg, Hannes; Moehle, Erica A.; Shales, Michael; Guthrie, Christine; Krogan, Nevan J.
We have achieved a residue-level resolution of genetic interaction mapping – a technique that measures how the function of one gene is affected by the alteration of a second gene – by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. PMID:24842270
Joanna L Davies
Full Text Available Genome-wide association study (GWAS data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into "ancestry groups" and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions.
Cui, Ying; Cai, Meng; Stanley, H. Eugene
Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.
Pardo, Luba M.
To characterize the promoterome of caudate and putamen regions (striatum), frontal and temporal cortices, and hippocampi from aged human brains, we used high-throughput cap analysis of gene expression to profile the transcription start sites and to quantify the differences in gene expression across the 5 brain regions. We also analyzed the extent to which methylation influenced the observed expression profiles. We sequenced more than 71 million cap analysis of gene expression tags corresponding to 70,202 promoter regions and 16,888 genes. More than 7000 transcripts were differentially expressed, mainly because of differential alternative promoter usage. Unexpectedly, 7% of differentially expressed genes were neurodevelopmental transcription factors. Functional pathway analysis on the differentially expressed genes revealed an overrepresentation of several signaling pathways (e.g., fibroblast growth factor and wnt signaling) in hippocampus and striatum. We also found that although 73% of methylation signals mapped within genes, the influence of methylation on the expression profile was small. Our study underscores alternative promoter usage as an important mechanism for determining the regional differences in gene expression at old age.
Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.
SUMMARY BACKGROUND: Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. AIM: To present the results of recent Dutch studies on the interaction between
Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at
O'Connor, Shannon M; Klump, Kelly L; VanHuysse, Jessica L; McGue, Matt; Iacono, William
Previous research suggests that parental divorce moderates genetic influences on body dissatisfaction. Specifically, the heritability of body dissatisfaction is higher in children of divorced versus intact families, suggesting possible gene-environment interaction effects. However, prior research is limited to a single, self-reported measure of body dissatisfaction. The primary aim of this study was to examine whether these findings extend to a different dimension of body dissatisfaction: body image perceptions. Participants were 1,534 female twins from the Minnesota Twin Family Study, aged 16-20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Although BRS scores were heritable in twins from divorced and intact families, the heritability estimates in the divorced group were not significantly greater than estimates in the intact group. However, there were differences in nonshared environmental effects, where the magnitude of these environmental influences was larger in the divorced as compared with the intact families. Different dimensions of body dissatisfaction (i.e., negative self-evaluation versus body image perceptions) may interact with environmental risk, such as parental divorce, in discrete ways. Future research should examine this possibility and explore differential gene-environment interactions using diverse measures. © 2015 Wiley Periodicals, Inc.
Seaman, Jonathan A; Alout, Haoues; Meyers, Jacob I; Stenglein, Mark D; Dabiré, Roch K; Lozano-Fuentes, Saul; Burton, Timothy A; Kuklinski, Wojtek S; Black, William C; Foy, Brian D
Ivermectin has been proposed as a novel malaria transmission control tool based on its insecticidal properties and unique route of acquisition through human blood. To maximize ivermectin's effect and identify potential resistance/tolerance mechanisms, it is important to understand its effect on mosquito physiology and potential to shift mosquito population age-structure. We therefore investigated ivermectin susceptibility and gene expression changes in several age groups of female Anopheles gambiae mosquitoes. The effect of aging on ivermectin susceptibility was analyzed in three age groups (2, 6, and 14-days) of colonized female Anopheles gambiaemosquitoes using standard survivorship assays. Gene expression patterns were then analyzed by transcriptome sequencing on an Illumina HiSeq 2500 platform. RT-qPCR was used to validate transcriptional changes and also to examine expression in a different, colonized strain and in wild mosquitoes, both of which blood fed naturally on an ivermectin-treated person. Mosquitoes of different ages and blood meal history died at different frequencies after ingesting ivermectin. Mortality was lowest in 2-day old mosquitoes exposed on their first blood meal and highest in 6-day old mosquitoes exposed on their second blood meal. Twenty-four hours following ivermectin ingestion, 101 and 187 genes were differentially-expressed relative to control blood-fed, in 2 and 6-day groups, respectively. Transcription patterns of select genes were similar in membrane-fed, colonized, and naturally-fed wild vectors. Transcripts from several unexpected functional classes were highly up-regulated, including Niemann-Pick Type C (NPC) genes, peritrophic matrix-associated genes, and immune-response genes, and these exhibited different transcription patterns between age groups, which may explain the observed susceptibility differences. Niemann-Pick Type 2 genes were the most highly up-regulated transcripts after ivermectin ingestion (up to 160 fold) and
Sigurdson, Alice J.; Land, Charles E.; Bhatti, Parveen; Pineda, Marbin; Brenner, Alina; Carr, Zhanat; Gusev, Boris I.; Zhumadilov, Zhaxibay; Simon, Steven L.; Bouville, Andre; Rutter, Joni L.; Ron, Elaine; Struewing, Jeffery P.
Risk factors for thyroid cancer remain largely unknown except for ionizing radiation exposure during childhood and a history of benign thyroid nodules. Because thyroid nodules are more common than thyroid cancers and are associated with thyroid cancer risk, we evaluated several polymorphisms potentially relevant to thyroid tumors and assessed interaction with ionizing radiation exposure to the thyroid gland. Thyroid nodules were detected in 1998 by ultrasound screening of 2997 persons who lived near the Semipalatinsk nuclear test site in Kazakhstan when they were children (1949-62). Cases with thyroid nodules (n=907) were frequency matched (1:1) to those without nodules by ethnicity (Kazakh or Russian), gender, and age at screening. Thyroid gland radiation doses were estimated from fallout deposition patterns, residence history, and diet. We analyzed 23 polymorphisms in 13 genes and assessed interaction with ionizing radiation exposure using likelihood ratio tests (LRT). Elevated thyroid nodule risks were associated with the minor alleles of RET S836S (rs1800862, p = 0.03) and GFRA1 -193C>G (rs not assigned, p = 0.05) and decreased risk with XRCC1 R194W (rs1799782, p-trend = 0.03) and TGFB1 T263I (rs1800472, p = 0.009). Similar patterns of association were observed for a small number of papillary thyroid cancers (n=25). Ionizing radiation exposure to the thyroid gland was associated with significantly increased risk of thyroid nodules (age and gender adjusted excess odds ratio/Gy = 0.30, 95% confidence interval 0.05-0.56), with evidence for interaction by genotype found for XRCC1 R194W (LRT p value = 0.02). Polymorphisms in RET signaling, DNA repair, and proliferation genes may be related to risk of thyroid nodules, consistent with some previous reports on thyroid cancer. Borderline support for gene-radiation interaction was found for a variant in XRCC1, a key base excision repair protein. Other pathways, such as genes in double strand break repair, apoptosis, and
Vetter, U.; Pirsig, W.; Heinze, E.
Growth activity in different areas of human septal cartilage was measured by the in vitro incorporation of 35 S-labeled NaSO 4 into chondroitin sulfate. Septal cartilage without perichondrium was obtained during rhinoplasty from 36 patients aged 6 to 35 years. It could be shown that the anterior free end of the septum displays high growth activity in all age groups. The supra-premaxillary area displayed its highest growth activity during prepuberty, showing thereafter a continuous decline during puberty and adulthood. A similar age-dependent pattern in growth activity was found in the caudal prolongation of the septal cartilage. No age-dependent variations could be detected in the posterior area of the septal cartilage
Full Text Available Genome-wide expression profiling of the human brain has revealed genes that are differentially expressed across the lifespan. Characterizing these genes adds to our understanding of both normal functions and pathological conditions. Additionally, the specific cell-types that contribute to the motor, sensory and cognitive declines during aging are unclear. Here we test if age-related genes show higher expression in specific neural cell types. Our study leverages data from two sources of murine single-cell expression data and two sources of age-associations from large gene expression studies of postmortem human brain. We used nonparametric gene set analysis to test for age-related enrichment of genes associated with specific cell-types; we also restricted our analyses to specific gene ontology groups. Our analyses focused on a primary pair of single-cell expression data from the mouse visual cortex and age-related human post-mortem gene expression information from the orbitofrontal cortex. Additional pairings that used data from the hippocampus, prefrontal cortex, somatosensory cortex and blood were used to validate and test specificity of our findings. We found robust age-related up-regulation of genes that are highly expressed in oligodendrocytes and astrocytes, while genes highly expressed in layer 2/3 glutamatergic neurons were down-regulated across age. Genes not specific to any neural cell type were also down-regulated, possibly due to the bulk tissue source of the age-related genes. A gene ontology-driven dissection of the cell-type enriched genes highlighted the strong down-regulation of genes involved in synaptic transmission and cell-cell signaling in the Somatostatin (Sst neuron subtype that expresses the cyclin dependent kinase 6 (Cdk6 and in the vasoactive intestinal peptide (Vip neuron subtype expressing myosin binding protein C, slow type (Mybpc1. These findings provide new insights into cell specific susceptibility to normal aging
We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)
Li, Wentian; Freudenberg, Jan; Oswald, Michaela
A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.
Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa
the same time reversibility and diversity in their interactions. Interestingly, as is shown in the paper by Mészáros et al, even though some disordered regions and proteins have a tendency to fold upon binding, the structures of their complexes still reveal their inherent flexibility. Indeed, disordered proteins and their complexes have certain properties which distinguish them from proteins with well-defined structures. This is evident from the papers by Lobanov and Galzitskaya, and Mészáros et al, which show that such characteristic features of disordered proteins allow their successful computational prediction from the sequence alone. Computational prediction of protein disorder has been used in another study by Takeda et al where the authors investigate the role of disorder in the function of a specific actin capping protein. The paper presents normal mode analysis with the elastic network model to examine the mechanisms of intrinsic flexibility and its biological role in actin function. Analysis of the underlying mechanisms and key factors in protein recognition might be essential for the prediction of protein-protein interactions. The papers by Tuncbag et al and Hashimoto et al demonstrate how incorporating the physico-chemical properties of binding interfaces and their atomic details obtained from protein crystal structures might be used to increase the accuracy of predicted protein-protein interactions and provide data on relative orientations of interacting proteins and on the locations of binding sites. Moreover, analysis of protein-protein interactions might require further fine-tuning for different types of assemblies, like that shown in the example of homooligomers by Hashimoto et al. Studies of protein-protein interactions at the molecular level have contributed considerably to understanding the principles of large-scale organization of the cellular interactome. Using graph theory as a unifying language, many characteristic properties of bimolecular
Schwarz, L.K.; Runge, M.C.
Age estimation of individuals is often an integral part of species management research, and a number of ageestimation techniques are commonly employed. Often, the error in these techniques is not quantified or accounted for in other analyses, particularly in growth curve models used to describe physiological responses to environment and human impacts. Also, noninvasive, quick, and inexpensive methods to estimate age are needed. This research aims to provide two Bayesian methods to (i) incorporate age uncertainty into an age-length Schnute growth model and (ii) produce a method from the growth model to estimate age from length. The methods are then employed for Florida manatee (Trichechus manatus) carcasses. After quantifying the uncertainty in the aging technique (counts of ear bone growth layers), we fit age-length data to the Schnute growth model separately by sex and season. Independent prior information about population age structure and the results of the Schnute model are then combined to estimate age from length. Results describing the age-length relationship agree with our understanding of manatee biology. The new methods allow us to estimate age, with quantified uncertainty, for 98% of collected carcasses: 36% from ear bones, 62% from length.
He, Lizhi; Marioutina, Mariya; Dunaief, Joshua L.; Marneros, Alexander G.
To conditionally inactivate genes in the retinal pigment epithelium (RPE) transgenic mouse strains have been developed, in which Cre recombinase (Cre) expression is driven by an RPE-specific gene promoter. The RPE is a quiescent epithelium, and continuous expression of Cre could affect its function. Here, we tested the hypothesis that continuous postnatal Cre expression in the RPE may lead to cellular abnormalities, which may depend on both age and Cre gene dosage. We therefore examined the eyes of homozygous and heterozygous VMD2-Cre mice at various ages. In VMD2-Cre heterozygous mice variable progressive age-dependent RPE abnormalities were noticed, including attenuation of phalloidin and cytoplasmic active β-catenin staining, reduced cell size, and loss of the typical honeycomb pattern of RPE morphology in those RPE cells that stained for Cre. These morphological RPE abnormalities were not noticed in Cre-negative RPE cells in VMD2-Cre or age-matched control mice. In addition, an abnormal number and morphology of cell nuclei were noticed in a subset of Cre-expressing RPE cells in aged heterozygous VMD2-Cre mice, whereas more severe nuclear abnormalities were observed already in young homozygous VMD2-Cre mice. Thus, continuous postnatal expression of Cre causes abnormalities in the RPE in an age- and Cre gene dosage-dependent manner, which needs to be considered in the interpretation of gene targeting studies in the RPE. PMID:24854863
Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun
The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.
Full Text Available Mammalian genomes contain several dozens of large (>0.5 Mbp lineage-specific gene loci harbouring functionally related genes. However, spatial chromatin folding, organization of the enhancer-promoter networks and their relevance to Topologically Associating Domains (TADs in these loci remain poorly understood. TADs are principle units of the genome folding and represents the DNA regions within which DNA interacts more frequently and less frequently across the TAD boundary. Here, we used Chromatin Conformation Capture Carbon Copy (5C technology to characterize spatial chromatin interaction network in the 3.1 Mb Epidermal Differentiation Complex (EDC locus harbouring 61 functionally related genes that show lineage-specific activation during terminal keratinocyte differentiation in the epidermis. 5C data validated by 3D-FISH demonstrate that the EDC locus is organized into several TADs showing distinct lineage-specific chromatin interaction networks based on their transcription activity and the gene-rich or gene-poor status. Correlation of the 5C results with genome-wide studies for enhancer-specific histone modifications (H3K4me1 and H3K27ac revealed that the majority of spatial chromatin interactions that involves the gene-rich TADs at the EDC locus in keratinocytes include both intra- and inter-TAD interaction networks, connecting gene promoters and enhancers. Compared to thymocytes in which the EDC locus is mostly transcriptionally inactive, these interactions were found to be keratinocyte-specific. In keratinocytes, the promoter-enhancer anchoring regions in the gene-rich transcriptionally active TADs are enriched for the binding of chromatin architectural proteins CTCF, Rad21 and chromatin remodeler Brg1. In contrast to gene-rich TADs, gene-poor TADs show preferential spatial contacts with each other, do not contain active enhancers and show decreased binding of CTCF, Rad21 and Brg1 in keratinocytes. Thus, spatial interactions between gene
Full Text Available Duchenne Muscular Dystrophy (DMD is an important pathology associated with the human skeletal muscle and has been studied extensively. Gene expression measurements on skeletal muscle of patients afflicted with DMD provides the opportunity to understand the underlying mechanisms that lead to the pathology. Community structure analysis is a useful computational technique for understanding and modeling genetic interaction networks. In this paper, we leverage this technique in combination with gene expression measurements from normal and DMD patient skeletal muscle tissue to study the structure of genetic interactions in the context of DMD. We define a novel framework for transforming a raw dataset of gene expression measurements into an interaction network, and subsequently apply algorithms for community structure analysis for the extraction of topological communities. The emergent communities are analyzed from a biological standpoint in terms of their constituent biological pathways, and an interpretation that draws correlations between functional and structural organization of the genetic interactions is presented. We also compare these communities and associated functions in pathology against those in normal human skeletal muscle. In particular, differential enhancements are observed in the following pathways between pathological and normal cases: Metabolic, Focal adhesion, Regulation of actin cytoskeleton and Cell adhesion, and implication of these mechanisms are supported by prior work. Furthermore, our study also includes a gene-level analysis to identify genes that are involved in the coupling between the pathways of interest. We believe that our results serve to highlight important distinguishing features in the structural/functional organization of constituent biological pathways, as it relates to normal and DMD cases, and provide the mechanistic basis for further biological investigations into specific pathways differently regulated
Berber, Slavica; Wood, Mallory; Llamosas, Estelle; Thaivalappil, Priya; Lee, Karen; Liao, Bing Mana; Chew, Yee Lian; Rhodes, Aaron; Yucel, Duygu; Crossley, Merlin; Nicholas, Hannah R
Proteins of the Homeodomain-Interacting Protein Kinase (HIPK) family regulate an array of processes in mammalian systems, such as the DNA damage response, cellular proliferation and apoptosis. The nematode Caenorhabditis elegans has a single HIPK homologue called HPK-1. Previous studies have implicated HPK-1 in longevity control and suggested that this protein may be regulated in a stress-dependent manner. Here we set out to expand these observations by investigating the role of HPK-1 in longevity and in the response to heat and oxidative stress. We find that levels of HPK-1 are regulated by heat stress, and that HPK-1 contributes to survival following heat or oxidative stress. Additionally, we show that HPK-1 is required for normal longevity, with loss of HPK-1 function leading to a faster decline of physiological processes that reflect premature ageing. Through microarray analysis, we have found that HPK-1-regulated genes include those encoding proteins that serve important functions in stress responses such as Phase I and Phase II detoxification enzymes. Consistent with a role in longevity assurance, HPK-1 also regulates the expression of age-regulated genes. Lastly, we show that HPK-1 functions in the same pathway as DAF-16 to regulate longevity and reveal a new role for HPK-1 in development.
Oskari Kilpeläinen, Tuomas
The role of gene x lifestyle interactions in the development of cardiometabolic diseases is often highlighted, but very few robustly replicated examples of interactions exist in the literature. The slow pace of discoveries may largely be due to interaction effects being generally small in magnitude...
Mandelli, Laura; Serretti, Alessandro
Increasing evidence supports the involvement of both heritable and environmental risk factors in major depression (MD) and suicidal behavior (SB). Studies investigating gene-environment interaction (G × E) may be useful for elucidating the role of biological mechanisms in the risk for mental disorders. In the present paper, we review the literature regarding the interaction between genes modulating brain functions and stressful life events in the etiology of MD and SB and discuss their potential added benefit compared to genetic studies only. Within the context of G × E investigation, thus far, only a few reliable results have been obtained, although some genes have consistently shown interactive effects with environmental risk in MD and, to a lesser extent, in SB. Further investigation is required to disentangle the direct and mediated effects that are common or specific to MD and SB. Since traditional G × E studies overall suffer from important methodological limitations, further effort is required to develop novel methodological strategies with an interdisciplinary approach. Copyright © 2013 Elsevier Ltd. All rights reserved.
Mandelli, Laura; Toscano, Elena; Porcelli, Stefano; Fabbri, Chiara; Serretti, Alessandro
In this study we evaluated the role of a candidate gene for major psychosis, Sialyltransferase (ST8SIA2), in the risk to develop a schizophrenia spectrum disorders, taking into account exposure to stressful life events (SLEs). Eight polymorphisms (SNPs) were tested in 94 Schizophreniainpatients and 176 healthy controls. Schizophrenia patients were also evaluated for SLEs in different life periods. None of the SNPs showed association with schizophrenia. Nevertheless, when crossing genetic variants with childhood SLEs, we could observe trends of interaction with age of onset. Though several limitations, our results support a protective role of ST8SIA2 in individuals exposed to moderate childhood stress.
Mohammad H Dezfulian
Full Text Available The Arabidopsis thaliana genome encodes several families of polypeptides that are known or predicted to participate in the formation of the SCF-class of E3-ubiquitin ligase complexes. One such gene family encodes the Skp1-like class of polypeptide subunits, where 21 genes have been identified and are known to be expressed in Arabidopsis. Phylogenetic analysis based on deduced polypeptide sequence organizes the family of ASK proteins into 7 clades. The complexity of the ASK gene family, together with the close structural similarity among its members raises the prospect of significant functional redundancy among select paralogs. We have assessed the potential for functional redundancy within the ASK gene family by analyzing an expanded set of criteria that define redundancy with higher resolution. The criteria used include quantitative expression of locus-specific transcripts using qRT-PCR, assessment of the sub-cellular localization of individual ASK:YFP auto-fluorescent fusion proteins expressed in vivo as well as the in planta assessment of individual ASK-F-Box protein interactions using bimolecular fluorescent complementation techniques in combination with confocal imagery in live cells. The results indicate significant functional divergence of steady state transcript abundance and protein-protein interaction specificity involving ASK proteins in a pattern that is poorly predicted by sequence-based phylogeny. The information emerging from this and related studies will prove important for defining the functional intersection of expression, localization and gene product interaction that better predicts the formation of discrete SCF complexes, as a prelude to investigating their molecular mode of action.
Pereira, Inês Tomás; Gallagher, Michela; Rapp, Peter R.
