#### Sample records for multiple imputation mi

1. Multiple imputation and its application

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Carpenter, James

2013-01-01

A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete  data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues ...

2. Multiple Improvements of Multiple Imputation Likelihood Ratio Tests

OpenAIRE

Chan, Kin Wai; Meng, Xiao-Li

2017-01-01

Multiple imputation (MI) inference handles missing data by first properly imputing the missing values \$m\$ times, and then combining the \$m\$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard \$F\$ distribution; (ii) it is not invariant to re-parametrization; ...

3. Multiple imputation in the presence of non-normal data.

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Lee, Katherine J; Carlin, John B

2017-02-20

Multiple imputation (MI) is becoming increasingly popular for handling missing data. Standard approaches for MI assume normality for continuous variables (conditionally on the other variables in the imputation model). However, it is unclear how to impute non-normally distributed continuous variables. Using simulation and a case study, we compared various transformations applied prior to imputation, including a novel non-parametric transformation, to imputation on the raw scale and using predictive mean matching (PMM) when imputing non-normal data. We generated data from a range of non-normal distributions, and set 50% to missing completely at random or missing at random. We then imputed missing values on the raw scale, following a zero-skewness log, Box-Cox or non-parametric transformation and using PMM with both type 1 and 2 matching. We compared inferences regarding the marginal mean of the incomplete variable and the association with a fully observed outcome. We also compared results from these approaches in the analysis of depression and anxiety symptoms in parents of very preterm compared with term-born infants. The results provide novel empirical evidence that the decision regarding how to impute a non-normal variable should be based on the nature of the relationship between the variables of interest. If the relationship is linear in the untransformed scale, transformation can introduce bias irrespective of the transformation used. However, if the relationship is non-linear, it may be important to transform the variable to accurately capture this relationship. A useful alternative is to impute the variable using PMM with type 1 matching. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

4. Synthetic Multiple-Imputation Procedure for Multistage Complex Samples

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Zhou Hanzhi

2016-03-01

Full Text Available Multiple imputation (MI is commonly used when item-level missing data are present. However, MI requires that survey design information be built into the imputation models. For multistage stratified clustered designs, this requires dummy variables to represent strata as well as primary sampling units (PSUs nested within each stratum in the imputation model. Such a modeling strategy is not only operationally burdensome but also inferentially inefficient when there are many strata in the sample design. Complexity only increases when sampling weights need to be modeled. This article develops a generalpurpose analytic strategy for population inference from complex sample designs with item-level missingness. In a simulation study, the proposed procedures demonstrate efficient estimation and good coverage properties. We also consider an application to accommodate missing body mass index (BMI data in the analysis of BMI percentiles using National Health and Nutrition Examination Survey (NHANES III data. We argue that the proposed methods offer an easy-to-implement solution to problems that are not well-handled by current MI techniques. Note that, while the proposed method borrows from the MI framework to develop its inferential methods, it is not designed as an alternative strategy to release multiply imputed datasets for complex sample design data, but rather as an analytic strategy in and of itself.

5. Bootstrap inference when using multiple imputation.

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Schomaker, Michael; Heumann, Christian

2018-04-16

Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. Copyright © 2018 John Wiley & Sons, Ltd.

6. Handling missing data in cluster randomized trials: A demonstration of multiple imputation with PAN through SAS

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Jiangxiu Zhou

2014-09-01

Full Text Available The purpose of this study is to demonstrate a way of dealing with missing data in clustered randomized trials by doing multiple imputation (MI with the PAN package in R through SAS. The procedure for doing MI with PAN through SAS is demonstrated in detail in order for researchers to be able to use this procedure with their own data. An illustration of the technique with empirical data was also included. In this illustration thePAN results were compared with pairwise deletion and three types of MI: (1 Normal Model (NM-MI ignoring the cluster structure; (2 NM-MI with dummy-coded cluster variables (fixed cluster structure; and (3 a hybrid NM-MI which imputes half the time ignoring the cluster structure, and the other half including the dummy-coded cluster variables. The empirical analysis showed that using PAN and the other strategies produced comparable parameter estimates. However, the dummy-coded MI overestimated the intraclass correlation, whereas MI ignoring the cluster structure and the hybrid MI underestimated the intraclass correlation. When compared with PAN, the p-value and standard error for the treatment effect were higher with dummy-coded MI, and lower with MI ignoring the clusterstructure, the hybrid MI approach, and pairwise deletion. Previous studies have shown that NM-MI is not appropriate for handling missing data in clustered randomized trials. This approach, in addition to the pairwise deletion approach, leads to a biased intraclass correlation and faultystatistical conclusions. Imputation in clustered randomized trials should be performed with PAN. We have demonstrated an easy way for using PAN through SAS.

7. Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

8. Sensitivity analysis in multiple imputation in effectiveness studies of psychotherapy.

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Crameri, Aureliano; von Wyl, Agnes; Koemeda, Margit; Schulthess, Peter; Tschuschke, Volker

2015-01-01

The importance of preventing and treating incomplete data in effectiveness studies is nowadays emphasized. However, most of the publications focus on randomized clinical trials (RCT). One flexible technique for statistical inference with missing data is multiple imputation (MI). Since methods such as MI rely on the assumption of missing data being at random (MAR), a sensitivity analysis for testing the robustness against departures from this assumption is required. In this paper we present a sensitivity analysis technique based on posterior predictive checking, which takes into consideration the concept of clinical significance used in the evaluation of intra-individual changes. We demonstrate the possibilities this technique can offer with the example of irregular longitudinal data collected with the Outcome Questionnaire-45 (OQ-45) and the Helping Alliance Questionnaire (HAQ) in a sample of 260 outpatients. The sensitivity analysis can be used to (1) quantify the degree of bias introduced by missing not at random data (MNAR) in a worst reasonable case scenario, (2) compare the performance of different analysis methods for dealing with missing data, or (3) detect the influence of possible violations to the model assumptions (e.g., lack of normality). Moreover, our analysis showed that ratings from the patient's and therapist's version of the HAQ could significantly improve the predictive value of the routine outcome monitoring based on the OQ-45. Since analysis dropouts always occur, repeated measurements with the OQ-45 and the HAQ analyzed with MI are useful to improve the accuracy of outcome estimates in quality assurance assessments and non-randomized effectiveness studies in the field of outpatient psychotherapy.

9. The use of multiple imputation for the accurate measurements of individual feed intake by electronic feeders.

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Jiao, S; Tiezzi, F; Huang, Y; Gray, K A; Maltecca, C

2016-02-01

Obtaining accurate individual feed intake records is the key first step in achieving genetic progress toward more efficient nutrient utilization in pigs. Feed intake records collected by electronic feeding systems contain errors (erroneous and abnormal values exceeding certain cutoff criteria), which are due to feeder malfunction or animal-feeder interaction. In this study, we examined the use of a novel data-editing strategy involving multiple imputation to minimize the impact of errors and missing values on the quality of feed intake data collected by an electronic feeding system. Accuracy of feed intake data adjustment obtained from the conventional linear mixed model (LMM) approach was compared with 2 alternative implementations of multiple imputation by chained equation, denoted as MI (multiple imputation) and MICE (multiple imputation by chained equation). The 3 methods were compared under 3 scenarios, where 5, 10, and 20% feed intake error rates were simulated. Each of the scenarios was replicated 5 times. Accuracy of the alternative error adjustment was measured as the correlation between the true daily feed intake (DFI; daily feed intake in the testing period) or true ADFI (the mean DFI across testing period) and the adjusted DFI or adjusted ADFI. In the editing process, error cutoff criteria are used to define if a feed intake visit contains errors. To investigate the possibility that the error cutoff criteria may affect any of the 3 methods, the simulation was repeated with 2 alternative error cutoff values. Multiple imputation methods outperformed the LMM approach in all scenarios with mean accuracies of 96.7, 93.5, and 90.2% obtained with MI and 96.8, 94.4, and 90.1% obtained with MICE compared with 91.0, 82.6, and 68.7% using LMM for DFI. Similar results were obtained for ADFI. Furthermore, multiple imputation methods consistently performed better than LMM regardless of the cutoff criteria applied to define errors. In conclusion, multiple imputation

10. The multiple imputation method: a case study involving secondary data analysis.

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Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

11. Using mi impute chained to fit ANCOVA models in randomized trials with censored dependent and independent variables

DEFF Research Database (Denmark)

Andersen, Andreas; Rieckmann, Andreas

2016-01-01

In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design.......In this article, we illustrate how to use mi impute chained with intreg to fit an analysis of covariance analysis of censored and nondetectable immunological concentrations measured in a randomized pretest–posttest design....

12. A nonparametric multiple imputation approach for missing categorical data

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Muhan Zhou

2017-06-01

Full Text Available Abstract Background Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness probabilities. Methods We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model and the other fits a logistic regression for predicting missingness probabilities (the missingness model. A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. Results The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. Conclusions We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with

13. Imputation and quality control steps for combining multiple genome-wide datasets

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Shefali S Verma

2014-12-01

Full Text Available The electronic MEdical Records and GEnomics (eMERGE network brings together DNA biobanks linked to electronic health records (EHRs from multiple institutions. Approximately 52,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes, and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2 were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

14. Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

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Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

15. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

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Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

16. Taking a multiple intelligences (MI) perspective.

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Gardner, Howard

2017-01-01

The theory of multiple intelligences (MI) seeks to describe and encompass the range of human cognitive capacities. In challenging the concept of general intelligence, we can apply an MI perspective that may provide a more useful approach to cognitive differences within and across species.

17. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

NARCIS (Netherlands)

Eekhout, I.; Wiel, M.A. van de; Heymans, M.W.

2017-01-01

Background. Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin’s Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels

18. Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

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Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

19. Multiple imputation strategies for zero-inflated cost data in economic evaluations : which method works best?

NARCIS (Netherlands)

MacNeil Vroomen, Janet; Eekhout, Iris; Dijkgraaf, Marcel G; van Hout, Hein; de Rooij, Sophia E; Heymans, Martijn W; Bosmans, Judith E

2016-01-01

Cost and effect data often have missing data because economic evaluations are frequently added onto clinical studies where cost data are rarely the primary outcome. The objective of this article was to investigate which multiple imputation strategy is most appropriate to use for missing

20. Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

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Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

1. Multiple imputation to account for missing data in a survey: estimating the prevalence of osteoporosis.

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Kmetic, Andrew; Joseph, Lawrence; Berger, Claudie; Tenenhouse, Alan

2002-07-01

Nonresponse bias is a concern in any epidemiologic survey in which a subset of selected individuals declines to participate. We reviewed multiple imputation, a widely applicable and easy to implement Bayesian methodology to adjust for nonresponse bias. To illustrate the method, we used data from the Canadian Multicentre Osteoporosis Study, a large cohort study of 9423 randomly selected Canadians, designed in part to estimate the prevalence of osteoporosis. Although subjects were randomly selected, only 42% of individuals who were contacted agreed to participate fully in the study. The study design included a brief questionnaire for those invitees who declined further participation in order to collect information on the major risk factors for osteoporosis. These risk factors (which included age, sex, previous fractures, family history of osteoporosis, and current smoking status) were then used to estimate the missing osteoporosis status for nonparticipants using multiple imputation. Both ignorable and nonignorable imputation models are considered. Our results suggest that selection bias in the study is of concern, but only slightly, in very elderly (age 80+ years), both women and men. Epidemiologists should consider using multiple imputation more often than is current practice.

2. Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

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Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

3. Limitations in Using Multiple Imputation to Harmonize Individual Participant Data for Meta-Analysis.

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Siddique, Juned; de Chavez, Peter J; Howe, George; Cruden, Gracelyn; Brown, C Hendricks

2018-02-01

Individual participant data (IPD) meta-analysis is a meta-analysis in which the individual-level data for each study are obtained and used for synthesis. A common challenge in IPD meta-analysis is when variables of interest are measured differently in different studies. The term harmonization has been coined to describe the procedure of placing variables on the same scale in order to permit pooling of data from a large number of studies. Using data from an IPD meta-analysis of 19 adolescent depression trials, we describe a multiple imputation approach for harmonizing 10 depression measures across the 19 trials by treating those depression measures that were not used in a study as missing data. We then apply diagnostics to address the fit of our imputation model. Even after reducing the scale of our application, we were still unable to produce accurate imputations of the missing values. We describe those features of the data that made it difficult to harmonize the depression measures and provide some guidelines for using multiple imputation for harmonization in IPD meta-analysis.

4. Missing data treatments matter: an analysis of multiple imputation for anterior cervical discectomy and fusion procedures.

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Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Cui, Jonathan J; Basques, Bryce A; Albert, Todd J; Grauer, Jonathan N

2018-04-09

5. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

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Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

6. Factors associated with low birth weight in Nepal using multiple imputation

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Usha Singh

2017-02-01

Full Text Available Abstract Background Survey data from low income countries on birth weight usually pose a persistent problem. The studies conducted on birth weight have acknowledged missing data on birth weight, but they are not included in the analysis. Furthermore, other missing data presented on determinants of birth weight are not addressed. Thus, this study tries to identify determinants that are associated with low birth weight (LBW using multiple imputation to handle missing data on birth weight and its determinants. Methods The child dataset from Nepal Demographic and Health Survey (NDHS, 2011 was utilized in this study. A total of 5,240 children were born between 2006 and 2011, out of which 87% had at least one measured variable missing and 21% had no recorded birth weight. All the analyses were carried out in R version 3.1.3. Transform-then impute method was applied to check for interaction between explanatory variables and imputed missing data. Survey package was applied to each imputed dataset to account for survey design and sampling method. Survey logistic regression was applied to identify the determinants associated with LBW. Results The prevalence of LBW was 15.4% after imputation. Women with the highest autonomy on their own health compared to those with health decisions involving husband or others (adjusted odds ratio (OR 1.87, 95% confidence interval (95% CI = 1.31, 2.67, and husband and women together (adjusted OR 1.57, 95% CI = 1.05, 2.35 were less likely to give birth to LBW infants. Mothers using highly polluting cooking fuels (adjusted OR 1.49, 95% CI = 1.03, 2.22 were more likely to give birth to LBW infants than mothers using non-polluting cooking fuels. Conclusion The findings of this study suggested that obtaining the prevalence of LBW from only the sample of measured birth weight and ignoring missing data results in underestimation.

7. Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data

Science.gov (United States)

2012-01-01

Background Multiple Imputation as usually implemented assumes that data are Missing At Random (MAR), meaning that the underlying missing data mechanism, given the observed data, is independent of the unobserved data. To explore the sensitivity of the inferences to departures from the MAR assumption, we applied the method proposed by Carpenter et al. (2007). This approach aims to approximate inferences under a Missing Not At random (MNAR) mechanism by reweighting estimates obtained after multiple imputation where the weights depend on the assumed degree of departure from the MAR assumption. Methods The method is illustrated with epidemiological data from a surveillance system of hepatitis C virus (HCV) infection in France during the 2001–2007 period. The subpopulation studied included 4343 HCV infected patients who reported drug use. Risk factors for severe liver disease were assessed. After performing complete-case and multiple imputation analyses, we applied the sensitivity analysis to 3 risk factors of severe liver disease: past excessive alcohol consumption, HIV co-infection and infection with HCV genotype 3. Results In these data, the association between severe liver disease and HIV was underestimated, if given the observed data the chance of observing HIV status is high when this is positive. Inference for two other risk factors were robust to plausible local departures from the MAR assumption. Conclusions We have demonstrated the practical utility of, and advocate, a pragmatic widely applicable approach to exploring plausible departures from the MAR assumption post multiple imputation. We have developed guidelines for applying this approach to epidemiological studies. PMID:22681630

8. Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study.

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Cornish, R P; Macleod, J; Carpenter, J R; Tilling, K

2017-01-01

When an outcome variable is missing not at random (MNAR: probability of missingness depends on outcome values), estimates of the effect of an exposure on this outcome are often biased. We investigated the extent of this bias and examined whether the bias can be reduced through incorporating proxy outcomes obtained through linkage to administrative data as auxiliary variables in multiple imputation (MI). Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) we estimated the association between breastfeeding and IQ (continuous outcome), incorporating linked attainment data (proxies for IQ) as auxiliary variables in MI models. Simulation studies explored the impact of varying the proportion of missing data (from 20 to 80%), the correlation between the outcome and its proxy (0.1-0.9), the strength of the missing data mechanism, and having a proxy variable that was incomplete. Incorporating a linked proxy for the missing outcome as an auxiliary variable reduced bias and increased efficiency in all scenarios, even when 80% of the outcome was missing. Using an incomplete proxy was similarly beneficial. High correlations (> 0.5) between the outcome and its proxy substantially reduced the missing information. Consistent with this, ALSPAC analysis showed inclusion of a proxy reduced bias and improved efficiency. Gains with additional proxies were modest. In longitudinal studies with loss to follow-up, incorporating proxies for this study outcome obtained via linkage to external sources of data as auxiliary variables in MI models can give practically important bias reduction and efficiency gains when the study outcome is MNAR.

9. Use of Multiple Imputation Method to Improve Estimation of Missing Baseline Serum Creatinine in Acute Kidney Injury Research

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Peterson, Josh F.; Eden, Svetlana K.; Moons, Karel G.; Ikizler, T. Alp; Matheny, Michael E.

2013-01-01

Summary Background and objectives Baseline creatinine (BCr) is frequently missing in AKI studies. Common surrogate estimates can misclassify AKI and adversely affect the study of related outcomes. This study examined whether multiple imputation improved accuracy of estimating missing BCr beyond current recommendations to apply assumed estimated GFR (eGFR) of 75 ml/min per 1.73 m2 (eGFR 75). Design, setting, participants, & measurements From 41,114 unique adult admissions (13,003 with and 28,111 without BCr data) at Vanderbilt University Hospital between 2006 and 2008, a propensity score model was developed to predict likelihood of missing BCr. Propensity scoring identified 6502 patients with highest likelihood of missing BCr among 13,003 patients with known BCr to simulate a “missing” data scenario while preserving actual reference BCr. Within this cohort (n=6502), the ability of various multiple-imputation approaches to estimate BCr and classify AKI were compared with that of eGFR 75. Results All multiple-imputation methods except the basic one more closely approximated actual BCr than did eGFR 75. Total AKI misclassification was lower with multiple imputation (full multiple imputation + serum creatinine) (9.0%) than with eGFR 75 (12.3%; Pcreatinine) (15.3%) versus eGFR 75 (40.5%; P<0.001). Multiple imputation improved specificity and positive predictive value for detecting AKI at the expense of modestly decreasing sensitivity relative to eGFR 75. Conclusions Multiple imputation can improve accuracy in estimating missing BCr and reduce misclassification of AKI beyond currently proposed methods. PMID:23037980

10. Multiple imputation of missing passenger boarding data in the national census of ferry operators

Science.gov (United States)

2008-08-01

This report presents findings from the 2006 National Census of Ferry Operators (NCFO) augmented with imputed values for passengers and passenger miles. Due to the imputation procedures used to calculate missing data, totals in Table 1 may not corresp...

11. Multiple imputation to account for measurement error in marginal structural models

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Edwards, Jessie K.; Cole, Stephen R.; Westreich, Daniel; Crane, Heidi; Eron, Joseph J.; Mathews, W. Christopher; Moore, Richard; Boswell, Stephen L.; Lesko, Catherine R.; Mugavero, Michael J.

2015-01-01

Background Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and non-differential measurement error in a marginal structural model. Methods We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. Results In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality [hazard ratio (HR): 1.2 (95% CI: 0.6, 2.3)]. The HR for current smoking and therapy (0.4 (95% CI: 0.2, 0.7)) was similar to the HR for no smoking and therapy (0.4; 95% CI: 0.2, 0.6). Conclusions Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies. PMID:26214338

12. Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

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Edwards, Jessie K; Cole, Stephen R; Westreich, Daniel; Crane, Heidi; Eron, Joseph J; Mathews, W Christopher; Moore, Richard; Boswell, Stephen L; Lesko, Catherine R; Mugavero, Michael J

2015-09-01

Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model. We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6). Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.

13. A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

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Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437

14. Trend in BMI z-score among Private Schools’ Students in Delhi using Multiple Imputation for Growth Curve Model

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Vinay K Gupta

2016-06-01

Full Text Available Objective: The aim of the study is to assess the trend in mean BMI z-score among private schools’ students from their anthropometric records when there were missing values in the outcome. Methodology: The anthropometric measurements of student from class 1 to 12 were taken from the records of two private schools in Delhi, India from 2005 to 2010. These records comprise of an unbalanced longitudinal data that is not all the students had measurements recorded at each year. The trend in mean BMI z-score was estimated through growth curve model. Prior to that, missing values of BMI z-score were imputed through multiple imputation using the same model. A complete case analysis was also performed after excluding missing values to compare the results with those obtained from analysis of multiply imputed data. Results: The mean BMI z-score among school student significantly decreased over time in imputed data (β= -0.2030, se=0.0889, p=0.0232 after adjusting age, gender, class and school. Complete case analysis also shows a decrease in mean BMI z-score though it was not statistically significant (β= -0.2861, se=0.0987, p=0.065. Conclusions: The estimates obtained from multiple imputation analysis were better than those of complete data after excluding missing values in terms of lower standard errors. We showed that anthropometric measurements from schools records can be used to monitor the weight status of children and adolescents and multiple imputation using growth curve model can be useful while analyzing such data

15. Auxiliary variables in multiple imputation in regression with missing X: a warning against including too many in small sample research

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Hardt Jochen

2012-12-01

Full Text Available Abstract Background Multiple imputation is becoming increasingly popular. Theoretical considerations as well as simulation studies have shown that the inclusion of auxiliary variables is generally of benefit. Methods A simulation study of a linear regression with a response Y and two predictors X1 and X2 was performed on data with n = 50, 100 and 200 using complete cases or multiple imputation with 0, 10, 20, 40 and 80 auxiliary variables. Mechanisms of missingness were either 100% MCAR or 50% MAR + 50% MCAR. Auxiliary variables had low (r=.10 vs. moderate correlations (r=.50 with X’s and Y. Results The inclusion of auxiliary variables can improve a multiple imputation model. However, inclusion of too many variables leads to downward bias of regression coefficients and decreases precision. When the correlations are low, inclusion of auxiliary variables is not useful. Conclusion More research on auxiliary variables in multiple imputation should be performed. A preliminary rule of thumb could be that the ratio of variables to cases with complete data should not go below 1 : 3.

16. Double sampling with multiple imputation to answer large sample meta-research questions: Introduction and illustration by evaluating adherence to two simple CONSORT guidelines

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Patrice L. Capers

2015-03-01

Full Text Available BACKGROUND: Meta-research can involve manual retrieval and evaluation of research, which is resource intensive. Creation of high throughput methods (e.g., search heuristics, crowdsourcing has improved feasibility of large meta-research questions, but possibly at the cost of accuracy. OBJECTIVE: To evaluate the use of double sampling combined with multiple imputation (DS+MI to address meta-research questions, using as an example adherence of PubMed entries to two simple Consolidated Standards of Reporting Trials (CONSORT guidelines for titles and abstracts. METHODS: For the DS large sample, we retrieved all PubMed entries satisfying the filters: RCT; human; abstract available; and English language (n=322,107. For the DS subsample, we randomly sampled 500 entries from the large sample. The large sample was evaluated with a lower rigor, higher throughput (RLOTHI method using search heuristics, while the subsample was evaluated using a higher rigor, lower throughput (RHITLO human rating method. Multiple imputation of the missing-completely-at-random RHITLO data for the large sample was informed by: RHITLO data from the subsample; RLOTHI data from the large sample; whether a study was an RCT; and country and year of publication. RESULTS: The RHITLO and RLOTHI methods in the subsample largely agreed (phi coefficients: title=1.00, abstract=0.92. Compliance with abstract and title criteria has increased over time, with non-US countries improving more rapidly. DS+MI logistic regression estimates were more precise than subsample estimates (e.g., 95% CI for change in title and abstract compliance by Year: subsample RHITLO 1.050-1.174 vs. DS+MI 1.082-1.151. As evidence of improved accuracy, DS+MI coefficient estimates were closer to RHITLO than the large sample RLOTHI. CONCLUSIONS: Our results support our hypothesis that DS+MI would result in improved precision and accuracy. This method is flexible and may provide a practical way to examine large corpora of

17. Multiple imputation of rainfall missing data in the Iberian Mediterranean context

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Miró, Juan Javier; Caselles, Vicente; Estrela, María José

2017-11-01

Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Júcar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfall estimation. A classification of precipitation according to their genetic origin was applied as pre-processing, and a quantile-mapping adjusting as post-processing technique. The results showed in general a better performance for the non-linear and hybrid methods, highlighting that the non-linear PCA (NLPCA) method outperforms considerably the Self Organizing Maps (SOM) method within non-linear approaches. On linear methods, the Regularized Expectation Maximization method (RegEM) was the best, but far from NLPCA. Applying EOF filtering as post-processing of NLPCA (hybrid approach) yielded the best results.

18. Multiple imputation for estimating the risk of developing dementia and its impact on survival.

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Yu, Binbing; Saczynski, Jane S; Launer, Lenore

2010-10-01

Dementia, Alzheimer's disease in particular, is one of the major causes of disability and decreased quality of life among the elderly and a leading obstacle to successful aging. Given the profound impact on public health, much research has focused on the age-specific risk of developing dementia and the impact on survival. Early work has discussed various methods of estimating age-specific incidence of dementia, among which the illness-death model is popular for modeling disease progression. In this article we use multiple imputation to fit multi-state models for survival data with interval censoring and left truncation. This approach allows semi-Markov models in which survival after dementia depends on onset age. Such models can be used to estimate the cumulative risk of developing dementia in the presence of the competing risk of dementia-free death. Simulations are carried out to examine the performance of the proposed method. Data from the Honolulu Asia Aging Study are analyzed to estimate the age-specific and cumulative risks of dementia and to examine the effect of major risk factors on dementia onset and death.

19. Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

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Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

2018-03-01

Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

20. A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to the Lewis et al. article in JOS 2014

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He Yulei

2016-03-01

Full Text Available Multiple imputation is a popular approach to handling missing data. Although it was originally motivated by survey nonresponse problems, it has been readily applied to other data settings. However, its general behavior still remains unclear when applied to survey data with complex sample designs, including clustering. Recently, Lewis et al. (2014 compared single- and multiple-imputation analyses for certain incomplete variables in the 2008 National Ambulatory Medicare Care Survey, which has a nationally representative, multistage, and clustered sampling design. Their study results suggested that the increase of the variance estimate due to multiple imputation compared with single imputation largely disappears for estimates with large design effects. We complement their empirical research by providing some theoretical reasoning. We consider data sampled from an equally weighted, single-stage cluster design and characterize the process using a balanced, one-way normal random-effects model. Assuming that the missingness is completely at random, we derive analytic expressions for the within- and between-multiple-imputation variance estimators for the mean estimator, and thus conveniently reveal the impact of design effects on these variance estimators. We propose approximations for the fraction of missing information in clustered samples, extending previous results for simple random samples. We discuss some generalizations of this research and its practical implications for data release by statistical agencies.

1. Combining item response theory with multiple imputation to equate health assessment questionnaires.

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Gu, Chenyang; Gutman, Roee

2017-09-01

The assessment of patients' functional status across the continuum of care requires a common patient assessment tool. However, assessment tools that are used in various health care settings differ and cannot be easily contrasted. For example, the Functional Independence Measure (FIM) is used to evaluate the functional status of patients who stay in inpatient rehabilitation facilities, the Minimum Data Set (MDS) is collected for all patients who stay in skilled nursing facilities, and the Outcome and Assessment Information Set (OASIS) is collected if they choose home health care provided by home health agencies. All three instruments or questionnaires include functional status items, but the specific items, rating scales, and instructions for scoring different activities vary between the different settings. We consider equating different health assessment questionnaires as a missing data problem, and propose a variant of predictive mean matching method that relies on Item Response Theory (IRT) models to impute unmeasured item responses. Using real data sets, we simulated missing measurements and compared our proposed approach to existing methods for missing data imputation. We show that, for all of the estimands considered, and in most of the experimental conditions that were examined, the proposed approach provides valid inferences, and generally has better coverages, relatively smaller biases, and shorter interval estimates. The proposed method is further illustrated using a real data set. © 2016, The International Biometric Society.

2. An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.

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Guo, Wei-Li; Huang, De-Shuang

2017-08-22

Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular processes and disease. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) enables genome-wide identification of in vivo TF binding sites. However, it is still difficult to map every TF in every cell line owing to cost and biological material availability, which poses an enormous obstacle for integrated analysis of gene regulation. To address this problem, we propose a novel computational approach, TFBSImpute, for predicting additional TF binding profiles by leveraging information from available ChIP-seq TF binding data. TFBSImpute fuses the dataset to a 3-mode tensor and imputes missing TF binding signals via simultaneous completion of multiple TF binding matrices with positional consistency. We show that signals predicted by our method achieve overall similarity with experimental data and that TFBSImpute significantly outperforms baseline approaches, by assessing the performance of imputation methods against observed ChIP-seq TF binding profiles. Besides, motif analysis shows that TFBSImpute preforms better in capturing binding motifs enriched in observed data compared with baselines, indicating that the higher performance of TFBSImpute is not simply due to averaging related samples. We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease.

3. Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic.

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Hopke, P K; Liu, C; Rubin, D B

2001-03-01

Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.

4. Identifying TF-MiRNA Regulatory Relationships Using Multiple Features.

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Mingyu Shao

Full Text Available MicroRNAs are known to play important roles in the transcriptional and post-transcriptional regulation of gene expression. While intensive research has been conducted to identify miRNAs and their target genes in various genomes, there is only limited knowledge about how microRNAs are regulated. In this study, we construct a pipeline that can infer the regulatory relationships between transcription factors and microRNAs from ChIP-Seq data with high confidence. In particular, after identifying candidate peaks from ChIP-Seq data, we formulate the inference as a PU learning (learning from only positive and unlabeled examples problem. Multiple features including the statistical significance of the peaks, the location of the peaks, the transcription factor binding site motifs, and the evolutionary conservation are derived from peaks for training and prediction. To further improve the accuracy of our inference, we also apply a mean reciprocal rank (MRR-based method to the candidate peaks. We apply our pipeline to infer TF-miRNA regulatory relationships in mouse embryonic stem cells. The experimental results show that our approach provides very specific findings of TF-miRNA regulatory relationships.

5. Multiple Imputation of Groundwater Data to Evaluate Spatial and Temporal Anthropogenic Influences on Subsurface Water Fluxes in Los Angeles, CA

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Manago, K. F.; Hogue, T. S.; Hering, A. S.

2014-12-01

In the City of Los Angeles, groundwater accounts for 11% of the total water supply on average, and 30% during drought years. Due to ongoing drought in California, increased reliance on local water supply highlights the need for better understanding of regional groundwater dynamics and estimating sustainable groundwater supply. However, in an urban setting, such as Los Angeles, understanding or modeling groundwater levels is extremely complicated due to various anthropogenic influences such as groundwater pumping, artificial recharge, landscape irrigation, leaking infrastructure, seawater intrusion, and extensive impervious surfaces. This study analyzes anthropogenic effects on groundwater levels using groundwater monitoring well data from the County of Los Angeles Department of Public Works. The groundwater data is irregularly sampled with large gaps between samples, resulting in a sparsely populated dataset. A multiple imputation method is used to fill the missing data, allowing for multiple ensembles and improved error estimates. The filled data is interpolated to create spatial groundwater maps utilizing information from all wells. The groundwater data is evaluated at a monthly time step over the last several decades to analyze the effect of land cover and identify other influencing factors on groundwater levels spatially and temporally. Preliminary results show irrigated parks have the largest influence on groundwater fluctuations, resulting in large seasonal changes, exceeding changes in spreading grounds. It is assumed that these fluctuations are caused by watering practices required to sustain non-native vegetation. Conversely, high intensity urbanized areas resulted in muted groundwater fluctuations and behavior decoupling from climate patterns. Results provides improved understanding of anthropogenic effects on groundwater levels in addition to providing high quality datasets for validation of regional groundwater models.

6. Post-transcriptional generation of miRNA variants by multiple nucleotidyl transferases contributes to miRNA transcriptome complexity.

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Wyman, Stacia K; Knouf, Emily C; Parkin, Rachael K; Fritz, Brian R; Lin, Daniel W; Dennis, Lucas M; Krouse, Michael A; Webster, Philippa J; Tewari, Muneesh

2011-09-01

Modification of microRNA sequences by the 3' addition of nucleotides to generate so-called "isomiRs" adds to the complexity of miRNA function, with recent reports showing that 3' modifications can influence miRNA stability and efficiency of target repression. Here, we show that the 3' modification of miRNAs is a physiological and common post-transcriptional event that shows selectivity for specific miRNAs and is observed across species ranging from C. elegans to human. The modifications result predominantly from adenylation and uridylation and are seen across tissue types, disease states, and developmental stages. To quantitatively profile 3' nucleotide additions, we developed and validated a novel assay based on NanoString Technologies' nCounter platform. For certain miRNAs, the frequency of modification was altered by processes such as cell differentiation, indicating that 3' modification is a biologically regulated process. To investigate the mechanism of 3' nucleotide additions, we used RNA interference to screen a panel of eight candidate miRNA nucleotidyl transferases for 3' miRNA modification activity in human cells. Multiple enzymes, including MTPAP, PAPD4, PAPD5, ZCCHC6, ZCCHC11, and TUT1, were found to govern 3' nucleotide addition to miRNAs in a miRNA-specific manner. Three of these enzymes-MTPAP, ZCCHC6, and TUT1-have not previously been known to modify miRNAs. Collectively, our results indicate that 3' modification observed in next-generation small RNA sequencing data is a biologically relevant process, and identify enzymatic mechanisms that may lead to new approaches for modulating miRNA activity in vivo.

7. Analyzing the Impacts of Alternated Number of Iterations in Multiple Imputation Method on Explanatory Factor Analysis

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Duygu KOÇAK

2017-11-01

Full Text Available The study aims to identify the effects of iteration numbers used in multiple iteration method, one of the methods used to cope with missing values, on the results of factor analysis. With this aim, artificial datasets of different sample sizes were created. Missing values at random and missing values at complete random were created in various ratios by deleting data. For the data in random missing values, a second variable was iterated at ordinal scale level and datasets with different ratios of missing values were obtained based on the levels of this variable. The data were generated using “psych” program in R software, while “dplyr” program was used to create codes that would delete values according to predetermined conditions of missing value mechanism. Different datasets were generated by applying different iteration numbers. Explanatory factor analysis was conducted on the datasets completed and the factors and total explained variances are presented. These values were first evaluated based on the number of factors and total variance explained of the complete datasets. The results indicate that multiple iteration method yields a better performance in cases of missing values at random compared to datasets with missing values at complete random. Also, it was found that increasing the number of iterations in both missing value datasets decreases the difference in the results obtained from complete datasets.

8. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

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Lazar, Cosmin; Gatto, Laurent; Ferro, Myriam; Bruley, Christophe; Burger, Thomas

2016-04-01

Missing values are a genuine issue in label-free quantitative proteomics. Recent works have surveyed the different statistical methods to conduct imputation and have compared them on real or simulated data sets and recommended a list of missing value imputation methods for proteomics application. Although insightful, these comparisons do not account for two important facts: (i) depending on the proteomics data set, the missingness mechanism may be of different natures and (ii) each imputation method is devoted to a specific type of missingness mechanism. As a result, we believe that the question at stake is not to find the most accurate imputation method in general but instead the most appropriate one. We describe a series of comparisons that support our views: For instance, we show that a supposedly "under-performing" method (i.e., giving baseline average results), if applied at the "appropriate" time in the data-processing pipeline (before or after peptide aggregation) on a data set with the "appropriate" nature of missing values, can outperform a blindly applied, supposedly "better-performing" method (i.e., the reference method from the state-of-the-art). This leads us to formulate few practical guidelines regarding the choice and the application of an imputation method in a proteomics context.

9. Arabidopsis ARGONAUTE7 selects miR390 through multiple checkpoints during RISC assembly.

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Endo, Yayoi; Iwakawa, Hiro-oki; Tomari, Yukihide

2013-07-01

Plant ARGONAUTE7 (AGO7) assembles RNA-induced silencing complex (RISC) specifically with miR390 and regulates the auxin-signalling pathway via production of TAS3 trans-acting siRNAs (tasiRNAs). However, how AGO7 discerns miR390 among other miRNAs remains unclear. Here, we show that the 5' adenosine of miR390 and the central region of miR390/miR390* duplex are critical for the specific interaction with AGO7. Furthermore, despite the existence of mismatches in the seed and central regions of the duplex, cleavage of the miR390* strand is required for maturation of AGO7-RISC. These findings suggest that AGO7 uses multiple checkpoints to select miR390, thereby circumventing promiscuous tasiRNA production.

10. miR-186 inhibits cell proliferation in multiple myeloma by repressing Jagged1

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Liu, Zengyan; Zhang, Guoqiang; Yu, Wenzheng; Gao, Na; Peng, Jun

2016-01-01

MicroRNAs (miRNAs) are small, noncoding ribonucleic acids that regulate gene expression by targeting mRNAs for translational repression and degradation. Accumulating experimental evidence supports a causal role of miRNAs in hematology tumorigenesis. However, the specific functions of miRNAs in the pathogenesis of multiple myeloma (MM) remain to be established. In this study, we demonstrated that miR-186 is commonly downregulated in MM cell lines and patient MM cells. Ectopic expression of miR-186 significantly inhibited cell growth, both in vitro and in vivo, and induced cell cycle G_0/G_1 arrest. Furthermore, miR-186 induced downregulation of Jagged1 protein expression by directly targeting its 3′-untranslated region (3′-UTR). Conversely, overexpression of Jagged1 rescued cells from miR-186-induced growth inhibition. Our collective results clearly indicate that miR-186 functions as a tumor suppressor in MM, supporting its potential as a therapeutic target for the disease. - Highlights: • miR-186 expression is decreased in MM. • miR-186 inhibits MM cell proliferation in vitro and in vivo. • Jagged1 is regulated by miR-186. • Overexpression of Jagged1 reverses the effects of miR-186.

11. miR-186 inhibits cell proliferation in multiple myeloma by repressing Jagged1

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Liu, Zengyan [Department of Hematology, Qilu Hospital, Shandong University, 107 Wenhuaxi Road, Jinan, Shandong 250012 (China); Department of Hematology, Hospital Affiliated to Binzhou Medical University, 661 Second Huanghe Street, Binzhou 256603 (China); Zhang, Guoqiang [Department of Thyroid and Breast Surgery, Hospital Affiliated to Binzhou Medical University, 661 Second Huanghe Street, Binzhou 256603 (China); Yu, Wenzheng; Gao, Na [Department of Hematology, Hospital Affiliated to Binzhou Medical University, 661 Second Huanghe Street, Binzhou 256603 (China); Peng, Jun, E-mail: junpeng885@sina.com [Department of Hematology, Qilu Hospital, Shandong University, 107 Wenhuaxi Road, Jinan, Shandong 250012 (China)

2016-01-15

MicroRNAs (miRNAs) are small, noncoding ribonucleic acids that regulate gene expression by targeting mRNAs for translational repression and degradation. Accumulating experimental evidence supports a causal role of miRNAs in hematology tumorigenesis. However, the specific functions of miRNAs in the pathogenesis of multiple myeloma (MM) remain to be established. In this study, we demonstrated that miR-186 is commonly downregulated in MM cell lines and patient MM cells. Ectopic expression of miR-186 significantly inhibited cell growth, both in vitro and in vivo, and induced cell cycle G{sub 0}/G{sub 1} arrest. Furthermore, miR-186 induced downregulation of Jagged1 protein expression by directly targeting its 3′-untranslated region (3′-UTR). Conversely, overexpression of Jagged1 rescued cells from miR-186-induced growth inhibition. Our collective results clearly indicate that miR-186 functions as a tumor suppressor in MM, supporting its potential as a therapeutic target for the disease. - Highlights: • miR-186 expression is decreased in MM. • miR-186 inhibits MM cell proliferation in vitro and in vivo. • Jagged1 is regulated by miR-186. • Overexpression of Jagged1 reverses the effects of miR-186.

12. Education and health and well-being: direct and indirect effects with multiple mediators and interactions with multiple imputed data in Stata.

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Sheikh, Mashhood Ahmed; Abelsen, Birgit; Olsen, Jan Abel

2017-11-01

Previous methods for assessing mediation assume no multiplicative interactions. The inverse odds weighting (IOW) approach has been presented as a method that can be used even when interactions exist. The substantive aim of this study was to assess the indirect effect of education on health and well-being via four indicators of adult socioeconomic status (SES): income, management position, occupational hierarchy position and subjective social status. 8516 men and women from the Tromsø Study (Norway) were followed for 17 years. Education was measured at age 25-74 years, while SES and health and well-being were measured at age 42-91 years. Natural direct and indirect effects (NIE) were estimated using weighted Poisson regression models with IOW. Stata code is provided that makes it easy to assess mediation in any multiple imputed dataset with multiple mediators and interactions. Low education was associated with lower SES. Consequently, low SES was associated with being unhealthy and having a low level of well-being. The effect (NIE) of education on health and well-being is mediated by income, management position, occupational hierarchy position and subjective social status. This study contributes to the literature on mediation analysis, as well as the literature on the importance of education for health-related quality of life and subjective well-being. The influence of education on health and well-being had different pathways in this Norwegian sample. © 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.

13. Multiply-Imputed Synthetic Data: Advice to the Imputer

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Loong Bronwyn

2017-12-01

Full Text Available Several statistical agencies have started to use multiply-imputed synthetic microdata to create public-use data in major surveys. The purpose of doing this is to protect the confidentiality of respondents’ identities and sensitive attributes, while allowing standard complete-data analyses of microdata. A key challenge, faced by advocates of synthetic data, is demonstrating that valid statistical inferences can be obtained from such synthetic data for non-confidential questions. Large discrepancies between observed-data and synthetic-data analytic results for such questions may arise because of uncongeniality; that is, differences in the types of inputs available to the imputer, who has access to the actual data, and to the analyst, who has access only to the synthetic data. Here, we discuss a simple, but possibly canonical, example of uncongeniality when using multiple imputation to create synthetic data, which specifically addresses the choices made by the imputer. An initial, unanticipated but not surprising, conclusion is that non-confidential design information used to impute synthetic data should be released with the confidential synthetic data to allow users of synthetic data to avoid possible grossly conservative inferences.

14. Dealing with missing data in a multi-question depression scale: a comparison of imputation methods

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Stuart Heather

2006-12-01

Full Text Available Abstract Background Missing data present a challenge to many research projects. The problem is often pronounced in studies utilizing self-report scales, and literature addressing different strategies for dealing with missing data in such circumstances is scarce. The objective of this study was to compare six different imputation techniques for dealing with missing data in the Zung Self-reported Depression scale (SDS. Methods 1580 participants from a surgical outcomes study completed the SDS. The SDS is a 20 question scale that respondents complete by circling a value of 1 to 4 for each question. The sum of the responses is calculated and respondents are classified as exhibiting depressive symptoms when their total score is over 40. Missing values were simulated by randomly selecting questions whose values were then deleted (a missing completely at random simulation. Additionally, a missing at random and missing not at random simulation were completed. Six imputation methods were then considered; 1 multiple imputation, 2 single regression, 3 individual mean, 4 overall mean, 5 participant's preceding response, and 6 random selection of a value from 1 to 4. For each method, the imputed mean SDS score and standard deviation were compared to the population statistics. The Spearman correlation coefficient, percent misclassified and the Kappa statistic were also calculated. Results When 10% of values are missing, all the imputation methods except random selection produce Kappa statistics greater than 0.80 indicating 'near perfect' agreement. MI produces the most valid imputed values with a high Kappa statistic (0.89, although both single regression and individual mean imputation also produced favorable results. As the percent of missing information increased to 30%, or when unbalanced missing data were introduced, MI maintained a high Kappa statistic. The individual mean and single regression method produced Kappas in the 'substantial agreement' range

15. Simultaneous inhibition of multiple oncogenic miRNAs by a multi-potent microRNA sponge.

Science.gov (United States)

Jung, Jaeyun; Yeom, Chanjoo; Choi, Yeon-Sook; Kim, Sinae; Lee, EunJi; Park, Min Ji; Kang, Sang Wook; Kim, Sung Bae; Chang, Suhwan

2015-08-21

The roles of oncogenic miRNAs are widely recognized in many cancers. Inhibition of single miRNA using antagomiR can efficiently knock-down a specific miRNA. However, the effect is transient and often results in subtle phenotype, as there are other miRNAs contribute to tumorigenesis. Here we report a multi-potent miRNA sponge inhibiting multiple miRNAs simultaneously. As a model system, we targeted miR-21, miR-155 and miR-221/222, known as oncogenic miRNAs in multiple tumors including breast and pancreatic cancers. To achieve efficient knockdown, we generated perfect and bulged-matched miRNA binding sites (MBS) and introduced multiple copies of MBS, ranging from one to five, in the multi-potent miRNA sponge. Luciferase reporter assay showed the multi-potent miRNA sponge efficiently inhibited 4 miRNAs in breast and pancreatic cancer cells. Furthermore, a stable and inducible version of the multi-potent miRNA sponge cell line showed the miRNA sponge efficiently reduces the level of 4 target miRNAs and increase target protein level of these oncogenic miRNAs. Finally, we showed the miRNA sponge sensitize cells to cancer drug and attenuate cell migratory activity. Altogether, our study demonstrates the multi-potent miRNA sponge is a useful tool to examine the functional impact of simultaneous inhibition of multiple miRNAs and proposes a therapeutic potential.

16. Flexible Imputation of Missing Data

CERN Document Server

van Buuren, Stef

2012-01-01

Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science--multiple imputation--fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise. Flexible Imputation of Missing Data is supported by many examples using real data taken from the author's vast experience of collaborative research, and presents a practical guide for handling missing data unde

17. Missing data imputation: focusing on single imputation.

Science.gov (United States)

Zhang, Zhongheng

2016-01-01

Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation. Imputations with mean, median and mode are simple but, like complete case analysis, can introduce bias on mean and deviation. Furthermore, they ignore relationship with other variables. Regression imputation can preserve relationship between missing values and other variables. There are many sophisticated methods exist to handle missing values in longitudinal data. This article focuses primarily on how to implement R code to perform single imputation, while avoiding complex mathematical calculations.

18. Multiple Regression Analysis of mRNA-miRNA Associations in Colorectal Cancer Pathway

Science.gov (United States)

Wang, Fengfeng; Wong, S. C. Cesar; Chan, Lawrence W. C.; Cho, William C. S.; Yip, S. P.; Yung, Benjamin Y. M.

2014-01-01

Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC. PMID:24895601

19. miR-181a regulates multiple pathways in hypopharyngeal ...

African Journals Online (AJOL)

Expression of four pathway reporters were significantly increased (p53/DNA damage, TGFβ, MAPK/ERK and MAPK/JNK), while expression of two pathway reporters were decreased (Wnt and NFkB) upon miR-181a down-regulation. Notch, Myc/Max, hypoxia and cell cycle/pRB-E2F pathways were not significantly affected ...

20. Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Science.gov (United States)

Shi, Hongbo; Zhang, Guangde; Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

1. Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Directory of Open Access Journals (Sweden)

Hongbo Shi

Full Text Available MicroRNAs (miRNAs play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

2. Estimating Classification Errors Under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC

Directory of Open Access Journals (Sweden)

Boeschoten Laura

2017-12-01

Full Text Available Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible combinations with scores on other variables. Furthermore, the latent class model, by multiply imputing a new variable, enhances the quality of statistics based on the composite data set. The performance of this method is investigated by a simulation study, which shows that whether or not the method can be applied depends on the entropy R2 of the latent class model and the type of analysis a researcher is planning to do. Finally, the method is applied to public data from Statistics Netherlands.

3. A Comparison of Joint Model and Fully Conditional Specification Imputation for Multilevel Missing Data

Science.gov (United States)

Mistler, Stephen A.; Enders, Craig K.

2017-01-01

Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional…

4. MiRroring the Multiple Potentials of MicroRNAs in Acute Myocardial Infarction

Directory of Open Access Journals (Sweden)

Solenne Paiva

2017-11-01

as AMI diagnostic or prognostic biomarkers. Furthermore, a precise combo was shown to be powerful enough to transdifferentiate human fibroblasts into CMs opening doors in the therapeutics. Following these discoveries, they also emerged as optional tools to transfect in order to mature CMs derived from pluripotent stem cells. Ultimately, the multiple potentials carried by the myomiRs miR-1; miR-133; miR-208a/b; and miR-499a still remain to be fully unveiled.

5. Identification of Subtype Specific miRNA-mRNA Functional Regulatory Modules in Matched miRNA-mRNA Expression Data: Multiple Myeloma as a Case

Directory of Open Access Journals (Sweden)

Yunpeng Zhang

2015-01-01

Full Text Available Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong algorithm and multiobjective genetic algorithm to identify subtype specific miRNA-mRNA functional regulatory modules (MFRMs through integrative analysis of three biological data sets: GO biological processes, miRNA target information, and matched miRNA and mRNA expression data. We applied our method on a heterogeneous disease, multiple myeloma (MM, to identify MM subtype specific MFRMs. The constructed miRNA-mRNA regulatory networks provide modular outlook at subtype specific miRNA-mRNA interactions. Furthermore, clustering analysis demonstrated that heterogeneous MFRMs were able to separate corresponding MM subtypes. These subtype specific MFRMs may aid in the further elucidation of the pathogenesis of each subtype and may serve to guide MM subtype diagnosis and treatment.

6. Multiple Myeloma-Derived Exosomes Regulate the Functions of Mesenchymal Stem Cells Partially via Modulating miR-21 and miR-146a

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Qian Cheng

2017-01-01

Full Text Available Exosomes derived from cancer cells can affect various functions of mesenchymal stem cells (MSCs via conveying microRNAs (miRs. miR-21 and miR-146a have been demonstrated to regulate MSC proliferation and transformation. Interleukin-6 (IL-6 secreted from transformed MSCs in turn favors the survival of multiple myeloma (MM cells. However, the effects of MM exosomes on MSC functions remain largely unclear. In this study, we investigated the effects of OPM2 (a MM cell line exosomes (OPM2-exo on regulating the proliferation, cancer-associated fibroblast (CAF transformation, and IL-6 secretion of MSCs and determined the role of miR-21 and miR-146a in these effects. We found that OPM2-exo harbored high levels of miR-21 and miR-146a and that OPM2-exo coculture significantly increased MSC proliferation with upregulation of miR-21 and miR-146a. Moreover, OPM2-exo induced CAF transformation of MSCs, which was evidenced by increased fibroblast-activated protein (FAP, α-smooth muscle actin (α-SMA, and stromal-derived factor 1 (SDF-1 expressions and IL-6 secretion. Inhibition of miR-21 or miR-146a reduced these effects of OPM2-exo on MSCs. In conclusion, MM could promote the proliferation, CAF transformation, and IL-6 secretion of MSCs partially through regulating miR21 and miR146a.

7. A note on the relationships between multiple imputation, maximum likelihood and fully Bayesian methods for missing responses in linear regression models.

Science.gov (United States)

Chen, Qingxia; Ibrahim, Joseph G

2014-07-01

Multiple Imputation, Maximum Likelihood and Fully Bayesian methods are the three most commonly used model-based approaches in missing data problems. Although it is easy to show that when the responses are missing at random (MAR), the complete case analysis is unbiased and efficient, the aforementioned methods are still commonly used in practice for this setting. To examine the performance of and relationships between these three methods in this setting, we derive and investigate small sample and asymptotic expressions of the estimates and standard errors, and fully examine how these estimates are related for the three approaches in the linear regression model when the responses are MAR. We show that when the responses are MAR in the linear model, the estimates of the regression coefficients using these three methods are asymptotically equivalent to the complete case estimates under general conditions. One simulation and a real data set from a liver cancer clinical trial are given to compare the properties of these methods when the responses are MAR.

8. An integrative genomic approach reveals coordinated expression of intronic miR-335, miR-342, and miR-561 with deregulated host genes in multiple myeloma

Directory of Open Access Journals (Sweden)

Agnelli Luca

2008-08-01

Full Text Available Abstract Background The role of microRNAs (miRNAs in multiple myeloma (MM has yet to be fully elucidated. To identify miRNAs that are potentially deregulated in MM, we investigated those mapping within transcription units, based on evidence that intronic miRNAs are frequently coexpressed with their host genes. To this end, we monitored host transcript expression values in a panel of 20 human MM cell lines (HMCLs and focused on transcripts whose expression varied significantly across the dataset. Methods miRNA expression was quantified by Quantitative Real-Time PCR. Gene expression and genome profiling data were generated on Affymetrix oligonucleotide microarrays. Significant Analysis of Microarrays algorithm was used to investigate differentially expressed transcripts. Conventional statistics were used to test correlations for significance. Public libraries were queried to predict putative miRNA targets. Results We identified transcripts specific to six miRNA host genes (CCPG1, GULP1, EVL, TACSTD1, MEST, and TNIK whose average changes in expression varied at least 2-fold from the mean of the examined dataset. We evaluated the expression levels of the corresponding intronic miRNAs and identified a significant correlation between the expression levels of MEST, EVL, and GULP1 and those of the corresponding miRNAs miR-335, miR-342-3p, and miR-561, respectively. Genome-wide profiling of the 20 HMCLs indicated that the increased expression of the three host genes and their corresponding intronic miRNAs was not correlated with local copy number variations. Notably, miRNAs and their host genes were overexpressed in a fraction of primary tumors with respect to normal plasma cells; however, this finding was not correlated with known molecular myeloma groups. The predicted putative miRNA targets and the transcriptional profiles associated with the primary tumors suggest that MEST/miR-335 and EVL/miR-342-3p may play a role in plasma cell homing and

9. Post-transcriptional generation of miRNA variants by multiple nucleotidyl transferases contributes to miRNA transcriptome complexity

OpenAIRE

Wyman, Stacia K.; Knouf, Emily C.; Parkin, Rachael K.; Fritz, Brian R.; Lin, Daniel W.; Dennis, Lucas M.; Krouse, Michael A.; Webster, Philippa J.; Tewari, Muneesh

2011-01-01

Modification of microRNA sequences by the 3′ addition of nucleotides to generate so-called “isomiRs” adds to the complexity of miRNA function, with recent reports showing that 3′ modifications can influence miRNA stability and efficiency of target repression. Here, we show that the 3′ modification of miRNAs is a physiological and common post-transcriptional event that shows selectivity for specific miRNAs and is observed across species ranging from C. elegans to human. The modifications resul...

10. miR-137 inhibits the invasion of melanoma cells through downregulation of multiple oncogenic target genes.

Science.gov (United States)

Luo, Chonglin; Tetteh, Paul W; Merz, Patrick R; Dickes, Elke; Abukiwan, Alia; Hotz-Wagenblatt, Agnes; Holland-Cunz, Stefan; Sinnberg, Tobias; Schittek, Birgit; Schadendorf, Dirk; Diederichs, Sven; Eichmüller, Stefan B

2013-03-01

MicroRNAs are small noncoding RNAs that regulate gene expression and have important roles in various types of cancer. Previously, miR-137 was reported to act as a tumor suppressor in different cancers, including malignant melanoma. In this study, we show that low miR-137 expression is correlated with poor survival in stage IV melanoma patients. We identified and validated two genes (c-Met and YB1) as direct targets of miR-137 and confirmed two previously known targets, namely enhancer of zeste homolog 2 (EZH2) and microphthalmia-associated transcription factor (MITF). Functional studies showed that miR-137 suppressed melanoma cell invasion through the downregulation of multiple target genes. The decreased invasion caused by miR-137 overexpression could be phenocopied by small interfering RNA knockdown of EZH2, c-Met, or Y box-binding protein 1 (YB1). Furthermore, miR-137 inhibited melanoma cell migration and proliferation. Finally, miR-137 induced apoptosis in melanoma cell lines and decreased BCL2 levels. In summary, our study confirms that miR-137 acts as a tumor suppressor in malignant melanoma and reveals that miR-137 regulates multiple targets including c-Met, YB1, EZH2, and MITF.

11. MiMC: Efficient encryption and cryptographic hashing with minimal multiplicative complexity

DEFF Research Database (Denmark)

Albrecht, Martin; Grassi, Lorenzo; Rechberger, Christian

2016-01-01

and cryptographic hash functions is to reconsider and simplify the round function of the Knudsen-Nyberg cipher from 1995. The mapping F(x) := x3 is used as the main component there and is also the main component of our family of proposals called “MiMC”. We study various attack vectors for this construction and give...... a new attack vector that outperforms others in relevant settings. Due to its very low number of multiplications, the design lends itself well to a large class of applications, especially when the depth does not matter but the total number of multiplications in the circuit dominates all aspects...

12. MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.

Science.gov (United States)

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-12

Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases. Especially, constructing computational methods to predict potential miRNA-disease associations is worthy of more studies because of the feasibility and effectivity. In this work, we developed a novel computational model of multiple kernels learning-based Kronecker regularized least squares for MiRNA-disease association prediction (MKRMDA), which could reveal potential miRNA-disease associations by automatically optimizing the combination of multiple kernels for disease and miRNA. MKRMDA obtained AUCs of 0.9040 and 0.8446 in global and local leave-one-out cross validation, respectively. Meanwhile, MKRMDA achieved average AUCs of 0.8894 ± 0.0015 in fivefold cross validation. Furthermore, we conducted three different kinds of case studies on some important human cancers for further performance evaluation. In the case studies of colonic cancer, esophageal cancer and lymphoma based on known miRNA-disease associations in HMDDv2.0 database, 76, 94 and 88% of the corresponding top 50 predicted miRNAs were confirmed by experimental reports, respectively. In another two kinds of case studies for new diseases without any known associated miRNAs and diseases only with known associations in HMDDv1.0 database, the verified ratios of two different cancers were 88 and 94%, respectively. All the results mentioned above adequately showed the reliable prediction ability of MKRMDA. We anticipated that MKRMDA could serve to facilitate further developments in the field and the follow-up investigations by biomedical researchers.

13. Public Undertakings and Imputability

DEFF Research Database (Denmark)

Ølykke, Grith Skovgaard

2013-01-01

In this article, the issue of impuability to the State of public undertakings’ decision-making is analysed and discussed in the context of the DSBFirst case. DSBFirst is owned by the independent public undertaking DSB and the private undertaking FirstGroup plc and won the contracts in the 2008...... Oeresund tender for the provision of passenger transport by railway. From the start, the services were provided at a loss, and in the end a part of DSBFirst was wound up. In order to frame the problems illustrated by this case, the jurisprudence-based imputability requirement in the definition of State aid...... in Article 107(1) TFEU is analysed. It is concluded that where the public undertaking transgresses the control system put in place by the State, conditions for imputability are not fulfilled, and it is argued that in the current state of law, there is no conditional link between the level of control...

14. Missing value imputation for epistatic MAPs

LENUS (Irish Health Repository)

Ryan, Colm

2010-04-20

expands the number of mapped epistatic interactions. In addition we make implementations of our algorithms available for use by other researchers. Conclusions We address the problem of missing value imputation for E-MAPs, and suggest the use of symmetric nearest neighbor based approaches as they offer consistently accurate imputations across multiple datasets in a tractable manner.

15. PSMB4 promotes multiple myeloma cell growth by activating NF-κB-miR-21 signaling

Energy Technology Data Exchange (ETDEWEB)

Zheng, Peihao; Guo, Honggang [Department of Hematology, Navy General Hospital, Beijing 100048 (China); Li, Guangchao [School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510006 (China); Han, Siqi [Department of Medical Oncology, Jinling Hospital, Nanjing 210002 (China); Luo, Fei [Department of Stomatology, Jinling Hospital, Nanjing 210002 (China); Liu, Yi, E-mail: liuyi2033@163.com [Department of Hematology, Navy General Hospital, Beijing 100048 (China)

2015-03-06

Proteasomal subunit PSMB4, was recently identified as potential cancer driver genes in several tumors. However, the regulatory mechanism of PSMB4 on carcinogenesis process remains unclear. In this study, we investigated the expression and roles of PSMB4 in multiple myeloma (MM). We found a significant up-regulation of PSMB4 in MM plasma and cell lines. Ectopic overexpression of PSMB4 promoted cell growth and colony forming ability of MM cells, whereas inhibition of PSMB4 led to a decrease of such events. Furthermore, our results demonstrated the up-regulation of miR-21 and a positive correlation between the levels of miR-21 and PSMB4 in MM. Re-expression of miR-21 markedly rescued PSMB4 knockdown-mediated suppression of cell proliferation and clone-formation. Additionally, while enforced expression of PSMB4 profoundly increased NF-κB activity and the level of miR-21, PSMB4 knockdown or NF-κB inhibition suppressed miR-21 expression in MM cells. Taken together, our results demonstrated that PSMB4 regulated MM cell growth in part by activating NF-κB-miR-21 signaling, which may represent promising targets for novel specific therapies. - Highlights: • First reported upregulation of PSMB4 in MM plasma and cell lines. • PSMB4 promoted MM cell growth and colony forming ability. • Further found miR-21 was up-regulated by PSMB4 in MM plasma and cell lines. • PSMB4-induced miR-21 expression was modulated by NF-κB. • PSMB4-NF-κB-miR-21 axis may be potential therapeutic targets of MM.

16. BRITS: Bidirectional Recurrent Imputation for Time Series

OpenAIRE

Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

2018-01-01

Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...

17. MiR-155 Enhances Insulin Sensitivity by Coordinated Regulation of Multiple Genes in Mice

Science.gov (United States)

Lin, Taoyan; Lin, Xia; Chen, Li; Zeng, Hui; Han, Yanjiang; Wu, Lihong; Huang, Shun; Wang, Meng; Huang, Shenhao; Xie, Raoying; Liang, Liqi; Liu, Yu; Liu, Ruiyu; Zhang, Tingting; Li, Jing; Wang, Shengchun; Sun, Penghui; Huang, Wenhua; Yao, Kaitai; Xu, Kang; Du, Tao; Xiao, Dong

2016-01-01

miR-155 plays critical roles in numerous physiological and pathological processes, however, its function in the regulation of blood glucose homeostasis and insulin sensitivity and underlying mechanisms remain unknown. Here, we reveal that miR-155 levels are downregulated in serum from type 2 diabetes (T2D) patients, suggesting that miR-155 might be involved in blood glucose control and diabetes. Gain-of-function and loss-of-function studies in mice demonstrate that miR-155 has no effects on the pancreatic β-cell proliferation and function. Global transgenic overexpression of miR-155 in mice leads to hypoglycaemia, improved glucose tolerance and insulin sensitivity. Conversely, miR-155 deficiency in mice causes hyperglycemia, impaired glucose tolerance and insulin resistance. In addition, consistent with a positive regulatory role of miR-155 in glucose metabolism, miR-155 positively modulates glucose uptake in all cell types examined, while mice overexpressing miR-155 transgene show enhanced glycolysis, and insulin-stimulated AKT and IRS-1 phosphorylation in liver, adipose tissue or skeletal muscle. Furthermore, we reveal these aforementioned phenomena occur, at least partially, through miR-155-mediated repression of important negative regulators (i.e. C/EBPβ, HDAC4 and SOCS1) of insulin signaling. Taken together, these findings demonstrate, for the first time, that miR-155 is a positive regulator of insulin sensitivity with potential applications for diabetes treatment. PMID:27711113

18. miR-34a: Multiple Opposing Targets and One Destiny in Hepatocellular Carcinoma.

Science.gov (United States)

Yacoub, Radwa Alaa; Fawzy, Injie Omar; Assal, Reem Amr; Hosny, Karim Adel; Zekri, Abdel-Rahman Nabawy; Esmat, Gamal; El Tayebi, Hend Mohamed; Abdelaziz, Ahmed Ihab

2016-12-28

Background and Aims: The role of miR-34a in hepatocellular carcinoma (HCC) is controversial and several unresolved issues remain, including its expression pattern and relevance to tumor etiology, tumor stage and prognosis, and finally, its impact on apoptosis. Methods: miR-34a expression was assessed in hepatitis C virus (HCV)-induced non-metastatic HCC tissues by RT-Q-PCR. Huh-7 cells were transfected with miR-34a mimics and the impact of miR-34a was examined on 84 pro-apoptotic/anti-apoptotic genes using PCR array; its net effect was tested on cell viability via MTT assay. Results: miR-34a expression was up-regulated in HCC tissues. Moreover, miR-34a induced a large set of pro-apoptotic/anti-apoptotic genes, with a net result of triggering apoptosis and repressing cell viability. Conclusions: HCC-related differential expression of miR-34a could be etiology-based or stage-specific, and low expression of miR-34a may predict poor prognosis. This study's findings also emphasize the role of miR-34a in apoptosis.

19. Comparação de métodos de imputação única e múltipla usando como exemplo um modelo de risco para mortalidade cirúrgica Comparison of simple and multiple imputation methods using a risk model for surgical mortality as example

Directory of Open Access Journals (Sweden)

Luciana Neves Nunes

2010-12-01

sample size was 450 patients. The imputation methods applied were: two single imputations and one multiple imputation and the assumption was MAR (Missing at Random. RESULTS: The variable with missing data was serum albumin with 27.1% of missing rate. The logistic models adjusted by simple imputation were similar, but differed from models obtained by multiple imputation in relation to the inclusion of variables. CONCLUSIONS: The results indicate that it is important to take into account the relationship of albumin to other variables observed, because different models were obtained in single and multiple imputations. Single imputation underestimates the variability generating narrower confidence intervals. It is important to consider the use of imputation methods when there is missing data, especially multiple imputation that takes into account the variability between imputations for estimates of the model.

20. Missing Value Imputation Improves Mortality Risk Prediction Following Cardiac Surgery: An Investigation of an Australian Patient Cohort.

Science.gov (United States)

Karim, Md Nazmul; Reid, Christopher M; Tran, Lavinia; Cochrane, Andrew; Billah, Baki

2017-03-01

The aim of this study was to evaluate the impact of missing values on the prediction performance of the model predicting 30-day mortality following cardiac surgery as an example. Information from 83,309 eligible patients, who underwent cardiac surgery, recorded in the Australia and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database registry between 2001 and 2014, was used. An existing 30-day mortality risk prediction model developed from ANZSCTS database was re-estimated using the complete cases (CC) analysis and using multiple imputation (MI) analysis. Agreement between the risks generated by the CC and MI analysis approaches was assessed by the Bland-Altman method. Performances of the two models were compared. One or more missing predictor variables were present in 15.8% of the patients in the dataset. The Bland-Altman plot demonstrated significant disagreement between the risk scores (prisk of mortality. Compared to CC analysis, MI analysis resulted in an average of 8.5% decrease in standard error, a measure of uncertainty. The MI model provided better prediction of mortality risk (observed: 2.69%; MI: 2.63% versus CC: 2.37%, Pvalues improved the 30-day mortality risk prediction following cardiac surgery. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

1. Identification of miRSNPs associated with the risk of multiple myeloma

DEFF Research Database (Denmark)

Macauda, Angelica; Calvetti, Diego; Maccari, Giuseppe

2017-01-01

to be associated with risk of various types of cancer, but they have never been investigated in MM. We performed an in silico genome-wide search for miRSNPs predicted to alter binding of miRNAs to their target sequences. We selected 12 miRSNPs and tested their association with MM risk. Our study population...... TCF19). Results from IMMEnSE were meta-analyzed with data from a previously published genome-wide association study (GWAS). The SNPs rs13409 (located in the 3'UTR of the POU5F1 gene), rs1419881 (TCF19), rs1049633, rs1049623 (both in DDR1) showed significant associations with MM risk. In conclusion, we...... pathogenesis, and several studies have identified single nucleotide polymorphisms (SNPs) associated with the susceptibility to the disease. SNPs within miRNA-binding sites in target genes (miRSNPs) may alter the strength of miRNA-mRNA interactions, thus deregulating protein expression. MiRSNPs are known...

2. Identification of Subtype Specific miRNA-mRNA Functional Regulatory Modules in Matched miRNA-mRNA Expression Data: Multiple Myeloma as a Case

OpenAIRE

Zhang, Yunpeng; Liu, Wei; Xu, Yanjun; Li, Chunquan; Wang, Yingying; Yang, Haixiu; Zhang, Chunlong; Su, Fei; Li, Yixue; Li, Xia

2015-01-01

Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it i...