Cognitive aging is accompanied by decline in multiple domains of memory. Here, we developed a T-maze task that required rats to learn competing hippocampal, and striatal navigation strategies in succession, across days. A final session increased demands on cognitive flexibility and required within-day switching between strategies, emphasizing capacities that engage the prefrontal cortex. Background characterization in young and aged rats used a water maze protocol optimized for individual differences in hippocampal integrity. Consistent with earlier work, young adults acquired place strategies in the T-maze faster than response, whereas the opposite was observed in aged rats with impaired spatial memory. The novel result was that aged animals with preserved spatial memory displayed a qualitatively distinct pattern, acquiring place and response strategies equally rapidly, without disruption when switching between them. Subsequent in situ hybridization for the plasticity-related immediate-early gene Arc revealed that while increasing demands on cognitive flexibility and within-day strategy switching potently engaged the prefrontal cortex in young adult and aged-impaired rats, Arc expression was insensitive in aged rats with normal spatial memory and superior switching abilities. Together, the results indicate that cognitive aging is an emergent property of the interactions between memory systems, and that successful cognitive outcomes reflect a distinct neuroadaptive process rather than a slower rate of aging. PMID:26281759
Viñuela, Ana; Brown, Andrew A; Buil, Alfonso; Tsai, Pei-Chien; Davies, Matthew N; Bell, Jordana T; Dermitzakis, Emmanouil T; Spector, Timothy D; Small, Kerrin S
Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation. © The Author(s) 2017. Published by Oxford University Press.
Objective To examine the associations of 10 singlenucleotide polymorphisms(SNPs)in peroxisome proliferator-activated receptor(PPARs)gene with lipoprotein(a)level,and to investigate if there is gene-gene interaction among the SNPs on lipoprotein(a)level.Methods Totally 644 subjects(234 men and 410 women)were enrolled from Prevention of Multiple Metabolic Disorders and Metabolic Syndrome Study Cohort,which was an urban community survey study conducted in Jiangsu province.Ten SNPs in PPARα(rs135539,rs4253778,
Jane C Figueiredo
Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.
Yang, Yi; Maxwell, Andrew; Zhang, Xiaowei; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping
Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting. Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential edge inference, mapping of genes with differential edges to pathways, and establishment of causal relationships between chemical concentration and perturbed pathways. A one-sample Gaussian process model and a linear regression model were used to identify genes that exhibited significant profile changes across an entire time course and between treatments, respectively. Interaction networks of differentially expressed (DE) genes were reconstructed for different treatments using a state space model and then compared to infer differential edges/interactions. DE genes possessing differential edges were mapped to biological pathways in databases such as KEGG pathways. Using the DNs approach, we analyzed a time-series Escherichia coli live cell gene expression dataset consisting of 4 treatments (control, 10, 100, 1000 mg/L naphthenic acids, NAs) and 18 time points. Through comparison of reconstructed networks and construction of differential networks, 80 genes were identified as DE genes with a significant number of differential edges, and 22 KEGG pathways were altered in a concentration-dependent manner. Some of these pathways were perturbed to a degree as high as 70% even at the lowest exposure concentration, implying a high sensitivity of our DNs approach
Full Text Available BACKGROUND: Curcumin has been demonstrated to have many neuroprotective properties, including improvement of cognition in humans and neurogenesis in animals, yet the mechanism of such effects remains unclear. METHODOLOGY: We assessed behavioural performance and hippocampal cell proliferation in aged rats after 6- and 12-week curcumin-fortified diets. Curcumin enhanced non-spatial and spatial memory, as well as dentate gyrate cell proliferation as compared to control diet rats. We also investigated underlying mechanistic pathways that might link curcumin treatment to increased cognition and neurogenesis via exon array analysis of cortical and hippocampal mRNA transcription. The results revealed a transcriptional network interaction of genes involved in neurotransmission, neuronal development, signal transduction, and metabolism in response to the curcumin treatment. CONCLUSIONS: The results suggest a neurogenesis- and cognition-enhancing potential of prolonged curcumin treatment in aged rats, which may be due to its diverse effects on genes related to growth and plasticity.
Mitchell, E. Siobhan; Xiu, Jin; Tiwari, Jyoti K.; Hu, Yinghe; Cao, Xiaohua; Zhao, Zheng
Background Curcumin has been demonstrated to have many neuroprotective properties, including improvement of cognition in humans and neurogenesis in animals, yet the mechanism of such effects remains unclear. Methodology We assessed behavioural performance and hippocampal cell proliferation in aged rats after 6- and 12-week curcumin-fortified diets. Curcumin enhanced non-spatial and spatial memory, as well as dentate gyrate cell proliferation as compared to control diet rats. We also investigated underlying mechanistic pathways that might link curcumin treatment to increased cognition and neurogenesis via exon array analysis of cortical and hippocampal mRNA transcription. The results revealed a transcriptional network interaction of genes involved in neurotransmission, neuronal development, signal transduction, and metabolism in response to the curcumin treatment. Conclusions The results suggest a neurogenesis- and cognition-enhancing potential of prolonged curcumin treatment in aged rats, which may be due to its diverse effects on genes related to growth and plasticity. PMID:22359574
Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.
Viñuela Rodriguez, A.; Snoek, L.B.; Riksen, J.A.G.; Kammenga, J.E.
Gene expression becomes more variable with age, and it is widely assumed that this is due to a decrease in expression regulation. But currently there is no understanding how gene expression regulatory patterns progress with age. Here we explored genome-wide gene expression variation and regulatory
Annette W M Spithoven
Full Text Available Gene-by-environment interaction (GxEs studies have gained popularity over the last decade, but the robustness of such observed interactions has been questioned. The current study contributes to this debate by replicating the only study on the interaction between the serotonin transporter gene (5-HTTLPR and perceived parental support on adolescents' peer-related loneliness. A total of 1,111 adolescents (51% boys with an average age of 13.70 years (SD = 0.93 participated and three annual waves of data were collected. At baseline, adolescent-reported parental support and peer-related loneliness were assessed and genetic information was collected. Assessment of peer-related loneliness was repeated at Waves 2 and 3. Using a cohort-sequential design, a Latent Growth Curve Model was estimated. Overall, a slight increase of loneliness over time was found. However, the development of loneliness over time was found to be different for boys and girls: girls' levels of loneliness increased over time, whereas boys' levels of loneliness decreased. Parental support was inversely related to baseline levels of loneliness, but unrelated to change of loneliness over time. We were unable to replicate the main effect of 5-HTTLPR or the 5-HTTLPR x Support interaction effect. In the Discussion, we examine the implications of our non-replication.
Metz, Sebastian; Haberzettl, Kerstin; Frühwirth, Sebastian; Teich, Kristin; Hasewinkel, Christian; Klug, Gabriele
The expression of photosynthesis genes in the facultatively photosynthetic bacterium Rhodobacter sphaeroides is controlled by the oxygen tension and by light quantity. Two photoreceptor proteins, AppA and CryB, have been identified in the past, which are involved in this regulation. AppA senses light by its N-terminal BLUF domain, its C-terminal part binds heme and is redox-responsive. Through its interaction to the transcriptional repressor PpsR the AppA photoreceptor controls expression of photosynthesis genes. The cryptochrome-like protein CryB was shown to affect regulation of photosynthesis genes, but the underlying signal chain remained unknown. Here we show that CryB interacts with the C-terminal domain of AppA and modulates the binding of AppA to the transcriptional repressor PpsR in a light-dependent manner. Consequently, binding of the transcription factor PpsR to its DNA target is affected by CryB. In agreement with this, all genes of the PpsR regulon showed altered expression levels in a CryB deletion strain after blue-light illumination. These results elucidate for the first time how a bacterial cryptochrome affects gene expression.
Huang, Yuan; Caputo, Christina R.; Noordmans, Gerda A.; Yazdani, Saleh; Monteiro, Luiz Henrique; van den Born, Jaap; van Goor, Harry; Heeringa, Peter; Korstanje, Ron; Hillebrands, Jan-Luuk
A hallmark of aging-related organ deterioration is a dysregulated immune response characterized by pathologic leukocyte infiltration of affected tissues. Mechanisms and genes involved are as yet unknown. To identify genes associated with aging-related renal infiltration, we analyzed kidneys from
Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.
Jeffrey, W.H.; Paul, J.H.
One assumption made in bacterial production estimates from [ 3 H]thymidine incorporation is that all heterotrophic bacteria can incorporate exogenous thymidine into DNA. Heterotrophic marine bacterium isolates from Tampa Bay, Fla., Chesapeake Bay, Md., and a coral surface microlayer were examined for thymidine uptake (transport), thymidine incorporation, the presence of thymidine kinase genes, and thymidine kinase enzyme activity. Of the 41 isolates tested, 37 were capable of thymidine incorporation into DNA. The four organisms that could not incorporate thymidine also transported the thymidine poorly and lacked thymidine kinase activity. Attempts to detect thymidine kinase genes in the marine isolates by molecular probing with gene probes made from Escherichia coli and herpes simplex virus thymidine kinase genes proved unsuccessful. To determine if the inability to incorporate thymidine was due to the lack of thymidine kinase, one organism, Vibro sp. strain DI9, was transformed with a plasmid (pGQ3) that contained an E. coli thymidine kinase gene. Although enzyme assays indicated high levels of thymidine kinase activity in transformants, these cells still failed to incorporate exogenous thymidine into DNA or to transport thymidine into cells. These results indicate that the inability of certain marine bacteria to incorporate thymidine may not be solely due to the lack of thymidine kinase activity but may also be due to the absence of thymidine transport systems
Wang, Tzu-Yun; Lee, Sheng-Yu; Chen, Shiou-Lan; Chang, Yun-Hsuan; Chen, Shih-Heng; Chu, Chun-Hsien; Huang, San-Yuan; Tzeng, Nian-Sheng; Wang, Chen-Lin; Lee, I Hui; Yeh, Tzung Lieh; Yang, Yen Kuang; Lu, Ru-Band
Several studies have hypothesized that genes regulating the components of the serotonin system, including serotonin transporter (5-HTTLPR) and serotonin 1 B receptor (5-HT1B), may be associated with alcoholism, but their results are contradictory because of alcoholism's heterogeneity. Therefore, we examined whether the 5-HTTLPR gene and 5-HT1B gene G861C polymorphism are susceptibility factors for a specific subtype of alcoholism, antisocial alcoholism in Han Chinese in Taiwan. We recruited 273 Han Chinese male inmates with antisocial personality disorder (ASPD) [antisocial alcoholism (AS-ALC) group (n=120) and antisocial non-alcoholism (AS-N-ALC) group (n=153)] and 191 healthy male controls from the community. Genotyping was done using PCR-RFLP. There were no significant differences in the genotypic frequency of the 5-HT1B G861C polymorphism between the 3 groups. Although AS-ALC group members more frequently carried the 5-HTTLPR S/S, S/LG, and LG/LG genotypes than controls, the difference became non-significant after controlling for the covarying effects of age. However, the 5-HTTLPR S/S, S/LG, and LG/LG genotypes may have interacted with the 5-HT1B G861C C/C polymorphism and increased the risk of becoming antisocial alcoholism. Our study suggests that neither the 5-HTTLPR gene nor the 5-HT1B G861C polymorphism alone is a risk factor for antisocial alcoholism in Taiwan's Han Chinese population, but that the interaction between both genes may increase susceptibility to antisocial alcoholism.
Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J
We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.
Stanley I Rapoport
Full Text Available Phosphoinositides, lipid-signaling molecules, participate in diverse brain processes within a wide metabolic cascade.Gene transcriptional networks coordinately regulate the phosphoinositide cascade during human brain Development and Aging.We used the public BrainCloud database for human dorsolateral prefrontal cortex to examine age-related expression levels of 49 phosphoinositide metabolic genes during Development (0 to 20+ years and Aging (21+ years.We identified three groups of partially overlapping genes in each of the two intervals, with similar intergroup correlations despite marked phenotypic differences between Aging and Development. In each interval, ITPKB, PLCD1, PIK3R3, ISYNA1, IMPA2, INPPL1, PI4KB, and AKT1 are in Group 1, PIK3CB, PTEN, PIK3CA, and IMPA1 in Group 2, and SACM1L, PI3KR4, INPP5A, SYNJ1, and PLCB1 in Group 3. Ten of the genes change expression nonlinearly during Development, suggesting involvement in rapidly changing neuronal, glial and myelination events. Correlated transcription for some gene pairs likely is facilitated by colocalization on the same chromosome band.Stable coordinated gene transcriptional networks regulate brain phosphoinositide metabolic pathways during human Development and Aging.
Calabria, Elisa; Mazza, Emilia Maria Cristina; Dyar, Kenneth Allen; Pogliaghi, Silvia; Bruseghini, Paolo; Morandi, Carlo; Salvagno, Gian Luca; Gelati, Matteo; Guidi, Gian Cesare; Bicciato, Silvio; Schiaffino, Stefano; Schena, Federico; Capelli, Carlo
The availability of reliable biomarkers of aging is important not only to monitor the effect of interventions and predict the timing of pathologies associated with aging but also to understand the mechanisms and devise appropriate countermeasures. Blood cells provide an easily available tissue and gene expression profiles from whole blood samples appear to mirror disease states and some aspects of the aging process itself. We report here a microarray analysis of whole blood samples from two cohorts of healthy adult and elderly subjects, aged 43±3 and 68±4 years, respectively, to monitor gene expression changes in the initial phase of the senescence process. A number of significant changes were found in the elderly compared to the adult group, including decreased levels of transcripts coding for components of the mitochondrial respiratory chain, which correlate with a parallel decline in the maximum rate of oxygen consumption (VO2max), as monitored in the same subjects. In addition, blood cells show age-related changes in the expression of several markers of immunosenescence, inflammation and oxidative stress. These findings support the notion that the immune system has a major role in tissue homeostasis and repair, which appears to be impaired since early stages of the aging process.
Yper, L.N. Van; Vermeire, K.; Vel, E.F. De; Beynon, A.J.; Dhooge, I.J.
OBJECTIVES: Age-related hearing loss hampers the ability to understand speech in adverse listening conditions. This is attributed to a complex interaction of changes in the peripheral and central auditory system. One aspect that may deteriorate across the lifespan is binaural interaction. The
Laansma, Frederike; Smidt, Eva; Crajé, Céline; Luinge, Margreet
A key element in social development is interaction with others. Preterm infants have an increased risk for problems in this aspect. We aimed to gain insight into parents’ perception about their preterm child’s social interaction upon reaching school age. Twelve caregivers of preterm infants aged
Hannaman, G.W.; Joksimovich, V.; Spurgin, A.J.; Worledge, D.H.
Recently, increased attention has been given to understanding the role of humans in the safe operation of nuclear power plants. By virtue of the ability to combine equipment reliability with human reliability probabilistic risk assessment (PRA) technology was deemed capable of providing significant insights about the contributions of human interations in accident scenarios. EPRI recognized the need to strengthen the methodology for incorporating human interactions into PRAs as one element of their broad research program to improve the credibility of PRAs. This research project lead to the development and detailed description of SHARP (Systematic Human Application Reliability Procedure) in EPRI NP-3583. The objective of this paper is to illustrate the SHARP framework. This should help PRA analysts state more clearly their assumptions and approach no matter which human reliability assessment technique is used. SHARP includes a structure of seven analysis steps which can be formally or informally performed during PRAs. The seven steps are termed definition, screening, breakdown, representation, impact assessment, quantification, and documentation
Longo Dan L
Full Text Available Abstract Background The aging of reproductive organs is not only a major social issue, but of special interest in aging research. A long-standing view of 'immortal germ line versus mortal soma' poses an important question of whether the reproductive tissues age in similar ways to the somatic tissues. As a first step to understand this phenomenon, we examine global changes in gene expression patterns by DNA microarrays in ovaries and testes of C57BL/6 mice at 1, 6, 16, and 24 months of age. In addition, we compared a group of mice on ad libitum (AL feeding with a group on lifespan-extending 40% calorie restriction (CR. Results We found that gene expression changes occurred in aging gonads, but were generally different from those in somatic organs during aging. For example, only two functional categories of genes previously associated with aging in muscle, kidney, and brain were confirmed in ovary: genes associated with complement activation were upregulated, and genes associated with mitochondrial electron transport were downregulated. The bulk of the changes in gonads were mostly related to gonad-specific functions. Ovaries showed extensive gene expression changes with age, especially in the period when ovulation ceases (from 6 to 16 months, whereas testes showed only limited age-related changes. The same trend was seen for the effects of CR: CR-mediated reversal of age-associated gene expression changes, reported in somatic organs previously, was limited to a small number of genes in gonads. Instead, in both ovary and testis, CR caused small and mostly gonad-specific effects: suppression of ovulation in ovary and activation of testis-specific genes in testis. Conclusion Overall, the results are consistent with unique modes of aging and its modification by CR in testis and ovary.
Full Text Available A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype than in PC3 (a drought sensitive genotype, indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.
Mizielińska, Małgorzata; Kowalska, Urszula; Jarosz, Michał; Sumińska, Patrycja; Landercy, Nicolas; Duquesne, Emmanuel
The aim of this study was to examine the influence of accelerated UV-aging on the activity against chosen microorganisms and the mechanical properties of poly-lactic acid (PLA) films enhanced with ZnO nanoparticles. The pure PLA films and tri-layered PLAZnO1%/PLA/PLAZnO1% films of 150 µm thickness were extruded. The samples were treated with UV-A and Q-SUN irradiation. After irradiation the antimicrobial activity and mechanical properties of the films were analyzed. The results of the study demonstrated that PLA films did not inhibit the growth of Staphylococcus aureus , Bacillus cereus , Escherichia coli , Bacillus atrophaeus , and Candida albicans cells. PLA films with incorporated zinc oxide nanoparticles decreased the number of analyzed microorganisms. Accelerated UV aging had no negative effect on the activity of the film containing nano-ZnO against Gram-positive bacteria, but it influenced the activity against Gram-negative cells and C. albicans . Q-SUN irradiation decreased the antimicrobial effect of films with incorporated nanoparticles against B. cereus . UV-A and Q-UV irradiation did not influence the mechanical properties of PLA films containing incorporated ZnO nanoparticles.
Mora, Mireia; Adam, Victoria; Palomera, Elisabet; Blesa, Sebastian; Díaz, Gonzalo; Buquet, Xavier; Serra-Prat, Mateu; Martín-Escudero, Juan Carlos; Palanca, Ana; Chaves, Javier Felipe; Puig-Domingo, Manuel
BACKGROUND: The role of genetic variations within the ghrelin gene on cardiometabolic profile and nutritional status is still not clear in humans, particularly in elderly people. OBJECTIVES: We investigated six SNPs of the ghrelin gene and their relationship with metabolic syndrome (MS) components. SUBJECTS AND METHODS: 824 subjects (413 men/411 women, age 77.31±5.04) participating in the Mataró aging study (n = 310) and the Hortega study (n = 514) were analyzed. Anthropometric variables, ghr...
Sherif F Tadros
Full Text Available Age-related hearing loss - presbycusis - is the number one neurodegenerative disorder and top communication deficit of our aged population. Like many aging disorders of the nervous system, damage from free radicals linked to production of reactive oxygen and/or nitrogen species (ROS and RNS, respectively may play key roles in disease progression. The efficacy of the antioxidant systems, e.g., glutathione and thioredoxin, is an important factor in pathophysiology of the aging nervous system. In this investigation, relations between the expression of antioxidant-related genes in the auditory portion of the inner ear - cochlea, and age-related hearing loss was explored for CBA/CaJ mice. Forty mice were classified into four groups according to age and degree of hearing loss. Cochlear mRNA samples were collected and cDNA generated. Using Affymetrix® GeneChip, the expressions of 56 antioxidant-related gene probes were analyzed to estimate the differences in gene expression between the four subject groups. The expression of Glutathione peroxidase 6, Gpx6; Thioredoxin reductase 1, Txnrd1; Isocitrate dehydrogenase 1, Idh1; and Heat shock protein 1, Hspb1; were significantly different, or showed large fold-change differences between subject groups. The Gpx6, Txnrd1 and Hspb1 gene expression changes were validated using qPCR. The Gpx6 gene was upregulated while the Txnrd1 gene was downregulated with age/hearing loss. The Hspb1 gene was found to be downregulated in middle-aged animals as well as those with mild presbycusis, whereas it was upregulated in those with severe presbycusis. These results facilitate development of future interventions to predict, prevent or slow down the progression of presbycusis.
Full Text Available Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors (age at menarche, parity, breastfeeding, body mass index, height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, physical activity in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene-environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between LSP1-rs3817198 and parity (Pinteraction = 2.4 × 10(-6 and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1 × 10(-4. Overall, the per-allele odds ratio (95% confidence interval for LSP1-rs3817198 was 1.08 (1.01-1.16 in nulliparous women and ranged from 1.03 (0.96-1.10 in parous women with one birth to 1.26 (1.16-1.37 in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85-0.98 in those with an alcohol intake of <20 g/day and 1.45 (1.14-1.85 in those who drank ≥ 20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3 × 10(-5, with a per-allele OR of 1.14 (1.11-1.17 in parous women and 0.98 (0.92-1.05 in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.