3. miR-320a regulates cell proliferation and apoptosis in multiple myeloma by targeting pre-B-cell leukemia transcription factor 3

Energy Technology Data Exchange (ETDEWEB)

Lu, Yinghao [Jiangsu Institute of Hematology, First Affiliated Hospital of Soochow University, Key Laboratory of Thrombosis and Hemostasis Under Ministry of Health, Collaborative Innovation Center of Hematology, Suzhou, 215006 (China); Department of Hematology, Affiliated Hospital of Guizhou Medical University, The Hematopoietic Stem Cell Transplant Center of Guizhou Province, Blood Diseases Diagnosis and Treatment Center of Guizhou Province, Guiyang, 550004, Guizhou Province (China); Wu, Depei, E-mail: wudepei@medmail.com.cn [Jiangsu Institute of Hematology, First Affiliated Hospital of Soochow University, Key Laboratory of Thrombosis and Hemostasis Under Ministry of Health, Collaborative Innovation Center of Hematology, Suzhou, 215006 (China); Wang, Jishi, E-mail: lgylhlyh@aliyun.com [Department of Hematology, Affiliated Hospital of Guizhou Medical University, The Hematopoietic Stem Cell Transplant Center of Guizhou Province, Blood Diseases Diagnosis and Treatment Center of Guizhou Province, Guiyang, 550004, Guizhou Province (China); Li, Yan; Chai, Xiao; Kang, Qian [Department of Hematology, Affiliated Hospital of Guizhou Medical University, The Hematopoietic Stem Cell Transplant Center of Guizhou Province, Blood Diseases Diagnosis and Treatment Center of Guizhou Province, Guiyang, 550004, Guizhou Province (China)

2016-05-13

Aberrant expression of microRNAs (miRNAs) is implicated in cancer development and progression. While miR-320a is reported to be deregulated in many malignancy types, its biological role in multiple myeloma (MM) remains unclear. Here, we observed reduced expression of miR-320a in MM samples and cell lines. Ectopic expression of miR-320a dramatically suppressed cell viability and clonogenicity and induced apoptosis in vitro. Mechanistic investigation led to the identification of Pre-B-cellleukemia transcription factor 3 (PBX3) as a novel and direct downstream target of miR-320a. Interestingly, reintroduction of PBX3 abrogated miR-320a-induced MM cell growth inhibition and apoptosis. In a mouse xenograft model, miR-320a overexpression inhibited tumorigenicity and promoted apoptosis. Our findings collectively indicate that miR-320a inhibits cell proliferation and induces apoptosis in MM cells by directly targeting PBX3, supporting its utility as a novel and potential therapeutic agent for miRNA-based MM therapy. -- Highlights: •Expression of miR-320a in MM cell induces apoptosis in vitro. •miR-320a represses PBX3 via targeting specific sequences in the 3′UTR region. •Exogenous expression of PBX3 reverses the effects of miR-320a in inhibiting MM cell growth and promoting apoptosis. •Overexpression of miR-320a inhibits tumor growth and increases apoptosis in vivo.

4. Synthetic miR-34a mimics as a novel therapeutic agent for multiple myeloma: in vitro and in vivo evidence.

Science.gov (United States)

Di Martino, Maria T; Leone, Emanuela; Amodio, Nicola; Foresta, Umberto; Lionetti, Marta; Pitari, Maria R; Cantafio, Maria E Gallo; Gullà, Annamaria; Conforti, Francesco; Morelli, Eugenio; Tomaino, Vera; Rossi, Marco; Negrini, Massimo; Ferrarini, Manlio; Caraglia, Michele; Shammas, Masood A; Munshi, Nikhil C; Anderson, Kenneth C; Neri, Antonino; Tagliaferri, Pierosandro; Tassone, Pierfrancesco

2012-11-15

Deregulated expression of miRNAs has been shown in multiple myeloma (MM). A promising strategy to achieve a therapeutic effect by targeting the miRNA regulatory network is to enforce the expression of miRNAs that act as tumor suppressor genes, such as miR-34a. Here, we investigated the therapeutic potential of synthetic miR-34a against human MM cells in vitro and in vivo. Either transient expression of miR-34a synthetic mimics or lentivirus-based miR-34a-stable enforced expression triggered growth inhibition and apoptosis in MM cells in vitro. Synthetic miR-34a downregulated canonic targets BCL2, CDK6, and NOTCH1 at both the mRNA and protein level. Lentiviral vector-transduced MM xenografts with constitutive miR-34a expression showed high growth inhibition in severe combined immunodeficient (SCID) mice. The anti-MM activity of lipidic-formulated miR-34a was further shown in vivo in two different experimental settings: (i) SCID mice bearing nontransduced MM xenografts; and (ii) SCID-synth-hu mice implanted with synthetic 3-dimensional scaffolds reconstituted with human bone marrow stromal cells and then engrafted with human MM cells. Relevant tumor growth inhibition and survival improvement were observed in mice bearing TP53-mutated MM xenografts treated with miR-34a mimics in the absence of systemic toxicity. Our findings provide a proof-of-principle that formulated synthetic miR-34a has therapeutic activity in preclinical models and support a framework for development of miR-34a-based treatment strategies in MM patients. ©2012 AACR.

5. R package imputeTestbench to compare imputations methods for univariate time series

OpenAIRE

Bokde, Neeraj; Kulat, Kishore; Beck, Marcus W; Asencio-Cortés, Gualberto

2016-01-01

This paper describes the R package imputeTestbench that provides a testbench for comparing imputation methods for missing data in univariate time series. The imputeTestbench package can be used to simulate the amount and type of missing data in a complete dataset and compare filled data using different imputation methods. The user has the option to simulate missing data by removing observations completely at random or in blocks of different sizes. Several default imputation methods are includ...

6. In vivo activity of miR-34a mimics delivered by stable nucleic acid lipid particles (SNALPs against multiple myeloma.

Directory of Open Access Journals (Sweden)

Maria Teresa Di Martino

Full Text Available Multiple myeloma (MM is a disease with an adverse outcome and new therapeutic strategies are urgently awaited. A rising body of evidence supports the notion that microRNAs (miRNAs, master regulators of eukaryotic gene expression, may exert anti-MM activity. Here, we evaluated the activity of synthetic miR-34a in MM cells. We found that transfection of miR-34a mimics in MM cells induces a significant change of gene expression with relevant effects on multiple signal transduction pathways. We detected early inactivation of pro-survival and proliferative kinases Erk-2 and Akt followed at later time points by caspase-6 and -3 activation and apoptosis induction. To improve the in vivo delivery, we encapsulated miR-34a mimics in stable nucleic acid lipid particles (SNALPs. We found that SNALPs miR-34a were highly efficient in vitro in inhibiting growth of MM cells. Then, we investigated the activity of the SNALPs miR-34a against MM xenografts in SCID mice. We observed significant tumor growth inhibition (p<0.05 which translated in mice survival benefits (p=0.0047. Analysis of miR-34a and NOTCH1 expression in tumor retrieved from animal demonstrated efficient delivery and gene modulation induced by SNALPs miR-34a in the absence of systemic toxicity. We here therefore provide evidence that SNALPs miR-34a may represent a promising tool for miRNA-therapeutics in MM.

7. Comparison of results from different imputation techniques for missing data from an anti-obesity drug trial

DEFF Research Database (Denmark)

Jørgensen, Anders W.; Lundstrøm, Lars H; Wetterslev, Jørn

2014-01-01

BACKGROUND: In randomised trials of medical interventions, the most reliable analysis follows the intention-to-treat (ITT) principle. However, the ITT analysis requires that missing outcome data have to be imputed. Different imputation techniques may give different results and some may lead to bias...... of handling missing data in a 60-week placebo controlled anti-obesity drug trial on topiramate. METHODS: We compared an analysis of complete cases with datasets where missing body weight measurements had been replaced using three different imputation methods: LOCF, baseline carried forward (BOCF) and MI...

8. 3D-MICE: integration of cross-sectional and longitudinal imputation for multi-analyte longitudinal clinical data.

Science.gov (United States)

Luo, Yuan; Szolovits, Peter; Dighe, Anand S; Baron, Jason M

2018-06-01

A key challenge in clinical data mining is that most clinical datasets contain missing data. Since many commonly used machine learning algorithms require complete datasets (no missing data), clinical analytic approaches often entail an imputation procedure to "fill in" missing data. However, although most clinical datasets contain a temporal component, most commonly used imputation methods do not adequately accommodate longitudinal time-based data. We sought to develop a new imputation algorithm, 3-dimensional multiple imputation with chained equations (3D-MICE), that can perform accurate imputation of missing clinical time series data. We extracted clinical laboratory test results for 13 commonly measured analytes (clinical laboratory tests). We imputed missing test results for the 13 analytes using 3 imputation methods: multiple imputation with chained equations (MICE), Gaussian process (GP), and 3D-MICE. 3D-MICE utilizes both MICE and GP imputation to integrate cross-sectional and longitudinal information. To evaluate imputation method performance, we randomly masked selected test results and imputed these masked results alongside results missing from our original data. We compared predicted results to measured results for masked data points. 3D-MICE performed significantly better than MICE and GP-based imputation in a composite of all 13 analytes, predicting missing results with a normalized root-mean-square error of 0.342, compared to 0.373 for MICE alone and 0.358 for GP alone. 3D-MICE offers a novel and practical approach to imputing clinical laboratory time series data. 3D-MICE may provide an additional tool for use as a foundation in clinical predictive analytics and intelligent clinical decision support.

9. [Imputing missing data in public health: general concepts and application to dichotomous variables].

Science.gov (United States)

Hernández, Gilma; Moriña, David; Navarro, Albert

The presence of missing data in collected variables is common in health surveys, but the subsequent imputation thereof at the time of analysis is not. Working with imputed data may have certain benefits regarding the precision of the estimators and the unbiased identification of associations between variables. The imputation process is probably still little understood by many non-statisticians, who view this process as highly complex and with an uncertain goal. To clarify these questions, this note aims to provide a straightforward, non-exhaustive overview of the imputation process to enable public health researchers ascertain its strengths. All this in the context of dichotomous variables which are commonplace in public health. To illustrate these concepts, an example in which missing data is handled by means of simple and multiple imputation is introduced. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

10. Imputing data that are missing at high rates using a boosting algorithm

Energy Technology Data Exchange (ETDEWEB)

Cauthen, Katherine Regina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lambert, Gregory [Apple Inc., Cupertino, CA (United States); Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Lefantzi, Sophia [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2016-09-01

Traditional multiple imputation approaches may perform poorly for datasets with high rates of missingness unless many m imputations are used. This paper implements an alternative machine learning-based approach to imputing data that are missing at high rates. Here, we use boosting to create a strong learner from a weak learner fitted to a dataset missing many observations. This approach may be applied to a variety of types of learners (models). The approach is demonstrated by application to a spatiotemporal dataset for predicting dengue outbreaks in India from meteorological covariates. A Bayesian spatiotemporal CAR model is boosted to produce imputations, and the overall RMSE from a k-fold cross-validation is used to assess imputation accuracy.

11. Data imputation analysis for Cosmic Rays time series

Science.gov (United States)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

12. Using imputation to provide location information for nongeocoded addresses.

Directory of Open Access Journals (Sweden)

Frank C Curriero

2010-02-01

Full Text Available The importance of geography as a source of variation in health research continues to receive sustained attention in the literature. The inclusion of geographic information in such research often begins by adding data to a map which is predicated by some knowledge of location. A precise level of spatial information is conventionally achieved through geocoding, the geographic information system (GIS process of translating mailing address information to coordinates on a map. The geocoding process is not without its limitations, though, since there is always a percentage of addresses which cannot be converted successfully (nongeocodable. This raises concerns regarding bias since traditionally the practice has been to exclude nongeocoded data records from analysis.In this manuscript we develop and evaluate a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses. The strategies are developed assuming a known zip code with increasing use of collateral information, namely the spatial distribution of the population at risk. Strategies are evaluated using prostate cancer data obtained from the Maryland Cancer Registry. We consider total case enumerations at the Census county, tract, and block group level as the outcome of interest when applying and evaluating the methods. Multiple imputation is used to provide estimated total case counts based on complete data (geocodes plus imputed nongeocodes with a measure of uncertainty. Results indicate that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels.The procedure allows for the potentially biased and likely under reported outcome, case enumerations based on only the geocoded records, to be presented with a statistically adjusted count (imputed count with a measure of uncertainty that are based on all the case data, the geocodes and imputed

13. MiR-17-5p impairs trafficking of H-ERG K+ channel protein by targeting multiple er stress-related chaperones during chronic oxidative stress.

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Qi Wang

Full Text Available BACKGROUND: To investigate if microRNAs (miRNAs play a role in regulating h-ERG trafficking in the setting of chronic oxidative stress as a common deleterious factor for many cardiac disorders. METHODS: We treated neonatal rat ventricular myocytes and HEK293 cells with stable expression of h-ERG with H2O2 for 12 h and 48 h. Expression of miR-17-5p seed miRNAs was quantified by real-time RT-PCR. Protein levels of chaperones and h-ERG trafficking were measured by Western blot analysis. Luciferase reporter gene assay was used to study miRNA and target interactions. Whole-cell patch-clamp techniques were employed to record h-ERG K(+ current. RESULTS: H-ERG trafficking was impaired by H2O2 after 48 h treatment, accompanied by reciprocal changes of expression between miR-17-5p seed miRNAs and several chaperones (Hsp70, Hsc70, CANX, and Golga2, with the former upregulated and the latter downregulated. We established these chaperones as targets for miR-17-5p. Application miR-17-5p inhibitor rescued H2O2-induced impairment of h-ERG trafficking. Upregulation of endogenous by H2O2 or forced miR-17-5p expression either reduced h-ERG current. Sequestration of AP1 by its decoy molecule eliminated the upregulation of miR-17-5p, and ameliorated impairment of h-ERG trafficking. CONCLUSIONS: Collectively, deregulation of the miR-17-5p seed family miRNAs can cause severe impairment of h-ERG trafficking through targeting multiple ER stress-related chaperones, and activation of AP1 likely accounts for the deleterious upregulation of these miRNAs, in the setting of prolonged duration of oxidative stress. These findings revealed the role of miRNAs in h-ERG trafficking, which may contribute to the cardiac electrical disturbances associated with oxidative stress.

14. MiR-17-5p impairs trafficking of H-ERG K+ channel protein by targeting multiple er stress-related chaperones during chronic oxidative stress.

Science.gov (United States)

Wang, Qi; Hu, Weina; Lei, Mingming; Wang, Yong; Yan, Bing; Liu, Jun; Zhang, Ren; Jin, Yuanzhe

2013-01-01

To investigate if microRNAs (miRNAs) play a role in regulating h-ERG trafficking in the setting of chronic oxidative stress as a common deleterious factor for many cardiac disorders. We treated neonatal rat ventricular myocytes and HEK293 cells with stable expression of h-ERG with H2O2 for 12 h and 48 h. Expression of miR-17-5p seed miRNAs was quantified by real-time RT-PCR. Protein levels of chaperones and h-ERG trafficking were measured by Western blot analysis. Luciferase reporter gene assay was used to study miRNA and target interactions. Whole-cell patch-clamp techniques were employed to record h-ERG K(+) current. H-ERG trafficking was impaired by H2O2 after 48 h treatment, accompanied by reciprocal changes of expression between miR-17-5p seed miRNAs and several chaperones (Hsp70, Hsc70, CANX, and Golga2), with the former upregulated and the latter downregulated. We established these chaperones as targets for miR-17-5p. Application miR-17-5p inhibitor rescued H2O2-induced impairment of h-ERG trafficking. Upregulation of endogenous by H2O2 or forced miR-17-5p expression either reduced h-ERG current. Sequestration of AP1 by its decoy molecule eliminated the upregulation of miR-17-5p, and ameliorated impairment of h-ERG trafficking. Collectively, deregulation of the miR-17-5p seed family miRNAs can cause severe impairment of h-ERG trafficking through targeting multiple ER stress-related chaperones, and activation of AP1 likely accounts for the deleterious upregulation of these miRNAs, in the setting of prolonged duration of oxidative stress. These findings revealed the role of miRNAs in h-ERG trafficking, which may contribute to the cardiac electrical disturbances associated with oxidative stress.

15. Missing data imputation using statistical and machine learning methods in a real breast cancer problem.

Science.gov (United States)

Jerez, José M; Molina, Ignacio; García-Laencina, Pedro J; Alba, Emilio; Ribelles, Nuria; Martín, Miguel; Franco, Leonardo

2010-10-01

Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. This work evaluates the performance of several statistical and machine learning imputation methods that were used to predict recurrence in patients in an extensive real breast cancer data set. Imputation methods based on statistical techniques, e.g., mean, hot-deck and multiple imputation, and machine learning techniques, e.g., multi-layer perceptron (MLP), self-organisation maps (SOM) and k-nearest neighbour (KNN), were applied to data collected through the "El Álamo-I" project, and the results were then compared to those obtained from the listwise deletion (LD) imputation method. The database includes demographic, therapeutic and recurrence-survival information from 3679 women with operable invasive breast cancer diagnosed in 32 different hospitals belonging to the Spanish Breast Cancer Research Group (GEICAM). The accuracies of predictions on early cancer relapse were measured using artificial neural networks (ANNs), in which different ANNs were estimated using the data sets with imputed missing values. The imputation methods based on machine learning algorithms outperformed imputation statistical methods in the prediction of patient outcome. Friedman's test revealed a significant difference (p=0.0091) in the observed area under the ROC curve (AUC) values, and the pairwise comparison test showed that the AUCs for MLP, KNN and SOM were significantly higher (p=0.0053, p=0.0048 and p=0.0071, respectively) than the AUC from the LD-based prognosis model. The methods based on machine learning techniques were the most suited for the imputation of missing values and led to a significant enhancement of prognosis accuracy compared to imputation methods based on statistical procedures. Copyright © 2010 Elsevier B.V. All rights reserved.

16. Genotype Imputation for Latinos Using the HapMap and 1000 Genomes Project Reference Panels

Directory of Open Access Journals (Sweden)

Xiaoyi eGao

2012-06-01

Full Text Available Genotype imputation is a vital tool in genome-wide association studies (GWAS and meta-analyses of multiple GWAS results. Imputation enables researchers to increase genomic coverage and to pool data generated using different genotyping platforms. HapMap samples are often employed as the reference panel. More recently, the 1000 Genomes Project resource is becoming the primary source for reference panels. Multiple GWAS and meta-analyses are targeting Latinos, the most populous and fastest growing minority group in the US. However, genotype imputation resources for Latinos are rather limited compared to individuals of European ancestry at present, largely because of the lack of good reference data. One choice of reference panel for Latinos is one derived from the population of Mexican individuals in Los Angeles contained in the HapMap Phase 3 project and the 1000 Genomes Project. However, a detailed evaluation of the quality of the imputed genotypes derived from the public reference panels has not yet been reported. Using simulation studies, the Illumina OmniExpress GWAS data from the Los Angles Latino Eye Study and the MACH software package, we evaluated the accuracy of genotype imputation in Latinos. Our results show that the 1000 Genomes Project AMR+CEU+YRI reference panel provides the highest imputation accuracy for Latinos, and that also including Asian samples in the panel can reduce imputation accuracy. We also provide the imputation accuracy for each autosomal chromosome using the 1000 Genomes Project panel for Latinos. Our results serve as a guide to future imputation-based analysis in Latinos.

17. A three-source capture-recapture estimate of the number of new HIV diagnoses in children in France from 2003–2006 with multiple imputation of a variable of heterogeneous catchability

Directory of Open Access Journals (Sweden)

Héraud-Bousquet Vanina

2012-10-01

Full Text Available Abstract Background Nearly all HIV infections in children worldwide are acquired through mother-to-child transmission (MTCT during pregnancy, labour, delivery or breastfeeding. The objective of our study was to estimate the number and rate of new HIV diagnoses in children less than 13 years of age in mainland France from 2003–2006. Methods We performed a capture-recapture analysis based on three sources of information: the mandatory HIV case reporting (DOVIH, the French Perinatal Cohort (ANRS-EPF and a laboratory-based surveillance of HIV (LaboVIH. The missing values of a variable of heterogeneous catchability were estimated through multiple imputation. Log-linear modelling provided estimates of the number of new HIV infections in children, taking into account dependencies between sources and variables of heterogeneous catchability. Results The three sources observed 216 new HIV diagnoses after record-linkage. The number of new HIV diagnoses in children was estimated at 387 (95%CI [271–503] from 2003–2006, among whom 60% were born abroad. The estimated rate of new HIV diagnoses in children in mainland France was 9.1 per million in 2006 and was 38 times higher in children born abroad than in those born in France. The estimated completeness of the three sources combined was 55.8% (95% CI [42.9 – 79.7] and varied according to the source; the completeness of DOVIH (28.4% and ANRS-EPF (26.1% were lower than that of LaboVIH (33.3%. Conclusion Our study provided, for the first time, an estimated annual rate of new HIV diagnoses in children under 13 years old in mainland France. A more systematic HIV screening of pregnant women that is repeated during pregnancy among women likely to engage in risky behaviour is needed to optimise the prevention of MTCT. HIV screening for children who migrate from countries with high HIV prevalence to France could be recommended to facilitate early diagnosis and treatment.

18. HyDR-MI : A hybrid algorithm to reduce dimensionality in multiple instance learning

NARCIS (Netherlands)

Zafra, A.; Pechenizkiy, M.; Ventura, S.

2013-01-01

Feature selection techniques have been successfully applied in many applications for making supervised learning more effective and efficient. These techniques have been widely used and studied in traditional supervised learning settings, where each instance is expected to have a label. In multiple

19. The Epstein-Barr Virus BART miRNA Cluster of the M81 Strain Modulates Multiple Functions in Primary B Cells

Science.gov (United States)

Lin, Xiaochen; Tsai, Ming-Han; Shumilov, Anatoliy; Poirey, Remy; Bannert, Helmut; Middeldorp, Jaap M.; Feederle, Regina; Delecluse, Henri-Jacques

2015-01-01

The Epstein-Barr virus (EBV) is a B lymphotropic virus that infects the majority of the human population. All EBV strains transform B lymphocytes, but some strains, such as M81, also induce spontaneous virus replication. EBV encodes 22 microRNAs (miRNAs) that form a cluster within the BART region of the virus and have been previously been found to stimulate tumor cell growth. Here we describe their functions in B cells infected by M81. We found that the BART miRNAs are downregulated in replicating cells, and that exposure of B cells in vitro or in vivo in humanized mice to a BART miRNA knockout virus resulted in an increased proportion of spontaneously replicating cells, relative to wild type virus. The BART miRNAs subcluster 1, and to a lesser extent subcluster 2, prevented expression of BZLF1, the key protein for initiation of lytic replication. Thus, multiple BART miRNAs cooperate to repress lytic replication. The BART miRNAs also downregulated pro- and anti-apoptotic mediators such as caspase 3 and LMP1, and their deletion did not sensitize B-cells to apoptosis. To the contrary, the majority of humanized mice infected with the BART miRNA knockout mutant developed tumors more rapidly, probably due to enhanced LMP1 expression, although deletion of the BART miRNAs did not modify the virus transforming abilities in vitro. This ability to slow cell growth could be confirmed in non-humanized immunocompromized mice. Injection of resting B cells exposed to a virus that lacks the BART miRNAs resulted in accelerated tumor growth, relative to wild type controls. Therefore, we found that the M81 BART miRNAs do not enhance B-cell tumorigenesis but rather repress it. The repressive effects of the BART miRNAs on potentially pathogenic viral functions in infected B cells are likely to facilitate long-term persistence of the virus in the infected host. PMID:26694854

20. Imputation methods for filling missing data in urban air pollution data for Malaysia

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Nur Afiqah Zakaria

2018-06-01

Full Text Available The air quality measurement data obtained from the continuous ambient air quality monitoring (CAAQM station usually contained missing data. The missing observations of the data usually occurred due to machine failure, routine maintenance and human error. In this study, the hourly monitoring data of CO, O3, PM10, SO2, NOx, NO2, ambient temperature and humidity were used to evaluate four imputation methods (Mean Top Bottom, Linear Regression, Multiple Imputation and Nearest Neighbour. The air pollutants observations were simulated into four percentages of simulated missing data i.e. 5%, 10%, 15% and 20%. Performance measures namely the Mean Absolute Error, Root Mean Squared Error, Coefficient of Determination and Index of Agreement were used to describe the goodness of fit of the imputation methods. From the results of the performance measures, Mean Top Bottom method was selected as the most appropriate imputation method for filling in the missing values in air pollutants data.

1. MiR-7 triggers cell cycle arrest at the G1/S transition by targeting multiple genes including Skp2 and Psme3.

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Noelia Sanchez

Full Text Available MiR-7 acts as a tumour suppressor in many cancers and abrogates proliferation of CHO cells in culture. In this study we demonstrate that miR-7 targets key regulators of the G1 to S phase transition, including Skp2 and Psme3, to promote increased levels of p27(KIP and temporary growth arrest of CHO cells in the G1 phase. Simultaneously, the down-regulation of DNA repair-specific proteins via miR-7 including Rad54L, and pro-apoptotic regulators such as p53, combined with the up-regulation of anti-apoptotic factors like p-Akt, promoted cell survival while arrested in G1. Thus miR-7 can co-ordinate the levels of multiple genes and proteins to influence G1 to S phase transition and the apoptotic response in order to maintain cellular homeostasis. This work provides further mechanistic insight into the role of miR-7 as a regulator of cell growth in times of cellular stress.

2. Effects of Different Missing Data Imputation Techniques on the Performance of Undiagnosed Diabetes Risk Prediction Models in a Mixed-Ancestry Population of South Africa.

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Katya L Masconi

Full Text Available Imputation techniques used to handle missing data are based on the principle of replacement. It is widely advocated that multiple imputation is superior to other imputation methods, however studies have suggested that simple methods for filling missing data can be just as accurate as complex methods. The objective of this study was to implement a number of simple and more complex imputation methods, and assess the effect of these techniques on the performance of undiagnosed diabetes risk prediction models during external validation.Data from the Cape Town Bellville-South cohort served as the basis for this study. Imputation methods and models were identified via recent systematic reviews. Models' discrimination was assessed and compared using C-statistic and non-parametric methods, before and after recalibration through simple intercept adjustment.The study sample consisted of 1256 individuals, of whom 173 were excluded due to previously diagnosed diabetes. Of the final 1083 individuals, 329 (30.4% had missing data. Family history had the highest proportion of missing data (25%. Imputation of the outcome, undiagnosed diabetes, was highest in stochastic regression imputation (163 individuals. Overall, deletion resulted in the lowest model performances while simple imputation yielded the highest C-statistic for the Cambridge Diabetes Risk model, Kuwaiti Risk model, Omani Diabetes Risk model and Rotterdam Predictive model. Multiple imputation only yielded the highest C-statistic for the Rotterdam Predictive model, which were matched by simpler imputation methods.Deletion was confirmed as a poor technique for handling missing data. However, despite the emphasized disadvantages of simpler imputation methods, this study showed that implementing these methods results in similar predictive utility for undiagnosed diabetes when compared to multiple imputation.

3. Data driven estimation of imputation error-a strategy for imputation with a reject option

DEFF Research Database (Denmark)

Bak, Nikolaj; Hansen, Lars Kai

2016-01-01

Missing data is a common problem in many research fields and is a challenge that always needs careful considerations. One approach is to impute the missing values, i.e., replace missing values with estimates. When imputation is applied, it is typically applied to all records with missing values i...

4. iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

Science.gov (United States)

Liu, Siwei; Molenaar, Peter C M

2014-12-01

This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

5. Improving accuracy of rare variant imputation with a two-step imputation approach

DEFF Research Database (Denmark)

Kreiner-Møller, Eskil; Medina-Gomez, Carolina; Uitterlinden, André G

2015-01-01

not being comprehensively scrutinized. Next-generation arrays ensuring sufficient coverage together with new reference panels, as the 1000 Genomes panel, are emerging to facilitate imputation of low frequent single-nucleotide polymorphisms (minor allele frequency (MAF) ... reference sample genotyped on a dense array and hereafter to the 1000 Genomes reference panel. We show that mean imputation quality, measured by the r(2) using this approach, increases by 28% for variants with a MAF between 1 and 5% as compared with direct imputation to 1000 Genomes reference. Similarly......Genotype imputation has been the pillar of the success of genome-wide association studies (GWAS) for identifying common variants associated with common diseases. However, most GWAS have been run using only 60 HapMap samples as reference for imputation, meaning less frequent and rare variants...

6. On multivariate imputation and forecasting of decadal wind speed missing data.

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Wesonga, Ronald

2015-01-01

This paper demonstrates the application of multiple imputations by chained equations and time series forecasting of wind speed data. The study was motivated by the high prevalence of missing wind speed historic data. Findings based on the fully conditional specification under multiple imputations by chained equations, provided reliable wind speed missing data imputations. Further, the forecasting model shows, the smoothing parameter, alpha (0.014) close to zero, confirming that recent past observations are more suitable for use to forecast wind speeds. The maximum decadal wind speed for Entebbe International Airport was estimated to be 17.6 metres per second at a 0.05 level of significance with a bound on the error of estimation of 10.8 metres per second. The large bound on the error of estimations confirms the dynamic tendencies of wind speed at the airport under study.

7. Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey.

Science.gov (United States)

Peyre, Hugo; Leplège, Alain; Coste, Joël

2011-03-01

Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. It remains unclear which of the various methods proposed to deal with missing data performs best in this context. We compared personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques using various realistic simulation scenarios of item missingness in QoL questionnaires constructed within the framework of classical test theory. Samples of 300 and 1,000 subjects were randomly drawn from the 2003 INSEE Decennial Health Survey (of 23,018 subjects representative of the French population and having completed the SF-36) and various patterns of missing data were generated according to three different item non-response rates (3, 6, and 9%) and three types of missing data (Little and Rubin's "missing completely at random," "missing at random," and "missing not at random"). The missing data methods were evaluated in terms of accuracy and precision for the analysis of one descriptive and one association parameter for three different scales of the SF-36. For all item non-response rates and types of missing data, multiple imputation and full information maximum likelihood appeared superior to the personal mean score and especially to hot deck in terms of accuracy and precision; however, the use of personal mean score was associated with insignificant bias (relative bias personal mean score appears nonetheless appropriate for dealing with items missing from completed SF-36 questionnaires in most situations of routine use. These results can reasonably be extended to other questionnaires constructed according to classical test theory.

8. Comparison of missing value imputation methods in time series: the case of Turkish meteorological data

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Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci

2013-04-01

This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.

9. Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies

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McElwee Joshua

2009-06-01

-eQTL discoveries detected by various methods can be interpreted as their relative statistical power in the GWAS. In this study, we find that imputation offer modest additional power (by 4% on top of either Ilmn317K or Ilmn650Y, much less than the power gain from Ilmn317K to Ilmn650Y (13%. Conclusion Current algorithms can accurately impute genotypes for untyped markers, which enables researchers to pool data between studies conducted using different SNP sets. While genotyping itself results in a small error rate (e.g. 0.5%, imputing genotypes is surprisingly accurate. We found that dense marker sets (e.g. Ilmn650Y outperform sparser ones (e.g. Ilmn317K in terms of imputation yield and accuracy. We also noticed it was harder to impute genotypes for African American samples, partially due to population admixture, although using a pooled reference boosts performance. Interestingly, GWAS carried out using imputed genotypes only slightly increased power on top of assayed SNPs. The reason is likely due to adding more markers via imputation only results in modest gain in genetic coverage, but worsens the multiple testing penalties. Furthermore, cis-eQTL mapping using dense SNP set derived from imputation achieves great resolution, and locate associate peak closer to causal variants than conventional approach.

10. Assessment of imputation methods using varying ecological information to fill the gaps in a tree functional trait database

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Poyatos, Rafael; Sus, Oliver; Vilà-Cabrera, Albert; Vayreda, Jordi; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2016-04-01

Plant functional traits are increasingly being used in ecosystem ecology thanks to the growing availability of large ecological databases. However, these databases usually contain a large fraction of missing data because measuring plant functional traits systematically is labour-intensive and because most databases are compilations of datasets with different sampling designs. As a result, within a given database, there is an inevitable variability in the number of traits available for each data entry and/or the species coverage in a given geographical area. The presence of missing data may severely bias trait-based analyses, such as the quantification of trait covariation or trait-environment relationships and may hamper efforts towards trait-based modelling of ecosystem biogeochemical cycles. Several data imputation (i.e. gap-filling) methods have been recently tested on compiled functional trait databases, but the performance of imputation methods applied to a functional trait database with a regular spatial sampling has not been thoroughly studied. Here, we assess the effects of data imputation on five tree functional traits (leaf biomass to sapwood area ratio, foliar nitrogen, maximum height, specific leaf area and wood density) in the Ecological and Forest Inventory of Catalonia, an extensive spatial database (covering 31900 km2). We tested the performance of species mean imputation, single imputation by the k-nearest neighbors algorithm (kNN) and a multiple imputation method, Multivariate Imputation with Chained Equations (MICE) at different levels of missing data (10%, 30%, 50%, and 80%). We also assessed the changes in imputation performance when additional predictors (species identity, climate, forest structure, spatial structure) were added in kNN and MICE imputations. We evaluated the imputed datasets using a battery of indexes describing departure from the complete dataset in trait distribution, in the mean prediction error, in the correlation matrix

11. Multiple Intelligences (MI of Associate in Hotel and Restaurant Management Students & Its Implication to the Teaching of Oral Communication

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Juvy G. Mojares

2015-11-01

Full Text Available A number of educators argue that MI helps students build positive attitudes toward learning in English class. A study says that “Students who are using their areas of strength to learn feel more competent and confident and enjoy the challenge of acquiring new information”. This study sought to find out the MI of selected Associate in Hotel and Restaurant Management (AHRMstudents. It also delved on the implication of MI to the teaching of the subject. The research design used was basically a descriptive method employing an adopted MI survey form administered to Oral Communication students. There were five sections of second year AHRM students. Out of 196 students, 111 were selected to answer the survey questions by the use of the combination of stratified random sampling and the Slovin’s formula. Results showed that the top three intelligences the respondents have based on their scores are intrapersonal, followed by bodily/kinesthetic and logical/mathematical intelligences; least of the intelligences are verbal/linguistic and visual/spatial.This implied that teaching of Oral Communication should nurture the intrapersonal intelligence and more importantly should enhance and develop the verbal strength of the AHRM students. Teaching should focus more on improving communication skills with others, and not just within themselves.

12. Estimating the accuracy of geographical imputation

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Boscoe Francis P

2008-01-01

Full Text Available Abstract Background To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address. Some analysts then use the postal code to assign information to the cases from finer-level geographies such as a census tract. Assignment is commonly completed using either a postal centroid or by a geographical imputation method which assigns a location by using both the demographic characteristics of the case and the population characteristics of the postal delivery area. To date no systematic evaluation of geographical imputation methods ("geo-imputation" has been completed. The objective of this study was to determine the accuracy of census tract assignment using geo-imputation. Methods Using a large dataset of breast, prostate and colorectal cancer cases reported to the New Jersey Cancer Registry, we determined how often cases were assigned to the correct census tract using alternate strategies of demographic based geo-imputation, and using assignments obtained from postal code centroids. Assignment accuracy was measured by comparing the tract assigned with the tract originally identified from the full street address. Results Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids. The addition of age characteristics increased the match rates even further. Match rates were highly dependent on both the geographic distribution of race/ethnicity groups and population density. Conclusion Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids. For a specific analysis, researchers will still need to consider the potential impact of geocoding quality on their results and evaluate

13. Cost reduction for web-based data imputation

KAUST Repository

Li, Zhixu; Shang, Shuo; Xie, Qing; Zhang, Xiangliang

2014-01-01

Web-based Data Imputation enables the completion of incomplete data sets by retrieving absent field values from the Web. In particular, complete fields can be used as keywords in imputation queries for absent fields. However, due to the ambiguity

14. Analyzing the changing gender wage gap based on multiply imputed right censored wages

OpenAIRE

Gartner, Hermann; Rässler, Susanne

2005-01-01

"In order to analyze the gender wage gap with the German IAB-employment register we have to solve the problem of censored wages at the upper limit of the social security system. We treat this problem as a missing data problem. We regard the missingness mechanism as not missing at random (NMAR, according to Little and Rubin, 1987, 2002) as well as missing by design. The censored wages are multiply imputed by draws of a random variable from a truncated distribution. The multiple imputation is b...

15. Fully conditional specification in multivariate imputation

NARCIS (Netherlands)

van Buuren, S.; Brand, J. P.L.; Groothuis-Oudshoorn, C. G.M.; Rubin, D. B.

2006-01-01

The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the

16. VIGAN: Missing View Imputation with Generative Adversarial Networks.

Science.gov (United States)

Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

17. LinkImputeR: user-guided genotype calling and imputation for non-model organisms.

Science.gov (United States)

Money, Daniel; Migicovsky, Zoë; Gardner, Kyle; Myles, Sean

2017-07-10

Genomic studies such as genome-wide association and genomic selection require genome-wide genotype data. All existing technologies used to create these data result in missing genotypes, which are often then inferred using genotype imputation software. However, existing imputation methods most often make use only of genotypes that are successfully inferred after having passed a certain read depth threshold. Because of this, any read information for genotypes that did not pass the threshold, and were thus set to missing, is ignored. Most genomic studies also choose read depth thresholds and quality filters without investigating their effects on the size and quality of the resulting genotype data. Moreover, almost all genotype imputation methods require ordered markers and are therefore of limited utility in non-model organisms. Here we introduce LinkImputeR, a software program that exploits the read count information that is normally ignored, and makes use of all available DNA sequence information for the purposes of genotype calling and imputation. It is specifically designed for non-model organisms since it requires neither ordered markers nor a reference panel of genotypes. Using next-generation DNA sequence (NGS) data from apple, cannabis and grape, we quantify the effect of varying read count and missingness thresholds on the quantity and quality of genotypes generated from LinkImputeR. We demonstrate that LinkImputeR can increase the number of genotype calls by more than an order of magnitude, can improve genotyping accuracy by several percent and can thus improve the power of downstream analyses. Moreover, we show that the effects of quality and read depth filters can differ substantially between data sets and should therefore be investigated on a per-study basis. By exploiting DNA sequence data that is normally ignored during genotype calling and imputation, LinkImputeR can significantly improve both the quantity and quality of genotype data generated from

18. Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data.

Science.gov (United States)

Rahman, Shah Atiqur; Huang, Yuxiao; Claassen, Jan; Heintzman, Nathaniel; Kleinberg, Samantha

2015-12-01

Most clinical and biomedical data contain missing values. A patient's record may be split across multiple institutions, devices may fail, and sensors may not be worn at all times. While these missing values are often ignored, this can lead to bias and error when the data are mined. Further, the data are not simply missing at random. Instead the measurement of a variable such as blood glucose may depend on its prior values as well as that of other variables. These dependencies exist across time as well, but current methods have yet to incorporate these temporal relationships as well as multiple types of missingness. To address this, we propose an imputation method (FLk-NN) that incorporates time lagged correlations both within and across variables by combining two imputation methods, based on an extension to k-NN and the Fourier transform. This enables imputation of missing values even when all data at a time point is missing and when there are different types of missingness both within and across variables. In comparison to other approaches on three biological datasets (simulated and actual Type 1 diabetes datasets, and multi-modality neurological ICU monitoring) the proposed method has the highest imputation accuracy. This was true for up to half the data being missing and when consecutive missing values are a significant fraction of the overall time series length. Copyright © 2015 Elsevier Inc. All rights reserved.

19. Clustering with Missing Values: No Imputation Required

Science.gov (United States)

Wagstaff, Kiri

2004-01-01

Clustering algorithms can identify groups in large data sets, such as star catalogs and hyperspectral images. In general, clustering methods cannot analyze items that have missing data values. Common solutions either fill in the missing values (imputation) or ignore the missing data (marginalization). Imputed values are treated as just as reliable as the truly observed data, but they are only as good as the assumptions used to create them. In contrast, we present a method for encoding partially observed features as a set of supplemental soft constraints and introduce the KSC algorithm, which incorporates constraints into the clustering process. In experiments on artificial data and data from the Sloan Digital Sky Survey, we show that soft constraints are an effective way to enable clustering with missing values.

20. Gaussian mixture clustering and imputation of microarray data.

Science.gov (United States)

Ouyang, Ming; Welsh, William J; Georgopoulos, Panos

2004-04-12

In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation. Two evaluation metrics of imputation accuracy are employed. First, the root mean squared error measures the difference between the true values and the imputed values. Second, the number of mis-clustered genes measures the difference between clustering with true values and that with imputed values; it examines the bias introduced by imputation to clustering. The Gaussian mixture clustering with model averaging imputation is superior to all other imputation methods, according to both evaluation metrics, on both time-series (correlated) and non-time series (uncorrelated) data sets.

1. Differential network analysis with multiply imputed lipidomic data.

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Maiju Kujala

Full Text Available The importance of lipids for cell function and health has been widely recognized, e.g., a disorder in the lipid composition of cells has been related to atherosclerosis caused cardiovascular disease (CVD. Lipidomics analyses are characterized by large yet not a huge number of mutually correlated variables measured and their associations to outcomes are potentially of a complex nature. Differential network analysis provides a formal statistical method capable of inferential analysis to examine differences in network structures of the lipids under two biological conditions. It also guides us to identify potential relationships requiring further biological investigation. We provide a recipe to conduct permutation test on association scores resulted from partial least square regression with multiple imputed lipidomic data from the LUdwigshafen RIsk and Cardiovascular Health (LURIC study, particularly paying attention to the left-censored missing values typical for a wide range of data sets in life sciences. Left-censored missing values are low-level concentrations that are known to exist somewhere between zero and a lower limit of quantification. To make full use of the LURIC data with the missing values, we utilize state of the art multiple imputation techniques and propose solutions to the challenges that incomplete data sets bring to differential network analysis. The customized network analysis helps us to understand the complexities of the underlying biological processes by identifying lipids and lipid classes that interact with each other, and by recognizing the most important differentially expressed lipids between two subgroups of coronary artery disease (CAD patients, the patients that had a fatal CVD event and the ones who remained stable during two year follow-up.

2. Reference miRNAs for miRNAome analysis of urothelial carcinomas.

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Full Text Available BACKGROUND/OBJECTIVE: Reverse transcription quantitative real-time PCR (RT-qPCR is widely used in microRNA (miRNA expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. METHODS: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. PRINCIPAL FINDINGS: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. CONCLUSIONS: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p or three (miR-148b, miR-181b, and miR-874

3. Genome-wide mRNA and miRNA expression profiling reveal multiple regulatory networks in colorectal cancer

DEFF Research Database (Denmark)

Vishnubalaji, R; Hamam, R; Abdulla, M-H

2015-01-01

Despite recent advances in cancer management, colorectal cancer (CRC) remains the third most common cancer and a major health-care problem worldwide. MicroRNAs have recently emerged as key regulators of cancer development and progression by targeting multiple cancer-related genes; however, such r...

4. Two-pass imputation algorithm for missing value estimation in gene expression time series.

Science.gov (United States)

Tsiporkova, Elena; Boeva, Veselka

2007-10-01

Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different

5. Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data.

Science.gov (United States)

Sehgal, Muhammad Shoaib B; Gondal, Iqbal; Dooley, Laurence S

2005-05-15

Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE

6. Multiple aspects of ATP-dependent nucleosome translocation by RSC and Mi-2 are directed by the underlying DNA sequence.

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Joke J F A van Vugt

Full Text Available BACKGROUND: Chromosome structure, DNA metabolic processes and cell type identity can all be affected by changing the positions of nucleosomes along chromosomal DNA, a reaction that is catalysed by SNF2-type ATP-driven chromatin remodelers. Recently it was suggested that in vivo, more than 50% of the nucleosome positions can be predicted simply by DNA sequence, especially within promoter regions. This seemingly contrasts with remodeler induced nucleosome mobility. The ability of remodeling enzymes to mobilise nucleosomes over short DNA distances is well documented. However, the nucleosome translocation processivity along DNA remains elusive. Furthermore, it is unknown what determines the initial direction of movement and how new nucleosome positions are adopted. METHODOLOGY/PRINCIPAL FINDINGS: We have used AFM imaging and high resolution PAGE of mononucleosomes on 600 and 2500 bp DNA molecules to analyze ATP-dependent nucleosome repositioning by native and recombinant SNF2-type enzymes. We report that the underlying DNA sequence can control the initial direction of translocation, translocation distance, as well as the new positions adopted by nucleosomes upon enzymatic mobilization. Within a strong nucleosomal positioning sequence both recombinant Drosophila Mi-2 (CHD-type and native RSC from yeast (SWI/SNF-type repositioned the nucleosome at 10 bp intervals, which are intrinsic to the positioning sequence. Furthermore, RSC-catalyzed nucleosome translocation was noticeably more efficient when beyond the influence of this sequence. Interestingly, under limiting ATP conditions RSC preferred to position the nucleosome with 20 bp intervals within the positioning sequence, suggesting that native RSC preferentially translocates nucleosomes with 15 to 25 bp DNA steps. CONCLUSIONS/SIGNIFICANCE: Nucleosome repositioning thus appears to be influenced by both remodeler intrinsic and DNA sequence specific properties that interplay to define ATPase

7. Cost reduction for web-based data imputation

KAUST Repository

Li, Zhixu

2014-01-01

Web-based Data Imputation enables the completion of incomplete data sets by retrieving absent field values from the Web. In particular, complete fields can be used as keywords in imputation queries for absent fields. However, due to the ambiguity of these keywords and the data complexity on the Web, different queries may retrieve different answers to the same absent field value. To decide the most probable right answer to each absent filed value, existing method issues quite a few available imputation queries for each absent value, and then vote on deciding the most probable right answer. As a result, we have to issue a large number of imputation queries for filling all absent values in an incomplete data set, which brings a large overhead. In this paper, we work on reducing the cost of Web-based Data Imputation in two aspects: First, we propose a query execution scheme which can secure the most probable right answer to an absent field value by issuing as few imputation queries as possible. Second, we recognize and prune queries that probably will fail to return any answers a priori. Our extensive experimental evaluation shows that our proposed techniques substantially reduce the cost of Web-based Imputation without hurting its high imputation accuracy. © 2014 Springer International Publishing Switzerland.

8. Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods.

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Nawar Shara

Full Text Available Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS. Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989-1991, 2 (1993-1995, and 3 (1998-1999 was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results.

9. Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

Science.gov (United States)

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

10. Hypermethylation of MIR21 in CD4+ T cells from patients with relapsing-remitting multiple sclerosis associates with lower miRNA-21 levels and concomitant up-regulation of its target genes

KAUST Repository

Ruhrmann, Sabrina

2017-08-02

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system caused by genetic and environmental factors. DNA methylation, an epigenetic mechanism that controls genome activity, may provide a link between genetic and environmental risk factors.We sought to identify DNA methylation changes in CD4+ T cells in patients with relapsing-remitting (RR-MS) and secondary-progressive (SP-MS) disease and healthy controls (HC).We performed DNA methylation analysis in CD4+ T cells from RR-MS, SP-MS, and HC and associated identified changes with the nearby risk allele, smoking, age, and gene expression.We observed significant methylation differences in the VMP1/MIR21 locus, with RR-MS displaying higher methylation compared to SP-MS and HC. VMP1/MIR21 methylation did not correlate with a known MS risk variant in VMP1 or smoking but displayed a significant negative correlation with age and the levels of mature miR-21 in CD4+ T cells. Accordingly, RR-MS displayed lower levels of miR-21 compared to SP-MS, which might reflect differences in age between the groups, and healthy individuals and a significant enrichment of up-regulated miR-21 target genes.Disease-related changes in epigenetic marking of MIR21 in RR-MS lead to differences in miR-21 expression with a consequence on miR-21 target genes.

11. Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes

Directory of Open Access Journals (Sweden)

Lotz Meredith J

2008-01-01

Full Text Available Abstract Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA

12. Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

Science.gov (United States)

Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-10

Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity

13. Loss of miR-141/200c ameliorates hepatic steatosis and inflammation by reprogramming multiple signaling pathways in NASH

Science.gov (United States)

Tran, Melanie; Lee, Sang-Min; Shin, Dong-Ju

2017-01-01

Accumulation of lipid droplets and inflammatory cell infiltration is the hallmark of nonalcoholic steatohepatitis (NASH). The roles of noncoding RNAs in NASH are less known. We aim to elucidate the function of miR-141/200c in diet-induced NASH. WT and miR-141/200c–/– mice were fed a methionine and choline deficient (MCD) diet for 2 weeks to assess markers of steatosis, liver injury, and inflammation. Hepatic miR-141 and miR-200c RNA levels were highly induced in human patients with NASH fatty liver and in WT MCD mice. miR-141/200c–/– MCD mice had reduced liver weights and triglyceride (TG) levels, which was associated with increased microsomal TG transfer protein (MTTP) and PPARα but reduced SREBP1c and FAS expression. Inflammation was attenuated and F4/80 macrophage activation was suppressed in miR-141/200c–/– mice, as evidenced by decreased serum aminotransferases and IL-6 and reduced hepatic proinflammatory, neutrophil, and profibrotic genes. Treatment with LPS in BM-derived macrophages isolated from miR-200c/141–/– mice polarized macrophages toward the M2 antiinflammatory state by increasing Arg1 and IL-10 levels while decreasing the M1 marker iNOS. In addition, elevated phosphorylated AMPK (p-AMPK), p-AKT, and p-GSK3β and diminished TLR4 and p-mTOR/p-4EBP1 proteins were observed. Lipidomics and metabolomics revealed alterations of TG and phosphatidylcholine (PC) lipid species by miR-141/200c deficiency. In summary, miR-141/200c deficiency diminished NASH-associated hepatic steatosis and inflammation by reprogramming lipid and inflammation signaling pathways. PMID:29093267

14. MiR-17-5p Impairs Trafficking of H-ERG K+ Channel Protein by Targeting Multiple ER Stress-Related Chaperones during Chronic Oxidative Stress

OpenAIRE

Wang, Qi; Hu, Weina; Lei, Mingming; Wang, Yong; Yan, Bing; Liu, Jun; Zhang, Ren; Jin, Yuanzhe

2013-01-01

BACKGROUND: To investigate if microRNAs (miRNAs) play a role in regulating h-ERG trafficking in the setting of chronic oxidative stress as a common deleterious factor for many cardiac disorders. METHODS: We treated neonatal rat ventricular myocytes and HEK293 cells with stable expression of h-ERG with H2O2 for 12 h and 48 h. Expression of miR-17-5p seed miRNAs was quantified by real-time RT-PCR. Protein levels of chaperones and h-ERG trafficking were measured by Western blot analysis. Lucifer...

15. Estimation of caries experience by multiple imputation and direct standardization

NARCIS (Netherlands)

Schuller, A. A.; Van Buuren, S.

2014-01-01

Valid estimates of caries experience are needed to monitor oral population health. Obtaining such estimates in practice is often complicated by nonresponse and missing data. The goal of this study was to estimate caries experiences in a population of children aged 5 and 11 years, in the presence of

16. Estimation of Caries Experience by Multiple Imputation and Direct Standardization

NARCIS (Netherlands)

Schuller, A. A.; van Buuren, S.

2014-01-01

Valid estimates of caries experience are needed to monitor oral population health. Obtaining such estimates in practice is often complicated by nonresponse and missing data. The goal of this study was to estimate caries experiences in a population of children aged 5 and 11 years, in the presence of

17. Comparison of different Methods for Univariate Time Series Imputation in R

OpenAIRE

Moritz, Steffen; Sardá, Alexis; Bartz-Beielstein, Thomas; Zaefferer, Martin; Stork, Jörg

2015-01-01

Missing values in datasets are a well-known problem and there are quite a lot of R packages offering imputation functions. But while imputation in general is well covered within R, it is hard to find functions for imputation of univariate time series. The problem is, most standard imputation techniques can not be applied directly. Most algorithms rely on inter-attribute correlations, while univariate time series imputation needs to employ time dependencies. This paper provides an overview of ...

18. Design of a bovine low-density SNP array optimized for imputation.

Directory of Open Access Journals (Sweden)

Didier Boichard

Full Text Available The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where densities were increased. The chip also includes SNPs on the Y chromosome and mitochondrial DNA loci that are useful for determining subspecies classification and certain paternal and maternal breed lineages. The total number of SNPs was 6,909. Accuracy of imputation to Illumina BovineSNP50 genotypes using the BovineLD chip was over 97% for most dairy and beef populations. The BovineLD imputations were about 3 percentage points more accurate than those from the Illumina GoldenGate Bovine3K BeadChip across multiple populations. The improvement was greatest when neither parent was genotyped. The minor allele frequencies were similar across taurine beef and dairy breeds as was the proportion of SNPs that were polymorphic. The new BovineLD chip should facilitate low-cost genomic selection in taurine beef and dairy cattle.

19. Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions

Science.gov (United States)

Turrado, Concepción Crespo; López, María del Carmen Meizoso; Lasheras, Fernando Sánchez; Gómez, Benigno Antonio Rodríguez; Rollé, José Luis Calvo; de Cos Juez, Francisco Javier

2014-01-01

Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW. PMID:25356644

20. Missing Data Imputation of Solar Radiation Data under Different Atmospheric Conditions

Directory of Open Access Journals (Sweden)

2014-10-01

Full Text Available Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE. This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW and Multiple Linear Regression (MLR. The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.

1. Missing data imputation of solar radiation data under different atmospheric conditions.

Science.gov (United States)

Turrado, Concepción Crespo; López, María Del Carmen Meizoso; Lasheras, Fernando Sánchez; Gómez, Benigno Antonio Rodríguez; Rollé, José Luis Calvo; Juez, Francisco Javier de Cos

2014-10-29

Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW.

2. A web-based approach to data imputation

KAUST Repository

Li, Zhixu

2013-10-24

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques. © 2013 Springer Science+Business Media New York.

3. Mobile Motion Capture--MiMiC.

Science.gov (United States)

Harbert, Simeon D; Jaiswal, Tushar; Harley, Linda R; Vaughn, Tyler W; Baranak, Andrew S

2013-01-01

The low cost, simple, robust, mobile, and easy to use Mobile Motion Capture (MiMiC) system is presented and the constraints which guided the design of MiMiC are discussed. The MiMiC Android application allows motion data to be captured from kinematic modules such as Shimmer 2r sensors over Bluetooth. MiMiC is cost effective and can be used for an entire day in a person's daily routine without being intrusive. MiMiC is a flexible motion capture system which can be used for many applications including fall detection, detection of fatigue in industry workers, and analysis of individuals' work patterns in various environments.

4. Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk

DEFF Research Database (Denmark)

Goode, Ellen L; Fridley, Brooke L; Vierkant, Robert A

2009-01-01

Polymorphisms in genes critical to cell cycle control are outstanding candidates for association with ovarian cancer risk; numerous genes have been interrogated by multiple research groups using differing tagging single-nucleotide polymorphism (SNP) sets. To maximize information gleaned from......, and rs3212891; CDK2 rs2069391, rs2069414, and rs17528736; and CCNE1 rs3218036. These results exemplify the utility of imputation in candidate gene studies and lend evidence to a role of cell cycle genes in ovarian cancer etiology, suggest a reduced set of SNPs to target in additional cases and controls....

5. Assessing accuracy of genotype imputation in American Indians.

Directory of Open Access Journals (Sweden)

Alka Malhotra

Full Text Available Genotype imputation is commonly used in genetic association studies to test untyped variants using information on linkage disequilibrium (LD with typed markers. Imputing genotypes requires a suitable reference population in which the LD pattern is known, most often one selected from HapMap. However, some populations, such as American Indians, are not represented in HapMap. In the present study, we assessed accuracy of imputation using HapMap reference populations in a genome-wide association study in Pima Indians.Data from six randomly selected chromosomes were used. Genotypes in the study population were masked (either 1% or 20% of SNPs available for a given chromosome. The masked genotypes were then imputed using the software Markov Chain Haplotyping Algorithm. Using four HapMap reference populations, average genotype error rates ranged from 7.86% for Mexican Americans to 22.30% for Yoruba. In contrast, use of the original Pima Indian data as a reference resulted in an average error rate of 1.73%.Our results suggest that the use of HapMap reference populations results in substantial inaccuracy in the imputation of genotypes in American Indians. A possible solution would be to densely genotype or sequence a reference American Indian population.

6. miRSeqNovel

DEFF Research Database (Denmark)

Qian, Kui; Auvinen, Eeva; Greco, Dario

2012-01-01

We present miRSeqNovel, an R based workflow for miRNA sequencing data analysis. miRSeqNovel can process both colorspace (SOLiD) and basespace (Illumina/Solexa) data by different mapping algorithms. It finds differentially expressed miRNAs and gives conservative prediction of novel miRNA candidates...... with customized parameters. miRSeqNovel is freely available at http://sourceforge.net/projects/mirseq/files....

7. miRNA-21 is dysregulated in response to vein grafting in multiple models and genetic ablation in mice attenuates neointima formation

NARCIS (Netherlands)

McDonald, Robert A; White, Katie M; Wu, Junxi; Cooley, Brian C; Robertson, Keith E; Halliday, Crawford A; McClure, John D; Francis, Sheila; Lu, Ruifaug; Kennedy, Simon; George, Sarah J; Wan, Song; van Rooij, Eva; Baker, Andrew H

AIMS: The long-term failure of autologous saphenous vein bypass grafts due to neointimal thickening is a major clinical burden. Identifying novel strategies to prevent neointimal thickening is important. Thus, this study aimed to identify microRNAs (miRNAs) that are dysregulated during neointimal

8. Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

9. Homeotic function of Drosophila Bithorax-Complex miRNAs mediates fertility by restricting multiple Hox genes and TALE cofactors in the central nervous system

Science.gov (United States)

Garaulet, Daniel L.; Castellanos, Monica; Bejarano, Fernando; Sanfilippo, Piero; Tyler, David M.; Allan, Douglas W.; Sánchez-Herrero, Ernesto; Lai, Eric C.

2014-01-01

The Drosophila Bithorax-Complex (BX-C) Hox cluster contains a bidirectionally-transcribed miRNA locus, and a deletion mutant (∆mir) lays no eggs and is completely sterile. We show these miRNAs are expressed and active in distinct spatial registers along the anterior-posterior axis in the central nervous system. ∆mir larvae derepress a network of direct homeobox gene targets in the posterior ventral nerve cord (VNC), including BX-C genes and their TALE cofactors. These are phenotypically critical targets, since sterility of ∆mir mutants was substantially rescued by heterozygosity of these genes. The posterior VNC contains Ilp7+ oviduct motoneurons, whose innervation and morphology are defective in ∆mir females, and substantially rescued by heterozygosity of ∆mir targets, especially within the BX-C. Collectively, we reveal (1) critical roles for Hox miRNAs that determine segment-specific expression of homeotic genes, which are not masked by transcriptional regulation, and (2) that BX-C miRNAs are essential for neural patterning and reproductive behavior. PMID:24909902

10. GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies.

Science.gov (United States)

Sulovari, Arvis; Li, Dawei

2014-07-19

Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep

11. TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu

2016-06-25

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

12. TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu; Qin, Lu; Cheng, Hong; Zhang, Xiangliang; Zhou, Xiaofang

2016-01-01

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

13. Missing value imputation: with application to handwriting data

Science.gov (United States)

Xu, Zhen; Srihari, Sargur N.

2015-01-01

Missing values make pattern analysis difficult, particularly with limited available data. In longitudinal research, missing values accumulate, thereby aggravating the problem. Here we consider how to deal with temporal data with missing values in handwriting analysis. In the task of studying development of individuality of handwriting, we encountered the fact that feature values are missing for several individuals at several time instances. Six algorithms, i.e., random imputation, mean imputation, most likely independent value imputation, and three methods based on Bayesian network (static Bayesian network, parameter EM, and structural EM), are compared with children's handwriting data. We evaluate the accuracy and robustness of the algorithms under different ratios of missing data and missing values, and useful conclusions are given. Specifically, static Bayesian network is used for our data which contain around 5% missing data to provide adequate accuracy and low computational cost.

14. Imputed prices of greenhouse gases and land forests

International Nuclear Information System (INIS)

Uzawa, Hirofumi

1993-01-01

The theory of dynamic optimum formulated by Maeler gives us the basic theoretical framework within which it is possible to analyse the economic and, possibly, political circumstances under which the phenomenon of global warming occurs, and to search for the policy and institutional arrangements whereby it would be effectively arrested. The analysis developed here is an application of Maeler's theory to atmospheric quality. In the analysis a central role is played by the concept of imputed price in the dynamic context. Our determination of imputed prices of atmospheric carbon dioxide and land forests takes into account the difference in the stages of economic development. Indeed, the ratios of the imputed prices of atmospheric carbon dioxide and land forests over the per capita level of real national income are identical for all countries involved. (3 figures, 2 tables) (Author)

15. miR-192, miR-194 and miR-215: a convergent microRNA network suppressing tumor progression in renal cell carcinoma.

Science.gov (United States)

Khella, H W Z; Bakhet, M; Allo, G; Jewett, M A S; Girgis, A H; Latif, A; Girgis, H; Von Both, I; Bjarnason, G A; Yousef, G M

2013-10-01

MicroRNAs (miRNAs) play a crucial role in tumor progression and metastasis. We, and others, recently identified a number of miRNAs that are dysregulated in metastatic renal cell carcinoma compared with primary renal cell carcinoma. Here, we investigated three miRNAs that are significantly downregulated in metastatic tumors: miR-192, miR-194 and miR-215. Gain-of-function analyses showed that restoration of their expression decreases cell migration and invasion in renal cell carcinoma cell line models, whereas knockdown of these miRNAs resulted in enhancing cellular migration and invasion abilities. We identified three targets of these miRNAs with potential role in tumor aggressiveness: murine double minute 2, thymidylate synthase, and Smad Interacting protein 1/zinc finger E-box binding homeobox 2. We observed a convergent effect (the same molecule can be targeted by all three miRNAs) and a divergent effect (the same miRNA can control multiple targets) for these miRNAs. We experimentally validated these miRNA-target interactions using three independent approaches. First, we observed that miRNA overexpression significantly reduces the mRNA and protein levels of their targets. In the second, we observed significant reduction of the luciferase signal of a vector containing the 3'UTR of the target upon miRNA overexpression. Finally, we show the presence of inverse correlation between miRNA changes and the expression levels of their targets in patient specimens. We also examined the prognostic significance of miR-215 in renal cell carcinoma. Lower expression of miR-215 is associated with significantly reduced disease-free survival time. These findings were validated on an independent data set from The Cancer Genome Atlas. These results can pave the way to the clinical use of miRNAs as prognostic markers and therapeutic targets.

16. Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel.

Science.gov (United States)

Mitt, Mario; Kals, Mart; Pärn, Kalle; Gabriel, Stacey B; Lander, Eric S; Palotie, Aarno; Ripatti, Samuli; Morris, Andrew P; Metspalu, Andres; Esko, Tõnu; Mägi, Reedik; Palta, Priit

2017-06-01

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies.

17. Sequence imputation of HPV16 genomes for genetic association studies.

Directory of Open Access Journals (Sweden)

Benjamin Smith

Full Text Available Human Papillomavirus type 16 (HPV16 causes over half of all cervical cancer and some HPV16 variants are more oncogenic than others. The genetic basis for the extraordinary oncogenic properties of HPV16 compared to other HPVs is unknown. In addition, we neither know which nucleotides vary across and within HPV types and lineages, nor which of the single nucleotide polymorphisms (SNPs determine oncogenicity.A reference set of 62 HPV16 complete genome sequences was established and used to examine patterns of evolutionary relatedness amongst variants using a pairwise identity heatmap and HPV16 phylogeny. A BLAST-based algorithm was developed to impute complete genome data from partial sequence information using the reference database. To interrogate the oncogenic risk of determined and imputed HPV16 SNPs, odds-ratios for each SNP were calculated in a case-control viral genome-wide association study (VWAS using biopsy confirmed high-grade cervix neoplasia and self-limited HPV16 infections from Guanacaste, Costa Rica.HPV16 variants display evolutionarily stable lineages that contain conserved diagnostic SNPs. The imputation algorithm indicated that an average of 97.5±1.03% of SNPs could be accurately imputed. The VWAS revealed specific HPV16 viral SNPs associated with variant lineages and elevated odds ratios; however, individual causal SNPs could not be distinguished with certainty due to the nature of HPV evolution.Conserved and lineage-specific SNPs can be imputed with a high degree of accuracy from limited viral polymorphic data due to the lack of recombination and the stochastic mechanism of variation accumulation in the HPV genome. However, to determine the role of novel variants or non-lineage-specific SNPs by VWAS will require direct sequence analysis. The investigation of patterns of genetic variation and the identification of diagnostic SNPs for lineages of HPV16 variants provides a valuable resource for future studies of HPV16

18. Imputing amino acid polymorphisms in human leukocyte antigens.

Directory of Open Access Journals (Sweden)

Xiaoming Jia

Full Text Available DNA sequence variation within human leukocyte antigen (HLA genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A, -B, -C and class II (-DPA1, -DPB1, -DQA1, -DQB1, and -DRB1 loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals. We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N = 918 with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the high-density Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.

19. Pharmaco-miR

DEFF Research Database (Denmark)

Rukov, Jakob Lewin; Wilentzik, Roni; Jaffe, Ishai

2014-01-01

MicroRNAs (miRNAs) are short regulatory RNAs that down-regulate gene expression. They are essential for cell homeostasis and active in many disease states. A major discovery is the ability of miRNAs to determine the efficacy of drugs, which has given rise to the field of 'miRNA pharmacogenomics......' through 'Pharmaco-miRs'. miRNAs play a significant role in pharmacogenomics by down-regulating genes that are important for drug function. These interactions can be described as triplet sets consisting of a miRNA, a target gene and a drug associated with the gene. We have developed a web server which...... links miRNA expression and drug function by combining data on miRNA targeting and protein-drug interactions. miRNA targeting information derive from both experimental data and computational predictions, and protein-drug interactions are annotated by the Pharmacogenomics Knowledge base (Pharm...

20. Imputation of the rare HOXB13 G84E mutation and cancer risk in a large population-based cohort.

Directory of Open Access Journals (Sweden)

Thomas J Hoffmann

2015-01-01

Full Text Available An efficient approach to characterizing the disease burden of rare genetic variants is to impute them into large well-phenotyped cohorts with existing genome-wide genotype data using large sequenced referenced panels. The success of this approach hinges on the accuracy of rare variant imputation, which remains controversial. For example, a recent study suggested that one cannot adequately impute the HOXB13 G84E mutation associated with prostate cancer risk (carrier frequency of 0.0034 in European ancestry participants in the 1000 Genomes Project. We show that by utilizing the 1000 Genomes Project data plus an enriched reference panel of mutation carriers we were able to accurately impute the G84E mutation into a large cohort of 83,285 non-Hispanic White participants from the Kaiser Permanente Research Program on Genes, Environment and Health Genetic Epidemiology Research on Adult Health and Aging cohort. Imputation authenticity was confirmed via a novel classification and regression tree method, and then empirically validated analyzing a subset of these subjects plus an additional 1,789 men from Kaiser specifically genotyped for the G84E mutation (r2 = 0.57, 95% CI = 0.37–0.77. We then show the value of this approach by using the imputed data to investigate the impact of the G84E mutation on age-specific prostate cancer risk and on risk of fourteen other cancers in the cohort. The age-specific risk of prostate cancer among G84E mutation carriers was higher than among non-carriers. Risk estimates from Kaplan-Meier curves were 36.7% versus 13.6% by age 72, and 64.2% versus 24.2% by age 80, for G84E mutation carriers and non-carriers, respectively (p = 3.4x10-12. The G84E mutation was also associated with an increase in risk for the fourteen other most common cancers considered collectively (p = 5.8x10-4 and more so in cases diagnosed with multiple cancer types, both those including and not including prostate cancer, strongly suggesting

1. Handling missing data for the identification of charged particles in a multilayer detector: A comparison between different imputation methods

Energy Technology Data Exchange (ETDEWEB)

Riggi, S., E-mail: sriggi@oact.inaf.it [INAF - Osservatorio Astrofisico di Catania (Italy); Riggi, D. [Keras Strategy - Milano (Italy); Riggi, F. [Dipartimento di Fisica e Astronomia - Università di Catania (Italy); INFN, Sezione di Catania (Italy)

2015-04-21

Identification of charged particles in a multilayer detector by the energy loss technique may also be achieved by the use of a neural network. The performance of the network becomes worse when a large fraction of information is missing, for instance due to detector inefficiencies. Algorithms which provide a way to impute missing information have been developed over the past years. Among the various approaches, we focused on normal mixtures’ models in comparison with standard mean imputation and multiple imputation methods. Further, to account for the intrinsic asymmetry of the energy loss data, we considered skew-normal mixture models and provided a closed form implementation in the Expectation-Maximization (EM) algorithm framework to handle missing patterns. The method has been applied to a test case where the energy losses of pions, kaons and protons in a six-layers’ Silicon detector are considered as input neurons to a neural network. Results are given in terms of reconstruction efficiency and purity of the various species in different momentum bins.