Minelli, Cosetta; Wei, Igor; Sagoo, Gurdeep; Jarvis, Debbie; Shaheen, Seif; Burney, Peter
Susceptibility to the respiratory effects of air pollution varies between individuals. Although some evidence suggests higher susceptibility for subjects carrying variants of antioxidant genes, findings from gene-pollution interaction studies conflict in terms of the presence and direction of interactions. The authors conducted a systematic review on antioxidant gene-pollution interactions which included 15 studies, with 12 supporting the presence of interactions. For the glutathione S-transferase M1 gene (GSTM1) (n=10 studies), only 1 study found interaction with the null genotype alone, although 5 observed interactions when GSTM1 was evaluated jointly with other genes (mainly NAD(P)H dehydrogenase [quinone] 1 (NQO1)). All studies on the glutathione S-transferase P1 (GSTP1) Ile105Val polymorphism (n=11) provided some evidence of interaction, but findings conflicted in terms of risk allele. Results were negative for glutathione S-transferase T1 (GSTT1) (n=3) and positive for heme oxygenase 1 (HMOX-1) (n=2). Meta-analysis could not be performed because there were insufficient data available for any specific gene-pollutant-outcome combination. Overall the evidence supports the presence of gene-pollution interactions, although which pollutant interacts with which gene is unclear. However, issues regarding multiple testing, selective reporting, and publication bias raise the possibility of false-positive findings. Larger studies with greater accuracy of pollution assessment and improved quality of conduct and reporting are required. © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
Podor, Thomas J; Campbell, Stephanie; Chindemi, Paul; Foulon, Denise M; Farrell, David H; Walton, Philip D; Weitz, Jeffrey I; Peterson, Cynthia B
Vitronectin is an abundant plasma protein that regulates coagulation, fibrinolysis, complement activation, and cell adhesion. Recently, we demonstrated that plasma vitronectin inhibits fibrinolysis by mediating the interaction of type 1 plasminogen activator inhibitor with fibrin (Podor, T. J., Peterson, C. B., Lawrence, D. A., Stefansson, S., Shaughnessy, S. G., Foulon, D. M., Butcher, M., and Weitz, J. I. (2000) J. Biol. Chem. 275, 19788-19794). The current studies were undertaken to further examine the interactions between vitronectin and fibrin(ogen). Comparison of vitronectin levels in plasma with those in serum indicates that approximately 20% of plasma vitronectin is incorporated into the clot. When the time course of biotinylated-vitronectin incorporation into clots formed from (125)I-fibrinogen is monitored, vitronectin incorporation into the clot parallels that of fibrinogen in the absence or presence of activated factor XIII. Vitronectin binds specifically to fibrin matrices with an estimated K(d) of approximately 0.6 microm. Additional vitronectin subunits are assembled on fibrin-bound vitronectin multimers through self-association. Confocal microscopy of fibrin clots reveals the globular vitronectin aggregates anchored at intervals along the fibrin fibrils. This periodicity raised the possibility that vitronectin interacts with the gamma A/gamma' variant of fibrin(ogen) that represents about 10% of total fibrinogen. In support of this concept, the vitronectin which contaminates fibrinogen preparations co-purifies with the gamma A/gamma' fibrinogen fraction, and clots formed from gamma A/gamma' fibrinogen preferentially bind vitronectin. These studies reveal that vitronectin associates with fibrin during coagulation, and may thereby modulate hemostasis and inflammation.
Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.
Levine, M E; Cole, S W; Weir, D R; Crimmins, E M
Adverse experiences in early life have the ability to "get under the skin" and affect future health. This study examined the relative influence of adversities during childhood and adulthood in accounting for individual differences in pro-inflammatory gene expression in late life. Using a pilot-sample from the Health and Retirement Study (N = 114) aged from 51 to 95, OLS regression models were run to determine the association between a composite score from three proinflammatory gene expression levels (PTGS2, ILIB, and IL8) and 1) childhood trauma, 2) childhood SES, 3) childhood health, 4) adult traumas, and 5) low SES in adulthood. Our results showed that only childhood trauma was found to be associated with increased inflammatory transcription in late life. Furthermore, examination of interaction effects showed that childhood trauma exacerbated the influence of low SES in adulthood on elevated levels of inflammatory gene expression-signifying that having low SES in adulthood was most damaging for persons who had experienced traumatic events during their childhood. Overall our study suggests that traumas experienced during childhood may alter the stress response, leading to more sensitive reactivity throughout the lifespan. As a result, individuals who experienced greater adversity in early life may be at higher risk of late life health outcomes, particularly if adulthood adversity related to SES persists. Copyright © 2015. Published by Elsevier Ltd.
Full Text Available The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2 is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445 and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445 and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605, in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605 may be involved in the susceptibility to paranoid
Lin, Zheng; Su, Yousong; Zhang, Chengfang; Xing, Mengjuan; Ding, Wenhua; Liao, Liwei; Guan, Yangtai; Li, Zezhi; Cui, Donghong
The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2) is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia) and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445) and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445) and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605), in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605) may be involved in the susceptibility to paranoid schizophrenia.
Tacutu, Robi; Craig, Thomas; Budovsky, Arie; Wuttke, Daniel; Lehmann, Gilad; Taranukha, Dmitri; Costa, Joana; Fraifeld, Vadim E.; de Magalhães, João Pedro
The Human Ageing Genomic Resources (HAGR, http://genomics.senescence.info) is a freely available online collection of research databases and tools for the biology and genetics of ageing. HAGR features now several databases with high-quality manually curated data: (i) GenAge, a database of genes associated with ageing in humans and model organisms; (ii) AnAge, an extensive collection of longevity records and complementary traits for >4000 vertebrate species; and (iii) GenDR, a newly incorporated database, containing both gene mutations that interfere with dietary restriction-mediated lifespan extension and consistent gene expression changes induced by dietary restriction. Since its creation about 10 years ago, major efforts have been undertaken to maintain the quality of data in HAGR, while further continuing to develop, improve and extend it. This article briefly describes the content of HAGR and details the major updates since its previous publications, in terms of both structure and content. The completely redesigned interface, more intuitive and more integrative of HAGR resources, is also presented. Altogether, we hope that through its improvements, the current version of HAGR will continue to provide users with the most comprehensive and accessible resources available today in the field of biogerontology. PMID:23193293
Combarros, Onofre; van Duijn, Cornelia M; Hammond, Naomi; Belbin, Olivia; Arias-Vásquez, Alejandro; Cortina-Borja, Mario; Lehmann, Michael G; Aulchenko, Yurii S; Schuur, Maaike; Kölsch, Heike; Heun, Reinhard; Wilcock, Gordon K; Brown, Kristelle; Kehoe, Patrick G; Harrison, Rachel; Coto, Eliecer; Alvarez, Victoria; Deloukas, Panos; Mateo, Ignacio; Gwilliam, Rhian; Morgan, Kevin; Warden, Donald R; Smith, A David; Lehmann, Donald J
Background Chronic inflammation is a characteristic of Alzheimer's disease (AD). An interaction associated with the risk of AD has been reported between polymorphisms in the regulatory regions of the genes for the pro-inflammatory cytokine, interleukin-6 (IL-6, gene: IL6), and the anti-inflammatory cytokine, interleukin-10 (IL-10, gene: IL10). Methods We examined this interaction in the Epistasis Project, a collaboration of 7 AD research groups, contributing DNA samples from 1,757 cases of AD and 6,295 controls. Results We replicated the interaction. For IL6 rs2069837 AA × IL10 rs1800871 CC, the synergy factor (SF) was 1.63 (95% confidence interval: 1.10–2.41, p = 0.01), controlling for centre, age, gender and apolipoprotein E ε4 (APOEε4) genotype. Our results are consistent between North Europe (SF = 1.7, p = 0.03) and North Spain (SF = 2.0, p = 0.09). Further replication may require a meta-analysis. However, association due to linkage disequilibrium with other polymorphisms in the regulatory regions of these genes cannot be excluded. Conclusion We suggest that dysregulation of both IL-6 and IL-10 in some elderly people, due in part to genetic variations in the two genes, contributes to the development of AD. Thus, inflammation facilitates the onset of sporadic AD. PMID:19698145
Lackington, William A; Raftery, Rosanne M; O'Brien, Fergal J
Despite the success of tissue engineered nerve guidance conduits (NGCs) for the treatment of small peripheral nerve injuries, autografts remain the clinical gold standard for larger injuries. The delivery of neurotrophic factors from conduits might enhance repair for more effective treatment of larger injuries but the efficacy of such systems is dependent on a safe, effective platform for controlled and localised therapeutic delivery. Gene therapy might offer an innovative approach to control the timing, release and level of neurotrophic factor production by directing cells to transiently sustain therapeutic protein production in situ. In this study, a gene-activated NGC was developed by incorporating non-viral polyethyleneimine-plasmid DNA (PEI-pDNA) nanoparticles (N/P 7 ratio, 2μg dose) with the pDNA encoding for nerve growth factor (NGF), glial derived neurotrophic factor (GDNF) or the transcription factor c-Jun. The physicochemical properties of PEI-pDNA nanoparticles, morphology, size and charge, were shown to be suitable for gene delivery and demonstrated high Schwann cell transfection efficiency (60±13%) in vitro. While all three genes showed therapeutic potential in terms of enhancing neurotrophic cytokine production while promoting neurite outgrowth, delivery of the gene encoding for c-Jun showed the greatest capacity to enhance regenerative cellular processes in vitro. Ultimately, this gene-activated NGC construct was shown to be capable of transfecting both Schwann cells (S42 cells) and neuronal cells (PC12 and dorsal root ganglia) in vitro, demonstrating potential for future therapeutic applications in vivo. The basic requirements of biomaterial-based nerve guidance conduits have now been well established and include being able to bridge a nerve injury to support macroscopic guidance between nerve stumps, while being strong enough to withstand longitudinal tension and circumferential compression, in addition to being mechanically sound to facilitate
Gregory, Alice M; Lau, Jennifer Y F; Eley, Thalia C
Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G x E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G x Es for phobias. In addition to the careful conceptualisation of new studies, it is suggested that data already collected should be re-analysed in light of increased understanding of processes influencing phobias.
Full Text Available Aging progression is a process that an individual encounters as they become older, and usually results from a series of normal physiological changes over time. The hippocampus, which contributes to the loss of spatial and episodic memory and learning in older people, is closely related to the detrimental effects of aging at the morphological and molecular levels. However, age-related genetic changes in hippocampal molecular mechanisms are not yet well-established. To provide additional insight into the aging process, differentially-expressed genes of 3- versus 24- and 29-month old mice were re-analyzed. The results revealed that a large number of immune and inflammatory response-related genes were up-regulated in the aged hippocampus, and membrane receptor-associated genes were down-regulated. The down-regulation of transmembrane receptors may indicate the weaker perception of environmental exposure in older people, since many transmembrane proteins participate in signal transduction. In addition, molecular interaction analysis of the up-regulated immune genes indicated that the hub gene, Ywhae, may play essential roles in immune and inflammatory responses during aging progression, as well as during hippocampal development. Our biological experiments confirmed the conserved roles of Ywhae and its partners between human and mouse. Furthermore, comparison of microarray data between advanced-age mice treated with human umbilical cord blood plasma protein and the phosphate-buffered saline control showed that the genes that contribute to the revitalization of advanced-age mice are different from the genes induced by aging. These results implied that the revitalization of advanced-age mice is not a simple reverse process of normal aging progression. Our data assigned novel roles of genes during aging progression and provided further theoretic evidence for future studies exploring the underlying mechanisms of aging and anti-aging-related disease
Vandenboom, Rene; Herron, Todd; Favre, Elizabeth; Albayya, Faris P.
The purpose of this study was to implement a living myocyte in vitro model system to test whether a motor domain-deleted headless myosin construct could be incorporated into the sarcomere and affect contractility. To this end we used gene transfer to express a “headless” myosin heavy chain (headless-MHC) in complement with the native full-length myosin motors in the cardiac sarcomere. An NH2-terminal Flag epitope was used for unique detection of the motor domain-deleted headless-MHC. Total MHC content (i.e., headless-MHC + endogenous MHC) remained constant, while expression of the headless-MHC in transduced myocytes increased from 24 to 72 h after gene transfer until values leveled off at 96 h after gene transfer, at which time the headless-MHC comprised ∼20% of total MHC. Moreover, immunofluorescence labeling and confocal imaging confirmed expression and demonstrated incorporation of the headless-MHC in the A band of the cardiac sarcomere. Functional measurements in intact myocytes showed that headless-MHC modestly reduced amplitude of dynamic twitch contractions compared with controls (P < 0.05). In chemically permeabilized myocytes, maximum steady-state isometric force and the tension-pCa relationship were unaltered by the headless-MHC. These data suggest that headless-MHC can express to 20% of total myosin and incorporate into the sarcomere yet have modest to no effects on dynamic and steady-state contractile function. This would indicate a degree of functional tolerance in the sarcomere for nonfunctional myosin molecules. PMID:21112946
Angeline S Andrew
Full Text Available Bladder cancer is the 4(th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62. This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63. The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25 than females (OR 1.56 95%CI 0.83-2.95, (SNP-gender interaction P = 0.048. We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003. The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.
Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu
Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.
Liao, Zhijie; Sosa, Sebastian; Wu, Chengfeng; Zhang, Peng
The social relationships that individuals experience at different life stages have a non-negligible influence on their lives, and this is particularly true for group living animals. The long lifespan of many primates makes it likely that these animals have various tactics of social interaction to adapt to complex changes in environmental or physical conditions. The different strategies used in social interaction by individuals at different life stages, and whether the position (central or peripheral) or role (initiator or recipient) of an individual in the group social network changes with age, are intriguing questions that remain to be investigated. We used social network analysis to examine age-related differences in social interaction patterns, social roles, and social positions in three affiliative social networks (approach, allogrooming, and social play) in a group of wild rhesus macaques (Macaca mulatta). Our results showed that social interaction patterns of rhesus macaques differ between age classes in the following ways: i) young individuals tend to allocate social time to a high number of groupmates, older individuals prefer to focus on fewer, specific partners; ii) as they grow older, individuals tend to be recipients in approach interactions and initiators in grooming interactions; and iii) regardless of the different social interaction strategies, individuals of all ages occupy a central position in the group. These results reveal a possible key role played by immature individuals in group social communication, a little-explored issue which deserves closer investigation in future research. © 2017 Wiley Periodicals, Inc.
Full Text Available Characterization of gene-environment interactions (GEIs in cancer is limited. We aimed at identifying GEIs in rectal cancer focusing on a relevant biologic process involving the angiogenesis pathway and relevant environmental exposures: cigarette smoking, alcohol consumption, and animal protein intake. We analyzed data from 747 rectal cancer cases and 956 controls from the Diet, Activity and Lifestyle as a Risk Factor for Rectal Cancer study. We applied a 3-step analysis approach: first, we searched for interactions among single nucleotide polymorphisms on the pathway genes; second, we searched for interactions among the genes, both steps using Logic regression; third, we examined the GEIs significant at the 5% level using logistic regression for cancer risk and Cox proportional hazards models for survival. Permutation-based test was used for multiple testing adjustment. We identified 8 significant GEIs associated with risk among 6 genes adjusting for multiple testing: TNF (OR = 1.85, 95% CI: 1.10, 3.11, TLR4 (OR = 2.34, 95% CI: 1.38, 3.98, and EGR2 (OR = 2.23, 95% CI: 1.04, 4.78 with smoking; IGF1R (OR = 1.69, 95% CI: 1.04, 2.72, TLR4 (OR = 2.10, 95% CI: 1.22, 3.60 and EGR2 (OR = 2.12, 95% CI: 1.01, 4.46 with alcohol; and PDGFB (OR = 1.75, 95% CI: 1.04, 2.92 and MMP1 (OR = 2.44, 95% CI: 1.24, 4.81 with protein. Five GEIs were associated with survival at the 5% significance level but not after multiple testing adjustment: CXCR1 (HR = 2.06, 95% CI: 1.13, 3.75 with smoking; and KDR (HR = 4.36, 95% CI: 1.62, 11.73, TLR2 (HR = 9.06, 95% CI: 1.14, 72.11, EGR2 (HR = 2.45, 95% CI: 1.42, 4.22, and EGFR (HR = 6.33, 95% CI: 1.95, 20.54 with protein. GEIs between angiogenesis genes and smoking, alcohol, and animal protein impact rectal cancer risk. Our results support the importance of considering the biologic hypothesis to characterize GEIs associated with cancer outcomes.
Kinik, F Pelin; Altintas, Cigdem; Balci, Volkan; Koyuturk, Burak; Uzun, Alper; Keskin, Seda
Experiments were combined with atomically detailed simulations and density functional theory (DFT) calculations to understand the effect of incorporation of an ionic liquid (IL), 1-n-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF 6 ]), into a metal organic framework (MOF with a zeolitic imidazolate framework), ZIF-8, on the CO 2 separation performance. The interactions between [BMIM][PF 6 ] and ZIF-8 were examined in deep detail, and their consequences on CO 2 /CH 4 , CO 2 /N 2 , and CH 4 /N 2 separation have been elucidated by using experimental measurements complemented by DFT calculations and atomically detailed simulations. Results suggest that IL-MOF interactions strongly affect the gas affinity of materials at low pressure, whereas available pore volume plays a key role for gas adsorption at high pressures. Direct interactions between IL and MOF lead to at least a doubling of CO 2 /CH 4 and CO 2 /N 2 selectivities of ZIF-8. These results provide opportunities for rational design and development of IL-incorporated MOFs with exceptional selectivity for target gas separation applications.
Full Text Available Background: Colorectal cancer (CRC is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an “omics” study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Materials and methods: Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. Result: We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene
Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L.; Rylander, Lars; Giwercman, Aleksander
As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism, but the number of studies is still limited. This type of interaction studies may improve our understanding of normal physiology and help us to identify the risk factors to male reproductive malfunction. We also shortly discuss other aspects of gene-environment interaction specifically associated with the issue of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity in the offspring. PMID:20348940
Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing
Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene
Full Text Available Abstract Background Several studies have hypothesized that genes regulating the components of the serotonin system, including serotonin transporter (5-HTTLPR and serotonin 1 B receptor (5-HT1B, may be associated with alcoholism, but their results are contradictory because of alcoholism’s heterogeneity. Therefore, we examined whether the 5-HTTLPR gene and 5-HT1B gene G861C polymorphism are susceptibility factors for a specific subtype of alcoholism, antisocial alcoholism in Han Chinese in Taiwan. Methods We recruited 273 Han Chinese male inmates with antisocial personality disorder (ASPD [antisocial alcoholism (AS-ALC group (n = 120 and antisocial non-alcoholism (AS-N-ALC group (n = 153] and 191 healthy male controls from the community. Genotyping was done using PCR-RFLP. Results There were no significant differences in the genotypic frequency of the 5-HT1B G861C polymorphism between the 3 groups. Although AS-ALC group members more frequently carried the 5-HTTLPR S/S, S/LG, and LG/LG genotypes than controls, the difference became non-significant after controlling for the covarying effects of age. However, the 5-HTTLPR S/S, S/LG, and LG/LG genotypes may have interacted with the 5-HT1B G861C C/C polymorphism and increased the risk of becoming antisocial alcoholism. Conclusion Our study suggests that neither the 5-HTTLPR gene nor the 5-HT1B G861C polymorphism alone is a risk factor for antisocial alcoholism in Taiwan’s Han Chinese population, but that the interaction between both genes may increase susceptibility to antisocial alcoholism.
Charles, Susan Turk; Piazza, Jennifer R
The current study examined age differences in the intensity of emotions experienced during social interactions. Because emotions are felt most intensely in situations central to motivational goals, age differences in emotional intensity may exist in social situations that meet the goals for one age group more than the other. Guided by theories of emotional intensity and socioemotional selectivity, it was hypothesized that social partner type would elicit different affective responses by age. Younger (n = 71) and older (n = 71) adults recalled experiences of positive and negative emotions with new friends, established friends, and family members from the prior week. Compared with younger adults, older adults reported lower intensity positive emotions with new friends, similarly intense positive emotions with established friends, and higher intensity positive emotions with family members. Older adults reported lower intensity negative emotions for all social partners than did younger adults, but this difference was most pronounced for interactions with new friends. ((c) 2007 APA, all rights reserved).
Chen, Qing; Yu, Can-Qing; Tang, Xun; Chen, Da-Fang; Tian, Jun; Cao, Yang; Fan, Wen-Yi; Cao, Wei-Hua; Zhan, Si-Yan; Lv, Jun; Guo, Xiao-Xia; Hu, Yong-Hua; Lee, Li-Ming
Angiotensin-converting enzyme inhibitors are widely used antihypertensive drugs with individual response variation. We studied whether interactions of AGT, AGTR1 and ACE2 gene polymorphisms affect this response. Our study is based on a 3-year field trial with 1831 hypertensive patients prescribed benazepril. Generalized multifactor dimensionality reduction was used to explore interaction models and logistic regressions were used to confirm them. A two-locus model involving the AGT and ACE2 genes was found in males, the sensitive genotypes showed an odds ratio (OR) of 1.9 (95% CI: 1.3-2.8) when compared with nonsensitive genotypes. Two AGT-AGTR1 models were found in females, with an OR of 3.5 (95% CI: 2.0-5.9) and 3.1 (95% CI: 1.8-5.3). Gender-specific gene-gene interactions of the AGT, AGTR1 and ACE2 genes were associated with individual variation of response to benazepril. Further studies are needed to confirm this finding.
Full Text Available Impact of female aging is an important issue in human reproduction. There was a need for an extensive analysis of age impact on transcriptome profile of cumulus cells (CCs to link oocyte quality and developmental potential with patient’s age. CCs from patients of three age groups were analyzed individually using microarrays. RT-qPCR validation was performed on independent CC cohorts. We focused here on pathways affected by aging in CCs that may explain the decline of oocyte quality with age. In CCs collected from patients >37 years, angiogenic genes including ANGPTL4, LEPR, TGFBR3, and FGF2 were significantly overexpressed compared to patients of the two younger groups. In contrast genes implicated in TGF-β signaling pathway such as AMH, TGFB1, inhibin, and activin receptor were underexpressed. CCs from patients whose ages are between 31 and 36 years showed an overexpression of genes related to insulin signaling pathway such as IGFBP3, PIK3R1, and IGFBP5. A bioinformatic analysis was performed to identify the microRNAs that are potential regulators of the differentially expressed genes of the study. It revealed that the pathways impacted by age were potential targets of specific miRNAs previously identified in our CCs small RNAs sequencing.
Norton, Gareth J; Nigar, Meher; Williams, Paul N; Dasgupta, Tapash; Meharg, Andrew A; Price, Adam H
In this study, the genetic mapping of the tolerance of root growth to 13.3 muM arsenate [As(V)] using the BalaxAzucena population is improved, and candidate genes for further study are identified. A remarkable three-gene model of tolerance is advanced, which appears to involve epistatic interaction between three major genes, two on chromosome 6 and one on chromosome 10. Any combination of two of these genes inherited from the tolerant parent leads to the plant having tolerance. Lists of potential positional candidate genes are presented. These are then refined using whole genome transcriptomics data and bioinformatics. Physiological evidence is also provided that genes related to phosphate transport are unlikely to be behind the genetic loci conferring tolerance. These results offer testable hypotheses for genes related to As(V) tolerance that might offer strategies for mitigating arsenic (As) accumulation in consumed rice.
Norton, Gareth J.; Nigar, Meher; Dasgupta, Tapash; Meharg, Andrew A.; Price, Adam H.
In this study, the genetic mapping of the tolerance of root growth to 13.3 μM arsenate [As(V)] using the Bala×Azucena population is improved, and candidate genes for further study are identified. A remarkable three-gene model of tolerance is advanced, which appears to involve epistatic interaction between three major genes, two on chromosome 6 and one on chromosome 10. Any combination of two of these genes inherited from the tolerant parent leads to the plant having tolerance. Lists of potential positional candidate genes are presented. These are then refined using whole genome transcriptomics data and bioinformatics. Physiological evidence is also provided that genes related to phosphate transport are unlikely to be behind the genetic loci conferring tolerance. These results offer testable hypotheses for genes related to As(V) tolerance that might offer strategies for mitigating arsenic (As) accumulation in consumed rice. PMID:18453529
Background This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD). Methods In a well-powered microarray study of young (20 to 59 years), aged (60 to 99 years), and AD (74 to 95 years) cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. Results Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%). In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets), with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine) that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc) receptors and human leukocyte antigens I
Cribbs David H
Full Text Available Abstract Background This study undertakes a systematic and comprehensive analysis of brain gene expression profiles of immune/inflammation-related genes in aging and Alzheimer’s disease (AD. Methods In a well-powered microarray study of young (20 to 59 years, aged (60 to 99 years, and AD (74 to 95 years cases, gene responses were assessed in the hippocampus, entorhinal cortex, superior frontal gyrus, and post-central gyrus. Results Several novel concepts emerge. First, immune/inflammation-related genes showed major changes in gene expression over the course of cognitively normal aging, with the extent of gene response far greater in aging than in AD. Of the 759 immune-related probesets interrogated on the microarray, approximately 40% were significantly altered in the SFG, PCG and HC with increasing age, with the majority upregulated (64 to 86%. In contrast, far fewer immune/inflammation genes were significantly changed in the transition to AD (approximately 6% of immune-related probesets, with gene responses primarily restricted to the SFG and HC. Second, relatively few significant changes in immune/inflammation genes were detected in the EC either in aging or AD, although many genes in the EC showed similar trends in responses as in the other brain regions. Third, immune/inflammation genes undergo gender-specific patterns of response in aging and AD, with the most pronounced differences emerging in aging. Finally, there was widespread upregulation of genes reflecting activation of microglia and perivascular macrophages in the aging brain, coupled with a downregulation of select factors (TOLLIP, fractalkine that when present curtail microglial/macrophage activation. Notably, essentially all pathways of the innate immune system were upregulated in aging, including numerous complement components, genes involved in toll-like receptor signaling and inflammasome signaling, as well as genes coding for immunoglobulin (Fc receptors and human
Liu, Amy Y; Scherer, Dominique; Poole, Elizabeth; Potter, John D; Curtin, Karen; Makar, Karen; Slattery, Martha L; Caan, Bette J; Ulrich, Cornelia M
The importance of folate-mediated one-carbon metabolism (FOCM) in colorectal carcinogenesis is emphasized by observations that high dietary folate intake is associated with decreased risk of colon cancer (CC) and its precursors. Additionally, polymorphisms in FOCM-related genes have been repeatedly associated with risk, supporting a causal relationship between folate and colorectal carcinogenesis. We investigated ten candidate polymorphisms with defined or probable functional impact in eight FOCM-related genes (SHMT1, DHFR, DNMT1, MTHFD1, MTHFR, MTRR, TCN2, and TDG) in 1609 CC cases and 1974 controls for association with CC risk and for interaction with dietary factors. No polymorphism was statistically significantly associated with overall risk of CC. However, statistically significant interactions modifying CC risk were observed for DNMT1 I311V with dietary folate, methionine, vitamin B2 , and vitamin B12 intake and for MTRR I22M with dietary folate, a predefined one-carbon dietary pattern, and vitamin B6 intake. We observed statistically significant gene-diet interactions with five additional polymorphisms. Our results provide evidence that FOCM-related dietary intakes modify the association between CC risk and FOCM allelic variants. These findings add to observations showing that folate-related gene-nutrient interactions play an important role in modifying the risk of CC. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Tuller, Tamir; Atar, Shimshi; Ruppin, Eytan; Gurevich, Michael; Achiron, Anat
Multiple sclerosis (MS) is a central nervous system autoimmune inflammatory T-cell-mediated disease with a relapsing-remitting course in the majority of patients. In this study, we performed a high-resolution systems biology analysis of gene expression and physical interactions in MS relapse and remission. To this end, we integrated 164 large-scale measurements of gene expression in peripheral blood mononuclear cells of MS patients in relapse or remission and healthy subjects, with large-scale information about the physical interactions between these genes obtained from public databases. These data were analyzed with a variety of computational methods. We find that there is a clear and significant global network-level signal that is related to the changes in gene expression of MS patients in comparison to healthy subjects. However, despite the clear differences in the clinical symptoms of MS patients in relapse versus remission, the network level signal is weaker when comparing patients in these two stages of the disease. This result suggests that most of the genes have relatively similar expression levels in the two stages of the disease. In accordance with previous studies, we found that the pathways related to regulation of cell death, chemotaxis and inflammatory response are differentially expressed in the disease in comparison to healthy subjects, while pathways related to cell adhesion, cell migration and cell-cell signaling are activated in relapse in comparison to remission. However, the current study includes a detailed report of the exact set of genes involved in these pathways and the interactions between them. For example, we found that the genes TP53 and IL1 are 'network-hub' that interacts with many of the differentially expressed genes in MS patients versus healthy subjects, and the epidermal growth factor receptor is a 'network-hub' in the case of MS patients with relapse versus remission. The statistical approaches employed in this study enabled us
... point to same risk gene for age-related macular degeneration NIH-funded research helps unravel the biology of ... rare, but powerful risk factor for age-related macular degeneration (AMD), a common cause of vision loss in ...
Perreau-Lenz, Stéphanie; Spanagel, Rainer
Adverse life events and highly stressful environments have deleterious consequences for mental health. Those environmental factors can potentiate alcohol and drug abuse in vulnerable individuals carrying specific genetic risk factors, hence producing the final risk for alcohol- and substance-use disorders development. The nature of these genes remains to be fully determined, but studies indicate their direct or indirect relation to the stress hypothalamo-pituitary-adrenal (HPA) axis and/or reward systems. Over the past decade, clock genes have been revealed to be key-players in influencing acute and chronic alcohol/drug effects. In parallel, the influence of chronic stress and stressful life events in promoting alcohol and substance use and abuse has been demonstrated. Furthermore, the reciprocal interaction of clock genes with various HPA-axis components, as well as the evidence for an implication of clock genes in stress-induced alcohol abuse, have led to the idea that clock genes, and Period genes in particular, may represent key genetic factors to consider when examining gene × environment interaction in the etiology of addiction. The aim of the present review is to summarize findings linking clock genes, stress, and alcohol and substance abuse, and to propose potential underlying neurobiological mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.
Costa, M; Piché, M; Lepore, F; Guillemot, J-P
It is well established that multisensory integration is a functional characteristic of the superior colliculus that disambiguates external stimuli and therefore reduces the reaction times toward simple audiovisual targets in space. However, in a condition where a complex audiovisual stimulus is used, such as the optical flow in the presence of modulated audio signals, little is known about the processing of the multisensory integration in the superior colliculus. Furthermore, since visual and auditory deficits constitute hallmark signs during aging, we sought to gain some insight on whether audiovisual processes in the superior colliculus are altered with age. Extracellular single-unit recordings were conducted in the superior colliculus of anesthetized Sprague-Dawley adult (10-12 months) and aged (21-22 months) rats. Looming circular concentric sinusoidal (CCS) gratings were presented alone and in the presence of sinusoidally amplitude modulated white noise. In both groups of rats, two different audiovisual response interactions were encountered in the spatial domain: superadditive, and suppressive. In contrast, additive audiovisual interactions were found only in adult rats. Hence, superior colliculus audiovisual interactions were more numerous in adult rats (38%) than in aged rats (8%). These results suggest that intersensory interactions in the superior colliculus play an essential role in space processing toward audiovisual moving objects during self-motion. Moreover, aging has a deleterious effect on complex audiovisual interactions. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
van der Linde, Karina; Kastner, Christine; Kumlehn, Jochen; Kahmann, Regine; Doehlemann, Gunther
Infection of maize (Zea mays) plants with the corn smut fungus Ustilago maydis leads to the formation of large tumors on the stem, leaves and inflorescences. In this biotrophic interaction, plant defense responses are actively suppressed by the pathogen, and previous transcriptome analyses of infected maize plants showed massive and stage-specific changes in host gene expression during disease progression. To identify maize genes that are functionally involved in the interaction with U. maydis, we adapted a virus-induced gene silencing (VIGS) system based on the brome mosaic virus (BMV) for maize. Conditions were established that allowed successful U. maydis infection of BMV-preinfected maize plants. This set-up enabled quantification of VIGS and its impact on U. maydis infection using a quantitative real-time PCR (qRT-PCR)-based readout. In proof-of-principle experiments, an U. maydis-induced terpene synthase was shown to negatively regulate disease development while a protein involved in cell death inhibition was required for full virulence of U. maydis. The results suggest that this system is a versatile tool for the rapid identification of maize genes that determine compatibility with U. maydis. © (2010) Max Planck Society. Journal compilation © New Phytologist Trust (2010).
Papenberg, Goran; Becker, Nina; Ferencz, Beata; Naveh-Benjamin, Moshe; Laukka, Erika J; Bäckman, Lars; Brehmer, Yvonne
Previous research shows that associative memory declines more than item memory in aging. Although the underlying mechanisms of this selective impairment remain poorly understood, animal and human data suggest that dopaminergic modulation may be particularly relevant for associative binding. We investigated the influence of dopamine (DA) receptor genes on item and associative memory in a population-based sample of older adults (n = 525, aged 60 years), assessed with a face-scene item associative memory task. The effects of single-nucleotide polymorphisms of DA D1 (DRD1; rs4532), D2 (DRD2/ANKK1/Taq1A; rs1800497), and D3 (DRD3/Ser9Gly; rs6280) receptor genes were examined and combined into a single genetic score. Individuals carrying more beneficial alleles, presumably associated with higher DA receptor efficacy (DRD1 C allele; DRD2 A2 allele; DRD3 T allele), performed better on associative memory than persons with less beneficial genotypes. There were no effects of these genes on item memory or other cognitive measures, such as working memory, executive functioning, fluency, and perceptual speed, indicating a selective association between DA genes and associative memory. By contrast, genetic risk for Alzheimer disease (AD) was associated with worse item and associative memory, indicating adverse effects of APOE ε4 and a genetic risk score for AD (PICALM, BIN1, CLU) on episodic memory in general. Taken together, our results suggest that DA may be particularly important for associative memory, whereas AD-related genetic variations may influence overall episodic memory in older adults without dementia.
Berchtold, Nicole C.; Coleman, Paul D.; Cribbs, David H.; Rogers, Joseph; Gillen, Daniel L.; Cotman, Carl W.
Synapses are essential for transmitting, processing, and storing information, all of which decline in aging and Alzheimer’s disease (AD). Because synapse loss only partially accounts for the cognitive declines seen in aging and AD, we hypothesized that existing synapses might undergo molecular changes that reduce their functional capacity. Microarrays were used to evaluate expression profiles of 340 synaptic genes in aging (20–99 years) and AD across 4 brain regions from 81 cases. The analysis revealed an unexpectedly large number of significant expression changes in synapse-related genes in aging, with many undergoing progressive downregulation across aging and AD. Functional classification of the genes showing altered expression revealed that multiple aspects of synaptic function are affected, notably synaptic vesicle trafficking and release, neurotransmitter receptors and receptor trafficking, postsynaptic density scaffolding, cell adhesion regulating synaptic stability, and neuromodulatory systems. The widespread declines in synaptic gene expression in normal aging suggests that function of existing synapses might be impaired, and that a common set of synaptic genes are vulnerable to change in aging and AD. PMID:23273601
Full Text Available Abstract Background Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. Results We have developed Genetic Interaction Motif Finding (GIMF, an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast. Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. Conclusion GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic
Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob
Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.
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
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
Full Text Available The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.
Zimmermann, Peter; Spangler, Gottfried
Adolescence is a time of increased emotionality and major changes in emotion regulation often elicited in autonomy-relevant situations. Both genetic as well as social factors may lead to inter-individual differences in emotional processes in adolescence. We investigated whether both 5-HTTLPR and attachment security influence adolescents’ observed emotionality, emotional dysregulation, and their aggressive hostile autonomy while interacting with their mothers. Eighty-eight adolescents at age 12 were observed in interaction with their mothers during a standardized, emotion eliciting computer game task. They were genotyped for the 5-HTTLPR, a repeat polymorphism in the promoter region of the serotonin transporter gene. Concurrent attachment quality was assessed by the Late Childhood Attachment Interview (LCAI). Results revealed a significant gene × attachment effect showing that ss/sl carriers of 5-HTTLPR show increased emotional dysregulation and aggressive hostile autonomy towards their mothers. The results of the study suggest that secure attachment in adolescence moderates the genetically based higher tendency for emotional dysregulation and aggressive reactions to restrictions of autonomy during emotional social interactions with their mothers. PMID:27378877
Zimmermann, Peter; Spangler, Gottfried
Adolescence is a time of increased emotionality and major changes in emotion regulation often elicited in autonomy-relevant situations. Both genetic as well as social factors may lead to inter-individual differences in emotional processes in adolescence. We investigated whether both 5-HTTLPR and attachment security influence adolescents' observed emotionality, emotional dysregulation, and their aggressive hostile autonomy while interacting with their mothers. Eighty-eight adolescents at age 12 were observed in interaction with their mothers during a standardized, emotion eliciting computer game task. They were genotyped for the 5-HTTLPR, a repeat polymorphism in the promoter region of the serotonin transporter gene. Concurrent attachment quality was assessed by the Late Childhood Attachment Interview (LCAI). Results revealed a significant gene × attachment effect showing that ss/sl carriers of 5-HTTLPR show increased emotional dysregulation and aggressive hostile autonomy towards their mothers. The results of the study suggest that secure attachment in adolescence moderates the genetically based higher tendency for emotional dysregulation and aggressive reactions to restrictions of autonomy during emotional social interactions with their mothers.
Matsushita, Masaya; Ochiai, Hiroshi; Suzuki, Ken-Ichi T; Hayashi, Sayaka; Yamamoto, Takashi; Awazu, Akinori; Sakamoto, Naoaki
The nuclear positioning and chromatin dynamics of eukaryotic genes are closely related to the regulation of gene expression, but they have not been well examined during early development, which is accompanied by rapid cell cycle progression and dynamic changes in nuclear organization, such as nuclear size and chromatin constitution. In this study, we focused on the early development of the sea urchin Hemicentrotus pulcherrimus and performed three-dimensional fluorescence in situ hybridization of gene loci encoding early histones (one of the types of histone in sea urchin). There are two non-allelic early histone gene loci per sea urchin genome. We found that during the morula stage, when the early histone gene expression levels are at their maximum, interchromosomal interactions were often formed between the early histone gene loci on separate chromosomes and that the gene loci were directed to locate to more interior positions. Furthermore, these interactions were associated with the active transcription of the early histone genes. Thus, such dynamic interchromosomal interactions may contribute to the efficient synthesis of early histone mRNA during the morula stage of sea urchin development. © 2017. Published by The Company of Biologists Ltd.
Robbers, Sylvana; van Oort, Floor; Huizink, Anja; Verhulst, Frank; van Beijsterveldt, Catharina; Boomsma, Dorret; Bartels, Meike
The importance of genetic and environmental influences on children's behavioral and emotional problems may vary as a function of environmental exposure. We previously reported that 12-year-olds with divorced parents showed more internalizing and externalizing problems than children with married parents, and that externalizing problems in girls precede and predict later parental divorce. The aim of the current study was to investigate as to whether genetic and environmental influences on internalizing and externalizing problems were different for children from divorced versus non-divorced families. Maternal ratings on internalizing and externalizing problems were collected with the Child Behavior Checklist in 4,592 twin pairs at ages 3 and 12 years, of whom 367 pairs had experienced a parental divorce between these ages. Variance in internalizing and externalizing problems at ages 3 and 12 was analyzed with biometric models in which additive genetic and environmental effects were allowed to depend on parental divorce and sex. A difference in the contribution of genetic and environmental influences between divorced and non-divorced groups would constitute evidence for gene-environment interaction. For both pre- and post-divorce internalizing and externalizing problems, the total variances were larger for children from divorced families, which was mainly due to higher environmental variances. As a consequence, heritabilities were lower for children from divorced families, and the relative contributions of environmental influences were higher. Environmental influences become more important in explaining variation in children's problem behaviors in the context of parental divorce.
Full Text Available Current dietary guidelines for fat intake have not taken into consideration the possible genetic differences underlying the individual variability in responsiveness to dietary components. Genetic variability has been identified in humans for all the known lipid metabolim-related genes resulting in a plethora of candidate genes and genetic variants to examine in diet-gene interaction studies focused on fat consumption. Some examples of fat-gene interaction are reviewed. These include: the interaction between total intake and the 514C/T in the hepatic lipase gene promoter in determining high-density lipoprotein cholesterol (HDL-C metabolism; the interaction between polyunsaturated fatty acids (PUFA and the 75G/A polymorphism in the APOA1 gene plasma HDL-C concentrations; the interaction between PUFA and the L162V polymorphism in the PPARA gene in determining triglycerides and APOC3 concentrations; and the interaction between PUFA intake and the 1131TC in the APOA5 gene in determining triglyceride metabolism. Although hundreds of diet-gene interaction studies in lipid metabolism have been published, the level of evidence to make specific nutritional recommendations to the population is still low and more research in nutrigenetics has to be undertaken.Las recomendaciones dietéticas actuales referentes al consumo de grasas en la dieta han sido realizadas sin tener en cuenta las posibles diferencias genéticas de las personas que podrían ser las responsables de las diferentes respuestas interindividuales que frecuentemente se observan ante la misma dieta. La presencia de variabilidad genética ha sido puesta de manifiesto para todos los genes relacionados con el metabolismo lipídico, por lo que existe un ingente número de genes y de variantes genéticas para ser incluidas en los estudios sobre interacciones dieta-genotipo en el ámbito específico del consumo de grasas y aceites. Se revisarán algunos ejemplos sobre interacciones grasa
Chaimayo, Chutikarn [Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642 (United States); Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700 (Thailand); Hayashi, Tsuyoshi; Underwood, Andrew; Hodges, Erin [Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642 (United States); Takimoto, Toru, E-mail: firstname.lastname@example.org [Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY 14642 (United States)
Influenza A viruses contain eight single-stranded, negative-sense RNA segments as viral genomes in the form of viral ribonucleoproteins (vRNPs). During genome replication in the nucleus, positive-sense complementary RNPs (cRNPs) are produced as replicative intermediates, which are not incorporated into progeny virions. To analyze the mechanism of selective vRNP incorporation into progeny virions, we quantified vRNPs and cRNPs in the nuclear and cytosolic fractions of infected cells, using a strand-specific qRT-PCR. Unexpectedly, we found that cRNPs were also exported to the cytoplasm. This export was chromosome region maintenance 1 (CRM1)-independent unlike that of vRNPs. Although both vRNPs and cRNPs were present in the cytosol, viral matrix (M1) protein, a key regulator for viral assembly, preferentially bound vRNPs over cRNPs. These results indicate that influenza A viruses selectively uptake cytosolic vRNPs through a specific interaction with M1 during viral assembly. - Highlights: •Influenza cRNPs are exported from the nucleus of an infected cell via a CRM1-independent pathway. •Influenza A viruses selectively incorporate cytosolic vRNPs through a specific interaction with M1 during viral assembly. •M1 dissociates from vRNP export complex after nuclear export, and is re-associated with vRNPs at the plasma membrane.