2. "Seed-Milarity" confers to hsa-miR-210 and hsa-miR-147b similar functional activity.

Directory of Open Access Journals (Sweden)

Thomas Bertero

Full Text Available Specificity of interaction between a microRNA (miRNA and its targets crucially depends on the seed region located in its 5'-end. It is often implicitly considered that two miRNAs sharing the same biological activity should display similarity beyond the strict six nucleotide region that forms the seed, in order to form specific complexes with the same mRNA targets. We have found that expression of hsa-miR-147b and hsa-miR-210, though triggered by different stimuli (i.e. lipopolysaccharides and hypoxia, respectively, induce very similar cellular effects in term of proliferation, migration and apoptosis. Hsa-miR-147b only shares a "minimal" 6-nucleotides seed sequence with hsa-miR-210, but is identical with hsa-miR-147a over 20 nucleotides, except for one base located in the seed region. Phenotypic changes induced after heterologous expression of miR-147a strikingly differ from those induced by miR-147b or miR-210. In particular, miR-147a behaves as a potent inhibitor of cell proliferation and migration. These data fit well with the gene expression profiles observed for miR-147b and miR-210, which are very similar, and the gene expression profile of miR-147a, which is distinct from the two others. Bioinformatics analysis of all human miRNA sequences indicates multiple cases of miRNAs from distinct families exhibiting the same kind of similarity that would need to be further characterized in terms of putative functional redundancy. Besides, it implies that functional impact of some miRNAs can be masked by robust expression of miRNAs belonging to distinct families.

3. An Imputation Model for Dropouts in Unemployment Data

Directory of Open Access Journals (Sweden)

Nilsson Petra

2016-09-01

Full Text Available Incomplete unemployment data is a fundamental problem when evaluating labour market policies in several countries. Many unemployment spells end for unknown reasons; in the Swedish Public Employment Service’s register as many as 20 percent. This leads to an ambiguity regarding destination states (employment, unemployment, retired, etc.. According to complete combined administrative data, the employment rate among dropouts was close to 50 for the years 1992 to 2006, but from 2007 the employment rate has dropped to 40 or less. This article explores an imputation approach. We investigate imputation models estimated both on survey data from 2005/2006 and on complete combined administrative data from 2005/2006 and 2011/2012. The models are evaluated in terms of their ability to make correct predictions. The models have relatively high predictive power.

4. Towards a more efficient representation of imputation operators in TPOT

OpenAIRE

Garciarena, Unai; Mendiburu, Alexander; Santana, Roberto

2018-01-01

Automated Machine Learning encompasses a set of meta-algorithms intended to design and apply machine learning techniques (e.g., model selection, hyperparameter tuning, model assessment, etc.). TPOT, a software for optimizing machine learning pipelines based on genetic programming (GP), is a novel example of this kind of applications. Recently we have proposed a way to introduce imputation methods as part of TPOT. While our approach was able to deal with problems with missing data, it can prod...

5. DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

6. Which DTW Method Applied to Marine Univariate Time Series Imputation

OpenAIRE

Phan , Thi-Thu-Hong; Caillault , Émilie; Lefebvre , Alain; Bigand , André

2017-01-01

International audience; Missing data are ubiquitous in any domains of applied sciences. Processing datasets containing missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Therefore, the aim of this paper is to build a framework for filling missing values in univariate time series and to perform a comparison of different similarity metrics used for the imputation task. This allows to suggest the most suitable methods for the imp...

7. Imputation of missing data in time series for air pollutants

Science.gov (United States)

Junger, W. L.; Ponce de Leon, A.

2015-02-01

Missing data are major concerns in epidemiological studies of the health effects of environmental air pollutants. This article presents an imputation-based method that is suitable for multivariate time series data, which uses the EM algorithm under the assumption of normal distribution. Different approaches are considered for filtering the temporal component. A simulation study was performed to assess validity and performance of proposed method in comparison with some frequently used methods. Simulations showed that when the amount of missing data was as low as 5%, the complete data analysis yielded satisfactory results regardless of the generating mechanism of the missing data, whereas the validity began to degenerate when the proportion of missing values exceeded 10%. The proposed imputation method exhibited good accuracy and precision in different settings with respect to the patterns of missing observations. Most of the imputations obtained valid results, even under missing not at random. The methods proposed in this study are implemented as a package called mtsdi for the statistical software system R.

8. A spatial haplotype copying model with applications to genotype imputation.

Science.gov (United States)

Yang, Wen-Yun; Hormozdiari, Farhad; Eskin, Eleazar; Pasaniuc, Bogdan

2015-05-01

Ever since its introduction, the haplotype copy model has proven to be one of the most successful approaches for modeling genetic variation in human populations, with applications ranging from ancestry inference to genotype phasing and imputation. Motivated by coalescent theory, this approach assumes that any chromosome (haplotype) can be modeled as a mosaic of segments copied from a set of chromosomes sampled from the same population. At the core of the model is the assumption that any chromosome from the sample is equally likely to contribute a priori to the copying process. Motivated by recent works that model genetic variation in a geographic continuum, we propose a new spatial-aware haplotype copy model that jointly models geography and the haplotype copying process. We extend hidden Markov models of haplotype diversity such that at any given location, haplotypes that are closest in the genetic-geographic continuum map are a priori more likely to contribute to the copying process than distant ones. Through simulations starting from the 1000 Genomes data, we show that our model achieves superior accuracy in genotype imputation over the standard spatial-unaware haplotype copy model. In addition, we show the utility of our model in selecting a small personalized reference panel for imputation that leads to both improved accuracy as well as to a lower computational runtime than the standard approach. Finally, we show our proposed model can be used to localize individuals on the genetic-geographical map on the basis of their genotype data.

9. miR-29b, miR-205 and miR-221 enhance chemosensitivity to gemcitabine in HuH28 human cholangiocarcinoma cells.

Directory of Open Access Journals (Sweden)

Kinya Okamoto

Full Text Available BACKGROUND AND AIMS: Cholangiocarcinoma (CCA is highly resistant to chemotherapy, including gemcitabine (Gem treatment. MicroRNAs (miRNAs are endogenous, non-coding, short RNAs that can regulate multiple genes expression. Some miRNAs play important roles in the chemosensitivity of tumors. Here, we examined the relationship between miRNA expression and the sensitivity of CCA cells to Gem. METHODS: Microarray analysis was used to determine the miRNA expression profiles of two CCA cell lines, HuH28 and HuCCT1. To determine the effect of candidate miRNAs on Gem sensitivity, expression of each candidate miRNA was modified via either transfection of a miRNA mimic or transfection of an anti-oligonucleotide. Ontology-based programs were used to identify potential target genes of candidate miRNAs that were confirmed to affect the Gem sensitivity of CCA cells. RESULTS: HuCCT1 cells were more sensitive to Gem than were HuH28 cells, and 18 miRNAs were differentially expressed whose ratios over ± 2log2 between HuH28 and HuCCT1. Among these 18 miRNAs, ectopic overexpression of each of three downregulated miRNAs in HuH28 (miR-29b, miR-205, miR-221 restored Gem sensitivity to HuH28. Suppression of one upregulated miRNA in HuH28, miR-125a-5p, inhibited HuH28 cell proliferation independently to Gem treatment. Selective siRNA-mediated downregulation of either of two software-predicted targets, PIK3R1 (target of miR-29b and miR-221 or MMP-2 (target of miR-29b, also conferred Gem sensitivity to HuH28. CONCLUSIONS: miRNA expression profiling was used to identify key miRNAs that regulate Gem sensitivity in CCA cells, and software that predicts miRNA targets was used to identify promising target genes for anti-tumor therapies.

10. Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data.

Science.gov (United States)

Ritz, Cecilia; Edén, Patrik

2008-01-19

For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such "one-channel depletion" is so far not included in algorithms for imputation of missing values. Calculating the mean deviation between imputed values and duplicate controls in five datasets, we show that KNN-based imputation gives a systematic bias of the imputed expression values of one-channel depleted spots. Evaluating the correction of this bias by cross-validation showed that the mean square deviation between imputed values and duplicates were reduced up to 51%, depending on dataset. By including more information in the imputation step, we more accurately estimate missing expression values.

11. Mi-DISCOVERER: A bioinformatics tool for the detection of mi-RNA in human genome.

Science.gov (United States)

2010-11-27

MicroRNAs (miRNAs) are 22 nucleotides non-coding RNAs that play pivotal regulatory roles in diverse organisms including the humans and are difficult to be identified due to lack of either sequence features or robust algorithms to efficiently identify. Therefore, we made a tool that is Mi-Discoverer for the detection of miRNAs in human genome. The tools used for the development of software are Microsoft Office Access 2003, the JDK version 1.6.0, BioJava version 1.0, and the NetBeans IDE version 6.0. All already made miRNAs softwares were web based; so the advantage of our project was to make a desktop facility to the user for sequence alignment search with already identified miRNAs of human genome present in the database. The user can also insert and update the newly discovered human miRNA in the database. Mi-Discoverer, a bioinformatics tool successfully identifies human miRNAs based on multiple sequence alignment searches. It's a non redundant database containing a large collection of publicly available human miRNAs.

12. Performance of genotype imputation for low frequency and rare variants from the 1000 genomes.

Science.gov (United States)

Zheng, Hou-Feng; Rong, Jing-Jing; Liu, Ming; Han, Fang; Zhang, Xing-Wei; Richards, J Brent; Wang, Li

2015-01-01

Genotype imputation is now routinely applied in genome-wide association studies (GWAS) and meta-analyses. However, most of the imputations have been run using HapMap samples as reference, imputation of low frequency and rare variants (minor allele frequency (MAF) 1000 Genomes panel) are available to facilitate imputation of these variants. Therefore, in order to estimate the performance of low frequency and rare variants imputation, we imputed 153 individuals, each of whom had 3 different genotype array data including 317k, 610k and 1 million SNPs, to three different reference panels: the 1000 Genomes pilot March 2010 release (1KGpilot), the 1000 Genomes interim August 2010 release (1KGinterim), and the 1000 Genomes phase1 November 2010 and May 2011 release (1KGphase1) by using IMPUTE version 2. The differences between these three releases of the 1000 Genomes data are the sample size, ancestry diversity, number of variants and their frequency spectrum. We found that both reference panel and GWAS chip density affect the imputation of low frequency and rare variants. 1KGphase1 outperformed the other 2 panels, at higher concordance rate, higher proportion of well-imputed variants (info>0.4) and higher mean info score in each MAF bin. Similarly, 1M chip array outperformed 610K and 317K. However for very rare variants (MAF ≤ 0.3%), only 0-1% of the variants were well imputed. We conclude that the imputation of low frequency and rare variants improves with larger reference panels and higher density of genome-wide genotyping arrays. Yet, despite a large reference panel size and dense genotyping density, very rare variants remain difficult to impute.

13. Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.

Science.gov (United States)

Frischknecht, Mirjam; Pausch, Hubert; Bapst, Beat; Signer-Hasler, Heidi; Flury, Christine; Garrick, Dorian; Stricker, Christian; Fries, Ruedi; Gredler-Grandl, Birgit

2017-12-29

Within the last few years a large amount of genomic information has become available in cattle. Densities of genomic information vary from a few thousand variants up to whole genome sequence information. In order to combine genomic information from different sources and infer genotypes for a common set of variants, genotype imputation is required. In this study we evaluated the accuracy of imputation from high density chips to whole genome sequence data in Brown Swiss cattle. Using four popular imputation programs (Beagle, FImpute, Impute2, Minimac) and various compositions of reference panels, the accuracy of the imputed sequence variant genotypes was high and differences between the programs and scenarios were small. We imputed sequence variant genotypes for more than 1600 Brown Swiss bulls and performed genome-wide association studies for milk fat percentage at two stages of lactation. We found one and three quantitative trait loci for early and late lactation fat content, respectively. Known causal variants that were imputed from the sequenced reference panel were among the most significantly associated variants of the genome-wide association study. Our study demonstrates that whole-genome sequence information can be imputed at high accuracy in cattle populations. Using imputed sequence variant genotypes in genome-wide association studies may facilitate causal variant detection.

14. The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

Directory of Open Access Journals (Sweden)

Rosa Aghdam

2017-12-01

Full Text Available Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/.

15. The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

Science.gov (United States)

Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

16. Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation.

Science.gov (United States)

Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi

2016-06-21

Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.

17. Imputation of genotypes in Danish two-way crossbred pigs using low density panels

DEFF Research Database (Denmark)

Xiang, Tao; Christensen, Ole Fredslund; Legarra, Andres

Genotype imputation is commonly used as an initial step of genomic selection. Studies on humans, plants and ruminants suggested many factors would affect the performance of imputation. However, studies rarely investigated pigs, especially crossbred pigs. In this study, different scenarios...... of imputation from 5K SNPs to 7K SNPs on Danish Landrace, Yorkshire, and crossbred Landrace-Yorkshire were compared. In conclusion, genotype imputation on crossbreds performs equally well as in purebreds, when parental breeds are used as the reference panel. When the size of reference is considerably large...... SNPs. This dataset will be analyzed for genomic selection in a future study...

18. miR-92a family and their target genes in tumorigenesis and metastasis

Energy Technology Data Exchange (ETDEWEB)

Li, Molin, E-mail: molin_li@hotmail.com [Department of Pathophysiology, Basic Medical Science of Dalian Medical University, Dalian 116044 (China); Institute of Cancer Stem Cell, Dalian Medical University Cancer Center, Dalian 116044 (China); Guan, Xingfang; Sun, Yuqiang [Department of Pathophysiology, Basic Medical Science of Dalian Medical University, Dalian 116044 (China); Mi, Jun [Institute of Cancer Stem Cell, Dalian Medical University Cancer Center, Dalian 116044 (China); Shu, Xiaohong [College of Pharmacy, Dalian Medical University Cancer Center, Dalian 116044 (China); Liu, Fang [Department of Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian 116027 (China); Li, Chuangang, E-mail: li_chuangang@sina.com [Department of Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian 116027 (China)

2014-04-15

The miR-92a family, including miR-25, miR-92a-1, miR-92a-2 and miR-363, arises from three different paralog clusters miR-17-92, miR-106a-363, and miR-106b-25 that are highly conservative in the process of evolution, and it was thought as a group of microRNAs (miRNAs) correlated with endothelial cells. Aberrant expression of miR-92a family was detected in multiple cancers, and the disturbance of miR-92a family was related with tumorigenesis and tumor development. In this review, the progress on the relationship between miR-92a family and their target genes and malignant tumors will be summarized. - Highlights: • Aberrant expression of miR-92a, miR-25 and miR-363 can be observed in many kinds of malignant tumors. • The expression of miR-92a family is regulated by LOH, epigenetic alteration, transcriptional factors such as SP1, MYC, E2F, wild-type p53 etc. • Roles of miR-92a family in tumorigenesis and development: promoting cell proliferation, invasion and metastasis, inhibiting cell apoptosis.

19. miR-92a family and their target genes in tumorigenesis and metastasis

International Nuclear Information System (INIS)

Li, Molin; Guan, Xingfang; Sun, Yuqiang; Mi, Jun; Shu, Xiaohong; Liu, Fang; Li, Chuangang

2014-01-01

The miR-92a family, including miR-25, miR-92a-1, miR-92a-2 and miR-363, arises from three different paralog clusters miR-17-92, miR-106a-363, and miR-106b-25 that are highly conservative in the process of evolution, and it was thought as a group of microRNAs (miRNAs) correlated with endothelial cells. Aberrant expression of miR-92a family was detected in multiple cancers, and the disturbance of miR-92a family was related with tumorigenesis and tumor development. In this review, the progress on the relationship between miR-92a family and their target genes and malignant tumors will be summarized. - Highlights: • Aberrant expression of miR-92a, miR-25 and miR-363 can be observed in many kinds of malignant tumors. • The expression of miR-92a family is regulated by LOH, epigenetic alteration, transcriptional factors such as SP1, MYC, E2F, wild-type p53 etc. • Roles of miR-92a family in tumorigenesis and development: promoting cell proliferation, invasion and metastasis, inhibiting cell apoptosis

20. Evaluation and application of summary statistic imputation to discover new height-associated loci.

Science.gov (United States)

Rüeger, Sina; McDaid, Aaron; Kutalik, Zoltán

2018-05-01

As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian

1. Improved Correction of Misclassification Bias With Bootstrap Imputation.

Science.gov (United States)

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

2. Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets

Directory of Open Access Journals (Sweden)

Min-Wei Huang

2018-01-01

Full Text Available Many real-world medical datasets contain some proportion of missing (attribute values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based on the (complete observed data. However, if the observed data contain some noisy information or outliers, the estimations of the missing values may not be reliable or may even be quite different from the real values. The aim of this paper is to examine whether a combination of instance selection from the observed data and missing value imputation offers better performance than performing missing value imputation alone. In particular, three instance selection algorithms, DROP3, GA, and IB3, and three imputation algorithms, KNNI, MLP, and SVM, are used in order to find out the best combination. The experimental results show that that performing instance selection can have a positive impact on missing value imputation over the numerical data type of medical datasets, and specific combinations of instance selection and imputation methods can improve the imputation results over the mixed data type of medical datasets. However, instance selection does not have a definitely positive impact on the imputation result for categorical medical datasets.

3. Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

NARCIS (Netherlands)

I. Tachmazidou (Ioanna); Süveges, D. (Dániel); J. Min (Josine); G.R.S. Ritchie (Graham R.S.); Steinberg, J. (Julia); K. Walter (Klaudia); V. Iotchkova (Valentina); J.A. Schwartzentruber (Jeremy); J. Huang (Jian); Y. Memari (Yasin); McCarthy, S. (Shane); Crawford, A.A. (Andrew A.); C. Bombieri (Cristina); M. Cocca (Massimiliano); A.-E. Farmaki (Aliki-Eleni); T.R. Gaunt (Tom); P. Jousilahti (Pekka); M.N. Kooijman (Marjolein ); Lehne, B. (Benjamin); G. Malerba (Giovanni); S. Männistö (Satu); A. Matchan (Angela); M.C. Medina-Gomez (Carolina); S. Metrustry (Sarah); A. Nag (Abhishek); I. Ntalla (Ioanna); L. Paternoster (Lavinia); N.W. Rayner (Nigel William); C. Sala (Cinzia); W.R. Scott (William R.); H.A. Shihab (Hashem A.); L. Southam (Lorraine); B. St Pourcain (Beate); M. Traglia (Michela); K. Trajanoska (Katerina); Zaza, G. (Gialuigi); W. Zhang (Weihua); M.S. Artigas; Bansal, N. (Narinder); M. Benn (Marianne); Chen, Z. (Zhongsheng); P. Danecek (Petr); Lin, W.-Y. (Wei-Yu); A. Locke (Adam); J. Luan (Jian'An); A.K. Manning (Alisa); Mulas, A. (Antonella); C. Sidore (Carlo); A. Tybjaerg-Hansen; A. Varbo (Anette); M. Zoledziewska (Magdalena); C. Finan (Chris); Hatzikotoulas, K. (Konstantinos); A.E. Hendricks (Audrey E.); J.P. Kemp (John); A. Moayyeri (Alireza); Panoutsopoulou, K. (Kalliope); Szpak, M. (Michal); S.G. Wilson (Scott); M. Boehnke (Michael); F. Cucca (Francesco); Di Angelantonio, E. (Emanuele); C. Langenberg (Claudia); C.M. Lindgren (Cecilia M.); McCarthy, M.I. (Mark I.); A.P. Morris (Andrew); B.G. Nordestgaard (Børge); R.A. Scott (Robert); M.D. Tobin (Martin); N.J. Wareham (Nick); P.R. Burton (Paul); J.C. Chambers (John); Smith, G.D. (George Davey); G.V. Dedoussis (George); J.F. Felix (Janine); O.H. Franco (Oscar); Gambaro, G. (Giovanni); P. Gasparini (Paolo); C.J. Hammond (Christopher J.); A. Hofman (Albert); V.W.V. Jaddoe (Vincent); M.E. Kleber (Marcus); J.S. Kooner (Jaspal S.); M. Perola (Markus); C.L. Relton (Caroline); S.M. Ring (Susan); F. Rivadeneira Ramirez (Fernando); V. Salomaa (Veikko); T.D. Spector (Timothy); O. Stegle (Oliver); D. Toniolo (Daniela); A.G. Uitterlinden (André); I.E. Barroso (Inês); C.M.T. Greenwood (Celia); Perry, J.R.B. (John R.B.); Walker, B.R. (Brian R.); A.S. Butterworth (Adam); Y. Xue (Yali); R. Durbin (Richard); K.S. Small (Kerrin); N. Soranzo (Nicole); N.J. Timpson (Nicholas); E. Zeggini (Eleftheria)

2016-01-01

textabstractDeep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the

4. Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

DEFF Research Database (Denmark)

Tachmazidou, Ioanna; Süveges, Dániel; Min, Josine L

2017-01-01

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader alleli...

5. 48 CFR 1830.7002-4 - Determining imputed cost of money.

Science.gov (United States)

2010-10-01

... money. 1830.7002-4 Section 1830.7002-4 Federal Acquisition Regulations System NATIONAL AERONAUTICS AND... Determining imputed cost of money. (a) Determine the imputed cost of money for an asset under construction, fabrication, or development by applying a cost of money rate (see 1830.7002-2) to the representative...

6. MiR-218 Mediates tumorigenesis and metastasis: Perspectives and implications

International Nuclear Information System (INIS)

Lu, Ying-fei; Zhang, Li; Waye, Mary Miu Yee; Fu, Wei-ming; Zhang, Jin-fang

2015-01-01

MicroRNAs (miRNAs) are a class of small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. As a highly conserved miRNA across a variety of species, microRNA-218 (miR-218) was found to play pivotal roles in tumorigenesis and progression. A group of evidence has demonstrated that miR-218 acts as a tumor suppressor by targeting many oncogenes related to proliferation, apoptosis and invasion. In this review, we provide a complex overview of miR-218, including its regulatory mechanisms, known functions in cancer and future challenges as a potential therapeutic target in human cancers. - Highlights: • miR-218 is frequently down regulated in multiple cancers. • miR-218 plays pivotal roles in carcinogenesis. • miR-218 mediates proliferation, apoptosis, metastasis, invasion, etc. • miR-218 mediates tumorigenesis and metastasis via multiple pathways

7. MiR-218 Mediates tumorigenesis and metastasis: Perspectives and implications

Energy Technology Data Exchange (ETDEWEB)

Lu, Ying-fei [Institute Guangzhou of Advanced Technology, Chinese Academy of Sciences, Guangzhou (China); Department of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (China); Zhang, Li [School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong (China); Department of Anatomical and Cellular Pathology, State Key Laboratory of Oncology in South China, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong (China); Waye, Mary Miu Yee [School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong (China); Fu, Wei-ming, E-mail: wm.fu@giat.ac.cn [Institute Guangzhou of Advanced Technology, Chinese Academy of Sciences, Guangzhou (China); School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong (China); Zhang, Jin-fang, E-mail: zhangjf06@cuhk.edu.hk [Department of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong (China); School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong (China); Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen (China)

2015-05-15

MicroRNAs (miRNAs) are a class of small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. As a highly conserved miRNA across a variety of species, microRNA-218 (miR-218) was found to play pivotal roles in tumorigenesis and progression. A group of evidence has demonstrated that miR-218 acts as a tumor suppressor by targeting many oncogenes related to proliferation, apoptosis and invasion. In this review, we provide a complex overview of miR-218, including its regulatory mechanisms, known functions in cancer and future challenges as a potential therapeutic target in human cancers. - Highlights: • miR-218 is frequently down regulated in multiple cancers. • miR-218 plays pivotal roles in carcinogenesis. • miR-218 mediates proliferation, apoptosis, metastasis, invasion, etc. • miR-218 mediates tumorigenesis and metastasis via multiple pathways.

8. Expression patterns of miR-146a and miR-146b in mastitis infected dairy cattle.

Science.gov (United States)

Wang, Xing Ping; Luoreng, Zhuo Ma; Zan, Lin Sen; Raza, Sayed Haidar Abbas; Li, Feng; Li, Na; Liu, Shuan

2016-10-01

This study reports a significant up-regulation of bta-miR-146a and bta-miR-146b expression levels in bovine mammary tissues infected with subclinical, clinical and experimental mastitis. Potential target genes are involved in multiple immunological pathways. These results suggest a regulatory function of both miRNAs for the bovine inflammatory response in mammary tissue. Copyright © 2016 Elsevier Ltd. All rights reserved.

9. Evaluating Imputation Algorithms for Low-Depth Genotyping-By-Sequencing (GBS Data.

Directory of Open Access Journals (Sweden)

Ariel W Chan

Full Text Available Well-powered genomic studies require genome-wide marker coverage across many individuals. For non-model species with few genomic resources, high-throughput sequencing (HTS methods, such as Genotyping-By-Sequencing (GBS, offer an inexpensive alternative to array-based genotyping. Although affordable, datasets derived from HTS methods suffer from sequencing error, alignment errors, and missing data, all of which introduce noise and uncertainty to variant discovery and genotype calling. Under such circumstances, meaningful analysis of the data is difficult. Our primary interest lies in the issue of how one can accurately infer or impute missing genotypes in HTS-derived datasets. Many of the existing genotype imputation algorithms and software packages were primarily developed by and optimized for the human genetics community, a field where a complete and accurate reference genome has been constructed and SNP arrays have, in large part, been the common genotyping platform. We set out to answer two questions: 1 can we use existing imputation methods developed by the human genetics community to impute missing genotypes in datasets derived from non-human species and 2 are these methods, which were developed and optimized to impute ascertained variants, amenable for imputation of missing genotypes at HTS-derived variants? We selected Beagle v.4, a widely used algorithm within the human genetics community with reportedly high accuracy, to serve as our imputation contender. We performed a series of cross-validation experiments, using GBS data collected from the species Manihot esculenta by the Next Generation (NEXTGEN Cassava Breeding Project. NEXTGEN currently imputes missing genotypes in their datasets using a LASSO-penalized, linear regression method (denoted 'glmnet'. We selected glmnet to serve as a benchmark imputation method for this reason. We obtained estimates of imputation accuracy by masking a subset of observed genotypes, imputing, and

10. Evaluating Imputation Algorithms for Low-Depth Genotyping-By-Sequencing (GBS) Data.

Science.gov (United States)

Chan, Ariel W; Hamblin, Martha T; Jannink, Jean-Luc

2016-01-01

Well-powered genomic studies require genome-wide marker coverage across many individuals. For non-model species with few genomic resources, high-throughput sequencing (HTS) methods, such as Genotyping-By-Sequencing (GBS), offer an inexpensive alternative to array-based genotyping. Although affordable, datasets derived from HTS methods suffer from sequencing error, alignment errors, and missing data, all of which introduce noise and uncertainty to variant discovery and genotype calling. Under such circumstances, meaningful analysis of the data is difficult. Our primary interest lies in the issue of how one can accurately infer or impute missing genotypes in HTS-derived datasets. Many of the existing genotype imputation algorithms and software packages were primarily developed by and optimized for the human genetics community, a field where a complete and accurate reference genome has been constructed and SNP arrays have, in large part, been the common genotyping platform. We set out to answer two questions: 1) can we use existing imputation methods developed by the human genetics community to impute missing genotypes in datasets derived from non-human species and 2) are these methods, which were developed and optimized to impute ascertained variants, amenable for imputation of missing genotypes at HTS-derived variants? We selected Beagle v.4, a widely used algorithm within the human genetics community with reportedly high accuracy, to serve as our imputation contender. We performed a series of cross-validation experiments, using GBS data collected from the species Manihot esculenta by the Next Generation (NEXTGEN) Cassava Breeding Project. NEXTGEN currently imputes missing genotypes in their datasets using a LASSO-penalized, linear regression method (denoted 'glmnet'). We selected glmnet to serve as a benchmark imputation method for this reason. We obtained estimates of imputation accuracy by masking a subset of observed genotypes, imputing, and calculating the

11. Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

Science.gov (United States)

Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

2009-02-01

One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

12. Traffic Speed Data Imputation Method Based on Tensor Completion

Directory of Open Access Journals (Sweden)

Bin Ran

2015-01-01

Full Text Available Traffic speed data plays a key role in Intelligent Transportation Systems (ITS; however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS. In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC, an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

13. Traffic speed data imputation method based on tensor completion.

Science.gov (United States)

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

14. An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data.

Science.gov (United States)

Liu, Yuzhe; Gopalakrishnan, Vanathi

2017-03-01

Many clinical research datasets have a large percentage of missing values that directly impacts their usefulness in yielding high accuracy classifiers when used for training in supervised machine learning. While missing value imputation methods have been shown to work well with smaller percentages of missing values, their ability to impute sparse clinical research data can be problem specific. We previously attempted to learn quantitative guidelines for ordering cardiac magnetic resonance imaging during the evaluation for pediatric cardiomyopathy, but missing data significantly reduced our usable sample size. In this work, we sought to determine if increasing the usable sample size through imputation would allow us to learn better guidelines. We first review several machine learning methods for estimating missing data. Then, we apply four popular methods (mean imputation, decision tree, k-nearest neighbors, and self-organizing maps) to a clinical research dataset of pediatric patients undergoing evaluation for cardiomyopathy. Using Bayesian Rule Learning (BRL) to learn ruleset models, we compared the performance of imputation-augmented models versus unaugmented models. We found that all four imputation-augmented models performed similarly to unaugmented models. While imputation did not improve performance, it did provide evidence for the robustness of our learned models.

15. The expression of miR-181a-5p and miR-371b-5p in chondrosarcoma.

Science.gov (United States)

Mutlu, S; Mutlu, H; Kirkbes, S; Eroglu, S; Kabukcuoglu, Y S; Kabukcuoglu, F; Duymus, T M; ISık, M; Ulasli, M

2015-07-01

Chondrosarcomas are malignant tumors of chondrocytes that affect bones and joints, and it represents the third most common type of primary bone tumors. Chondrosarcoma is difficult to treat because it is relatively resistant to both chemotherapy and radiation. Thus, surgery remains the best available treatment. It is important to find new diagnostic markers and improve treatment options. miRNAs are small non-coding transcripts (19-25 nucleotides) that regulate gene expression via targeting complementary sequences within messenger RNAs (mRNAs). miRNAs have been shown to be involved in regulation of many biochemical pathways. Dysregulated expression of many miRNAs has also been associated with multiple human diseases, such as cancer. 18 surgical chondrosarcoma specimens were obtained from patients. RNA extractions were performed from decalcified paraffin embedded tissues. The aim of this study was to investigate the expression levels of miR-181a and miR-371b in patients with chondrosarcoma by using RT-PCR and to evaluate the relationship between these miRNAs and chondrosarcoma. miR-181a was found to be upregulated in chondrosarcoma specimens whereas no significant alteration was found for miR-371b expression. It has been proposed that miRNA expression studies might be used as diagnostic, prognostic marker in cancer. miRNA expression data produced in our study may contribute future chondrosarcoma diagnosis and therapy.

16. miR-200b mediates post-transcriptional repression of ZFHX1B

DEFF Research Database (Denmark)

Christoffersen, Nanna Rønbjerg; Silahtaroglu, Asli; Ørom, Ulf Lupo Andersson

2007-01-01

of E-cadherin. We show that Zfhx1b and miR-200b are regionally coexpressed in the adult mouse brain and that miR-200b represses the expression of Zfhx1b via multiple sequence elements present in the 3'-untranslated region. Overexpression of miR-200b leads to repression of endogenous ZFHX1B...

17. Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population

DEFF Research Database (Denmark)

Ma, Peipei; Lund, Mogens Sandø; Ding, X

2015-01-01

This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows...... was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy...... to increase reference population rather than increasing marker density...

18. miR-181a and miR-630 regulate cisplatin-induced cancer cell death.

Science.gov (United States)

Galluzzi, Lorenzo; Morselli, Eugenia; Vitale, Ilio; Kepp, Oliver; Senovilla, Laura; Criollo, Alfredo; Servant, Nicolas; Paccard, Caroline; Hupé, Philippe; Robert, Thomas; Ripoche, Hugues; Lazar, Vladimir; Harel-Bellan, Annick; Dessen, Philippe; Barillot, Emmanuel; Kroemer, Guido

2010-03-01

MicroRNAs (miRNA) are noncoding RNAs that regulate multiple cellular processes, including proliferation and apoptosis. We used microarray technology to identify miRNAs that were upregulated by non-small cell lung cancer (NSCLC) A549 cells in response to cisplatin (CDDP). The corresponding synthetic miRNA precursors (pre-miRNAs) per se were not lethal when transfected into A549 cells yet affected cell death induction by CDDP, C2-ceramide, cadmium, etoposide, and mitoxantrone in an inducer-specific fashion. Whereas synthetic miRNA inhibitors (anti-miRNAs) targeting miR-181a and miR-630 failed to modulate the response of A549 to CDDP, pre-miR-181a and pre-miR-630 enhanced and reduced CDDP-triggered cell death, respectively. Pre-miR-181a and pre-miR-630 consistently modulated mitochondrial/postmitochondrial steps of the intrinsic pathway of apoptosis, including Bax oligomerization, mitochondrial transmembrane potential dissipation, and the proteolytic maturation of caspase-9 and caspase-3. In addition, pre-miR-630 blocked early manifestations of the DNA damage response, including the phosphorylation of the ataxia-telangiectasia mutated (ATM) kinase and of two ATM substrates, histone H2AX and p53. Pharmacologic and genetic inhibition of p53 corroborated the hypothesis that pre-miR-630 (but not pre-miR-181a) blocks the upstream signaling pathways that are ignited by DNA damage and converge on p53 activation. Pre-miR-630 arrested A549 cells in the G0-G1 phase of the cell cycle, correlating with increased levels of the cell cycle inhibitor p27(Kip1) as well as with reduced proliferation rates and resulting in greatly diminished sensitivity of A549 cells to the late S-G2-M cell cycle arrest mediated by CDDP. Altogether, these results identify miR-181a and miR-630 as novel modulators of the CDDP response in NSCLC.