Chaimayo, Chutikarn; Hayashi, Tsuyoshi; Underwood, Andrew; Hodges, Erin; Takimoto, Toru
Influenza A viruses contain eight single-stranded, negative-sense RNA segments as viral genomes in the form of viral ribonucleoproteins (vRNPs). During genome replication in the nucleus, positive-sense complementary RNPs (cRNPs) are produced as replicative intermediates, which are not incorporated into progeny virions. To analyze the mechanism of selective vRNP incorporation into progeny virions, we quantified vRNPs and cRNPs in the nuclear and cytosolic fractions of infected cells, using a strand-specific qRT-PCR. Unexpectedly, we found that cRNPs were also exported to the cytoplasm. This export was chromosome region maintenance 1 (CRM1)-independent unlike that of vRNPs. Although both vRNPs and cRNPs were present in the cytosol, viral matrix (M1) protein, a key regulator for viral assembly, preferentially bound vRNPs over cRNPs. These results indicate that influenza A viruses selectively uptake cytosolic vRNPs through a specific interaction with M1 during viral assembly. - Highlights: •Influenza cRNPs are exported from the nucleus of an infected cell via a CRM1-independent pathway. •Influenza A viruses selectively incorporate cytosolic vRNPs through a specific interaction with M1 during viral assembly. •M1 dissociates from vRNP export complex after nuclear export, and is re-associated with vRNPs at the plasma membrane.
Full Text Available Retinitis pigmentosa (RP is a highly heterogeneous genetic visual disorder with more than 70 known causative genes, some of them shared with other non-syndromic retinal dystrophies (e.g. Leber congenital amaurosis, LCA. The identification of RP genes has increased steadily during the last decade, and the 30% of the cases that still remain unassigned will soon decrease after the advent of exome/genome sequencing. A considerable amount of genetic and functional data on single RD genes and mutations has been gathered, but a comprehensive view of the RP genes and their interacting partners is still very fragmentary. This is the main gap that needs to be filled in order to understand how mutations relate to progressive blinding disorders and devise effective therapies.We have built an RP-specific network (RPGeNet by merging data from different sources: high-throughput data from BioGRID and STRING databases, manually curated data for interactions retrieved from iHOP, as well as interactions filtered out by syntactical parsing from up-to-date abstracts and full-text papers related to the RP research field. The paths emerging when known RP genes were used as baits over the whole interactome have been analysed, and the minimal number of connections among the RP genes and their close neighbors were distilled in order to simplify the search space.In contrast to the analysis of single isolated genes, finding the networks linking disease genes renders powerful etiopathological insights. We here provide an interactive interface, RPGeNet, for the molecular biologist to explore the network centered on the non-syndromic and syndromic RP and LCA causative genes. By integrating tissue-specific expression levels and phenotypic data on top of that network, a more comprehensive biological view will highlight key molecular players of retinal degeneration and unveil new RP disease candidates.
van Haaften, Gijs; Vastenhouw, Nadine L; Nollen, Ellen A A; Plasterk, Ronald H A; Tijsterman, Marcel
Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect
Mark D Alter
Full Text Available A causal role of mutations in multiple general transcription factors in neurodevelopmental disorders including autism suggested that alterations in global levels of gene expression regulation might also relate to disease risk in sporadic cases of autism. This premise can be tested by evaluating for changes in the overall distribution of gene expression levels. For instance, in mice, variability in hippocampal-dependent behaviors was associated with variability in the pattern of the overall distribution of gene expression levels, as assessed by variance in the distribution of gene expression levels in the hippocampus. We hypothesized that a similar change in variance might be found in children with autism. Gene expression microarrays covering greater than 47,000 unique RNA transcripts were done on RNA from peripheral blood lymphocytes (PBL of children with autism (n = 82 and controls (n = 64. Variance in the distribution of gene expression levels from each microarray was compared between groups of children. Also tested was whether a risk factor for autism, increased paternal age, was associated with variance. A decrease in the variance in the distribution of gene expression levels in PBL was associated with the diagnosis of autism and a risk factor for autism, increased paternal age. Traditional approaches to microarray analysis of gene expression suggested a possible mechanism for decreased variance in gene expression. Gene expression pathways involved in transcriptional regulation were down-regulated in the blood of children with autism and children of older fathers. Thus, results from global and gene specific approaches to studying microarray data were complimentary and supported the hypothesis that alterations at the global level of gene expression regulation are related to autism and increased paternal age. Global regulation of transcription, thus, represents a possible point of convergence for multiple etiologies of autism and other
Nimgaonkar, V L; Prasad, K M; Chowdari, K V; Severance, E G; Yolken, R H
The pathogenesis of schizophrenia is considered to be multi-factorial, with likely gene-environment interactions (GEI). Genetic and environmental risk factors are being identified with increasing frequency, yet their very number vastly increases the scope of possible GEI, making it difficult to identify them with certainty. Accumulating evidence suggests a dysregulated complement pathway among the pathogenic processes of schizophrenia. The complement pathway mediates innate and acquired immunity, and its activation drives the removal of damaged cells, autoantigens and environmentally derived antigens. Abnormalities in complement functions occur in many infectious and autoimmune disorders that have been linked to schizophrenia. Many older reports indicate altered serum complement activity in schizophrenia, though the data are inconclusive. Compellingly, recent genome-wide association studies suggest repeat polymorphisms incorporating the complement 4A (C4A) and 4B (C4B) genes as risk factors for schizophrenia. The C4A/C4B genetic associations have re-ignited interest not only in inflammation-related models for schizophrenia pathogenesis, but also in neurodevelopmental theories, because rodent models indicate a role for complement proteins in synaptic pruning and neurodevelopment. Thus, the complement system could be used as one of the 'staging posts' for a variety of focused studies of schizophrenia pathogenesis. They include GEI studies of the C4A/C4B repeat polymorphisms in relation to inflammation-related or infectious processes, animal model studies and tests of hypotheses linked to autoimmune diseases that can co-segregate with schizophrenia. If they can be replicated, such studies would vastly improve our understanding of pathogenic processes in schizophrenia through GEI analyses and open new avenues for therapy.
Jongstra, Susan; Beishuizen, Cathrien; Andrieu, Sandrine; Barbera, Mariagnese; van Dorp, Matthijs; van de Groep, Bram; Guillemont, Juliette; Mangialasche, Francesca; van Middelaar, Tessa; Moll van Charante, Eric; Soininen, Hilkka; Kivipelto, Miia; Richard, Edo
A myriad of Web-based applications on self-management have been developed, but few focus on older people. In the face of global aging, older people form an important target population for cardiovascular prevention. This article describes the full development of an interactive Internet platform for older people, which was designed for the Healthy Ageing Through Internet Counselling in the Elderly (HATICE) study. We provide recommendations to design senior-friendly Web-based applications for a new approach to multicomponent cardiovascular prevention. The development of the platform followed five phases: (1) conceptual framework; (2) platform concept and functional design; (3) platform building (software and content); (4) testing and pilot study; and (5) final product. We performed a meta-analysis, reviewed guidelines for cardiovascular diseases, and consulted end users, experts, and software developers to create the platform concept and content. The software was built in iterative cycles. In the pilot study, 41 people aged ≥65 years used the platform for 8 weeks. Participants used the interactive features of the platform and appreciated the coach support. During all phases adjustments were made to incorporate all improvements from the previous phases. The final platform is a personal, secured, and interactive platform supported by a coach. When carefully designed, an interactive Internet platform is acceptable and feasible for use by older people with basic computer skills. To improve acceptability by older people, we recommend involving the end users in the process of development, to personalize the platform and to combine the application with human support. The interactive HATICE platform will be tested for efficacy in a multinational randomized controlled trial (ISRCTN48151589).
Ortega, Ángeles; Berná, Genoveva; Rojas, Anabel; Martín, Franz; Soria, Bernat
Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM. PMID:28574454
Foulger, R E; Osumi-Sutherland, D; McIntosh, B K; Hulo, C; Masson, P; Poux, S; Le Mercier, P; Lomax, J
The Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms. To address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms. Building on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.
Dato, Serena; De Rango, Francesco; Crocco, Paolina; Passarino, Giuseppe; Rose, Giuseppina
Oxidative stress is a major determinant of human aging and common hallmark of age-related diseases. A protective role against free radicals accumulation was shown for thioredoxin reductase TrxR1, a key antioxidant selenoprotein. The variability of encoding gene (TXNRD1) was previously found associated with physical status at old age and extreme survival in a Danish cohort. To further investigate the influence of the gene variability on age-related physiological decline, we analyzed 9 tagging SNPs in relation to markers of physical (Activity of Daily Living, Hand Grip, Chair stand, and Walking) and cognitive (Mini Mental State Examination) status, in a Southern-Italian cohort of 64-107 aged individuals. We replicated the association of TXNRD1 variability with physical performance, with three variants (rs4445711, rs1128446, and rs11111979) associated with physical functioning after 85 years of age (p longevity (rs4964728 and rs7310505) in our cohort, the last associated with health status and survival in Northern Europeans too. Overall, the evidences of association in a different population here reported extend the proposed role of TXNRD1 gene in modulating physical decline at extreme ages, further supporting the investigation of thioredoxin pathway in relation to the quality of human aging.
Aronow Bruce J
Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.
Battaglia, Marco; Marino, Cecilia; Maziade, Michel; Molteni, Massimo; D'Amato, Francesca
It has been observed that 'No aspect of human behavioral genetics has caused more confusion and generated more obscurantism than the analysis and interpretation of various types of non-additivity and non-independence of gene and environmental action and interaction' (Eaves LJ et al 1977 Br J Math Stat Psychol 30:1-42). On the other hand, a bulk of newly published studies appear to speak in favour of common and frequent interplay--and possibly interaction--between identified genetic polymorphisms and specified environmental variables in shaping behavior and behavioral disorders. Considerable interest has arisen from the introduction of putative functional 'endophenotypes' which would represent a more proximate biological link to genes, as well as an obligatory intermediate of behavior. While explicit criteria to identify valid endophenotypes have been offered, a number of new 'alternative phenotypes' are now being proposed as possible 'endophenotypes' for behavioral and psychiatric genetics research, sometimes with less than optimal stringency. Nonetheless, we suggest that some endophenotypes can be helpful in investigating several instances of gene-environment interactions and be employed as additional tools to reduce the risk for spurious results in this controversial area.
Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.
Sander, Miriam; Avlund, Kirsten; Lauritzen, Martin
of human aging. To foster interactions and collaboration between diverse scientists interested in the biochemical, physiological, epidemiological and psychosocial aspects of aging, The University of Copenhagen Faculty of Health Sciences recently organized and co-sponsored a workshop entitled Aging......-From Molecules to Populations. The following questions about human aging were discussed at the workshop: What is the limit of human life expectancy? What are the key indicators of human aging? What are the key drivers of human aging? Which genes have the greatest impact on human aging? How similar is aging...
Talbourdet, Sylvie; Sadick, Neil S; Lazou, Kristell; Bonnet-Duquennoy, Mathilde; Kurfurst, Robin; Neveu, Michele; Heusèle, Catherine; André, Patrice; Schnebert, Sylvianne; Draelos, Zoe D; Perrier, Eric
[corrected] The signs of aging may originate from natural processes or from exposure to the sun, wind, or other environmental factors. To evaluate the anti-aging effects of potential agents researchers must first identify and be able to quantify epidermal markers that change with aging. This paper summarizes the results of studies conducted to evaluate the transcriptional effects of an Aframomum angustifolium seed extract and Malva Sylvestris extract, and the antiaging efficacy of a skin care product containing the Aframomum angustifolium seed extract. The transcriptional effect of an Aframomum angustifolium seed extract on normal human keratinocytes (NHKs) and normal human fibroblasts (NHF) was evaluated in vitro with the use of a low-density DNA array technology. The Malva Sylvestris extract was studied with a commercial DNA macroarray and by a real-time quantitative reverse transcriptase-polymerase chain reaction. The in vitro anti-aging activities of the Malva sylvestris extract were compared with those of all-trans retinoic acid (RA), a well-established topical therapy for photodamage and wrinkles. The genes studied were known to be modified by RA. The anti-aging efficacy of a facial skin care product containing Aframomum angustifolium seed extract was evaluated in a single-center study using image processing analysis and in a 2-center study by evaluation of the photographs by the investigator, independent evaluators, and subjects. In general, the Aframomum angustifolium seed extract strongly modified the gene expression profiles of NHKs and weakly modified the gene expression profiles of NHFs. After incubation with Aframomum angustifolium seed extract, the expressions of 3 antioxidant genes (metallothionein 1, metallothionein 2, and thioredoxin) were increased in NHKs, while expressions of 1 antioxidant gene (glutathione peroxidase) was increased in NHFs. Concerning the Malva sylvestris extract, a cDNA macro-array technology experiment with the reconstructed
Park, Sunmin; Zhang, Xin; Lee, Na Ra; Jin, Hyun-Seok
Different transient receptor potential vanilloid 1 (TRPV1) variants may be differently activated by noxious stimuli. We investigated how TRPV1 variants modulated the prevalence of type 2 diabetes and specific gene-nutrient interactions. Among 8,842 adults aged 40-69 years in the Korean Genome Epidemiology Study, the associations between TRPV1 genotypes and the prevalence of type 2 diabetes as well as their gene-nutrient interactions were investigated after adjusting for the covariates of age, gender, residence area, body mass index, daily energy intake, and total activity. The TRPV1 rs161364 and rs8065080 minor alleles lowered HOMA-IR and the risk of type 2 diabetes after adjusting for covariates. There were gene-nutrient interactions between TRPV1 variants rs161364 and rs8065080 and preference for oily taste, intake of oily foods, and fat intake after adjusting for covariates. Among subjects with the minor alleles of TRPV1 rs161364 and rs8065080, the group with a high preference for oily foods had a lower odds ratio for type 2 diabetes. Consistent with the preference for taste, among subjects with the minor alleles, the group with high fat intake from oily foods also exhibited a lower risk of type 2 diabetes than subjects with the major alleles. People with the minor alleles of the TRPV1 single nucleotide polymorphisms rs161364 and rs8065080 have a lower risk of diabetes with a high-fat diet, but people with the major alleles are at a higher risk of type 2 diabetes when consuming high-fat diets. The majority of people should be careful about a high fat intake. © 2016 S. Karger AG, Basel.
Nagai, Taku; Ibi, Daisuke; Yamada, Kiyofumi
Schizophrenia is a devastating psychiatric disorder that impairs mental and social functioning and affects approximately 1% of the population worldwide. Genetic susceptibility factors for schizophrenia have recently been reported, some of which are known to play a role in neurodevelopment; these include neuregulin-1, dysbindin, and disrupted-in-schizophrenia 1 (DISC1). Moreover, epidemiologic studies suggest that environmental insults, such as prenatal infection and perinatal complication, are involved in the development of schizophrenia. The possible interaction between environment and genetic susceptibility factors, especially during neurodevelopment, is proposed as a promising disease etiology of schizophrenia. Polyriboinosinic-polyribocytidilic acid (polyI : C) is a synthetic analogue of double-stranded RNA that leads to the pronounced but time-limited production of pro-inflammatory cytokines. Maternal immune activation by polyI : C exposure in rodents is known to precipitate a wide spectrum of behavioral, cognitive, and pharmacological abnormalities in adult offspring. Recently, we have reported that neonatal injection of polyI : C in mice results in schizophrenia-like behavioral alterations in adulthood. In this review, we show how gene-environment interactions during neurodevelopment result in phenotypic changes in adulthood by injecting polyI : C into transgenic mice that express a dominant-negative form of human DISC1 (DN-DISC1). Our findings suggest that polyI : C-treated DN-DISC1 mice are a well-validated animal model for schizophrenia that reflects gene-environment interactions.
Full Text Available Abstract Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs have multiple cores, whereas Graphics Processing Units (GPUs also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1 the interaction of SNPs within it in parallel, and 2 the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.
Voloshanenko, Oksana; Gmach, Philipp; Winter, Jan; Kranz, Dominique; Boutros, Michael
Signaling pathway modules are often encoded by several closely related paralogous genes that can have redundant roles and are therefore difficult to analyze by loss-of-function analysis. A typical example is the Wnt signaling pathway, which in mammals is mediated by 19 Wnt ligands that can bind to 10 Frizzled (FZD) receptors. Although significant progress in understanding Wnt-FZD receptor interactions has been made in recent years, tools to generate systematic interaction maps have been largely lacking. Here we generated cell lines with multiplex mutant alleles of FZD1 , FZD2 , and FZD7 and demonstrate that these cells are unresponsive to canonical Wnt ligands. Subsequently, we performed genetic rescue experiments with combinations of FZDs and canonical Wnts to create a functional ligand-receptor interaction map. These experiments showed that whereas several Wnt ligands, such as Wnt3a, induce signaling through a broad spectrum of FZD receptors, others, such as Wnt8a, act through a restricted set of FZD genes. Together, our results map functional interactions of FZDs and 10 Wnt ligands and demonstrate how multiplex targeting by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 can be used to systematically elucidate the functions of multigene families.-Voloshanenko, O., Gmach, P., Winter, J., Kranz, D., Boutros, M. Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families. © The Author(s).
Aldarmahi, Ahmed; Elliott, Sarah; Russell, Jean; Fazeli, Alireza
The oviduct plays a crucial role in sperm storage, maintenance of sperm viability and sperm transport to the site of fertilisation. The aim of the present study was to investigate the effects of oviductal cell culture passage number, oviductal cell age and spermatozoa-oviduct coincubation times on gene expression in oviductal cells. Immortalised oviductal epithelial cells (OPEC) obtained from two different cell passages (36 and 57) were subcultured three times with and without spermatozoa for 24 h (control group). In a second study, OPEC were cocultured with spermatozoa for different time intervals (0, 4, 12 and 24 h). Expression of adrenomedullin (ADM), heat shock 70 kDa protein 8 (HSPA8) and prostaglandin E synthase (PGES) in OPEC was measured by quantitative polymerase chain reaction. The expression of ADM and HSPA8 was decreased significantly in OPEC cells from Passage 57, particularly in the later subculture group. These effects on HSPA8, but not ADM, expression in OPEC were further altered after coculture with spermatozoa for 24 h. We also demonstrated that spermatozoa-oviduct coculture for 12 and 24 h resulted in significantly higher expression of ADM, HSPA8 and PGES in OPEC. Overall, the data suggest that the OPEC lose some of their properties as a result of oviductal cell aging and that there are spermatozoa-oviduct interactions leading to increased oviductal cell gene expression.
Hühne, Rolf; Thalheim, Torsten; Sühnel, Jürgen
AgeFactDB (http://agefactdb.jenage.de) is a database aimed at the collection and integration of ageing phenotype data including lifespan information. Ageing factors are considered to be genes, chemical compounds or other factors such as dietary restriction, whose action results in a changed lifespan or another ageing phenotype. Any information related to the effects of ageing factors is called an observation and is presented on observation pages. To provide concise access to the complete information for a particular ageing factor, corresponding observations are also summarized on ageing factor pages. In a first step, ageing-related data were primarily taken from existing databases such as the Ageing Gene Database—GenAge, the Lifespan Observations Database and the Dietary Restriction Gene Database—GenDR. In addition, we have started to include new ageing-related information. Based on homology data taken from the HomoloGene Database, AgeFactDB also provides observation and ageing factor pages of genes that are homologous to known ageing-related genes. These homologues are considered as candidate or putative ageing-related genes. AgeFactDB offers a variety of search and browse options, and also allows the download of ageing factor or observation lists in TSV, CSV and XML formats. PMID:24217911
Sørensen, Mette; Nygaard, Marianne; Debrabant, Birgit
additional genes repeatedly considered as candidates for human longevity: APOE, APOA4, APOC3, ACE, CETP, HFE, IL6, IL6R, MTHFR, TGFB1, SIRTs 1, 3, 6; and HSPAs 1A, 1L, 14. Altogether, 1,049 single nucleotide polymorphisms (SNPs) were genotyped in 1,088 oldest-old (age 92-93 years) Danes and analysed......In this study we explored the association between aging-related phenotypes previously reported to predict survival in old age and variation in 77 genes from the DNA repair pathway, 32 genes from the growth hormone 1/ insulin-like growth factor 1/insulin (GH/IGF-1/INS) signalling pathway and 16...... in the relevant phenotype over time (7 years of follow-up) and none of the SNPs could be confirmed in a replication sample of 1,281 oldest-old Danes (age 94-100). Hence, our study does not support association between common variation in the investigated longevity candidate genes and aging-related phenotypes...