19. MiRNA-directed regulation of VEGF and other angiogenic factors under hypoxia.

Directory of Open Access Journals (Sweden)

Zhong Hua

Full Text Available MicroRNAs (miRNAs are a class of 20-24 nt non-coding RNAs that regulate gene expression primarily through post-transcriptional repression or mRNA degradation in a sequence-specific manner. The roles of miRNAs are just beginning to be understood, but the study of miRNA function has been limited by poor understanding of the general principles of gene regulation by miRNAs. Here we used CNE cells from a human nasopharyngeal carcinoma cell line as a cellular system to investigate miRNA-directed regulation of VEGF and other angiogenic factors under hypoxia, and to explore the principles of gene regulation by miRNAs. Through computational analysis, 96 miRNAs were predicted as putative regulators of VEGF. But when we analyzed the miRNA expression profile of CNE and four other VEGF-expressing cell lines, we found that only some of these miRNAs could be involved in VEGF regulation, and that VEGF may be regulated by different miRNAs that were differentially chosen from 96 putative regulatory miRNAs of VEGF in different cells. Some of these miRNAs also co-regulate other angiogenic factors (differential regulation and co-regulation principle. We also found that VEGF was regulated by multiple miRNAs using different combinations, including both coordinate and competitive interactions. The coordinate principle states that miRNAs with independent binding sites in a gene can produce coordinate action to increase the repressive effect of miRNAs on this gene. By contrast, the competitive principle states when multiple miRNAs compete with each other for a common binding site, or when a functional miRNA competes with a false positive miRNA for the same binding site, the repressive effects of miRNAs may be decreased. Through the competitive principle, false positive miRNAs, which cannot directly repress gene expression, can sometimes play a role in miRNA-mediated gene regulation. The competitive principle, differential regulation, multi-miRNA binding sites, and false

20. Search for $<$mi>CP> Violation and Measurement of the Branching Fraction in the Decay $<$mi>D>0<mi>KS>0<mi>KS>0

Energy Technology Data Exchange (ETDEWEB)

Dash, N.; Bahinipati, S.; Bhardwaj, V.; Trabelsi, K.; Adachi, I.; Aihara, H.; Al Said, S.; Asner, D. M.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Badhrees, I.; Bakich, A. M.; Bansal, V.; Barberio, E.; Bhuyan, B.; Biswal, J.; Bobrov, A.; Bondar, A.; Bonvicini, G.; Bozek, A.; Bračko, M.; Breibeck, F.; Browder, T. E.; Červenkov, D.; Chang, M. -C.; Chekelian, V.; Chen, A.; Cheon, B. G.; Chilikin, K.; Cho, K.; Choi, Y.; Cinabro, D.; Di Carlo, S.; Doležal, Z.; Drásal, Z.; Dutta, D.; Eidelman, S.; Epifanov, D.; Farhat, H.; Fast, J. E.; Ferber, T.; Fulsom, B. G.; Gaur, V.; Gabyshev, N.; Garmash, A.; Gillard, R.; Goldenzweig, P.; Haba, J.; Hara, T.; Hayasaka, K.; Hayashii, H.; Hedges, M. T.; Hou, W. -S.; Iijima, T.; Inami, K.; Ishikawa, A.; Itoh, R.; Iwasaki, Y.; Jacobs, W. W.; Jaegle, I.; Jeon, H. B.; Jin, Y.; Joffe, D.; Joo, K. K.; Julius, T.; Kahn, J.; Kaliyar, A. B.; Karyan, G.; Katrenko, P.; Kawasaki, T.; Kiesling, C.; Kim, D. Y.; Kim, H. J.; Kim, J. B.; Kim, K. T.; Kim, M. J.; Kim, S. H.; Kim, Y. J.; Kinoshita, K.; Kodyš, P.; Korpar, S.; Kotchetkov, D.; Križan, P.; Krokovny, P.; Kuhr, T.; Kulasiri, R.; Kumar, R.; Kumita, T.; Kuzmin, A.; Kwon, Y. -J.; Lange, J. S.; Lee, I. S.; Li, C. H.; Li, L.; Li, Y.; Li Gioi, L.; Libby, J.; Liventsev, D.; Lubej, M.; Luo, T.; Masuda, M.; Matvienko, D.; Merola, M.; Miyabayashi, K.; Miyata, H.; Mizuk, R.; Mohanty, G. B.; Mohanty, S.; Moon, H. K.; Mori, T.; Mussa, R.; Nakano, E.; Nakao, M.; Nanut, T.; Nath, K. J.; Natkaniec, Z.; Nayak, M.; Niiyama, M.; Nisar, N. K.; Nishida, S.; Ogawa, S.; Okuno, S.; Ono, H.; Pakhlov, P.; Pakhlova, G.; Pal, B.; Pardi, S.; Park, C. -S.; Park, H.; Paul, S.; Pedlar, T. K.; Pesántez, L.; Pestotnik, R.; Piilonen, L. E.; Prasanth, K.; Ritter, M.; Rostomyan, A.; Sahoo, H.; Sakai, Y.; Sandilya, S.; Santelj, L.; Sanuki, T.; Sato, Y.; Savinov, V.; Schneider, O.; Schnell, G.; Schwanda, C.; Schwartz, A. J.; Seino, Y.; Senyo, K.; Sevior, M. E.; Shebalin, V.; Shen, C. P.; Shibata, T. -A.; Shiu, J. -G.; Shwartz, B.; Simon, F.; Sokolov, A.; Solovieva, E.; Starič, M.; Strube, J. F.; Stypula, J.; Sumisawa, K.; Sumiyoshi, T.; Takizawa, M.; Tamponi, U.; Tanida, K.; Tenchini, F.; Uchida, M.; Uglov, T.; Unno, Y.; Uno, S.; Urquijo, P.; Usov, Y.; Van Hulse, C.; Varner, G.; Vorobyev, V.; Vossen, A.; Waheed, E.; Wang, C. H.; Wang, M. -Z.; Wang, P.; Watanabe, M.; Watanabe, Y.; Widmann, E.; Williams, K. M.; Won, E.; Yamashita, Y.; Ye, H.; Yelton, J.; Yook, Y.; Yuan, C. Z.; Yusa, Y.; Zhang, Z. P.; Zhilich, V.; Zhukova, V.; Zhulanov, V.; Zupanc, A.

2017-10-01

We report a study of the decay $<$mi>D>0<mi>KS>0<mi>KS>0 using 921 fb-1 of data collected at or near the Υ(4S) and Υ(5S) resonances with the Belle detector at the KEKB asymmetric energy e+e- collider. The measured time-integrated CP asymmetry is ACP($<$mi>D>0<mi>KS>0<mi>KS>0) = (-0.02 ± 1.53 ± 0.02 ± 0.17)%, and the branching fraction is B($<$mi>D>0<mi>KS>0<mi>KS>0) = (1.321 ± 0.023 ± 0.036 ± 0.044) × 10-4, where the first uncertainty is statistical, the second is systematic, and the third is due to the normalization mode ($<$mi>D>0<mi>KS>0π0). These results are significantly more precise than previous measurements available for this mode. The ACP measurement is consistent with the standard model expectation.

1. RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning

KAUST Repository

Kim, Ji-Sung; Gao, Xin; Rzhetsky, Andrey

2018-01-01

are predictive of race and ethnicity. We used these characterizations of informative features to perform a systematic comparison of differential disease patterns by race and ethnicity. The fact that clinical histories are informative for imputing race

2. Comparison of three boosting methods in parent-offspring trios for genotype imputation using simulation study

Directory of Open Access Journals (Sweden)

Abbas Mikhchi

2016-01-01

Full Text Available Abstract Background Genotype imputation is an important process of predicting unknown genotypes, which uses reference population with dense genotypes to predict missing genotypes for both human and animal genetic variations at a low cost. Machine learning methods specially boosting methods have been used in genetic studies to explore the underlying genetic profile of disease and build models capable of predicting missing values of a marker. Methods In this study strategies and factors affecting the imputation accuracy of parent-offspring trios compared from lower-density SNP panels (5 K to high density (10 K SNP panel using three different Boosting methods namely TotalBoost (TB, LogitBoost (LB and AdaBoost (AB. The methods employed using simulated data to impute the un-typed SNPs in parent-offspring trios. Four different datasets of G1 (100 trios with 5 k SNPs, G2 (100 trios with 10 k SNPs, G3 (500 trios with 5 k SNPs, and G4 (500 trio with 10 k SNPs were simulated. In four datasets all parents were genotyped completely, and offspring genotyped with a lower density panel. Results Comparison of the three methods for imputation showed that the LB outperformed AB and TB for imputation accuracy. The time of computation were different between methods. The AB was the fastest algorithm. The higher SNP densities resulted the increase of the accuracy of imputation. Larger trios (i.e. 500 was better for performance of LB and TB. Conclusions The conclusion is that the three methods do well in terms of imputation accuracy also the dense chip is recommended for imputation of parent-offspring trios.

3. Simple nuclear norm based algorithms for imputing missing data and forecasting in time series

OpenAIRE

Butcher, Holly Louise; Gillard, Jonathan William

2017-01-01

There has been much recent progress on the use of the nuclear norm for the so-called matrix completion problem (the problem of imputing missing values of a matrix). In this paper we investigate the use of the nuclear norm for modelling time series, with particular attention to imputing missing data and forecasting. We introduce a simple alternating projections type algorithm based on the nuclear norm for these tasks, and consider a number of practical examples.

4. Missing value imputation for microarray gene expression data using histone acetylation information

Directory of Open Access Journals (Sweden)

Feng Jihua

2008-05-01

Full Text Available Abstract Background It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages. Results The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor and LLS(local least square imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE. Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information. Conclusion We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

5. The utility of imputed matched sets. Analyzing probabilistically linked databases in a low information setting.

Science.gov (United States)

Thomas, A M; Cook, L J; Dean, J M; Olson, L M

2014-01-01

To compare results from high probability matched sets versus imputed matched sets across differing levels of linkage information. A series of linkages with varying amounts of available information were performed on two simulated datasets derived from multiyear motor vehicle crash (MVC) and hospital databases, where true matches were known. Distributions of high probability and imputed matched sets were compared against the true match population for occupant age, MVC county, and MVC hour. Regression models were fit to simulated log hospital charges and hospitalization status. High probability and imputed matched sets were not significantly different from occupant age, MVC county, and MVC hour in high information settings (p > 0.999). In low information settings, high probability matched sets were significantly different from occupant age and MVC county (p sets were not (p > 0.493). High information settings saw no significant differences in inference of simulated log hospital charges and hospitalization status between the two methods. High probability and imputed matched sets were significantly different from the outcomes in low information settings; however, imputed matched sets were more robust. The level of information available to a linkage is an important consideration. High probability matched sets are suitable for high to moderate information settings and for situations involving case-specific analysis. Conversely, imputed matched sets are preferable for low information settings when conducting population-based analyses.

6. Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things

Directory of Open Access Journals (Sweden)

Xiaobo Yan

2015-01-01

Full Text Available This paper addresses missing value imputation for the Internet of Things (IoT. Nowadays, the IoT has been used widely and commonly by a variety of domains, such as transportation and logistics domain and healthcare domain. However, missing values are very common in the IoT for a variety of reasons, which results in the fact that the experimental data are incomplete. As a result of this, some work, which is related to the data of the IoT, can’t be carried out normally. And it leads to the reduction in the accuracy and reliability of the data analysis results. This paper, for the characteristics of the data itself and the features of missing data in IoT, divides the missing data into three types and defines three corresponding missing value imputation problems. Then, we propose three new models to solve the corresponding problems, and they are model of missing value imputation based on context and linear mean (MCL, model of missing value imputation based on binary search (MBS, and model of missing value imputation based on Gaussian mixture model (MGI. Experimental results showed that the three models can improve the accuracy, reliability, and stability of missing value imputation greatly and effectively.

7. Imputation-based analysis of association studies: candidate regions and quantitative traits.

Directory of Open Access Journals (Sweden)

Bertrand Servin

2007-07-01

Full Text Available We introduce a new framework for the analysis of association studies, designed to allow untyped variants to be more effectively and directly tested for association with a phenotype. The idea is to combine knowledge on patterns of correlation among SNPs (e.g., from the International HapMap project or resequencing data in a candidate region of interest with genotype data at tag SNPs collected on a phenotyped study sample, to estimate ("impute" unmeasured genotypes, and then assess association between the phenotype and these estimated genotypes. Compared with standard single-SNP tests, this approach results in increased power to detect association, even in cases in which the causal variant is typed, with the greatest gain occurring when multiple causal variants are present. It also provides more interpretable explanations for observed associations, including assessing, for each SNP, the strength of the evidence that it (rather than another correlated SNP is causal. Although we focus on association studies with quantitative phenotype and a relatively restricted region (e.g., a candidate gene, the framework is applicable and computationally practical for whole genome association studies. Methods described here are implemented in a software package, Bim-Bam, available from the Stephens Lab website http://stephenslab.uchicago.edu/software.html.

8. MiDAS

DEFF Research Database (Denmark)

McIlroy, Simon Jon; Saunders, Aaron Marc; Albertsen, Mads

2015-01-01

The Microbial Database for Activated Sludge (MiDAS) field guide is a freely available online resource linking the identity of abundant and process critical microorganisms in activated sludge wastewater treatment systems to available data related to their functional importance. Phenotypic properties...... of some of these genera are described, but most are known only from sequence data. The MiDAS taxonomy is a manual curation of the SILVA taxonomy that proposes a name for all genus-level taxa observed to be abundant by large-scale 16 S rRNA gene amplicon sequencing of full-scale activated sludge...... communities. The taxonomy can be used to classify unknown sequences, and the online MiDAS field guide links the identity to the available information about their morphology, diversity, physiology and distribution. The use of a common taxonomy across the field will provide a solid foundation for the study...

9. Stress-activated miR-21/miR-21* in hepatocytes promotes lipid and glucose metabolic disorders associated with high-fat diet consumption.

Science.gov (United States)

Calo, Nicolas; Ramadori, Pierluigi; Sobolewski, Cyril; Romero, Yannick; Maeder, Christine; Fournier, Margot; Rantakari, Pia; Zhang, Fu-Ping; Poutanen, Matti; Dufour, Jean-François; Humar, Bostjan; Nef, Serge; Foti, Michelangelo

2016-11-01

miR-21 is an oncomir highly upregulated in hepatocellular carcinoma and in early stages of liver diseases characterised by the presence of steatosis. Whether upregulation of miR-21 contributes to hepatic metabolic disorders and their progression towards cancer is unknown. This study aims at investigating the role of miR-21/miR-21* in early stages of metabolic liver disorders associated with diet-induced obesity (DIO). Constitutive miR-21/miR-21* knockout (miR21KO) and liver-specific miR-21/miR-21* knockout (LImiR21KO) mice were generated. Mice were then fed with high-fat diet (HFD) and alterations of the lipid and glucose metabolism were investigated. Serum and ex vivo explanted liver tissue were analysed. Under normal breeding conditions and standard diet, miR-21/miR-21* deletion in mice was not associated with any detectable phenotypic alterations. However, when mice were challenged with an obesogenic diet, glucose intolerance, steatosis and adiposity were improved in mice lacking miR-21/miR-21* . Deletion of miR-21/miR-21* specifically in hepatocytes led to similar improvements in mice fed an HFD, indicating a crucial role for hepatic miR-21/miR-21* in metabolic disorders associated with DIO. Further molecular analyses demonstrated that miR-21/miR-21* deletion in hepatocytes increases insulin sensitivity and modulates the expression of multiple key metabolic transcription factors involved in fatty acid uptake, de novo lipogenesis, gluconeogenesis and glucose output. Hepatic miR-21/miR-21* deficiency prevents glucose intolerance and steatosis in mice fed an obesogenic diet by altering the expression of several master metabolic regulators. This study points out miR-21/miR-21 * as a potential therapeutic target for non-alcoholic fatty liver disease and the metabolic syndrome. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

10. Multi-generational imputation of single nucleotide polymorphism marker genotypes and accuracy of genomic selection.

Science.gov (United States)

Toghiani, S; Aggrey, S E; Rekaya, R

2016-07-01

Availability of high-density single nucleotide polymorphism (SNP) genotyping platforms provided unprecedented opportunities to enhance breeding programmes in livestock, poultry and plant species, and to better understand the genetic basis of complex traits. Using this genomic information, genomic breeding values (GEBVs), which are more accurate than conventional breeding values. The superiority of genomic selection is possible only when high-density SNP panels are used to track genes and QTLs affecting the trait. Unfortunately, even with the continuous decrease in genotyping costs, only a small fraction of the population has been genotyped with these high-density panels. It is often the case that a larger portion of the population is genotyped with low-density and low-cost SNP panels and then imputed to a higher density. Accuracy of SNP genotype imputation tends to be high when minimum requirements are met. Nevertheless, a certain rate of genotype imputation errors is unavoidable. Thus, it is reasonable to assume that the accuracy of GEBVs will be affected by imputation errors; especially, their cumulative effects over time. To evaluate the impact of multi-generational selection on the accuracy of SNP genotypes imputation and the reliability of resulting GEBVs, a simulation was carried out under varying updating of the reference population, distance between the reference and testing sets, and the approach used for the estimation of GEBVs. Using fixed reference populations, imputation accuracy decayed by about 0.5% per generation. In fact, after 25 generations, the accuracy was only 7% lower than the first generation. When the reference population was updated by either 1% or 5% of the top animals in the previous generations, decay of imputation accuracy was substantially reduced. These results indicate that low-density panels are useful, especially when the generational interval between reference and testing population is small. As the generational interval

11. Treasury Offset Program (TOP) MI

Data.gov (United States)

Social Security Administration — The TOP MI helps OPSOS coordinate TOP case processing in the regions. The MI also helped communicate our progress and findings to BFQM and ORDP, as well as the ACOSS.

12. Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle

DEFF Research Database (Denmark)

Ma, Peipei; Brøndum, Rasmus Froberg; Qin, Zahng

2013-01-01

This study investigated the imputation accuracy of different methods, considering both the minor allele frequency and relatedness between individuals in the reference and test data sets. Two data sets from the combined population of Swedish and Finnish Red Cattle were used to test the influence...... coefficient was lower when the minor allele frequency was lower. The results indicate that Beagle and IMPUTE2 provide the most robust and accurate imputation accuracies, but considering computing time and memory usage, FImpute is another alternative method....

13. Improved Ancestry Estimation for both Genotyping and Sequencing Data using Projection Procrustes Analysis and Genotype Imputation

Science.gov (United States)

Wang, Chaolong; Zhan, Xiaowei; Liang, Liming; Abecasis, Gonçalo R.; Lin, Xihong

2015-01-01

Accurate estimation of individual ancestry is important in genetic association studies, especially when a large number of samples are collected from multiple sources. However, existing approaches developed for genome-wide SNP data do not work well with modest amounts of genetic data, such as in targeted sequencing or exome chip genotyping experiments. We propose a statistical framework to estimate individual ancestry in a principal component ancestry map generated by a reference set of individuals. This framework extends and improves upon our previous method for estimating ancestry using low-coverage sequence reads (LASER 1.0) to analyze either genotyping or sequencing data. In particular, we introduce a projection Procrustes analysis approach that uses high-dimensional principal components to estimate ancestry in a low-dimensional reference space. Using extensive simulations and empirical data examples, we show that our new method (LASER 2.0), combined with genotype imputation on the reference individuals, can substantially outperform LASER 1.0 in estimating fine-scale genetic ancestry. Specifically, LASER 2.0 can accurately estimate fine-scale ancestry within Europe using either exome chip genotypes or targeted sequencing data with off-target coverage as low as 0.05×. Under the framework of LASER 2.0, we can estimate individual ancestry in a shared reference space for samples assayed at different loci or by different techniques. Therefore, our ancestry estimation method will accelerate discovery in disease association studies not only by helping model ancestry within individual studies but also by facilitating combined analysis of genetic data from multiple sources. PMID:26027497

14. Characterization of novel precursor miRNAs using next generation sequencing and prediction of miRNA targets in Atlantic halibut.

Directory of Open Access Journals (Sweden)

Teshome Tilahun Bizuayehu

Full Text Available BACKGROUND: microRNAs (miRNAs are implicated in regulation of many cellular processes. miRNAs are processed to their mature functional form in a step-wise manner by multiple proteins and cofactors in the nucleus and cytoplasm. Many miRNAs are conserved across vertebrates. Mature miRNAs have recently been characterized in Atlantic halibut (Hippoglossus hippoglossus L.. The aim of this study was to identify and characterize precursor miRNA (pre-miRNAs and miRNA targets in this non-model flatfish. Discovery of miRNA precursor forms and targets in non-model organisms is difficult because of limited source information available. Therefore, we have developed a methodology to overcome this limitation. METHODS: Genomic DNA and small transcriptome of Atlantic halibut were sequenced using Roche 454 pyrosequencing and SOLiD next generation sequencing (NGS, respectively. Identified pre- miRNAs were further validated with reverse-transcription PCR. miRNA targets were identified using miRanda and RNAhybrid target prediction tools using sequences from public databases. Some of miRNA targets were also identified using RACE-PCR. miRNA binding sites were validated with luciferase assay using the RTS34st cell line. RESULTS: We obtained more than 1.3 M and 92 M sequence reads from 454 genomic DNA sequencing and SOLiD small RNA sequencing, respectively. We identified 34 known and 9 novel pre-miRNAs. We predicted a number of miRNA target genes involved in various biological pathways. miR-24 binding to kisspeptin 1 receptor-2 (kiss1-r2 was confirmed using luciferase assay. CONCLUSION: This study demonstrates that identification of conserved and novel pre-miRNAs in a non-model vertebrate lacking substantial genomic resources can be performed by combining different next generation sequencing technologies. Our results indicate a wide conservation of miRNA precursors and involvement of miRNA in multiple regulatory pathways, and provide resources for further research on mi

15. A 4-miRNA signature to predict survival in glioblastomas

DEFF Research Database (Denmark)

Hermansen, Simon K; Sørensen, Mia D; Hansen, Anker

2017-01-01

multiple genes representing an additional level of gene regulation possibly more prognostically powerful than a single gene. The aim of the study was to identify a novel miRNA signature with the ability to separate patients into prognostic subgroups. Samples from 40 glioblastoma patients were included...... association to survival in univariate (HR 8.50; 95% CI 3.06-23.62; psignature of miR-107 and miR-331 (miR sum score), which were the only miRNAs available...

16. PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population.

Directory of Open Access Journals (Sweden)

Oren E Livne

2015-03-01

Full Text Available Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm, a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs, from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.

17. Mi-spillet

DEFF Research Database (Denmark)

Larsen, Lea Lund; Hejlesen, Stine

2003-01-01

MI-spillet er et undervisningsspil til folkeskolens mellemtrin og udskolingen. Spillet omformer Howard Gardners teori om de mange intelligenser til et praktisk og håndgribeligt værktøj til brug i folkeskolen. Spillet indeholder et undervisningsmateriale bestående af lærervejledning og kopimappe...... emnebaseret eller tværfagligt arbejde. Alt materialet ligger samlet på en cd-rom, hvorfra materialet printes. Skolen kan derfor ved køb af én cd-rom printe og producere et ubegrænset antal spil. Cd-rommen indeholder: 1. Lærervejledning 2. MI-spillet * Gulvpladerne * Spørgsmål til spillet * Bilag til...

18. Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

Science.gov (United States)

Johnson, Eric O; Hancock, Dana B; Levy, Joshua L; Gaddis, Nathan C; Saccone, Nancy L; Bierut, Laura J; Page, Grier P

2013-05-01

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.

19. A New Missing Data Imputation Algorithm Applied to Electrical Data Loggers

Directory of Open Access Journals (Sweden)

2015-12-01

Full Text Available Nowadays, data collection is a key process in the study of electrical power networks when searching for harmonics and a lack of balance among phases. In this context, the lack of data of any of the main electrical variables (phase-to-neutral voltage, phase-to-phase voltage, and current in each phase and power factor adversely affects any time series study performed. When this occurs, a data imputation process must be accomplished in order to substitute the data that is missing for estimated values. This paper presents a novel missing data imputation method based on multivariate adaptive regression splines (MARS and compares it with the well-known technique called multivariate imputation by chained equations (MICE. The results obtained demonstrate how the proposed method outperforms the MICE algorithm.

20. Time Series Imputation via L1 Norm-Based Singular Spectrum Analysis

Science.gov (United States)

Kalantari, Mahdi; Yarmohammadi, Masoud; Hassani, Hossein; Silva, Emmanuel Sirimal

Missing values in time series data is a well-known and important problem which many researchers have studied extensively in various fields. In this paper, a new nonparametric approach for missing value imputation in time series is proposed. The main novelty of this research is applying the L1 norm-based version of Singular Spectrum Analysis (SSA), namely L1-SSA which is robust against outliers. The performance of the new imputation method has been compared with many other established methods. The comparison is done by applying them to various real and simulated time series. The obtained results confirm that the SSA-based methods, especially L1-SSA can provide better imputation in comparison to other methods.

1. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Directory of Open Access Journals (Sweden)

Momoko Horikoshi

2015-07-01

Full Text Available Reference panels from the 1000 Genomes (1000G Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS, supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI at genome-wide significance, and two for fasting glucose (FG, none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3 and FG (GCK and G6PC2. The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

2. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Science.gov (United States)

Horikoshi, Momoko; Mӓgi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S; Winkler, Thomas W; Willems, Sara M; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K E; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R; Groves, Christopher J; Bennett, Amanda J; Lehtimӓki, Terho; Viikari, Jorma S; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M; Karssen, Lennart C; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J; de Craen, Anton J M; Deelen, Joris; Havulinna, Aki S; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D; Samani, Nilesh J; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M; Slagboom, P Eline; Metspalu, Andres; van Duijn, Cornelia M; Eriksson, Johan G; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T; Power, Chris; Penninx, Brenda W J H; de Geus, Eco; Smit, Johannes H; Boomsma, Dorret I; Pedersen, Nancy L; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I; Morris, Andrew P

2015-07-01

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

3. A suggested approach for imputation of missing dietary data for young children in daycare.

Science.gov (United States)

Stevens, June; Ou, Fang-Shu; Truesdale, Kimberly P; Zeng, Donglin; Vaughn, Amber E; Pratt, Charlotte; Ward, Dianne S

2015-01-01

Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult. The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method. Data were from children aged 2-5 years in the My Parenting SOS project (n=308; 870 24-h diet recalls). Mixed models were used to simultaneously predict breakfast, dinner, and evening snacks (B+D+ES); lunch; and daytime snacks for all children after adjusting for age, sex, and body mass index (BMI). From these models, we imputed the missing weekday daycare lunches by interpolation using the mean lunch to B+D+ES [L/(B+D+ES)] ratio among non-daycare children on weekdays and the L/(B+D+ES) ratio for all children on weekends. Daytime snack data were used to impute snacks. The reported mean (± standard deviation) weekday intake was lower for daycare children [725 (±324) kcal] compared to non-daycare children [1,048 (±463) kcal]. Weekend intake for all children was 1,173 (±427) kcal. After imputation, weekday caloric intake for daycare children was 1,230 (±409) kcal. Daily intakes that included imputed data were associated with age and sex but not with BMI. This work indicates that imputation is a promising method for improving the precision of daily nutrient data from young children.

4. Saturated linkage map construction in Rubus idaeus using genotyping by sequencing and genome-independent imputation

Directory of Open Access Journals (Sweden)

Ward Judson A

2013-01-01

Full Text Available Abstract Background Rapid development of highly saturated genetic maps aids molecular breeding, which can accelerate gain per breeding cycle in woody perennial plants such as Rubus idaeus (red raspberry. Recently, robust genotyping methods based on high-throughput sequencing were developed, which provide high marker density, but result in some genotype errors and a large number of missing genotype values. Imputation can reduce the number of missing values and can correct genotyping errors, but current methods of imputation require a reference genome and thus are not an option for most species. Results Genotyping by Sequencing (GBS was used to produce highly saturated maps for a R. idaeus pseudo-testcross progeny. While low coverage and high variance in sequencing resulted in a large number of missing values for some individuals, a novel method of imputation based on maximum likelihood marker ordering from initial marker segregation overcame the challenge of missing values, and made map construction computationally tractable. The two resulting parental maps contained 4521 and 2391 molecular markers spanning 462.7 and 376.6 cM respectively over seven linkage groups. Detection of precise genomic regions with segregation distortion was possible because of map saturation. Microsatellites (SSRs linked these results to published maps for cross-validation and map comparison. Conclusions GBS together with genome-independent imputation provides a rapid method for genetic map construction in any pseudo-testcross progeny. Our method of imputation estimates the correct genotype call of missing values and corrects genotyping errors that lead to inflated map size and reduced precision in marker placement. Comparison of SSRs to published R. idaeus maps showed that the linkage maps constructed with GBS and our method of imputation were robust, and marker positioning reliable. The high marker density allowed identification of genomic regions with segregation

5. A suggested approach for imputation of missing dietary data for young children in daycare

Directory of Open Access Journals (Sweden)

June Stevens

2015-12-01

Full Text Available Background: Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult. Objective: The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method. Design: Data were from children aged 2-5 years in the My Parenting SOS project (n=308; 870 24-h diet recalls. Mixed models were used to simultaneously predict breakfast, dinner, and evening snacks (B+D+ES; lunch; and daytime snacks for all children after adjusting for age, sex, and body mass index (BMI. From these models, we imputed the missing weekday daycare lunches by interpolation using the mean lunch to B+D+ES [L/(B+D+ES] ratio among non-daycare children on weekdays and the L/(B+D+ES ratio for all children on weekends. Daytime snack data were used to impute snacks. Results: The reported mean (± standard deviation weekday intake was lower for daycare children [725 (±324 kcal] compared to non-daycare children [1,048 (±463 kcal]. Weekend intake for all children was 1,173 (±427 kcal. After imputation, weekday caloric intake for daycare children was 1,230 (±409 kcal. Daily intakes that included imputed data were associated with age and sex but not with BMI. Conclusion: This work indicates that imputation is a promising method for improving the precision of daily nutrient data from young children.

6. A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation.

Science.gov (United States)

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2017-05-31

Label-free mass spectrometry (MS) has developed into an important tool applied in various fields of biological and life sciences. Several software exist to process the raw MS data into quantified protein abundances, including open source and commercial solutions. Each software includes a set of unique algorithms for different tasks of the MS data processing workflow. While many of these algorithms have been compared separately, a thorough and systematic evaluation of their overall performance is missing. Moreover, systematic information is lacking about the amount of missing values produced by the different proteomics software and the capabilities of different data imputation methods to account for them.In this study, we evaluated the performance of five popular quantitative label-free proteomics software workflows using four different spike-in data sets. Our extensive testing included the number of proteins quantified and the number of missing values produced by each workflow, the accuracy of detecting differential expression and logarithmic fold change and the effect of different imputation and filtering methods on the differential expression results. We found that the Progenesis software performed consistently well in the differential expression analysis and produced few missing values. The missing values produced by the other software decreased their performance, but this difference could be mitigated using proper data filtering or imputation methods. Among the imputation methods, we found that the local least squares (lls) regression imputation consistently increased the performance of the software in the differential expression analysis, and a combination of both data filtering and local least squares imputation increased performance the most in the tested data sets. © The Author 2017. Published by Oxford University Press.

7. UniFIeD Univariate Frequency-based Imputation for Time Series Data

OpenAIRE

Friese, Martina; Stork, Jörg; Ramos Guerra, Ricardo; Bartz-Beielstein, Thomas; Thaker, Soham; Flasch, Oliver; Zaefferer, Martin

2013-01-01

This paper introduces UniFIeD, a new data preprocessing method for time series. UniFIeD can cope with large intervals of missing data. A scalable test function generator, which allows the simulation of time series with different gap sizes, is presented additionally. An experimental study demonstrates that (i) UniFIeD shows a significant better performance than simple imputation methods and (ii) UniFIeD is able to handle situations, where advanced imputation methods fail. The results are indep...

8. Diagnostic and prognostic potential of serum miR-7, miR-16, miR-25, miR-93, miR-182, miR-376a and miR-429 in ovarian cancer patients.

Science.gov (United States)

Meng, Xiaodan; Joosse, Simon A; Müller, Volkmar; Trillsch, Fabian; Milde-Langosch, Karin; Mahner, Sven; Geffken, Maria; Pantel, Klaus; Schwarzenbach, Heidi

2015-11-03

Owing to late diagnosis in advanced disease stages, prognosis of patients with epithelial ovarian cancer (EOC) is poor. The quantification of deregulated levels of microRNAs could facilitate earlier diagnosis and improve prognosis of EOC. Seven microRNAs (miR-7, miR-16, miR-25, miR-93, miR-182, miR-376a and miR-429) were quantified in the serum of 180 EOC patients and 66 healthy women by TaqMan PCR microRNA assays. Median follow-up time was 21 months. The effects of miR-7 and miR-429 on apoptosis, cell proliferation, migration and invasion were investigated in two (EOC) cell lines. Serum levels of miR-25 (P=0.0001) and miR-93 (P=0.0001) were downregulated, whereas those of miR-7 (P=0.001) and miR-429 (P=0.0001) were upregulated in EOC patients compared with healthy women. The four microRNAs discriminated EOC patients from healthy women with a sensitivity of 93% and a specificity of 92%. The levels of miR-429 positively correlated with CA125 values (P=0.0001) and differed between FIGO I-II and III-IV stages (P=0.001). MiR-429 was an independent predictor of overall survival (P=0.011). Overexpressed miR-429 in SKOV3 cells led to suppression of cell migration (P=0.037) and invasion (P=0.011). Increased levels of miR-7 were associated with lymph node metastases (P=0.0001) and FIGO stages III-IV (P=0.0001). Overexpressed miR-7 in SKOV3 cells resulted in increased cell migration (P=0.001) and invasion (P=0.011). Additionally, the increased levels of miR-376a correlated with FIGO stages III-IV (P=0.02). Our data indicate the diagnostic potential of miR-7, miR-25, miR-93 and miR-429 in EOC and the prognostic potential of miR-429. This microRNA panel may be promising molecules to be targeted in the treatment of EOC.

9. Reclaiming Sámi languages

DEFF Research Database (Denmark)

Rasmussen, Torkel; Nolan, John Shaun

2011-01-01

, this paper investigates what subsequently happens at the grassroots or micro level. This investigation shows that despite more positive policies, there is a strong sentiment of defeatism with regard to Sámi. Sámi speakers face problems because of the lack of implementation of nationally decided laws...... and for the sake of cultural maintenance, but also for instrumental reasons, i.e. to give their children better opportunities in the labor market where knowledge of Sámi is necessary....

10. MiDAS

DEFF Research Database (Denmark)

McIlroy, Simon Jon; Kirkegaard, Rasmus Hansen; McIlroy, Bianca

A deep understanding of the microbial communities and dynamics in wastewater treatment systems is a powerful tool for process optimization and design (Rittmann et al., 2006). With the advent of amplicon sequencing of the 16S rRNA gene, the diversity within the microbial communities can now...... web platform about the microbes in activated sludge and their associated ADs. The MiDAS taxonomy proposes putative names for each genus-level-taxon that can be used as a common vocabulary for all researchers in the field....

11. TargetCompare: A web interface to compare simultaneous miRNAs targets.

Science.gov (United States)

Moreira, Fabiano Cordeiro; Dustan, Bruno; Hamoy, Igor G; Ribeiro-Dos-Santos, André M; Dos Santos, Andrea Ribeiro

2014-01-01

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs. We cross validated the tool in eight most highly expressed miRNAs in the antrum region of stomach. This helped to identify 43 potential genes that are target of at least six of the referred miRNAs. The developed tool aims to reduce the randomness and increase the chance of selecting strong candidate target genes and miRNAs responsible for playing important roles in the studied tissue. http://lghm.ufpa.br/targetcompare.

12. Multiple Imputation for Estimating the Risk of Developing Dementia and Its Impact on Survival

OpenAIRE

Yu, Binbing; Saczynski, Jane S.; Launer, Lenore J.

2010-01-01

Dementia, Alzheimer’s disease in particular, is one of the major causes of disability and decreased quality of life among the elderly and a leading obstacle to successful aging. Given the profound impact on public health, much research has focused on the age-specific risk of developing dementia and the impact on survival. Early work has discussed various methods of estimating age-specific incidence of dementia, among which the illness-death model is popular for modeling disease progression. I...

13. Applying an efficient K-nearest neighbor search to forest attribute imputation

Science.gov (United States)

Andrew O. Finley; Ronald E. McRoberts; Alan R. Ek

2006-01-01

This paper explores the utility of an efficient nearest neighbor (NN) search algorithm for applications in multi-source kNN forest attribute imputation. The search algorithm reduces the number of distance calculations between a given target vector and each reference vector, thereby, decreasing the time needed to discover the NN subset. Results of five trials show gains...

14. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Science.gov (United States)

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

15. Mapping change of older forest with nearest-neighbor imputation and Landsat time-series

Science.gov (United States)

Janet L. Ohmann; Matthew J. Gregory; Heather M. Roberts; Warren B. Cohen; Robert E. Kennedy; Zhiqiang. Yang

2012-01-01

The Northwest Forest Plan (NWFP), which aims to conserve late-successional and old-growth forests (older forests) and associated species, established new policies on federal lands in the Pacific Northwest USA. As part of monitoring for the NWFP, we tested nearest-neighbor imputation for mapping change in older forest, defined by threshold values for forest attributes...

16. Is missing geographic positioning system data in accelerometry studies a problem, and is imputation the solution?

DEFF Research Database (Denmark)

Meseck, Kristin; Jankowska, Marta M; Schipperijn, Jasper

2016-01-01

The main purpose of the present study was to assess the impact of global positioning system (GPS) signal lapse on physical activity analyses, discover any existing associations between missing GPS data and environmental and demographics attributes, and to determine whether imputation is an accurate...

17. Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data

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Minkyung Kim

2017-10-01

Full Text Available This paper proposes a learning-based adaptive imputation method (LAI for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture the patterns from past power data, we newly model a feature vector by using past data and its variations. The proposed LAI then learns the optimal length of the feature vector and the optimal historical length, which are significant hyper parameters of the proposed method, by utilizing intentional missing data. Based on a weighted distance between feature vectors representing a missing situation and past situation, missing power data are estimated by referring to the k most similar past situations in the optimal historical length. We further extend the proposed LAI to alleviate the effect of unexpected variation in power data and refer to this new approach as the extended LAI method (eLAI. The eLAI selects a method between linear interpolation (LI and the proposed LAI to improve accuracy under unexpected variations. Finally, from a simulation under various energy consumption profiles, we verify that the proposed eLAI achieves about a 74% reduction of the average imputation error in an energy system, compared to the existing imputation methods.

18. Missing value imputation in DNA microarrays based on conjugate gradient method.

Science.gov (United States)

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

19. Estimating past hepatitis C infection risk from reported risk factor histories: implications for imputing age of infection and modeling fibrosis progression

Directory of Open Access Journals (Sweden)

Busch Michael P

2007-12-01

Full Text Available Abstract Background Chronic hepatitis C virus infection is prevalent and often causes hepatic fibrosis, which can progress to cirrhosis and cause liver cancer or liver failure. Study of fibrosis progression often relies on imputing the time of infection, often as the reported age of first injection drug use. We sought to examine the accuracy of such imputation and implications for modeling factors that influence progression rates. Methods We analyzed cross-sectional data on hepatitis C antibody status and reported risk factor histories from two large studies, the Women's Interagency HIV Study and the Urban Health Study, using modern survival analysis methods for current status data to model past infection risk year by year. We compared fitted distributions of past infection risk to reported age of first injection drug use. Results Although injection drug use appeared to be a very strong risk factor, models for both studies showed that many subjects had considerable probability of having been infected substantially before or after their reported age of first injection drug use. Persons reporting younger age of first injection drug use were more likely to have been infected after, and persons reporting older age of first injection drug use were more likely to have been infected before. Conclusion In cross-sectional studies of fibrosis progression where date of HCV infection is estimated from risk factor histories, modern methods such as multiple imputation should be used to account for the substantial uncertainty about when infection occurred. The models presented here can provide the inputs needed by such methods. Using reported age of first injection drug use as the time of infection in studies of fibrosis progression is likely to produce a spuriously strong association of younger age of infection with slower rate of progression.

20. Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

Science.gov (United States)

Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2018-05-01

The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in

1. Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

Directory of Open Access Journals (Sweden)

R. Poyatos

2018-05-01

Full Text Available The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2. We simulated gaps at different missingness levels (10–80 % in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN, ordinary and regression kriging, and multivariate imputation using chained equations (MICE to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %, species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables

2. DLEU2, frequently deleted in malignancy, functions as a critical host gene of the cell cycle inhibitory microRNAs miR-15a and miR-16-1

International Nuclear Information System (INIS)

Lerner, Mikael; Harada, Masako; Loven, Jakob; Castro, Juan; Davis, Zadie; Oscier, David; Henriksson, Marie; Sangfelt, Olle; Grander, Dan; Corcoran, Martin M.

2009-01-01

The microRNAs miR-15a and miR-16-1 are downregulated in multiple tumor types and are frequently deleted in chronic lymphocytic leukemia (CLL), myeloma and mantle cell lymphoma. Despite their abundance in most cells the transcriptional regulation of miR-15a/16-1 remains unclear. Here we demonstrate that the putative tumor suppressor DLEU2 acts as a host gene of these microRNAs. Mature miR-15a/miR-16-1 are produced in a Drosha-dependent process from DLEU2 and binding of the Myc oncoprotein to two alterative DLEU2 promoters represses both the host gene transcript and levels of mature miR-15a/miR-16-1. In line with a functional role for DLEU2 in the expression of the microRNAs, the miR-15a/miR-16-1 locus is retained in four CLL cases that delete both promoters of this gene and expression analysis indicates that this leads to functional loss of mature miR-15a/16-1. We additionally show that DLEU2 negatively regulates the G1 Cyclins E1 and D1 through miR-15a/miR-16-1 and provide evidence that these oncoproteins are subject to miR-15a/miR-16-1-mediated repression under normal conditions. We also demonstrate that DLEU2 overexpression blocks cellular proliferation and inhibits the colony-forming ability of tumor cell lines in a miR-15a/miR-16-1-dependent way. Together the data illuminate how inactivation of DLEU2 promotes cell proliferation and tumor progression through functional loss of miR-15a/miR-16-1.

3. Inclusion of Population-specific Reference Panel from India to the 1000 Genomes Phase 3 Panel Improves Imputation Accuracy.

Science.gov (United States)

Ahmad, Meraj; Sinha, Anubhav; Ghosh, Sreya; Kumar, Vikrant; Davila, Sonia; Yajnik, Chittaranjan S; Chandak, Giriraj R

2017-07-27

Imputation is a computational method based on the principle of haplotype sharing allowing enrichment of genome-wide association study datasets. It depends on the haplotype structure of the population and density of the genotype data. The 1000 Genomes Project led to the generation of imputation reference panels which have been used globally. However, recent studies have shown that population-specific panels provide better enrichment of genome-wide variants. We compared the imputation accuracy using 1000 Genomes phase 3 reference panel and a panel generated from genome-wide data on 407 individuals from Western India (WIP). The concordance of imputed variants was cross-checked with next-generation re-sequencing data on a subset of genomic regions. Further, using the genome-wide data from 1880 individuals, we demonstrate that WIP works better than the 1000 Genomes phase 3 panel and when merged with it, significantly improves the imputation accuracy throughout the minor allele frequency range. We also show that imputation using only South Asian component of the 1000 Genomes phase 3 panel works as good as the merged panel, making it computationally less intensive job. Thus, our study stresses that imputation accuracy using 1000 Genomes phase 3 panel can be further improved by including population-specific reference panels from South Asia.

4. Down-regulation of 5S rRNA by miR-150 and miR-383 enhances c-Myc-rpL11 interaction and inhibits proliferation of esophageal squamous carcinoma cells.

Science.gov (United States)

Wang, Xinyu; Ren, Yanli; Wang, Zhiqiong; Xiong, Xiangyu; Han, Sichong; Pan, Wenting; Chen, Hongwei; Zhou, Liqing; Zhou, Changchun; Yuan, Qipeng; Yang, Ming

2015-12-21

5S rRNA plays an important part in ribosome biology and is over-expression in multiple cancers. In this study, we found that 5S rRNA is a direct target of miR-150 and miR-383 in esophageal squamous cell carcinoma (ESCC). Overexpression of miR-150 and miR-383 inhibited ESCC cell proliferation in vitro and in vivo. Moreover, 5S rRNA silencing by miR-150 and miR-383 might intensify rpL11-c-Myc interaction, which attenuated role of c-Myc as an oncogenic transcriptional factor and dysregulation of multiple c-Myc target genes. Taken together, our results highlight the involvement of miRNAs in ribosomal regulation during tumorigenesis. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

5. Accuracy of hemoglobin A1c imputation using fasting plasma glucose in diabetes research using electronic health records data

Directory of Open Access Journals (Sweden)

Stanley Xu

2014-05-01

Full Text Available In studies that use electronic health record data, imputation of important data elements such as Glycated hemoglobin (A1c has become common. However, few studies have systematically examined the validity of various imputation strategies for missing A1c values. We derived a complete dataset using an incident diabetes population that has no missing values in A1c, fasting and random plasma glucose (FPG and RPG, age, and gender. We then created missing A1c values under two assumptions: missing completely at random (MCAR and missing at random (MAR. We then imputed A1c values, compared the imputed values to the true A1c values, and used these data to assess the impact of A1c on initiation of antihyperglycemic therapy. Under MCAR, imputation of A1c based on FPG 1 estimated a continuous A1c within ± 1.88% of the true A1c 68.3% of the time; 2 estimated a categorical A1c within ± one category from the true A1c about 50% of the time. Including RPG in imputation slightly improved the precision but did not improve the accuracy. Under MAR, including gender and age in addition to FPG improved the accuracy of imputed continuous A1c but not categorical A1c. Moreover, imputation of up to 33% of missing A1c values did not change the accuracy and precision and did not alter the impact of A1c on initiation of antihyperglycemic therapy. When using A1c values as a predictor variable, a simple imputation algorithm based only on age, sex, and fasting plasma glucose gave acceptable results.

6. Genetic versus Non-Genetic Regulation of miR-103, miR-143 and miR-483-3p Expression in Adipose Tissue and Their Metabolic Implications—A Twin Study

Directory of Open Access Journals (Sweden)

Jette Bork-Jensen

2014-07-01

Full Text Available Murine models suggest that the microRNAs miR-103 and miR-143 may play central roles in the regulation of subcutaneous adipose tissue (SAT and development of type 2 diabetes (T2D. The microRNA miR-483-3p may reduce adipose tissue expandability and cause ectopic lipid accumulation, insulin resistance and T2D. We aimed to explore the genetic and non-genetic factors that regulate these microRNAs in human SAT, and to investigate their impact on metabolism in humans. Levels of miR-103, miR-143 and miR-483-3p were measured in SAT biopsies from 244 elderly monozygotic and dizygotic twins using real-time PCR. Heritability estimates were calculated and multiple regression analyses were performed to study associations between these microRNAs and measures of metabolism, as well as between these microRNAs and possible regulating factors. We found that increased BMI was associated with increased miR-103 expression levels. In addition, the miR-103 levels were positively associated with 2 h plasma glucose levels and hemoglobin A1c independently of BMI. Heritability estimates for all three microRNAs were low. In conclusion, the expression levels of miR-103, miR-143 and miR-483-3p in adipose tissue are primarily influenced by non-genetic factors, and miR-103 may be involved in the development of adiposity and control of glucose metabolism in humans.

7. Tumor-Suppressing Effect of MiR-4458 on Human Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Dan Tang

2015-03-01

Full Text Available Background: Besides multiple genetic and epigenetic changes of protein coding genes in hepatocellular carcinoma (HCC, growing evidence indicate that deregulation of miRNAs contribute to HCC development by influencing cell growth, apoptosis, migration, or invasion. IKBKE is amplified and over-expressed in a large percentage of human breast tumors and identified as an oncogene of human breast tumor. Microarray analysis showed that miR-4458 was down-regulated in HCC tissues. Methods: The level of miR-4458 was up-regulated by miR-4458 mimics transfection, or down-regulated by miR-4458 ASO transfection. Cell proliferation was assayed by MTT analysis. MiRNAs and mRNA expression were assayed by qRT-PCR. These potential targeted genes of miR-4458 were predicted by bioinformatic algorithms. Dual luciferase reporter assay system was used to analyze the interaction between miR-4458 and IKBKE. IKBKE protein level was assayed by Western blot. The role of miR-4458 or IKBKE in the survival of HCC patients were revealed by Kaplan-Meier plot of overall survival. Results: Lower miR-4458 expression level or higher IKBKE level in HCC tissues correlated with worse prognosis of HCC patients. Overexpression of miR-4458 inhibited the HCC cells growth and vice versa. MiR-4458 played its role via targeting 3'UTR of IKBKE. Conclusions: MiR-4458 or IKBKE may be potential predictors of HCC prognosis. Restoration of miR-4458 or inhibition of IKBKE could be a prospective therapeutic approach for HCC.

8. PPARγ inhibits ovarian cancer cells proliferation through upregulation of miR-125b

Energy Technology Data Exchange (ETDEWEB)

Luo, Shuang, E-mail: luoshuangsch@163.com [Department of Obstetrics and Gynecology, Suining Central Hospital, Suining (China); Wang, Jidong [Department of Gynecology and Obsterics, Jinan Central Hospital, Jinan (China); Ma, Ying [Department of Otorhinolaryngolgy, Suining Central Hospital, Suining (China); Yao, Zhenwei [Department of Gynecology and Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing (China); Pan, Hongjuan [Department of Gynecology and Obsterics, Zhongshan Hospital, Wuhan (China)

2015-06-26

miR-125b has essential roles in coordinating tumor proliferation, angiogenesis, invasiveness, metastasis and chemotherapy recurrence. In ovarian cancer miR-125b has been shown to be downregulated and acts as a tumor suppressor by targeting proto-oncogene BCL3. PPARγ, a multiple functional transcription factor, has been reported to have anti-tumor effects through inhibition of proliferation and induction of differentiation and apoptosis by targeting the tumor related genes. However, it is unclear whether miR-125b is regulated by PPARγ in ovarian cancer. In this study, we demonstrated that the miR-125b downregulated in ovarian cancer tissues and cell lines. Ligands-activated PPARγ suppressed proliferation of ovarian cancer cells and this PPARγ-induced growth inhibition is mediated by the upregulation of miR-125b. PPARγ promoted the expression of miR-125b by directly binding to the responsive element in miR-125b gene promoter region. Thus, our results suggest that PPARγ can induce growth suppression of ovarian cancer by upregulating miR-125b which inhibition of proto-oncogene BCL3. These findings will extend our understanding of the function of PPARγ in tumorigenesis and miR-125b may be a therapeutic intervention of ovarian cancer. - Highlights: • miR-125b is down-regulated in ovarian cancer tissues and cells. • PPARγ upregulates miR-125b and downregulates its target gene BCL3 expression. • Silence of miR-125b attenuates PPARγ-mediated growth suppression of ovarian cancer cells. • PPARγ promotes the transcription of miR-125b via binding to PPARE in miR-125b gene promoter region.

9. Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

Science.gov (United States)

Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P 1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

10. miR-200a-3p promotes β-Amyloid-induced neuronal apoptosis ...

Qi-Shun Zhang

2017-07-20

Jul 20, 2017 ... through down-regulation of SIRT1 in Alzheimer's disease. QI-SHUN ... purpose of this study was to examine whether miR-200a-3p regulated ... miR-29b-1 can modulate b-site amyloid precursor protein- ... multiple important cellular processes, including cell meta- .... Institutes of Health, Bethesda, MD, USA).

11. MiR-210 disturbs mitotic progression through regulating a group of mitosis-related genes

OpenAIRE

He, Jie; Wu, Jiangbin; Xu, Naihan; Xie, Weidong; Li, Mengnan; Li, Jianna; Jiang, Yuyang; Yang, Burton B.; Zhang, Yaou

2012-01-01

MiR-210 is up-regulated in multiple cancer types but its function is disputable and further investigation is necessary. Using a bioinformatics approach, we identified the putative target genes of miR-210 in hypoxia-induced CNE cells from genome-wide scale. Two functional gene groups related to cell cycle and RNA processing were recognized as the major targets of miR-210. Here, we investigated the molecular mechanism and biological consequence of miR-210 in cell cycle regulation, particularly ...

12. Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

Directory of Open Access Journals (Sweden)

Wilson Barry Tyler

2013-01-01

Full Text Available Abstract The U.S. has been providing national-scale estimates of forest carbon (C stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon and spatial scales (e.g., sub-county to biome. Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations. In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area, with weaker agreement for detrital pools (e.g., standing dead trees. Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC and regional scales (e.g., Reducing Emissions from Deforestation and Forest

13. Exploring the miRNA regulatory network using evolutionary correlations.

Directory of Open Access Journals (Sweden)

Benedikt Obermayer

2014-10-01

Full Text Available Post-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective.

14. Conservation and diversification of the miR166 family in soybean and potential roles of newly identified miR166s.

Science.gov (United States)

Li, Xuyan; Xie, Xin; Li, Ji; Cui, Yuhai; Hou, Yanming; Zhai, Lulu; Wang, Xiao; Fu, Yanli; Liu, Ranran; Bian, Shaomin

2017-02-01

microRNA166 (miR166) is a highly conserved family of miRNAs implicated in a wide range of cellular and physiological processes in plants. miR166 family generally comprises multiple miR166 members in plants, which might exhibit functional redundancy and specificity. The soybean miR166 family consists of 21 members according to the miRBase database. However, the evolutionary conservation and functional diversification of miR166 family members in soybean remain poorly understood. We identified five novel miR166s in soybean by data mining approach, thus enlarging the size of miR166 family from 21 to 26 members. Phylogenetic analyses of the 26 miR166s and their precursors indicated that soybean miR166 family exhibited both evolutionary conservation and diversification, and ten pairs of miR166 precursors with high sequence identity were individually grouped into a discrete clade in the phylogenetic tree. The analysis of genomic organization and evolution of MIR166 gene family revealed that eight segmental duplications and four tandem duplications might occur during evolution of the miR166 family in soybean. The cis-elements in promoters of MIR166 family genes and their putative targets pointed to their possible contributions to the functional conservation and diversification. The targets of soybean miR166s were predicted, and the cleavage of ATHB14-LIKE transcript was experimentally validated by RACE PCR. Further, the expression patterns of the five newly identified MIR166s and 12 target genes were examined during seed development and in response to abiotic stresses, which provided important clues for dissecting their functions and isoform specificity. This study enlarged the size of soybean miR166 family from 21 to 26 members, and the 26 soybean miR166s exhibited evolutionary conservation and diversification. These findings have laid a foundation for elucidating functional conservation and diversification of miR166 family members, especially during seed development or

15. In vivo delivery of miRNAs for cancer therapy: Challenges and strategies⋆

Science.gov (United States)

Chen, Yunching; Gao, Dong-Yu; Huang, Leaf

2016-01-01

MicroRNAs (miRNAs), small non-coding RNAs, can regulate post-transcriptional gene expressions and silence a broad set of target genes. miRNAs, aberrantly expressed in cancer cells, play an important role in modulating gene expressions, thereby regulating downstream signaling pathways and affecting cancer formation and progression. Oncogenes or tumor suppressor genes regulated by miRNAs mediate cell cycle progression, metabolism, cell death, angiogenesis, metastasis and immunosuppression in cancer. Recently, miRNAs have emerged as therapeutic targets or tools and biomarkers for diagnosis and therapy monitoring in cancer. Since miRNAs can regulate multiple cancer-related genes simultaneously, using miRNAs as a therapeutic approach plays an important role in cancer therapy. However, one of the major challenges of miRNA-based cancer therapy is to achieve specific, efficient and safe systemic delivery of therapeutic miRNAs In vivo. This review discusses the key challenges to the development of the carriers for miRNA-based therapy and explores current strategies to systemically deliver miRNAs to cancer without induction of toxicity. PMID:24859533

16. MiR-338-3p regulates neuronal maturation and suppresses glioblastoma proliferation.

Directory of Open Access Journals (Sweden)

James R Howe

Full Text Available Neurogenesis is a highly-regulated process occurring in the dentate gyrus that has been linked to learning, memory, and antidepressant efficacy. MicroRNAs (miRNAs have been previously shown to play an important role in the regulation of neuronal development and neurogenesis in the dentate gyrus via modulation of gene expression. However, this mode of regulation is both incompletely described in the literature thus far and highly multifactorial. In this study, we designed sensors and detected relative levels of expression of 10 different miRNAs and found miR-338-3p was most highly expressed in the dentate gyrus. Comparison of miR-338-3p expression with neuronal markers of maturity indicates miR-338-3p is expressed most highly in the mature neuron. We also designed a viral "sponge" to knock down in vivo expression of miR-338-3p. When miR-338-3p is knocked down, neurons sprout multiple primary dendrites that branch off of the soma in a disorganized manner, cellular proliferation is upregulated, and neoplasms form spontaneously in vivo. Additionally, miR-338-3p overexpression in glioblastoma cell lines slows their proliferation in vitro. Further, low miR-338-3p expression is associated with increased mortality and disease progression in patients with glioblastoma. These data identify miR-338-3p as a clinically relevant tumor suppressor in glioblastoma.

17. MiR-122 Induces Radiosensitization in Non-Small Cell Lung Cancer Cell Line

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Debin Ma

2015-09-01

Full Text Available MiR-122 is a novel tumor suppresser and its expression induces cell cycle arrest, or apoptosis, and inhibits cell proliferation in multiple cancer cells, including non-small cell lung cancer (NSCLC cells. Radioresistance of cancer cell leads to the major drawback of radiotherapy for NSCLC and the induction of radiosensitization could be a useful strategy to fix this problem. The present work investigates the function of miR-122 in inducing radiosensitization in A549 cell, a type of NSCLC cells. MiR-122 induces the radiosensitization of A549 cells. MiR-122 also boosts the inhibitory activity of ionizing radiation (IR on cancer cell anchor-independent growth and invasion. Moreover, miR-122 reduced the expression of its targeted genes related to tumor-survival or cellular stress response. These results indicate that miR-122 would be a novel strategy for NSCLC radiation-therapy.

18. Three novel serum biomarkers, miR-1, miR-133a, and miR-206 for Limb-girdle muscular dystrophy, Facioscapulohumeral muscular dystrophy, and Becker muscular dystrophy.

Science.gov (United States)

Matsuzaka, Yasunari; Kishi, Soichiro; Aoki, Yoshitsugu; Komaki, Hirofumi; Oya, Yasushi; Takeda, Shin-Ichi; Hashido, Kazuo

2014-11-01

Muscular dystrophies are a clinically and genetically heterogeneous group of inherited myogenic disorders. In clinical tests for these diseases, creatine kinase (CK) is generally used as diagnostic blood-based biomarker. However, because CK levels can be altered by various other factors, such as vigorous exercise, etc., false positive is observed. Therefore, three microRNAs (miRNAs), miR-1, miR-133a, and miR-206, were previously reported as alternative biomarkers for duchenne muscular dystrophy (DMD). However, no alternative biomarkers have been established for the other muscular dystrophies. We, therefore, evaluated whether these miR-1, miR-133a, and miR-206 can be used as powerful biomarkers using the serum from muscular dystrophy patients including DMD, myotonic dystrophy 1 (DM1), limb-girdle muscular dystrophy (LGMD), facioscapulohumeral muscular dystrophy (FSHD), becker muscular dystrophy (BMD), and distal myopathy with rimmed vacuoles (DMRV) by qualitative polymerase chain reaction (PCR) amplification assay. Statistical analysis indicated that all these miRNA levels in serum represented no significant differences between all muscle disorders examined in this study and controls by Bonferroni correction. However, some of these indicated significant differences without correction for testing multiple diseases (P < 0.05). The median values of miR-1 levels in the serum of patients with LGMD, FSHD, and BMD were approximately 5.5, 3.3 and 1.7 compared to that in controls, 0.68, respectively. Similarly, those of miR-133a and miR-206 levels in the serum of BMD patients were about 2.5 and 2.1 compared to those in controls, 1.03 and 1.32, respectively. Taken together, our data demonstrate that levels of miR-1, miR-133a, and miR-206 in serum of BMD and miR-1 in sera of LGMD and FSHD patients showed no significant differences compared with those of controls by Bonferroni correction. However, the results might need increase in sample sizes to evaluate these three miRNAs as

19. A Study of Chinese Undergraduates' MI Distribution in EFL Class

Science.gov (United States)

Liu, Ning

2008-01-01

This paper initiates an investigation of the college students' MI (multiple intelligences) distribution in English class. The participants are a group of Chinese sophomores from different majors: city planning, tourism, software engineering, financial administration and arts of English. With a view to make the investigation more specified in…

20. Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.

Science.gov (United States)

Wood, Andrew R; Perry, John R B; Tanaka, Toshiko; Hernandez, Dena G; Zheng, Hou-Feng; Melzer, David; Gibbs, J Raphael; Nalls, Michael A; Weedon, Michael N; Spector, Tim D; Richards, J Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B; Frayling, Timothy M

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.

1. Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations

DEFF Research Database (Denmark)

Dassonneville, R; Brøndum, Rasmus Froberg; Druet, T

2011-01-01

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data...... of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test...... with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected...

2. Semiautomatic imputation of activity travel diaries : use of global positioning system traces, prompted recall, and context-sensitive learning algorithms

NARCIS (Netherlands)

Moiseeva, A.; Jessurun, A.J.; Timmermans, H.J.P.; Stopher, P.

2016-01-01

Anastasia Moiseeva, Joran Jessurun and Harry Timmermans (2010), ‘Semiautomatic Imputation of Activity Travel Diaries: Use of Global Positioning System Traces, Prompted Recall, and Context-Sensitive Learning Algorithms’, Transportation Research Record: Journal of the Transportation Research Board,

3. Imputation Accuracy from Low to Moderate Density Single Nucleotide Polymorphism Chips in a Thai Multibreed Dairy Cattle Population

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Danai Jattawa

2016-04-01

Full Text Available The objective of this study was to investigate the accuracy of imputation from low density (LDC to moderate density SNP chips (MDC in a Thai Holstein-Other multibreed dairy cattle population. Dairy cattle with complete pedigree information (n = 1,244 from 145 dairy farms were genotyped with GeneSeek GGP20K (n = 570, GGP26K (n = 540 and GGP80K (n = 134 chips. After checking for single nucleotide polymorphism (SNP quality, 17,779 SNP markers in common between the GGP20K, GGP26K, and GGP80K were used to represent MDC. Animals were divided into two groups, a reference group (n = 912 and a test group (n = 332. The SNP markers chosen for the test group were those located in positions corresponding to GeneSeek GGP9K (n = 7,652. The LDC to MDC genotype imputation was carried out using three different software packages, namely Beagle 3.3 (population-based algorithm, FImpute 2.2 (combined family- and population-based algorithms and Findhap 4 (combined family- and population-based algorithms. Imputation accuracies within and across chromosomes were calculated as ratios of correctly imputed SNP markers to overall imputed SNP markers. Imputation accuracy for the three software packages ranged from 76.79% to 93.94%. FImpute had higher imputation accuracy (93.94% than Findhap (84.64% and Beagle (76.79%. Imputation accuracies were similar and consistent across chromosomes for FImpute, but not for Findhap and Beagle. Most chromosomes that showed either high (73% or low (80% imputation accuracies were the same chromosomes that had above and below average linkage disequilibrium (LD; defined here as the correlation between pairs of adjacent SNP within chromosomes less than or equal to 1 Mb apart. Results indicated that FImpute was more suitable than Findhap and Beagle for genotype imputation in this Thai multibreed population. Perhaps additional increments in imputation accuracy could be achieved by increasing the completeness of pedigree information.

4. Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

Science.gov (United States)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

5. Expression profiling of miR-96, miR-584 and miR-422a in colon ...

African Journals Online (AJOL)

Purpose: To determine the correlation between miRNAs; miR-96, miR-422a and miR584, and colon cancer, and also to test whether any of these miRNAs can act as non-invasive biomarkers in colon cancer. Methods: The tumor samples and the corresponding normal mucosa used in this study were collected from 60 ...

6. Generation of miRNA sponge constructs

NARCIS (Netherlands)

Kluiver, Joost; Slezak-Prochazka, Izabella; Smigielska-Czepiel, Katarzyna; Halsema, Nancy; Kroesen, Bart-Jan; van den Berg, Anke

2012-01-01

MicroRNA (miRNA) sponges are RNA molecules with repeated miRNA antisense sequences that can sequester miRNAs from their endogenous targets and thus serve as a decoy. Stably expressed miRNA sponges are especially valuable for long-term loss-of-function studies and can be used in vitro and in vivo. We

7. Imputing historical statistics, soils information, and other land-use data to crop area

Science.gov (United States)

Perry, C. R., Jr.; Willis, R. W.; Lautenschlager, L.

1982-01-01

In foreign crop condition monitoring, satellite acquired imagery is routinely used. To facilitate interpretation of this imagery, it is advantageous to have estimates of the crop types and their extent for small area units, i.e., grid cells on a map represent, at 60 deg latitude, an area nominally 25 by 25 nautical miles in size. The feasibility of imputing historical crop statistics, soils information, and other ancillary data to crop area for a province in Argentina is studied.

8. Interactions of miR-323/miR-326/miR-329 and miR-130a/miR-155/miR-210 as prognostic indicators for clinical outcome of glioblastoma patients

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Qiu Shuwei

2013-01-01

Full Text Available Abstract Background Glioblastoma multiforme (GBM is the most common and aggressive brain tumor with poor clinical outcome. Identification and development of new markers could be beneficial for the diagnosis and prognosis of GBM patients. Deregulation of microRNAs (miRNAs or miRs is involved in GBM. Therefore, we attempted to identify and develop specific miRNAs as prognostic and predictive markers for GBM patient survival. Methods Expression profiles of miRNAs and genes and the corresponding clinical information of 480 GBM samples from The Cancer Genome Atlas (TCGA dataset were downloaded and interested miRNAs were identified. Patients’ overall survival (OS and progression-free survival (PFS associated with interested miRNAs and miRNA-interactions were performed by Kaplan-Meier survival analysis. The impacts of miRNA expressions and miRNA-interactions on survival were evaluated by Cox proportional hazard regression model. Biological processes and network of putative and validated targets of miRNAs were analyzed by bioinformatics. Results In this study, 6 interested miRNAs were identified. Survival analysis showed that high levels of miR-326/miR-130a and low levels of miR-323/miR-329/miR-155/miR-210 were significantly associated with long OS of GBM patients, and also showed that high miR-326/miR-130a and low miR-155/miR-210 were related with extended PFS. Moreover, miRNA-323 and miRNA-329 were found to be increased in patients with no-recurrence or long time to progression (TTP. More notably, our analysis revealed miRNA-interactions were more specific and accurate to discriminate and predict OS and PFS. This interaction stratified OS and PFS related with different miRNA levels more detailed, and could obtain longer span of mean survival in comparison to that of one single miRNA. Moreover, miR-326, miR-130a, miR-155, miR-210 and 4 miRNA-interactions were confirmed for the first time as independent predictors for survival by Cox regression model

9. miRNA signature and Dicer requirement during human endometrial stromal decidualization in vitro.

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Carlos Estella

Full Text Available Decidualization is a morphological and biochemical transformation of endometrial stromal fibroblast into differentiated decidual cells, which is critical for embryo implantation and pregnancy establishment. The complex regulatory networks have been elucidated at both the transcriptome and the proteome levels, however very little is known about the post-transcriptional regulation of this process. miRNAs regulate multiple physiological pathways and their de-regulation is associated with human disorders including gynaecological conditions such as endometriosis and preeclampsia. In this study we profile the miRNAs expression throughout human endometrial stromal (hESCs decidualization and analyze the requirement of the miRNA biogenesis enzyme Dicer during this process. A total of 26 miRNAs were upregulated and 17 miRNAs downregulated in decidualized hESCs compared to non-decidualized hESCs. Three miRNAs families, miR-181, miR-183 and miR-200, are down-regulated during the decidualization process. Using miRNAs target prediction algorithms we have identified the potential targets and pathways regulated by these miRNAs. The knockdown of Dicer has a minor effect on hESCs during in vitro decidualization. We have analyzed a battery of decidualization markers such as cell morphology, Prolactin, IGFBP-1, MPIF-1 and TIMP-3 secretion as well as HOXA10, COX2, SP1, C/EBPß and FOXO1 expression in decidualized hESCs with decreased Dicer function. We found decreased levels of HOXA10 and altered intracellular organization of actin filaments in Dicer knockdown decidualized hESCs compared to control. Our results provide the miRNA signature of hESC during the decidualization process in vitro. We also provide the first functional characterization of Dicer during human endometrial decidualization although surprisingly we found that Dicer plays a minor role regulating this process suggesting that alternative biogenesis miRNAs pathways must be involved in human

10. Identification of miR-508-3p and miR-509-3p that are associated with cell invasion and migration and involved in the apoptosis of renal cell carcinoma

International Nuclear Information System (INIS)

Zhai, Qingna; Zhou, Liang; Zhao, Chunjuan; Wan, Jun; Yu, Zhendong; Guo, Xin; Qin, Jie; Chen, Jing; Lu, Ruijing

2012-01-01

Highlights: ► Previous method was the second-generation sequencing technology. ► miR-508-3p and miR-509-3p were significantly down-regulated in RCC tissues. ► They can inhibit cell proliferation and migration and promote cell apoptosis. ► The expression of miR-508-3p was significantly decreased in RCC patients plasma. ► miR-508-3p may be a novel diagnostic marker of RCC. -- Abstract: MicroRNAs (miRNAs) have emerged as powerful regulators of multiple processes linked to human cancer, including cell apoptosis, proliferation and migration, suggesting that the regulation of miRNA function could play a critical role in cancer progression. Recent studies have found that human serum/plasma contains stably expressed miRNAs. If they prove indicative of disease states, miRNAs measured from peripheral blood samples may be a source for routine clinical detection of cancer. Our studies showed that both miR-508-3p and miR-509-3p were down-regulated in renal cancer tissues. The level of miR-508-3p but not miR-509-3p in renal cell carcinoma (RCC) patient plasma demonstrated significant differences from that in control plasma. In addition, the overexpression of miR-508-3p and miR-509-3p suppressed the proliferation of RCC cells (786-0), induced cell apoptosis and inhibited cell migration in vitro. Our data demonstrated that miR-508-3p and miR-509-3p played an important role as tumor suppressor genes during tumor formation and that they may serve as novel diagnostic markers for RCC.