Full Text Available Fatty acids (FA play an integral role in brain function and alterations have been implicated in a variety of complex neurological disorders. Several recent genomic studies have highlighted genetic variability in the fatty acid desaturase (FADS1/2/3 gene cluster as an important contributor to FA alterations in serum lipids as well as measures of FA desaturase index estimated by ratios of relevant FAs. The contribution to alterations of FAs within the brain by local synthesis is still a matter of debate. Thus, the impact of genetic variants in FADS genes on gene expression and brain FA levels is an important avenue to investigate.Analyses were performed on brain tissue from prefrontal cortex Brodmann area 47 (BA47 of 61 male subjects of French Canadian ancestry ranging in age from young adulthood to middle age (18-58 years old, with the exception of one teenager (15 years old. Haplotype tagging SNPs were selected using the publicly available HapMap genotyping dataset in conjunction with Haploview. DNA sequencing was performed by the Sanger method and gene expression was measured by quantitative real-time PCR. FAs in brain tissue were analysed by gas chromatography. Variants in the FADS1 gene region were sequenced and analyzed for their influence on both FADS gene expression and FAs in brain tissue.Our results suggest an association of the minor haplotype with alteration in estimated fatty acid desaturase activity. Analysis of the impact of DNA variants on expression and alternative transcripts of FADS1 and FADS2, however, showed no differences. Furthermore, there was a significant interaction between haplotype and age on certain brain FA levels.This study suggests that genetic variability in the FADS genes cluster, previously shown to be implicated in alterations in peripheral FA levels, may also affect FA composition in brain tissue, but not likely by local synthesis.
Doelen, R.H.A. van der; Arnoldussen, I.A.C.; Ghareh, H.; Och, L. van; Homberg, J.R.; Kozicz, L.T.
The interaction between childhood maltreatment and the serotonin transporter (5-HTT) gene linked polymorphic region has been associated with increased risk to develop major depression. This Gene x Environment interaction has furthermore been linked with increased levels of anxiety and glucocorticoid
Full Text Available Objective To explore the effect of FTO gene and physical activity interaction on trunk fat percentage. Design and Methods Subjects are 3,004 individuals from Newfoundland and Labrador whose trunk fat percentage and physical activity were recorded, and who were genotyped for 11 single-nucleotide polymorphisms (SNPs in the FTO gene. Subjects were stratified by gender. Multiple tests and multiple regressions were used to analyze the effects of physical activity, variants of FTO , age, and their interactions on trunk fat percentage. Dietary information and other environmental factors were not considered. Results Higher levels of physical activity tend to reduce trunk fat percentage in all individuals. Furthermore, in males, rs9939609 and rs1421085 were significant (α = 0.05 in explaining central body fat, but no SNPs were significant in females. For highly active males, trunk fat percentage varied significantly between variants of rs9939609 and rs1421085, but there is no significant effect among individuals with low activity. The other SNPs examined were not significant in explaining trunk fat percentage. Conclusions Homozygous male carriers of non-obesity risk alleles at rs9939609 and rs1421085 will have significant reduction in central body fat from physical activity in contrast to homozygous males of the obesity-risk alleles. The additive effect of these SNPs is found in males with high physical activity only.
Biagianti, Bruno; Quraishi, Sophia H; Schlosser, Danielle A
Peer-to-peer interactions and support groups mitigate experiences of social isolation and loneliness often reported by individuals with psychotic disorders. Online peer-to-peer communication can promote broader use of this form of social support. Peer-to-peer interactions occur naturally on social media platforms, but they can negatively affect mental health. Recent digital interventions for persons with psychotic disorders have harnessed the principles of social media to incorporate peer-to-peer communication. This review examined the feasibility, acceptability, and preliminary efficacy of recent digital interventions in order to identify strategies to maximize benefits of online peer-to-peer communication for persons with psychotic disorders. An electronic database search of PubMed, EMBASE, PsycINFO, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and Health Technology Assessment Database was conducted in February 2017 and yielded a total of 1,015 results. Eight publications that reported data from six independent trials and five interventions were reviewed. The technology supporting peer-to-peer communication varied greatly across studies, from online forums to embedded social networking. When peer-to-peer interactions were moderated by facilitators, retention, engagement, acceptability, and efficacy were higher than for interventions with no facilitators. Individuals with psychotic disorders were actively engaged with moderated peer-to-peer communication and showed improvements in perceived social support. Studies involving service users in intervention design showed higher rates of acceptability. Individuals with psychotic disorders value and benefit from digital interventions that include moderated peer-to-peer interactions. Incorporating peer-to-peer communication into digital interventions for this population may increase compliance with other evidence-based therapies by producing more acceptable and engaging online environments.
Demmig-Adams, Barbara; Adams, William W
This chapter provides an overview of diet-gene interaction and the role of dietary factors in human health and disease. Human master control genes that regulate processes of fundamental importance, such as cell proliferation and the immune response, are introduced and their modulation by nutraceuticals, produced by plants and photosynthetic microbes, is reviewed. Emphasis is placed on antioxidants and polyunsaturated fatty acids as regulators of master control genes. Furthermore, a case study is presented on xanthophylls, a group of carotenoids with multiple health benefits in the protection against eye disease and other chronic diseases, as well as the synergism between xanthophylls and other dietary factors. Lastly, dietary sources of the xanthophylls zeaxanthin and lutein are reviewed and their enhancement via genetic engineering is discussed.
Su, Yousong; Ding, Wenhua; Xing, Mengjuan; Qi, Dake; Li, Zezhi; Cui, Donghong
Although previous studies showed the reduced risk of cancer in patients with schizophrenia, whether patients with schizophrenia possess genetic factors that also contribute to tumor suppressor is still unknown. In the present study, based on our previous microarray data, we focused on the tumor suppressor genes TXNIP and AF1q, which differentially expressed in patients with schizophrenia. A total of 413 patients and 578 healthy controls were recruited. We found no significant differences in genotype, allele, or haplotype frequencies at the selected five single nucleotide polymorphisms (SNPs) (rs2236566 and rs7211 in TXNIP gene; rs10749659, rs2140709, and rs3738481 in AF1q gene) between patients with schizophrenia and controls. However, we found the association between the interaction of TXNIP and AF1q with schizophrenia by using the MDR method followed by traditional statistical analysis. The best gene-gene interaction model identified was a three-locus model TXNIP (rs2236566, rs7211)-AF1q (rs2140709). After traditional statistical analysis, we found the high-risk genotype combination was rs2236566 (GG)-rs7211(CC)-rs2140709(CC) (OR = 1.35 [1.03-1.76]). The low-risk genotype combination was rs2236566 (GT)-rs7211(CC)-rs2140709(CC) (OR = 0.67 [0.49-0.91]). Our finding suggested statistically significant role of interaction of TXNIP and AF1q polymorphisms (TXNIP-rs2236566, TXNIP-rs7211, and AF1q-rs2769605) in schizophrenia susceptibility.
Full Text Available Gene-environment interactions may play an important role in modulating the impact of early-life stressful events on the clinical course of bipolar disorder (BD, particularly associated to early age at onset. Immune dysfunction is thought to be an important mechanism linking childhood trauma with early-onset BD, thus the genetic diversity of immune-related loci may account for an important part of the interindividual susceptibility to this severe subform. Here we investigated the potential interaction between genetic variants of Toll-like receptors 2 (TLR2 and 4 (TLR4, major innate immune response molecules to pathogens, and the childhood trauma questionnaire (CTQ in age at onset of BD. We recruited 531 BD patients (type I and II or not otherwise specified, genotyped for the TLR2 rs4696480 and rs3804099 and TLR4 rs1927914 and rs11536891 single-nucleotide polymorphisms and recorded for history of childhood trauma using the CTQ. TLR2 and TLR4 risk genotype carrier state and history of childhood emotional, physical and sexual abuses were evaluated in relation to age at onset as defined by the age at first manic or depressive episode. We observed a combined effect of TLR2 rs3804099 TT genotype and reported sexual abuse on determining an earlier age at onset of BD by means of a Kaplan-Meier survival curve (p = 0.002; corrected p = 0.02. Regression analysis, however, was non-significant for the TLR2-CTQ sexual abuse interaction term. The negative effects of childhood sexual abuse on age at onset of BD may be amplified in TLR2 rs3804099 risk genotype carriers through immune-mediated pathways. Clinical characteristics of illness severity, immune phenotypes and history of early life infectious insults should be included in future studies involving large patient cohorts.
Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia
DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.
Borelli, Jessica L; Smiley, Patricia A; Rasmussen, Hannah F; Gómez, Anthony; Seaman, Lauren C; Nurmi, Erika L
Attachment insecurity is influenced by both environmental and genetic factors, but few studies have examined the effects of gene-environment interactions. In the context of environmental stress, a functional variant in the glucocorticoid receptor co-chaperone FKBP5 gene has been repeatedly shown to increase risk for psychiatric illness, including depression. We expand on prior work by exploring cross-sectional attachment by gene effects on both attachment insecurity and downstream physiological and behavioral measures in a diverse community sample of school-aged children (N=99, 49% girls, M age =10.29years, 66.6% non-White) and their mothers. Specifically, we examined moderating effects of FKBP5 rs3800373 genotype on the links between parenting insensitivity (overcontrol) and child attachment. Further, we assessed whether FKBP5 moderates the links between maternal and child attachment and children's emotion regulation self-report, respiratory sinus arrhythmia (RSA) in response to a standardized laboratory stressor, and depressive symptoms. Higher levels of overcontrol predicted lower child attachment security only in FKBP5 minor allele carriers. Among children with two minor alleles (CC), attachment security was negatively associated with emotion suppression, rumination, depressive symptoms, and RSA reactivity; similarly, for these children, maternal attachment anxiety was positively associated with depressive symptoms. The findings can be conceptualized in a differential susceptibility framework, where the FKBP5 minor allele confers either risk or resilience, depending on the parenting environment. Copyright © 2016 Elsevier B.V. All rights reserved.
Havill, Lorena M; Mahaney, Michael C; L Binkley, Teresa; Specker, Bonny L
Quantitative genetic analyses of bone data for 710 inter-related individuals 8-85 yr of age found high heritability estimates for BMC, bone area, and areal and volumetric BMD that varied across bone sites. Activity levels, especially time in moderate plus vigorous activity, had notable effects on bone. In some cases, these effects were age and sex specific. Genetic and environmental factors play a complex role in determining BMC, bone size, and BMD. This study assessed the heritability of bone measures; characterized the effects of age, sex, and physical activity on bone; and tested for age- and sex-specific bone effects of activity. Measures of bone size and areal and volumetric density (aBMD and vBMD, respectively) were obtained by DXA and pQCT on 710 related individuals (466 women) 8-85 yr of age. Measures of activity included percent time in moderate + vigorous activity (%ModVig), stair flights climbed per day, and miles walked per day. Quantitative genetic analyses were conducted to model the effects of activity and covariates on bone outcomes. Accounting for effects of age, sex, and activity levels, genes explained 40-62% of the residual variation in BMC and BMD and 27-75% in bone size (all pBMC and cross-sectional area (CSA) at the 4% radius, but this was not observed among women (sex-by-activity interaction, both p
Winham, Stacey J.; Biernacka, Joanna M.
Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…
Liu, Jianmin; Liu, Jing; Wang, Guang'an; Liu, Guangya; Zhou, Huanjiao; Fan, Yun; Liang, Fengxia; Wang, Hua
To investigate the molecular mechanisms of sub-acutely aging and demonstrate the effect of electroacupuncture (EA) at the Guanyuan (CV 4), Zusanli (ST 36) and Baihui (DU 20) acupoint on the sub-acutely aging brain, cDNA microarrays and bioinformatics analyses were carried out. Thirty Sprague-Dawley (SD) male rats were selected and randomly divided into three groups: the control group (C), the sub-acutely aging model group (M) and the electroacupuncture group (M+EA). Sub-acutely aging model rats were obtained by D-galactose s.c. injection continuously for 40 days. Total RNA was extracted from the hippocampus area of brains in three groups for cDNA microarrays. The data of different groups were compared and analyzed by differential expression analysis, Gene ontology (GO) term enrichment, Kyoto Encyclopedia of Genes Genomes (KEGG) pathway enrichment and quantitative real-time PCR. According to the results, 4052 DE genes were identified in our study. Among them, there were 3079 differentially expressed (DE) genes between group M and group C, and these genes are associated with the aging of rats. Moreover, 983 genes were expressed differently in group M+EA compared with group M, revealing that points stimuli could regulate gene expression in brain with aging. Gene ontology (GO) term enrichment and KEGG enrichment were performed to further classify the differential expression genes. Important GO terms and KEGG pathways connected with sub-acutely aging EA effects were identified. At last, 3 significant differentially expressed genes were selected for real-time quantitative PCR to clarify the cDNA microarray results. In conclusion, the cDNA microarray data first compared and analyzed the differences of gene expression profile in the hippocampus of rats in different groups, which contribute to our knowledge on the molecular mechanisms of EA towards sub-acutely aging.
Full Text Available Oxidative stress is a major determinant of human aging and common hallmark of age-related diseases. A protective role against free radicals accumulation was shown for thioredoxin reductase TrxR1, a key antioxidant selenoprotein. The variability of encoding gene (TXNRD1 was previously found associated with physical status at old age and extreme survival in a Danish cohort. To further investigate the influence of the gene variability on age-related physiological decline, we analyzed 9 tagging SNPs in relation to markers of physical (Activity of Daily Living, Hand Grip, Chair stand, and Walking and cognitive (Mini Mental State Examination status, in a Southern-Italian cohort of 64–107 aged individuals. We replicated the association of TXNRD1 variability with physical performance, with three variants (rs4445711, rs1128446, and rs11111979 associated with physical functioning after 85 years of age (p<0.022. In addition, we found two SNPs borderline influencing longevity (rs4964728 and rs7310505 in our cohort, the last associated with health status and survival in Northern Europeans too. Overall, the evidences of association in a different population here reported extend the proposed role of TXNRD1 gene in modulating physical decline at extreme ages, further supporting the investigation of thioredoxin pathway in relation to the quality of human aging.
Yeh, Shu-Hui; Liu, Cheng-Ling; Chang, Ren-Chieh; Wu, Chih-Chiang; Lin, Chia-Hsueh; Yang, Kuender D
This study investigated whether aging was associated with epigenetic changes of DNA hypermethylation on immune gene expression and lymphocyte differentiation. We screened CG sites of methylation in blood leukocytes from different age populations, picked up genes with age-related increase of CG methylation content more than 15%, and validated immune related genes with CG hypermethylation involved in lymphocyte differentiation in the aged population. We found that 12 genes (EXHX1ã IL-10ã TSP50ã GSTM1ãSLC5A5ãSPI1ãF2RãLMO2ãPTPN6ãFGFR2ãMMP9ãMET) were associated with promoter or exon one DNA hypermethylation in the aged group. Two immune related genes, GSTM1 and LMO2, were chosen to validate its aging-related CG hypermethylation in different leukocytes. We are the first to validate that GSTM1_P266 and LMO2_E128 CG methylation contents in T lymphocytes but not polymorphonuclear cells (PMNs) or mononuclear cells (MNCs) were significantly increased in the aged population. The GSTM1 mRNA expression in T lymphocytes but not PMNs or MNCs was inversely associated with the GSTM1 CG hypermethylation levels in the aged population studied. Further studies showed that lower GSTM1 CG methylation content led to the higher GSTM1 mRNA expression in T cells and knockdown of GSTM1 mRNA expression decreased type 1 T helper cell (Th1) differentiation in Jurkat T cells and normal adult CD4 T cells. The GSTM1_P266 hypermethylation in the aged population associated with lower GSTM1 mRNA expression was involved in Th1 differentiation, highlighting that modulation of aging-associated GSTM1 methylation may be able to enhance T helper cell immunity in the elders.
Tohru Ikuta; Yuet Wai Kan
The authors have investigated in vivo protein-DNA interactions in the β-globin gene locus by dimethyl sulfate (DMS) footprinting in K562 cells, which express var-epsilon- and γ-globin but not β-globin. In the locus control region, hypersensitive site 2 (HS-2) exhibited footprints in several putative protein binding motifs. HS-3 was not footprinted. The β promoter was also not footprinted, while extensive footprints were observed in the promoter of the active γ-globin gene. No footprints were seen in the A γ and β3' enhancers. With several motifs, additional protein interactions and alterations in binding patterns occurred with hemin induction. In HeLa cells, some footprints were observed in some of the motifs in HS-2, compatible with the finding that HS-2 has some enhancer function in HeLa cells, albeit much weaker than its activity in K562 cells. No footprint was seen in B lymphocytes. In vivo footprinting is a useful method for studying relevant protein-DNA interactions in erythroid cells
Microglia Polarization, Gene-Environment Interactions and Wnt/β-Catenin Signaling: Emerging Roles of Glia-Neuron and Glia-Stem/Neuroprogenitor Crosstalk for Dopaminergic Neurorestoration in Aged Parkinsonian Brain
Full Text Available Neuroinflammatory processes are recognized key contributory factors in Parkinson's disease (PD physiopathology. While the causes responsible for the progressive loss of midbrain dopaminergic (mDA neuronal cell bodies in the subtantia nigra pars compacta are poorly understood, aging, genetics, environmental toxicity, and particularly inflammation, represent prominent etiological factors in PD development. Especially, reactive astrocytes, microglial cells, and infiltrating monocyte-derived macrophages play dual beneficial/harmful effects, via a panel of pro- or anti-inflammatory cytokines, chemokines, neurotrophic and neurogenic transcription factors. Notably, with age, microglia may adopt a potent neurotoxic, pro-inflammatory “primed” (M1 phenotype when challenged with inflammatory or neurotoxic stimuli that hamper brain's own restorative potential and inhibit endogenous neurorepair mechanisms. In the last decade we have provided evidence for a major role of microglial crosstalk with astrocytes, mDA neurons and neural stem progenitor cells (NSCs in the MPTP- (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine- mouse model of PD, and identified Wnt/β-catenin signaling, a pivotal morphogen for mDA neurodevelopment, neuroprotection, and neuroinflammatory modulation, as a critical actor in glia-neuron and glia-NSCs crosstalk. With age however, Wnt signaling and glia-NSC-neuron crosstalk become dysfunctional with harmful consequences for mDA neuron plasticity and repair. These findings are of importance given the deregulation of Wnt signaling in PD and the emerging link between most PD related genes, Wnt signaling and inflammation. Especially, in light of the expanding field of microRNAs and inflammatory PD-related genes as modulators of microglial-proinflammatory status, uncovering the complex molecular circuitry linking PD and neuroinflammation will permit the identification of new druggable targets for the cure of the disease. Here we summarize
Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James
networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional
Trigos, Anna S; Pearson, Richard B; Papenfuss, Anthony T; Goode, David L
Tumors of distinct tissues of origin and genetic makeup display common hallmark cellular phenotypes, including sustained proliferation, suppression of cell death, and altered metabolism. These phenotypic commonalities have been proposed to stem from disruption of conserved regulatory mechanisms evolved during the transition to multicellularity to control fundamental cellular processes such as growth and replication. Dating the evolutionary emergence of human genes through phylostratigraphy uncovered close association between gene age and expression level in RNA sequencing data from The Cancer Genome Atlas for seven solid cancers. Genes conserved with unicellular organisms were strongly up-regulated, whereas genes of metazoan origin were primarily inactivated. These patterns were most consistent for processes known to be important in cancer, implicating both selection and active regulation during malignant transformation. The coordinated expression of strongly interacting multicellularity and unicellularity processes was lost in tumors. This separation of unicellular and multicellular functions appeared to be mediated by 12 highly connected genes, marking them as important general drivers of tumorigenesis. Our findings suggest common principles closely tied to the evolutionary history of genes underlie convergent changes at the cellular process level across a range of solid cancers. We propose altered activity of genes at the interfaces between multicellular and unicellular regions of human gene regulatory networks activate primitive transcriptional programs, driving common hallmark features of cancer. Manipulation of cross-talk between biological processes of different evolutionary origins may thus present powerful and broadly applicable treatment strategies for cancer.
Su, Shih-Heng; Krysan, Patrick J
Mitogen-activated protein kinase cascades are conserved in all eukaryotes. In Arabidopsis thaliana there are approximately 80 genes encoding MAP kinase kinase kinases (MAP3K), 10 genes encoding MAP kinase kinases (MAP2K), and 20 genes encoding MAP kinases (MAPK). Reverse genetic analysis has failed to reveal abnormal phenotypes for a majority of these genes. One strategy for uncovering gene function when single-mutant lines do not produce an informative phenotype is to perform a systematic genetic interaction screen whereby double-mutants are created from a large library of single-mutant lines. Here we describe a new collection of 275 double-mutant lines derived from a library of single-mutants targeting genes related to MAP kinase signaling. To facilitate this study, we developed a high-throughput double-mutant generating pipeline using a system for growing Arabidopsis seedlings in 96-well plates. A quantitative root growth assay was used to screen for evidence of genetic interactions in this double-mutant collection. Our screen revealed four genetic interactions, all of which caused synthetic enhancement of the root growth defects observed in a MAP kinase 4 (MPK4) single-mutant line. Seeds for this double-mutant collection are publicly available through the Arabidopsis Biological Resource Center. Scientists interested in diverse biological processes can now screen this double-mutant collection under a wide range of growth conditions in order to search for additional genetic interactions that may provide new insights into MAP kinase signaling. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.
Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand
Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.
Cao, HuanHuan; Zhang, YuHang; Zhao, Jia; Zhu, Liucun; Wang, Yi; Li, JiaRui; Feng, Yuan-Ming; Zhang, Ning
Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm. We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes. Copyright© Bentham Science Publishers; For any queries, please email at email@example.com.
Russell, Michael; Berardi, Philip; Gong Wei; Riabowol, Karl
The INhibitor of Growth (ING) family of plant homeodomain (PHD) proteins induce apoptosis and regulate gene expression through stress-inducible binding of phospholipids with subsequent nuclear and nucleolar localization. Relocalization occurs concomitantly with interaction with a subset of nuclear proteins, including PCNA, p53 and several regulators of acetylation such as the p300/CBP and PCAF histone acetyltransferases (HATs), as well as the histone deacetylases HDAC1 and hSir2. These interactions alter the localized state of chromatin compaction, subsequently affecting the expression of subsets of genes, including those associated with the stress response (Hsp70), apoptosis (Bax, MDM2) and cell cycle regulation (p21 WAF1 , cyclin B) in a cell- and tissue-specific manner. The expression levels and subcellular localization of ING proteins are altered in a significant number of human cancer types, while the expression of ING isoforms changes during cellular aging, suggesting that ING proteins may play a role in linking cellular transformation and replicative senescence. The variety of functions attributed to ING proteins suggest that this tumor suppressor serves to link the disparate processes of cell cycle regulation, cell suicide and cellular aging through epigenetic regulation of gene expression. This review examines recent findings in the ING field with a focus on the functions of protein-protein interactions involving ING family members and the mechanisms by which these interactions facilitate the various roles that ING proteins play in tumorigenesis, apoptosis and senescence
Lissner, Michelle M; Thomas, Brandon J; Wee, Kathleen; Tong, Ann-Jay; Kollmann, Tobias R; Smale, Stephen T
A variety of age-related differences in the innate and adaptive immune systems have been proposed to contribute to the increased susceptibility to infection of human neonates and older adults. The emergence of RNA sequencing (RNA-seq) provides an opportunity to obtain an unbiased, comprehensive, and quantitative view of gene expression differences in defined cell types from different age groups. An examination of ex vivo human monocyte responses to lipopolysaccharide stimulation or Listeria monocytogenes infection by RNA-seq revealed extensive similarities between neonates, young adults, and older adults, with an unexpectedly small number of genes exhibiting statistically significant age-dependent differences. By examining the differentially induced genes in the context of transcription factor binding motifs and RNA-seq data sets from mutant mouse strains, a previously described deficiency in interferon response factor-3 activity could be implicated in most of the differences between newborns and young adults. Contrary to these observations, older adults exhibited elevated expression of inflammatory genes at baseline, yet the responses following stimulation correlated more closely with those observed in younger adults. Notably, major differences in the expression of constitutively expressed genes were not observed, suggesting that the age-related differences are driven by environmental influences rather than cell-autonomous differences in monocyte development.
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
Etter, Franziska; Knechtle, Beat; Bukowski, Arkadiusz; Rüst, Christoph Alexander; Rosemann, Thomas; Lepers, Romuald
This study investigated the participation and performance trends as well as the age and gender interaction at the Olympic distance 'Zürich Triathlon' (1.5 km swim, 40 km cycle and 10 km run) from 2000 to 2010 in 7,939 total finishers (1,666 females and 6,273 males). Female triathletes aged from 40 to 54 years significantly (P distance triathlon performance increased after the age of 35 years, which appeared earlier compared to long distance triathlon as suggested by previous studies. Future investigations should compare gender difference in performance for different endurance events across age to confirm a possible effect of exercise duration on gender difference with advancing age.
Laura A Nucci
Full Text Available Sepsis is a complex disease that is characterized by activation and inhibition of different cell signaling pathways according to the disease stage. Here, we evaluated genes involved in the TLR signaling pathway, oxidative phosphorylation and oxidative metabolism, aiming to assess their interactions and resulting cell functions and pathways that are disturbed in septic patients.Blood samples were obtained from 16 patients with sepsis secondary to community acquired pneumonia at admission (D0, and after 7 days (D7, N = 10 of therapy. Samples were also collected from 8 healthy volunteers who were matched according to age and gender. Gene expression of 84 genes was performed by real-time polymerase chain reactions. Their expression was considered up- or down-regulated when the fold change was greater than 1.5 compared to the healthy volunteers. A p-value of ≤ 0.05 was considered significant.Twenty-two genes were differently expressed in D0 samples; most of them were down-regulated. When gene expression was analyzed according to the outcomes, higher number of altered genes and a higher intensity in the disturbance was observed in non-survivor than in survivor patients. The canonical pathways altered in D0 samples included interferon and iNOS signaling; the role of JAK1, JAK2 and TYK2 in interferon signaling; mitochondrial dysfunction; and superoxide radical degradation pathways. When analyzed according to outcomes, different pathways were disturbed in surviving and non-surviving patients. Mitochondrial dysfunction, oxidative phosphorylation and superoxide radical degradation pathway were among the most altered in non-surviving patients.Our data show changes in the expression of genes belonging to the interacting TLR cascades, NADPH-oxidase and oxidative phosphorylation. Importantly, distinct patterns are clearly observed in surviving and non-surviving patients. Interferon signaling, marked by changes in JAK-STAT modulation, had prominent changes in
Wang, Ke-Sheng; Wang, Liang; Liu, Xuefeng; Zeng, Min
The heparan sulfate 6-O-sulfotransferase 3 (HS6ST3) gene is involved in heparan sulphate and heparin metabolism, and has been reported to be associated with diabetic retinopathy in type 2 diabetes.We hypothesized that HS6ST3 gene polymorphisms might play an important role in obesity and related phenotypes (such as triglycerides). We examined genetic associations of 117 single-nucleotide polymorphisms (SNPs) within the HS6ST3 gene with obesity and triglycerides using two Caucasian samples: the Marshfield sample (1442 obesity cases and 2122 controls), and the Health aging and body composition (Health ABC) sample (305 cases and 1336 controls). Logistic regression analysis of obesity as a binary trait and linear regression analysis of triglycerides as a continuous trait, adjusted for age and sex, were performed using PLINK. Single marker analysis showed that six SNPs in the Marshfield sample and one SNP in the Health ABC sample were associated with obesity (P triglycerides in the Marshfield sample (P triglycerides in the Marshfield sample. These findings contribute new insights into the pathogenesis of obesity and triglycerides and demonstrate the importance of gender differences in the aetiology.
Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2dfcoffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that
Hamza, Taye H; Chen, Honglei; Hill-Burns, Erin M; Rhodes, Shannon L; Montimurro, Jennifer; Kay, Denise M; Tenesa, Albert; Kusel, Victoria I; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M; Kendler, Kenneth S; Bacanu, Silviu-Alin; Scott, William K; Ritz, Beate; Nutt, John; Factor, Stewart A; Zabetian, Cyrus P; Payami, Haydeh
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df) = 10(-6), GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7)) but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication) = 0.59, P(Replication) = 10(-3); OR(Pooled) = 0.51, P(Pooled) = 7×10(-8). Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3)), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13)). Imputation revealed a block of SNPs that achieved P(2df)coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify
Full Text Available Abstract Background Age-related gene expression patterns of Homo sapiens as well as of model organisms such as Mus musculus, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster are a basis for understanding the genetic mechanisms of ageing. For an effective analysis and interpretation of expression profiles it is necessary to store and manage huge amounts of data in an organized way, so that these data can be accessed and processed easily. Description GiSAO.db (Genes involved in senescence, apoptosis and oxidative stress database is a web-based database system for storing and retrieving ageing-related experimental data. Expression data of genes and miRNAs, annotation data like gene identifiers and GO terms, orthologs data and data of follow-up experiments are stored in the database. A user-friendly web application provides access to the stored data. KEGG pathways were incorporated and links to external databases augment the information in GiSAO.db. Search functions facilitate retrieval of data which can also be exported for further processing. Conclusions We have developed a centralized database that is very well suited for the management of data for ageing research. The database can be accessed at https://gisao.genome.tugraz.at and all the stored data can be viewed with a guest account.
Full Text Available Ischemic stroke (IS is a multifactorial disorder caused by both genetic and environmental factors. The combined effects of multiple susceptibility genes might result in a higher risk for IS than a single gene. Therefore, we investigated whether interactions among multiple susceptibility genes were associated with an increased risk of IS by evaluating gene polymorphisms identified in previous meta-analyses, including methylenetetrahydrofolate reductase (MTHFR C677T, beta fibrinogen (FGB, β-FG A455G and T148C, apolipoprotein E (APOE ε2-4, angiotensin-converting enzyme (ACE insertion/deletion (I/D, and endothelial nitric oxide synthase (eNOS G894T. In order to examine these interactions, 712 patients with IS and 774 controls in a Chinese Han population were genotyped using the SNaPshot method, and multifactor dimensionality reduction analysis was used to detect potential interactions among the candidate genes. The results of this study found that ACE I/D and β-FG T148C were significant synergistic contributors to IS. In particular, the ACE DD + β-FG 148CC, ACE DD + β-FG 148CT, and ACE ID + β-FG 148CC genotype combinations resulted in higher risk of IS. After adjusting for potential confounding IS risk factors (age, gender, family history of IS, hypertension history and history of diabetes mellitus using a logistic analysis, a significant correlation between the genotype combinations and IS patients persisted (overall stroke: adjusted odds ratio [OR] = 1.57, 95% confidence interval [CI]: 1.22-2.02, P < 0.001, large artery atherosclerosis subtype: adjusted OR = 1.50, 95% CI: 1.08-2.07, P = 0.016, small-artery occlusion subtype: adjusted OR = 2.04, 95% CI: 1.43-2.91, P < 0.001. The results of this study indicate that the ACE I/D and β-FG T148C combination may result in significantly higher risk of IS in this Chinese population.
Osgood, Doreen; Miller, Miles C; Messier, Arthur A; Gonzalez, Liliana; Silverberg, Gerald D
Decreased clearance of potentially toxic metabolites, due to aging changes, likely plays a significant role in the accumulation of amyloid-beta (Aβ) peptides and other macromolecules in the brain of the elderly and in the patients with Alzheimer's disease (AD). Aging is the single most important risk factor for AD development. Aβ transport receptor proteins expressed at the blood-brain barrier are significantly altered with age: the efflux transporters lipoprotein receptor-related protein 1 and P-glycoprotein are reduced, whereas the influx transporter receptor for advanced glycation end products is increased. These receptors play an important role in maintaining brain biochemical homeostasis. We now report that, in a rat model of aging, gene transcription is altered in aging, as measured by Aβ receptor gene messenger RNA (mRNA) at 3, 6, 9, 12, 15, 20, 30, and 36 months. Gene mRNA expression from isolated cerebral microvessels was measured by quantitative polymerase chain reaction. Lipoprotein receptor-related protein 1 and P-glycoprotein mRNA were significantly reduced in aging, and receptor for advanced glycation end products was increased, in parallel with the changes seen in receptor protein expression. Transcriptional changes appear to play a role in aging alterations in blood-brain barrier receptor expression and Aβ accumulation. Copyright © 2017 Elsevier Inc. All rights reserved.
Tucker, George; Loh, Po-Ru; Berger, Bonnie
Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely
D'Souza, Mary; Zhu, Xiaoxia; Frisina, Robert D.
Presbycusis – age-related hearing loss – is the number one communicative disorder and one of the top three chronic medical condition of our aged population. High-throughput technologies potentially can be used to identify differentially expressed genes that may be better diagnostic and therapeutic targets for sensory and neural disorders. Here we analyzed gene expression for a set of GABA receptors in the cochlea of aging CBA mice using the Affymetrix GeneChip MOE430A. Functional phenotypic hearing measures were made, including auditory brainstem response (ABR) thresholds and distortion-product otoacoustic emission (DPOAE) amplitudes (four age groups). Four specific criteria were used to assess gene expression changes from RMA normalized microarray data (40 replicates). Linear regression models were used to fit the neurophysiological hearing measurements to probe-set expression profiles. These data were first subjected to one-way ANOVA, and then linear regression was performed. In addition, the log signal ratio was converted to fold change, and selected gene expression changes were confirmed by relative real-time PCR. Major findings: expression of GABA-A receptor subunit α6 was upregulated with age and hearing loss, whereas subunit α1 was repressed. In addition, GABA-A receptor associated protein like-1 and GABA-A receptor associated protein like-2 were strongly downregulated with age and hearing impairment. Lastly, gene expression measures were correlated with pathway/network relationships relevant to the inner ear using Pathway Architect, to identify key pathways consistent with the gene expression changes observed. PMID:18455804
de Andrade, Fabiana M; Bulhões, Andréa C; Maluf, Sharbel W; Schuch, Jaqueline B; Voigt, Francine; Lucatelli, Juliana F; Barros, Alessandra C; Hutz, Mara H
Nutrigenetics is a new field with few studies in Latin America. Our aim is to investigate the way in which different genes related to the lipid profile influence the response to specific dietary habits. Eight polymorphisms on seven genes were investigated in a sample (n = 567) from Porto Alegre, RS, Brazil. All the volunteers completed a food diary that was then assessed and classified into nine food groups. A number of nutrigenetic interactions were detected primarily related to the apolipoprotein E (apoE) gene. For example, frequent consumption of foods rich in polyunsaturated fat resulted in the beneficial effect of increasing HDL-C only in individuals who were not carriers of the E*4 allele of the APOE gene, whereas variations in eating habits of E*4 carriers did not affect their HDL-C (P = 0.018). Our data demonstrate for the first time nutrigenetic interactions in a Brazilian population.
Primiani, Christopher T; Ryan, Veronica H; Rao, Jagadeesh S; Cam, Margaret C; Ahn, Kwangmi; Modi, Hiren R; Rapoport, Stanley I
Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks that operate
Zhu Xiaodong; Guo Ya; Qu Song; Li Ling; Huang Shiting; Li Danrong; Zhang Wei
Objective: To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods: Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results: Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions: The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. (authors)
Yang, Po-Yu; Miao, Nae-Fang; Lin, Chiao-Wen; Chou, Ying-Erh; Yang, Shun-Fa; Huang, Hui-Chuan; Chang, Hsiu-Ju; Tsai, Hsiu-Ting
The purpose of this study was to identify gene polymorphisms of mammary serine protease inhibitor (Maspin) specific to patients with oral cancer susceptibility and clinicopathological status. Three single-nucleotide polymorphisms (SNPs) of the Maspin gene from 741 patients with oral cancer and 601 non-cancer controls were analyzed by real-time PCR. The participants with G/G homozygotes or with G/C heterozygotes of Maspin rs2289520 polymorphism had a 2.07-fold (p = 0.01) and a 2.01-fold (p = 0.02) risk of developing oral cancer compared to those with C/C homozygotes. Moreover, gene-gene interaction increased the risk of oral cancer susceptibility among subjects expose to oral cancer related risk factors, including areca, alcohol, and tobacco consumption. G allele of Maspin rs2289520 polymorphism may be a factor that increases the susceptibility to oral cancer. The interactions of gene to oral cancer-related environmental risk factors have a synergetic effect that can further enhance oral cancer development.
Mota, R R; Guimarães, S E F; Fortes, M R S; Hayes, B; Silva, F F; Verardo, L L; Kelly, M J; de Campos, C F; Guimarães, J D; Wenceslau, R R; Penitente-Filho, J M; Garcia, J F; Moore, S
We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken. © 2017 Blackwell Verlag GmbH.
Full Text Available Abstract Background As part of the NHLBI Family Blood Pressure Program, the Genetic Epidemiology Network of Arteriopathy (GENOA recruited 575 sibships (n = 1583 individuals from Rochester, MN who had at least two hypertensive siblings diagnosed before age 60. Linkage analysis identified a region on chromosome 2 that was investigated using 70 single nucleotide polymorphisms (SNPs typed in 7 positional candidate genes, including adducin 2 (ADD2. Method To investigate whether blood pressure (BP levels in these hypertensives (n = 1133 were influenced by gene-by-drug interactions, we used cross-validation statistical methods (i.e., estimating a model for predicting BP levels in one subgroup and testing it in a different subgroup. These methods greatly reduced the chance of false positive findings. Results Eight SNPs in ADD2 were significantly associated with systolic BP in untreated hypertensives (p-value Conclusion Our findings suggest that hypertension candidate gene variation may influence BP responses to specific antihypertensive drug therapies and measurement of genetic variation may assist in identifying subgroups of hypertensive patients who will benefit most from particular antihypertensive drug therapies.
Koppik, Mareike; Fricke, Claudia
Senescence is accompanied by loss of reproductive functions. Here, we studied reproductive ageing in Drosophila melanogaster males and asked whether the expected decline in male reproductive success is due to diminished functionality of the male accessory gland (AG). The male AG produces the majority of seminal fluid proteins (SFPs) transferred to the female at mating. SFPs induce female postmating changes and are key to male reproductive success. We measured age-dependent gene expression changes for five representative SFP genes in males from four different age groups ranging from 1 to 6 weeks after eclosion. Simultaneously, we also measured male reproductive success in postmating traits mediated by transfer of these five SFPs. We found a decreased in male SFP gene expression with advancing age and an accompanying decline in male postmating success. Hence, male reproductive senescence is associated with a decline in functionality of the male AG. While overall individual SFP genes decreased in expression, our results point towards the idea that the composition of an ejaculate might change with male age as the rate of change was variable for those five genes. © 2017 John Wiley & Sons Ltd.
Full Text Available Epistasis (gene-gene interaction is a ubiquitous component of the genetic architecture of complex traits such as susceptibility to common human diseases. Given the strong negative correlation between circulating adiponectin and resistin levels, the potential intermolecular epistatic interactions between ADIPOQ (SNP+45T > G, SNP+276G > T, SNP+639T > C and SNP+1212A > G and RETN (SNP-420C > G and SNP+299G > A gene polymorphisms in the genetic risk underlying type 2 diabetes (T2DM and metabolic syndrome (MS were assessed. The potential mutual influence of the ADIPOQ and RETN genes on their adipokine levels was also examined. The rare homozygous genotype (risk alleles of SNP-420C > G at the RETN locus tended to be co-inherited together with the common homozygous genotypes (protective alleles of SNP+639T > C and SNP+1212A > G at the ADIPOQ locus. Despite the close structural relationship between the ADIPOQ and RETN genes, there was no evidence of an intermolecular epistatic interaction between these genes. There was also no reciprocal effect of the ADIPOQ and RETN genes on their adipokine levels, i.e., ADIPOQ did not affect resistin levels nor did RETN affect adiponectin levels. The possible influence of the ADIPOQ gene on RETN expression warrants further investigation.
Pinto, Márcia Ferreira Teixeira; Steffen, Ricardo; Entringer, Aline; Costa, Ana Carolina Carioca da; Trajman, Anete
The study aimed to estimate the budget impact of GeneXpert MTB/RIF for diagnosis of tuberculosis from the perspective of the Brazilian National Program for Tuberculosis Control, drawing on a static model using the epidemiological method, from 2013 to 2017. GeneXpert MTB/RIF was compared with two diagnostic sputum smear tests. The study used epidemiological, population, and cost data, exchange rates, and databases from the Brazilian Unified National Health System. Sensitivity analysis of scenarios was performed. Incorporation of GeneXpert MTB/RIF would cost BRL 147 million (roughly USD 45 million) in five years and would have an impact of 23 to 26% in the first two years and some 11% between 2015 and 2017. The results can support Brazilian and other Latin American health administrators in planning and managing the decision on incorporating the technology.
Full Text Available Abstract Background The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. Results By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17% showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. Conclusion An
Full Text Available The genes FTO and GNB3 are implicated in essential hypertension but their interaction remains to be explored. This study investigates the role of interaction between the two genes in the pathophysiology of essential hypertension.In a case-control study comprising 750 controls and 550 patients, interaction between the polymorphisms of FTO and GNB3 was examined using multifactor dimensionality reduction (MDR. The influence of interaction on clinical phenotypes like systolic and diastolic blood pressure, mean arterial pressure and body mass index was also investigated. The 3-locus MDR model comprising FTO rs8050136C/A and GNB3 rs1129649T/C and rs5443C/T emerged as the best disease conferring model. Moreover, the interacted-genotypes having either 1, 2, 3, 4 or 5 risk alleles correlated with linearly increasing odds ratios of 1.91 (P = 0.027; 3.93 (P = 2.08E-06; 4.51 (P = 7.63E-07; 7.44 (P = 3.66E-08 and 11.57 (P = 1.18E-05, respectively, when compared with interacted-genotypes devoid of risk alleles. Furthermore, interactions among haplotypes of FTO (H1-9 and GNB3 (Ha-d differed by >1.5-fold for protective-haplotypes, CTGGC+TC [H2+Ha] and CTGAC+TC [H4+Ha] (OR = 0.39, P = 0.003; OR = 0.22, P = 6.86E-05, respectively and risk-haplotypes, AAAGC+CT [H3+Hc] and AAAGC+TT [H3+Hd] (OR = 2.91, P = 9.98E-06; OR = 2.50, P = 0.004, respectively compared to individual haplotypes. Moreover, the effectiveness of gene-gene interaction was further corroborated with a 1.29-, 1.25- and 1.38-fold higher SBP, MAP and BMI, respectively, in patients having risk interacted-haplotype H3+Hc and 2.48-fold higher SBP having risk interacted-haplotype H3+Hd compared to individual haplotypes.Interactions between genetic variants of FTO and GNB3 influence clinical parameters to augment hypertension.
Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro
For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p relation to gene-environment interactions in the prevention of CRC.
Tucker, A S; Al Khamis, A; Sharpe, P T
Tooth development is regulated by a reciprocal series of epithelial-mesenchymal interactions. Bmp4 has been identified as a candidate signalling molecule in these interactions, initially as an epithelial signal and then later at the bud stage as a mesenchymal signal (Vainio et al.  Cell 75:45-58). A target gene for Bmp4 signalling is the homeobox gene Msx-1, identified by the ability of recombinant Bmp4 protein to induce expression in mesenchyme. There is, however, no evidence that Bmp4 is the endogenous inducer of Msx-1 expression. Msx-1 and Bmp-4 show dynamic, interactive patterns of expression in oral epithelium and ectomesenchyme during the early stages of tooth development. In this study, we compare the temporal and spatial expression of these two genes to determine whether the changing expression patterns of these genes are consistent with interactions between the two molecules. We show that changes in Bmp-4 expression precede changes in Msx-1 expression. At embryonic day (E)10.5-E11.0, expression patterns are consistent with BMP4 from the epithelium, inducing or maintaining Msx-1 in underlying mesenchyme. At E11.5, Bmp-4 expression shifts from epithelium to mesenchyme and is rapidly followed by localised up-regulation of Msx-1 expression at the sites of Bmp-4 expression. Using cultured explants of developing mandibles, we confirm that exogenous BMP4 is capable of replacing the endogenous source in epithelium and inducing Msx-1 gene expression in mesenchyme. By using noggin, a BMP inhibitor, we show that endogenous Msx-1 expression can be inhibited at E10.5 and E11.5, providing the first evidence that endogenous Bmp-4 from the epithelium is responsible for regulating the early spatial expression of Msx-1. We also show that the mesenchymal shift in Bmp-4 is responsible for up-regulating Msx-1 specifically at the sites of future tooth formation. Thus, we establish that a reciprocal series of interactions act to restrict expression of both genes to future
Baur, Brittany; Bozdag, Serdar
One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.
S. Pamela K. Shiao
Full Text Available For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene–environment interactions and predictors of colorectal cancer (CRC by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black. We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05, on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05 except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike’s information criterion and leave-one-out cross validation methods. Body mass index (BMI and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene–environment interactions in the prevention of CRC.
Umek, Ljubica Marjanovic; Lesnik, Petra
This study compared the social interaction and types of symbolic play found in mixed-age and same-age preschool groups. The sample included 8 groups of 14 to 20 children, which were naturally formed and had been operating since the beginning of the school year. The four same-age groups included a group of 3- to 4-year-olds, a group of 4- to…
Araújo, Welington Luiz; Santos, Daiene Souza; Dini-Andreote, Francisco; Salgueiro-Londoño, Jennifer Katherine; Camargo-Neves, Aline Aparecida; Andreote, Fernando Dini; Dourado, Manuella Nóbrega
The genus Methylobacterium is composed of pink-pigmented methylotrophic bacterial species that are widespread in natural environments, such as soils, stream water and plants. When in association with plants, this genus colonizes the host plant epiphytically and/or endophytically. This association is known to promote plant growth, induce plant systemic resistance and inhibit plant infection by phytopathogens. In the present study, we focused on evaluating the colonization of soybean seedling-roots by Methylobacterium mesophilicum strain SR1.6/6. We focused on the identification of the key genes involved in the initial step of soybean colonization by methylotrophic bacteria, which includes the plant exudate recognition and adaptation by planktonic bacteria. Visualization by scanning electron microscopy revealed that M. mesophilicum SR1.6/6 colonizes soybean roots surface effectively at 48 h after inoculation, suggesting a mechanism for root recognition and adaptation before this period. The colonization proceeds by the development of a mature biofilm on roots at 96 h after inoculation. Transcriptomic analysis of the planktonic bacteria (with plant) revealed the expression of several genes involved in membrane transport, thus confirming an initial metabolic activation of bacterial responses when in the presence of plant root exudates. Moreover, antioxidant genes were mostly expressed during the interaction with the plant exudates. Further evaluation of stress- and methylotrophic-related genes expression by qPCR showed that glutathione peroxidase and glutathione synthetase genes were up-regulated during the Methylobacterium-soybean interaction. These findings support that glutathione (GSH) is potentially a key molecule involved in cellular detoxification during plant root colonization. In addition to methylotrophic metabolism, antioxidant genes, mainly glutathione-related genes, play a key role during soybean exudate recognition and adaptation, the first step in
Klein, Ronald; Myers, Chelsea E.; Buitendijk, Gabriëlle H. S.; Rochtchina, Elena; Gao, Xiaoyi; de Jong, Paulus T. V. M.; Sivakumaran, Theru A.; Burlutsky, George; McKean-Cowdin, Roberta; Hofman, Albert; Iyengar, Sudha K.; Lee, Kristine E.; Stricker, Bruno H.; Vingerling, Johannes R.; Mitchell, Paul; Klein, Barbara E. K.; Klaver, Caroline C. W.; Wang, Jie Jin
To describe associations of serum lipid levels and lipid pathway genes to the incidence of age-related macular degeneration (AMD). Meta-analysis. setting: Three population-based cohorts. population: A total of 6950 participants from the Beaver Dam Eye Study (BDES), Blue Mountains Eye Study (BMES),
Full Text Available Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions. In line with these changes, high-resolution immunohistochemistry demonstrated decreased numbers of oligodendrocytes and of neuronal subpopulations in the aging brain cortex. Finally, glial-specific genes predict age with greater precision than neuron-specific genes, thus highlighting the need for greater mechanistic understanding of neuron-glia interactions in aging and late-life diseases.
Soreq, Lilach; Rose, Jamie; Soreq, Eyal; Hardy, John; Trabzuni, Daniah; Cookson, Mark R; Smith, Colin; Ryten, Mina; Patani, Rickie; Ule, Jernej
Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions. In line with these changes, high-resolution immunohistochemistry demonstrated decreased numbers of oligodendrocytes and of neuronal subpopulations in the aging brain cortex. Finally, glial-specific genes predict age with greater precision than neuron-specific genes, thus highlighting the need for greater mechanistic understanding of neuron-glia interactions in aging and late-life diseases. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Forsyth, Jennifer K; Ellman, Lauren M; Tanskanen, Antti; Mustonen, Ulla; Huttunen, Matti O; Suvisaari, Jaana; Cannon, Tyrone D
Low birth weight (LBW) and hypoxia are among the environmental factors most reliably associated with schizophrenia; however, the nature of this relationship is unclear and both gene-environment interaction and gene-environment covariation models have been proposed as explanations. High-risk (HR) designs that explore whether obstetric complications differentially predict outcomes in offspring at low risk (LR) vs HR for schizophrenia, while accounting for differences in rates of maternal risk factors, may shed light on this question. This study used prospectively obtained data to examine relationships between LBW and hypoxia on school outcome at age 15-16 years in a Finnish sample of 1070 offspring at LR for schizophrenia and 373 offspring at HR for schizophrenia, based on parental psychiatric history. Controlling for offspring sex, maternal smoking, social support, parity, age, and number of prenatal care visits, HR offspring performed worse than LR offspring across academic, nonacademic, and physical education domains. LBW predicted poorer academic and physical education performance in HR offspring, but not in LR offspring, and this association was similar for offspring of fathers vs mothers with schizophrenia. Hypoxia predicted poorer physical education score across risk groups. Rates of LBW and hypoxia were similar for LR and HR offspring and for offspring of fathers vs mothers with schizophrenia. Results support the hypothesis that genetic susceptibility to schizophrenia confers augmented vulnerability of the developing brain to the effects of obstetric complications, possibly via epigenetic mechanisms.
Full Text Available The development and homeostasis of multicellular organisms depends on sheets of epithelial cells. Bazooka (Baz; PAR-3 localizes to the apical circumference of epithelial cells and is a key hub in the protein interaction network regulating epithelial structure. We sought to identify additional proteins that function with Baz to regulate epithelial structure in the Drosophila embryo.The baz zygotic mutant cuticle phenotype could be dominantly enhanced by loss of known interaction partners. To identify additional enhancers, we screened molecularly defined chromosome 2 and 3 deficiencies. 37 deficiencies acted as strong dominant enhancers. Using deficiency mapping, bioinformatics, and available single gene mutations, we identified 17 interacting genes encoding known and predicted polarity, cytoskeletal, transmembrane, trafficking and signaling proteins. For each gene, their loss of function enhanced adherens junction defects in zygotic baz mutants during early embryogenesis. To further evaluate involvement in epithelial polarity, we generated GFP fusion proteins for 15 of the genes which had not been found to localize to the apical domain previously. We found that GFP fusion proteins for Drosophila ASAP, Arf79F, CG11210, Septin 5 and Sds22 could be recruited to the apical circumference of epithelial cells. Nine of the other proteins showed various intracellular distributions, and one was not detected.Our enhancer screen identified 17 genes that function with Baz to regulate epithelial structure in the Drosophila embryo. Our secondary localization screen indicated that some of the proteins may affect epithelial cell polarity by acting at the apical cell cortex while others may act through intracellular processes. For 13 of the 17 genes, this is the first report of a link to baz or the regulation of epithelial structure.
Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters
Christopher T Primiani
Full Text Available Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases.Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades.We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains and Aging (22 to 78 years, 144 brains intervals, in transcription levels of 39 genes.Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1.Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks
Primiani, Christopher T.; Ryan, Veronica H.; Rao, Jagadeesh S.; Cam, Margaret C.; Ahn, Kwangmi; Modi, Hiren R.; Rapoport, Stanley I.
Background Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Hypothesis Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. Methods We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Results Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Conclusions Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable
Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah
Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.
Speiser, Daniel I; Pankey, M Sabrina; Zaharoff, Alexander K; Battelle, Barbara A; Bracken-Grissom, Heather D; Breinholt, Jesse W; Bybee, Seth M; Cronin, Thomas W; Garm, Anders; Lindgren, Annie R; Patel, Nipam H; Porter, Megan L; Protas, Meredith E; Rivera, Ajna S; Serb, Jeanne M; Zigler, Kirk S; Crandall, Keith A; Oakley, Todd H
Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository ( http://bitbucket.org/osiris_phylogenetics/pia/ ) and we demonstrate PIA on a publicly-accessible web server ( http://galaxy-dev.cnsi.ucsb.edu/pia/ ). Our new
Nielsen, Kaspar René; Rodrigo-Domingo, Maria; Steffensen, Rudi
The origin of multiple myeloma depends on interactions with stromal cells in the course of normal B-cell differentiation and evolution of immunity. The concept of the present study is that genes involved in MM pathogenesis, such as immune response genes, can be identified by screening for single......3L1 gene promoters. The occurrence of single polymorphisms, haplotypes and SNP-SNP interactions were statistically analyzed for association with disease risk and outcome following high-dose therapy. Identified genes that carried SNPs or haplotypes that were identified as risk or prognostic factors......= .005). The 'risk genes' were analyzed for expression in normal B-cell subsets (N = 6) from seven healthy donors and we found TNFA and IL-6 expressed both in naïve and in memory B cells when compared to preBI, II, immature and plasma cells. The 'prognosis genes' CHI3L1, IL-6 and IL-10 were differential...
Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.
van den Berg, Arjen; Mols, Johann; Han, Jiahuai
Summary Small RNA molecules have been known and utilized to suppress gene expression for more than a decade. The discovery that these small RNA molecules are endogenously expressed in many organisms and have a critical role in controlling gene expression have led to the arising of a whole new field of research. Termed small interfering RNA (siRNA) or microRNA (miRNA) these ~22 nt RNA molecules have the capability to suppress gene expression through various mechanisms once they are incorporated in the multi-protein RNA-Induced Silencing Complex (RISC) and interact with their target mRNA. This review introduces siRNAs and microRNAs in a historical perspective and focuses on the key molecules in RISC, structural properties and mechanisms underlying the process of small RNA regulated post-transcriptional suppression of gene expression. PMID:18692607
Aliahmat, Nor Syahida; Abdul Sani, Nur Fathiah; Wan Hasan, Wan Nuraini; Makpol, Suzana; Wan Ngah, Wan Zurinah; Mohd Yusof, Yasmin Anum
The objective of this study was to elucidate the underlying antioxidant mechanism of aqueous extract of Piper betle (PB) in aging rats. The nuclear factor erythroid 2-related factor 2 (Nrf2)/ARE pathway involving phase II detoxifying and antioxidant enzymes plays an important role in the antioxidant system by reducing electrophiles and reactive oxygen species through induction of phase II enzymes and proteins. Genes and proteins of phase II detoxifying antioxidant enzymes were analyzed by QuantiGenePlex 2.0 Assay and Western blot analysis. PB significantly induced genes and proteins of phase II and antioxidant enzymes, NAD(P)H quinone oxidoreductase 1, and catalase in aging mice (p < 0.05). The expression of these enzymes were stimulated via translocation of Nrf2 into the nucleus, indicating the involvement of ARE, a cis-acting motif located in the promoter region of nearly all phase II genes. PB was testified for the first time to induce cytoprotective genes through the Nrf2/ARE signaling pathway, thus unraveling the antioxidant mechanism of PB during the aging process. © 2016 S. Karger AG, Basel.
Snieder, H.; Doornen, L.J.P. van; Boomsma, D.I. [Vrije Universiteit, Amsterdam (Netherlands)
The aim of this study was to investigate and disentangle the genetic and nongenetic causes of stability and change in lipids and (apo)lipoproteins that occur during the lifespan. Total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a) (Lp[a]) were measured in a group of 160 middle-aged parents and their twin offspring (first project) and in a group of 203 middle-aged twin pairs (second project). Combining the data of both projects enabled the estimation of the extent to which measured lipid parameters are influenced by different genes in adolescence and adulthood. To that end, an extended quantitative genetic model was specified, which allowed the estimation of heritabilities for each sex and generation separately. Heritabilities were similar for both sexes and both generations. Larger variances in the parental generation could be ascribed to proportional increases in both unique environmental and additive genetic variance from childhood to adulthood, which led to similar heritability estimates in adolescent and middle-aged twins. Although the magnitudes of heritabilities were similar across generations, results showed that, for total cholesterol, triglycerides, HDL, and LDL, partly different genes are expressed in adolescence compared to adulthood. For triglycerides, only 46% of the genetic variance was common to both age groups; for total cholesterol this was 80%. Intermediate values were found for HDL (66%) and LDL (76%). For ApoA1, ApoB, and Lp(a), the same genes seem to act in both generations. 56 refs., 2 figs., 5 tabs.
Kim, Hyun-Jin; Min, Jin-Young; Min, Kyoung-Bok
Obesity is a major risk factor for chronic diseases and arises from the interactions between environmental factors and multiple genes. Psychosocial stress may affect the risk for obesity, modifying food intake and choice. A recent study suggested regulator of G-protein signaling 6 (RGS6) as a novel candidate gene for obesity in terms of reward-related feeding under stress. In this study, we tried to verify the unidentified connection between RGS6 and human obesity with psychosocial stress in a Korean population. A total of 1,462 adult subjects, who participated in the Korean Association Resource cohort project, were included for this analysis. Obesity-related traits including waist circumference, body mass index, and visceral adipose tissue were recorded. A total of 4 intronic SNPs for the RGS6 gene were used for this study. We found that interactions between SNP rs2239219 and psychosocial stress are significantly associated with abdominal obesity (p = 0.007). As risk allele of this SNP increased, prevalence of abdominal obesity under high-stress conditions gradually increased (p = 0.013). However, we found no SNPs-by-stress interaction effect on other adiposity phenotypes. This study suggests that RGS6 is closely linked to stress-induced abdominal obesity in Korean adults.
Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan
In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in
Feng, Yang; Jiang, Chen-Dong; Chang, Ai-Min; Shi, Ying; Gao, Junjun; Zhu, Linlin; Zhang, Zhan
The aim of this study was to investigate the correlations and interactions between the polymorphisms of insulin resistance-related genes (ADIPOQ rs2241766), inflammation factors (TNF-α rs1800629, IL-6 rs1800795), obesity-related genes (GNB3 rs5443, ADRB rs1042714), and risk factors for gestational diabetes mellitus (GDM) such as diet structure in the development of GDM. This research was conducted among women who visited the third-affiliate hospital of Zhengzhou University for pregnancy checkups from 1 June 2014 to 30 December 2014. Based on the results of a 75-g glucose tolerance test (OGTT), 140 pregnant women with GDM were randomly selected as a part of the GDM group and140 healthy, pregnant women as part of the control group. Relevant clinical and laboratory data for the child and the mother including her pregnancy outcomes and the delivery mode were collected for the epidemiological survey. The results showed that risk factors for GDM are advanced age, the hepatitis B virus, family history of diabetes, high body mass index before pregnancy, and weight gain of ≥10 kg before 24-week gestation. We found that diet structures were severely unbalanced. The polymorphisms rs2241766 and rs5443 were found to potentially be associated with GDM; moreover, a positive interaction was demonstrated between rs2241766 and age, and a negative interaction was demonstrated with weight gain of ≥10 kg before 24-week gestation. Our findings demonstrate that both environmental risk factors and genetic background contribute to the development of GDM.
Pedro Pereira Correia
Full Text Available In a more transparent and dynamic world, in which consumers trust other consumers more for advice and recommendations on products and services, the continuity of organizations appears to be associated with socialization, the sharing of interests and the interaction with the audience. This is associated with the incorporation of digital technologies to business, specifically the use of social media. Consequently, it is timely and interesting to explore the phenomenon of virtual socialization, although it is a little-studied field and what is needed is an innovative and theoretical approach based upon theories of marketing and communication. Expertise in these areas is present in all organizations and their performance is important for appropriate development of them. This work is a qualitative analysis about the behavior, reactions and attitudes of individuals to organizations, in order to understand the social factors that contribute to sustainable competitive advantages of organizations which can support strategic and future actions. We conclude that relevant factors associated with the tacit knowledge of the organization, specifically to learning and social interaction of the organization and their knowledge of virtual communities. The higher the coexistence of factors, the more difficult is the replication and greater will be the hypothesis of sustainable competitive advantage.
Shiao, S Pamela K; Grayson, James; Lie, Amanda; Yu, Chong Ho
To personalize nutrition, the purpose of this study was to examine five key genes in the folate metabolism pathway, and dietary parameters and related interactive parameters as predictors of colorectal cancer (CRC) by measuring the healthy eating index (HEI) in multiethnic families. The five genes included methylenetetrahydrofolate reductase ( MTHFR ) 677 and 1298, methionine synthase ( MTR ) 2756, methionine synthase reductase ( MTRR 66), and dihydrofolate reductase ( DHFR ) 19bp , and they were used to compute a total gene mutation score. We included 53 families, 53 CRC patients and 53 paired family friend members of diverse population groups in Southern California. We measured multidimensional data using the ensemble bootstrap forest method to identify variables of importance within domains of genetic, demographic, and dietary parameters to achieve dimension reduction. We then constructed predictive generalized regression (GR) modeling with a supervised machine learning validation procedure with the target variable (cancer status) being specified to validate the results to allow enhanced prediction and reproducibility. The results showed that the CRC group had increased total gene mutation scores compared to the family members ( p < 0.05). Using the Akaike's information criterion and Leave-One-Out cross validation GR methods, the HEI was interactive with thiamine (vitamin B1), which is a new finding for the literature. The natural food sources for thiamine include whole grains, legumes, and some meats and fish which HEI scoring included as part of healthy portions (versus limiting portions on salt, saturated fat and empty calories). Additional predictors included age, as well as gender and the interaction of MTHFR 677 with overweight status (measured by body mass index) in predicting CRC, with the cancer group having more men and overweight cases. The HEI score was significant when split at the median score of 77 into greater or less scores, confirmed through
Full Text Available Major Depressive Disorder (MDD is a multifactorial and polygenic disorder, where multiple and partially overlapping sets of susceptibility genes interact each other and with the environment, predisposing individuals to the development of the illness. Thus, MDD results from a complex interplay of vulnerability genes and environmental factors that act cumulatively throughout individual's lifetime. Among these environmental factors, stressful life experiences, especially those occurring early in life, have been suggested to exert a crucial impact on brain development, leading to permanent functional changes that may contribute to life long risk for mental health outcomes. In this review we will discuss how genetic variants (polymorphisms, SNPs within genes operating in neurobiological systems that mediate stress response and synaptic plasticity, can impact, by themselves, the vulnerability risk for MDD; we will also consider how this MDD risk can be further modulated when gene X environment interaction is taken into account. Finally, we will discuss the role of epigenetic mechanisms, and in particular of DNA methylation and miRNAs expression changes, in mediating the effect of the stress on the vulnerability risk to develop MDD. Taken together, in this review we aim to underlie the role of genetic and epigenetic processes involved in stress and neuroplasticity related biolog