11. Construction and application of a Korean reference panel for imputing classical alleles and amino acids of human leukocyte antigen genes.

Science.gov (United States)

Kim, Kwangwoo; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol

2014-01-01

Genetic variations of human leukocyte antigen (HLA) genes within the major histocompatibility complex (MHC) locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs) at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans.

12. Construction and application of a Korean reference panel for imputing classical alleles and amino acids of human leukocyte antigen genes.

Directory of Open Access Journals (Sweden)

Kwangwoo Kim

Full Text Available Genetic variations of human leukocyte antigen (HLA genes within the major histocompatibility complex (MHC locus are strongly associated with disease susceptibility and prognosis for many diseases, including many autoimmune diseases. In this study, we developed a Korean HLA reference panel for imputing classical alleles and amino acid residues of several HLA genes. An HLA reference panel has potential for use in identifying and fine-mapping disease associations with the MHC locus in East Asian populations, including Koreans. A total of 413 unrelated Korean subjects were analyzed for single nucleotide polymorphisms (SNPs at the MHC locus and six HLA genes, including HLA-A, -B, -C, -DRB1, -DPB1, and -DQB1. The HLA reference panel was constructed by phasing the 5,858 MHC SNPs, 233 classical HLA alleles, and 1,387 amino acid residue markers from 1,025 amino acid positions as binary variables. The imputation accuracy of the HLA reference panel was assessed by measuring concordance rates between imputed and genotyped alleles of the HLA genes from a subset of the study subjects and East Asian HapMap individuals. Average concordance rates were 95.6% and 91.1% at 2-digit and 4-digit allele resolutions, respectively. The imputation accuracy was minimally affected by SNP density of a test dataset for imputation. In conclusion, the Korean HLA reference panel we developed was highly suitable for imputing HLA alleles and amino acids from MHC SNPs in East Asians, including Koreans.

13. Imputation of microsatellite alleles from dense SNP genotypes for parental verification

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Matthew eMcclure

2012-08-01

Full Text Available Microsatellite (MS markers have recently been used for parental verification and are still the international standard despite higher cost, error rate, and turnaround time compared with Single Nucleotide Polymorphisms (SNP-based assays. Despite domestic and international interest from producers and research communities, no viable means currently exist to verify parentage for an individual unless all familial connections were analyzed using the same DNA marker type (MS or SNP. A simple and cost-effective method was devised to impute MS alleles from SNP haplotypes within breeds. For some MS, imputation results may allow inference across breeds. A total of 347 dairy cattle representing 4 dairy breeds (Brown Swiss, Guernsey, Holstein, and Jersey were used to generate reference haplotypes. This approach has been verified (>98% accurate for imputing the International Society of Animal Genetics (ISAG recommended panel of 12 MS for cattle parentage verification across a validation set of 1,307 dairy animals.. Implementation of this method will allow producers and breed associations to transition to SNP-based parentage verification utilizing MS genotypes from historical data on parents where SNP genotypes are missing. This approach may be applicable to additional cattle breeds and other species that wish to migrate from MS- to SNP- based parental verification.

14. TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION.

Science.gov (United States)

Allen, Genevera I; Tibshirani, Robert

2010-06-01

Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable , meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate normal, the mean-restricted matrix-variate normal , in which the rows and columns each have a separate mean vector and covariance matrix. By placing additive penalties on the inverse covariance matrices of the rows and columns, these so called transposable regularized covariance models allow for maximum likelihood estimation of the mean and non-singular covariance matrices. Using these models, we formulate EM-type algorithms for missing data imputation in both the multivariate and transposable frameworks. We present theoretical results exploiting the structure of our transposable models that allow these models and imputation methods to be applied to high-dimensional data. Simulations and results on microarray data and the Netflix data show that these imputation techniques often outperform existing methods and offer a greater degree of flexibility.

15. Data Editing and Imputation in Business Surveys Using “R”

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Elena Romascanu

2014-06-01

Full Text Available Purpose – Missing data are a recurring problem that can cause bias or lead to inefficient analyses. The objective of this paper is a direct comparison between the two statistical software features R and SPSS, in order to take full advantage of the existing automated methods for data editing process and imputation in business surveys (with a proper design of consistency rules as a partial alternative to the manual editing of data. Approach – The comparison of different methods on editing surveys data, in R with the ‘editrules’ and ‘survey’ packages because inside those, exist commonly used transformations in ofﬁcial statistics, as visualization of missing values pattern using ‘Amelia’ and ‘VIM’ packages, imputation approaches for longitudinal data using ‘VIMGUI’ and a comparison of another statistical software performance on the same features, such as SPSS. Findings – Data on business statistics received by NIS’s (National Institute of Statistics are not ready to be used for direct analysis due to in-record inconsistencies, errors and missing values from the collected data sets. The appropriate automatic methods from R packages, offers the ability to set the erroneous fields in edit-violating records, to verify the results after the imputation of missing values providing for users a flexible, less time consuming approach and easy to perform automation in R than in SPSS Macros syntax situations, when macros are very handy.

16. Whose Music of a Century? Performance, History and Multiple Voices

African Journals Online (AJOL)

It's the small words that do the most cultural work. THE MUSIC OF A CENTURY, the title of the conference for which this paper was written, imputes a spurious singularity to a multiplicity of cultural practices, and begs the question of in whose interests this singularity is being constructed. An alternative question, 'WHOSE ...

17. miR-21 modulates resistance of HR-HPV positive cervical cancer cells to radiation through targeting LATS1

Energy Technology Data Exchange (ETDEWEB)

Liu, Shikai; Song, Lili, E-mail: commasll@163.com; Zhang, Liang; Zeng, Saitian; Gao, Fangyuan

2015-04-17

18. miR-21 modulates resistance of HR-HPV positive cervical cancer cells to radiation through targeting LATS1

International Nuclear Information System (INIS)

Liu, Shikai; Song, Lili; Zhang, Liang; Zeng, Saitian; Gao, Fangyuan

2015-01-01

19. Clinical relevance of microRNA miR-21, miR-31, miR-92a, miR-101, miR-106a and miR-145 in colorectal cancer

International Nuclear Information System (INIS)

Schee, Kristina; Boye, Kjetil; Abrahamsen, Torveig Weum; Fodstad, Øystein; Flatmark, Kjersti

2012-01-01

MicroRNAs (miRNAs) regulate gene expression by binding to mRNA, and can function as oncogenes or tumor suppressors depending on the target. In this study, using qRT-PCR, we examined the expression of six miRNAs (miR-21, miR-31, miR-92a, miR-101, miR-106a and miR-145) in tumors from 193 prospectively recruited patients with colorectal cancer, and associations with clinicopathological parameters and patient outcome were analyzed. The miRNAs were chosen based on previous studies for their biomarker potential and suggested biological relevance in colorectal cancer. The miRNA expression was examined by qRT-PCR. Associations between miRNA expression and clinicopathological variables were explored using Mann–Whitney U and Kruskal-Wallis test while survival was estimated using the Kaplan-Meier method and compared using the log-rank test. MiR-101 was hardly expressed in the tumor samples, while for the other miRNAs, variable expression levels and expression ranges were observed, with miR-21 being most abundantly expressed relative to the reference (RNU44). In our study cohort, major clinical significance was demonstrated only for miR-31, as high expression was associated with advanced tumor stage and poor differentiation. No significant associations were found between expression of the investigated miRNAs and metastasis-free or overall survival. Investigating the expression of six miRNAs previously identified as candidate biomarkers in colorectal cancer, few clinically relevant associations were detected in our patient cohort. Our results emphasize the importance of validating potential tumor markers in independent patient cohorts, and indicate that the role of miRNAs as colorectal cancer biomarkers is still undetermined

20. Hypermethylation of MIR21 in CD4+ T cells from patients with relapsing-remitting multiple sclerosis associates with lower miRNA-21 levels and concomitant up-regulation of its target genes

KAUST Repository

Ruhrmann, Sabrina; Ewing, Ewoud; Piket, Eliane; Kular, Lara; Cetrulo Lorenzi, Julio Cesar; Fernandes, Sunjay Jude; Morikawa, Hiromasa; Aeinehband, Shahin; Sayols-Baixeras, Sergi; Aslibekyan, Stella; Absher, Devin M; Arnett, Donna K; Tegner, Jesper; Gomez-Cabrero, David; Piehl, Fredrik; Jagodic, Maja

2017-01-01

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system caused by genetic and environmental factors. DNA methylation, an epigenetic mechanism that controls genome activity, may provide a link between genetic

1. Exploring the Application of Multiple Intelligences Theory to Career Counseling

Science.gov (United States)

Shearer, C. Branton; Luzzo, Darrell Anthony

2009-01-01

This article demonstrates the practical value of applying H. Gardner's (1993) theory of multiple intelligences (MI) to the practice of career counseling. An overview of H. Gardner's MI theory is presented, and the ways in which educational and vocational planning can be augmented by the integration of MI theory in career counseling contexts are…

2. Quick, “Imputation-free” meta-analysis with proxy-SNPs

Directory of Open Access Journals (Sweden)

Meesters Christian

2012-09-01

Full Text Available Abstract Background Meta-analysis (MA is widely used to pool genome-wide association studies (GWASes in order to a increase the power to detect strong or weak genotype effects or b as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software, however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming. Results Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127. Conclusions YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy

3. miREE: miRNA recognition elements ensemble

Science.gov (United States)

2011-01-01

Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between

4. Identification of targets of miR-200b by a SILAC-based quantitative proteomic approach

Directory of Open Access Journals (Sweden)

Arivusudar Marimuthu

2014-09-01

Full Text Available miRNAs regulate gene expression by binding to cognate mRNAs causing mRNA degradation or translational repression. Mass spectrometry-based proteomic analysis is being widely used to identify miRNA targets. The miR-200b miRNA cluster is often overexpressed in multiple cancer types, but the identity of the targets remains elusive. Using SILAC-based analysis, we examined the effects of overexpression of a miR-200b mimic or a control miRNA in fibrosarcoma cells. We identified around 300 potential targets of miR-200b based on a change in the expression of protein levels. We validated a subset of potential targets at the transcript level using quantitative PCR.

5. miRNA-Processing Gene Methylation and Cancer Risk.

Science.gov (United States)

Joyce, Brian T; Zheng, Yinan; Zhang, Zhou; Liu, Lei; Kocherginsky, Masha; Murphy, Robert; Achenbach, Chad J; Musa, Jonah; Wehbe, Firas; Just, Allan; Shen, Jincheng; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A; Hou, Lifang

2018-05-01

Background: Dysregulation of miRNA and methylation levels are epigenetic hallmarks of cancer, potentially linked via miRNA-processing genes. Studies have found genetic alterations to miRNA-processing genes in cancer cells and human population studies. Our objective was to prospectively examine changes in DNA methylation of miRNA-processing genes and their associations with cancer risk. Methods: We examined cohort data from the Department of Veterans' Affairs Normative Aging Study. Participants were assessed every 3 to 5 years starting in 1999 through 2013 including questionnaires, medical record review, and blood collection. Blood from 686 consenting participants was analyzed using the Illumina 450K BeadChip array to measure methylation at CpG sites throughout the genome. We selected 19 genes based on a literature review, with 519 corresponding CpG sites. We then used Cox proportional hazards models to examine associations with cancer incidence, and generalized estimating equations to examine associations with cancer prevalence. Associations at false discovery rate time to cancer development (positively for cg06751583, inversely for cg23230564 and cg21034183), whereas methylation of one CpG site ( DROSHA : cg16131300) was positively associated with cancer prevalence. Conclusions: DNA methylation of DROSHA , a key miRNA-processing gene, and TNRC6B may play a role in early carcinogenesis. Impact: Changes in miRNA processing may exert multiple effects on cancer development, including protecting against it via altered global miRNAs, and may be a useful early detection biomarker of cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 550-7. ©2018 AACR . ©2018 American Association for Cancer Research.

6. MiR-210 disturbs mitotic progression through regulating a group of mitosis-related genes.

Science.gov (United States)

He, Jie; Wu, Jiangbin; Xu, Naihan; Xie, Weidong; Li, Mengnan; Li, Jianna; Jiang, Yuyang; Yang, Burton B; Zhang, Yaou

2013-01-07

MiR-210 is up-regulated in multiple cancer types but its function is disputable and further investigation is necessary. Using a bioinformatics approach, we identified the putative target genes of miR-210 in hypoxia-induced CNE cells from genome-wide scale. Two functional gene groups related to cell cycle and RNA processing were recognized as the major targets of miR-210. Here, we investigated the molecular mechanism and biological consequence of miR-210 in cell cycle regulation, particularly mitosis. Hypoxia-induced up-regulation of miR-210 was highly correlated with the down-regulation of a group of mitosis-related genes, including Plk1, Cdc25B, Cyclin F, Bub1B and Fam83D. MiR-210 suppressed the expression of these genes by directly targeting their 3'-UTRs. Over-expression of exogenous miR-210 disturbed mitotic progression and caused aberrant mitosis. Furthermore, miR-210 mimic with pharmacological doses reduced tumor formation in a mouse metastatic tumor model. Taken together, these results implicate that miR-210 disturbs mitosis through targeting multi-genes involved in mitotic progression, which may contribute to its inhibitory role on tumor formation.

7. miRNA-135a promotes breast cancer cell migration and invasion by targeting HOXA10

International Nuclear Information System (INIS)

Chen, Yating; Zhang, Hongwei; Ma, Duan; Zhang, Jin; Wang, Huijun; Zhao, Jiayi; Xu, Cheng; Du, Yingying; Luo, Xin; Zheng, Fengyun; Liu, Rui

2012-01-01

miRNAs are a group of small RNA molecules regulating target genes by inducing mRNA degradation or translational repression. Aberrant expression of miRNAs correlates with various cancers. Although miR-135a has been implicated in several other cancers, its role in breast cancer is unknown. HOXA10 however, is associated with multiple cancer types and was recently shown to induce p53 expression in breast cancer cells and reduce their invasive ability. Because HOXA10 is a confirmed miR-135a target in more than one tissue, we examined miR-135a levels in relation to breast cancer phenotypes to determine if miR-135a plays role in this cancer type. Expression levels of miR-135a in tissues and cells were determined by poly (A)-RT PCR. The effect of miR-135a on proliferation was evaluated by CCK8 assay, cell migration and invasion were evaluated by transwell migration and invasion assays, and target protein expression was determined by western blotting. GFP and luciferase reporter plasmids were constructed to confirm the action of miR-135a on downstream target genes including HOXA10. Results are reported as means ± S.D. and differences were tested for significance using 2-sided Student's t-test. Here we report that miR-135a was highly expressed in metastatic breast tumors. We found that the expression of miR-135a was required for the migration and invasion of breast cancer cells, but not their proliferation. HOXA10, which encodes a transcription factor required for embryonic development and is a metastasis suppressor in breast cancer, was shown to be a direct target of miR-135a in breast cancer cells. Our analysis showed that miR-135a suppressed the expression of HOXA10 both at the mRNA and protein level, and its ability to promote cellular migration and invasion was partially reversed by overexpression of HOXA10. In summary, our results indicate that miR-135a is an onco-miRNA that can promote breast cancer cell migration and invasion. HOXA10 is a target gene for mi

8. Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

Science.gov (United States)

He, Jun; Xu, Jiaqi; Wu, Xiao-Lin; Bauck, Stewart; Lee, Jungjae; Morota, Gota; Kachman, Stephen D; Spangler, Matthew L

2018-04-01

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

9. miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy.

Directory of Open Access Journals (Sweden)

Alexander S Baras

Full Text Available Small RNA RNA-seq for microRNAs (miRNAs is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM. Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench, miRge was faster (4 to 32-fold and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.

10. MiRNA Biogenesis and Intersecting Pathways

DEFF Research Database (Denmark)

Ben Chaabane, Samir

MicroRNAs (miRNAs) are small non-coding RNAs that function as guide molecules in RNA silencing. Plant miRNAs are critical for plant growth, development and stress response, and are processed in Arabidopsis from primary miRNA transcripts (pri-miRNAs) by the endonuclease activity of the DICER-LIKE1...... questions need to be addressed to establish a valid link, we provide encouraging evidence of the involvement of chromatin remodeling factors FAS1 and FAS2 in miRNA biogenesis. Together, we have expanded our understanding of the intersections between miRNA biogenesis and other pathways....

11. miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells

DEFF Research Database (Denmark)

Hua, Youjia; Duan, Shiwei; Murmann, Andrea E

2011-01-01

have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. We have developed a novel strategy for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment......micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information....... By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, we have clustered miRNAs into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT...

12. Diet and lifestyle factors associated with miRNA expression in colorectal tissue

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Slattery ML

2016-12-01

Full Text Available Martha L Slattery,1 Jennifer S Herrick,1 Lila E Mullany,1 John R Stevens,2 Roger K Wolff1 1Department of Internal Medicine, The University of Utah, Salt Lake City, 2Department of Mathematics and Statistics, Utah State University, Logan, UT, USA Abstract: MicroRNAs (miRNAs are small non-protein-coding RNA molecules that regulate gene expression. Diet and lifestyle factors have been hypothesized to be involved in the regulation of miRNA expression. In this study it was hypothesized that diet and lifestyle factors are associated with miRNA expression. Data from 1,447 cases of colorectal cancer to evaluate 34 diet and lifestyle variables using miRNA expression in normal colorectal mucosa as well as for differential expression between paired carcinoma and normal tissue were used. miRNA data were obtained using an Agilent platform. Multiple comparisons were adjusted for using the false discovery rate q-value. There were 250 miRNAs differentially expressed between carcinoma and normal colonic tissue by level of carbohydrate intake and 198 miRNAs differentially expressed by the level of sucrose intake. Of these miRNAs, 166 miRNAs were differentially expressed for both carbohydrate intake and sucrose intake. Ninety-nine miRNAs were differentially expressed by the level of whole grain intake in normal colonic mucosa. Level of oxidative balance score was associated with 137 differentially expressed miRNAs between carcinoma and paired normal rectal mucosa. Additionally, 135 miRNAs were differentially expressed in colon tissue based on recent NSAID use. Other dietary factors, body mass index, waist and hip circumference, and long-term physical activity levels did not alter miRNA expression after adjustment for multiple comparisons. These results suggest that diet and lifestyle factors regulate miRNA level. They provide additional support for the influence of carbohydrate, sucrose, whole grains, NSAIDs, and oxidative balance score on colorectal cancer risk

13. Circulating miRNAs miR-34a and miR-150 associated with colorectal cancer progression

Czech Academy of Sciences Publication Activity Database

Aherne, S.T.; Madden, S.F.; Hughes, D. J.; Pardini, B.; Naccarati, A.; Levý, M.; Vodička, Pavel; Neary, P.; Dowling, P.; Clynes, M.

2015-01-01

Roč. 15, apr 30 (2015), s. 2-13 ISSN 1471-2407 R&D Projects: GA ČR GAP304/10/1286 Institutional support: RVO:68378041 Keywords : colorectal cancer * circulating miRNAs * miR-34a * miR-150 * miR-923 Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.265, year: 2015

14. Missing data in clinical trials: control-based mean imputation and sensitivity analysis.

Science.gov (United States)

Mehrotra, Devan V; Liu, Fang; Permutt, Thomas

2017-09-01

In some randomized (drug versus placebo) clinical trials, the estimand of interest is the between-treatment difference in population means of a clinical endpoint that is free from the confounding effects of "rescue" medication (e.g., HbA1c change from baseline at 24 weeks that would be observed without rescue medication regardless of whether or when the assigned treatment was discontinued). In such settings, a missing data problem arises if some patients prematurely discontinue from the trial or initiate rescue medication while in the trial, the latter necessitating the discarding of post-rescue data. We caution that the commonly used mixed-effects model repeated measures analysis with the embedded missing at random assumption can deliver an exaggerated estimate of the aforementioned estimand of interest. This happens, in part, due to implicit imputation of an overly optimistic mean for "dropouts" (i.e., patients with missing endpoint data of interest) in the drug arm. We propose an alternative approach in which the missing mean for the drug arm dropouts is explicitly replaced with either the estimated mean of the entire endpoint distribution under placebo (primary analysis) or a sequence of increasingly more conservative means within a tipping point framework (sensitivity analysis); patient-level imputation is not required. A supplemental "dropout = failure" analysis is considered in which a common poor outcome is imputed for all dropouts followed by a between-treatment comparison using quantile regression. All analyses address the same estimand and can adjust for baseline covariates. Three examples and simulation results are used to support our recommendations. Copyright © 2017 John Wiley & Sons, Ltd.

15. Imputation of Baseline LDL Cholesterol Concentration in Patients with Familial Hypercholesterolemia on Statins or Ezetimibe.

Science.gov (United States)

Ruel, Isabelle; Aljenedil, Sumayah; Sadri, Iman; de Varennes, Émilie; Hegele, Robert A; Couture, Patrick; Bergeron, Jean; Wanneh, Eric; Baass, Alexis; Dufour, Robert; Gaudet, Daniel; Brisson, Diane; Brunham, Liam R; Francis, Gordon A; Cermakova, Lubomira; Brophy, James M; Ryomoto, Arnold; Mancini, G B John; Genest, Jacques

2018-02-01

Familial hypercholesterolemia (FH) is the most frequent genetic disorder seen clinically and is characterized by increased LDL cholesterol (LDL-C) (>95th percentile), family history of increased LDL-C, premature atherosclerotic cardiovascular disease (ASCVD) in the patient or in first-degree relatives, presence of tendinous xanthomas or premature corneal arcus, or presence of a pathogenic mutation in the LDLR , PCSK9 , or APOB genes. A diagnosis of FH has important clinical implications with respect to lifelong risk of ASCVD and requirement for intensive pharmacological therapy. The concentration of baseline LDL-C (untreated) is essential for the diagnosis of FH but is often not available because the individual is already on statin therapy. To validate a new algorithm to impute baseline LDL-C, we examined 1297 patients. The baseline LDL-C was compared with the imputed baseline obtained within 18 months of the initiation of therapy. We compared the percent reduction in LDL-C on treatment from baseline with the published percent reductions. After eliminating individuals with missing data, nonstandard doses of statins, or medications other than statins or ezetimibe, we provide data on 951 patients. The mean ± SE baseline LDL-C was 243.0 (2.2) mg/dL [6.28 (0.06) mmol/L], and the mean ± SE imputed baseline LDL-C was 244.2 (2.6) mg/dL [6.31 (0.07) mmol/L] ( P = 0.48). There was no difference in response according to the patient's sex or in percent reduction between observed and expected for individual doses or types of statin or ezetimibe. We provide a validated estimation of baseline LDL-C for patients with FH that may help clinicians in making a diagnosis. © 2017 American Association for Clinical Chemistry.

16. Using the Superpopulation Model for Imputations and Variance Computation in Survey Sampling

Directory of Open Access Journals (Sweden)

Petr Novák

2012-03-01

Full Text Available This study is aimed at variance computation techniques for estimates of population characteristics based on survey sampling and imputation. We use the superpopulation regression model, which means that the target variable values for each statistical unit are treated as random realizations of a linear regression model with weighted variance. We focus on regression models with one auxiliary variable and no intercept, which have many applications and straightforward interpretation in business statistics. Furthermore, we deal with caseswhere the estimates are not independent and thus the covariance must be computed. We also consider chained regression models with auxiliary variables as random variables instead of constants.

17. Missing Value Imputation Based on Gaussian Mixture Model for the Internet of Things

OpenAIRE

Yan, Xiaobo; Xiong, Weiqing; Hu, Liang; Wang, Feng; Zhao, Kuo

2015-01-01

This paper addresses missing value imputation for the Internet of Things (IoT). Nowadays, the IoT has been used widely and commonly by a variety of domains, such as transportation and logistics domain and healthcare domain. However, missing values are very common in the IoT for a variety of reasons, which results in the fact that the experimental data are incomplete. As a result of this, some work, which is related to the data of the IoT, can’t be carried out normally. And it leads to the red...

18. Non-imputability, criminal dangerousness and curative safety measures: myths and realities

Directory of Open Access Journals (Sweden)

Frank Harbottle Quirós

2017-04-01

Full Text Available The curative safety measures are imposed in a criminal proceeding to the non-imputable people provided that through a prognosis it is concluded in an affirmative way about its criminal dangerousness. Although this statement seems very elementary, in judicial practice several myths remain in relation to these legal institutes whose versions may vary, to a greater or lesser extent, between the different countries of the world. In this context, the present article formulates ten myths based on the experience of Costa Rica and provides an explanation that seeks to weaken or knock them down, inviting the reader to reflect on them.

19. A suggested approach for imputation of missing dietary data for young children in daycare

OpenAIRE

Stevens, June; Ou, Fang-Shu; Truesdale, Kimberly P.; Zeng, Donglin; Vaughn, Amber E.; Pratt, Charlotte; Ward, Dianne S.

2015-01-01

Background: Parent-reported 24-h diet recalls are an accepted method of estimating intake in young children. However, many children eat while at childcare making accurate proxy reports by parents difficult.Objective: The goal of this study was to demonstrate a method to impute missing weekday lunch and daytime snack nutrient data for daycare children and to explore the concurrent predictive and criterion validity of the method.Design: Data were from children aged 2-5 years in the My Parenting...

20. Expression profiling of miR-96, miR-584 and miR-422a in colon ...

African Journals Online (AJOL)

. Lower miRNA ... Thus, the ratio of miR-96/miR-638 in plasma is a potential non- ... leading cause of cancer related deaths. ... breast cancer cells have revealed a total of 51 ... Corresponding negative control ..... The American Joint Committee.

1. 34A, miRNA-944, miRNA-101 and miRNA-218 in cervical cancer

African Journals Online (AJOL)

RNAs (21 - 24 nucleotides in length) that are critical for many important processes such as development, ... RNA extraction and reverse transcription. Total RNA was extracted from each of the experimental groups using ... used as an endogenous control to normalize the expression of miRNA-143, miRNA-34A, miRNA-.

2. Encuentro "Mi marca y yo"

OpenAIRE

Universidad de Alicante. Observatorio Comunicación en Cambio

2013-01-01

La gestión de la marca personal, especialmente en los entornos digitales, ha cobrado actualmente gran importancia como estrategia de posicionamiento profesional. Te invitamos a que asistas a nuestro encuentro "Mi marca y yo" para reflexionar sobre qué implica contar con una marca personal.

3. Zcchc11 Uridylates Mature miRNAs to Enhance Neonatal IGF-1 Expression, Growth, and Survival

Science.gov (United States)

Kozlowski, Elyse; Matsuura, Kori Y.; Ferrari, Joseph D.; Morris, Samantha A.; Powers, John T.; Daley, George Q.; Quinton, Lee J.; Mizgerd, Joseph P.

2012-01-01

The Zcchc11 enzyme is implicated in microRNA (miRNA) regulation. It can uridylate let-7 precursors to decrease quantities of the mature miRNA in embryonic stem cell lines, suggested to mediate stem cell maintenance. It can uridylate mature miR-26 to relieve silencing activity without impacting miRNA content in cancer cell lines, suggested to mediate cytokine and growth factor expression. Broader roles of Zcchc11 in shaping or remodeling the miRNome or in directing biological or physiological processes remain entirely speculative. We generated Zcchc11-deficient mice to address these knowledge gaps. Zcchc11 deficiency had no impact on embryogenesis or fetal development, but it significantly decreased survival and growth immediately following birth, indicating a role for this enzyme in early postnatal fitness. Deep sequencing of small RNAs from neonatal livers revealed roles of this enzyme in miRNA sequence diversity. Zcchc11 deficiency diminished the lengths and terminal uridine frequencies for diverse mature miRNAs, but it had no influence on the quantities of any miRNAs. The expression of IGF-1, a liver-derived protein essential to early growth and survival, was enhanced by Zcchc11 expression in vitro, and miRNA silencing of IGF-1 was alleviated by uridylation events observed to be Zcchc11-dependent in the neonatal liver. In neonatal mice, Zcchc11 deficiency significantly decreased IGF-1 mRNA in the liver and IGF-1 protein in the blood. We conclude that the Zcchc11-mediated terminal uridylation of mature miRNAs is pervasive and physiologically significant, especially important in the neonatal period for fostering IGF-1 expression and enhancing postnatal growth and survival. We propose that the miRNA 3′ terminus is a regulatory node upon which multiple enzymes converge to direct silencing activity and tune gene expression. PMID:23209448

4. Zcchc11 uridylates mature miRNAs to enhance neonatal IGF-1 expression, growth, and survival.

Directory of Open Access Journals (Sweden)

Matthew R Jones

Full Text Available The Zcchc11 enzyme is implicated in microRNA (miRNA regulation. It can uridylate let-7 precursors to decrease quantities of the mature miRNA in embryonic stem cell lines, suggested to mediate stem cell maintenance. It can uridylate mature miR-26 to relieve silencing activity without impacting miRNA content in cancer cell lines, suggested to mediate cytokine and growth factor expression. Broader roles of Zcchc11 in shaping or remodeling the miRNome or in directing biological or physiological processes remain entirely speculative. We generated Zcchc11-deficient mice to address these knowledge gaps. Zcchc11 deficiency had no impact on embryogenesis or fetal development, but it significantly decreased survival and growth immediately following birth, indicating a role for this enzyme in early postnatal fitness. Deep sequencing of small RNAs from neonatal livers revealed roles of this enzyme in miRNA sequence diversity. Zcchc11 deficiency diminished the lengths and terminal uridine frequencies for diverse mature miRNAs, but it had no influence on the quantities of any miRNAs. The expression of IGF-1, a liver-derived protein essential to early growth and survival, was enhanced by Zcchc11 expression in vitro, and miRNA silencing of IGF-1 was alleviated by uridylation events observed to be Zcchc11-dependent in the neonatal liver. In neonatal mice, Zcchc11 deficiency significantly decreased IGF-1 mRNA in the liver and IGF-1 protein in the blood. We conclude that the Zcchc11-mediated terminal uridylation of mature miRNAs is pervasive and physiologically significant, especially important in the neonatal period for fostering IGF-1 expression and enhancing postnatal growth and survival. We propose that the miRNA 3' terminus is a regulatory node upon which multiple enzymes converge to direct silencing activity and tune gene expression.

5. Serum MiRNA Biomarkers serve as a Fingerprint for Proliferative Diabetic Retinopathy

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Shao Qing

2014-11-01

Full Text Available Background: Diabetic retinopathy (DR is a retinopathy resulting from diabetes mellitus (DM which was classified into non-proliferative DR (NPDR and proliferative DR (PDR. Without an early screening and effective diagnosis, patients with PDR will develop serious complications. Therefore, we sought to identify special serum microRNAs (miRNAs that can serve as a novel non-invasive screening signature of PDR and test its specificity and sensitivity in the early diagnosis of PDR. Methods: In total, we obtained serum samples from 90 PDR cases, 90 matched NPDR patients and 20 controls. An initial screening of miRNA expression was performed through TaqMan Low Density Array (TLDA. The candidate miRNAs were validated by individual reverse transcription quantitative real-time PCR (RT-qPCR arranged in an initial and a two-stage validation sets. Moreover, additional double-blind testing was performed in 20 patients clinically suspected of having DR to evaluate the diagnostic value and accuracy of the serum miRNA profiling system in predicting PDR. Results: Three miRNAs were significantly increased in patients with PDR compared with NPDR after the multiple stages. The areas under the receiver operating characteristic (ROC curves of the validated three-serum miRNAs signature were 0.830, 0.803 and 0.873 in the initial and two validation sets, respectively. Combination of miR-21, miR-181c, and miR-1179 possessed a moderate ability to discrimination between PDR and NPDR with an area under ROC value of 0.89. The accuracy rate of the three-miRNA profile as PDR signature was 82.6%. Conclusions: These data provide evidence that serum miRNAs have the potential to be sensitive, cost-effective biomarkers for the early detection of PDR. These biomarkers could serve as a dynamic monitoring factor for detecting the progression of PDR from NPDR.

6. Treating pre-instrumental data as "missing" data: using a tree-ring-based paleoclimate record and imputations to reconstruct streamflow in the Missouri River Basin

Science.gov (United States)

Ho, M. W.; Lall, U.; Cook, E. R.

2015-12-01

Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.

7. The Association of Circulating MiR-29b and Interleukin-6 with Subclinical Atherosclerosis

Directory of Open Access Journals (Sweden)

Yu-qing Huang

2017-12-01

Full Text Available Background/Aims: Although it is widely acknowledged that atherosclerosis is mainly a chronic inflammatory process, in which both miR-29b and interleukin-6 (IL-6 play multifaceted roles, the association between miR-29b and IL-6 remains unknown. The aim of the present study was to explore the relationship between miR-29b and IL-6 and to test whether circulating levels of miR-29b and IL-6 could predict atherosclerosis. Methods: A total of 170 participants were divided into two groups according to carotid intima-media thickness (CIMT: study group (CIMT ≥ 0.9mm and control group (CIMT < 0.9mm. Levels of circulating miR-29b and IL-6 were measured by quantitative real-time polymerase chain reaction (qRT-PCR and enzyme-linked immunosorbent assay (ELISA, respectively. The association of miR-29b and IL-6 levels with CIMT was assessed using Spearman correlation analysis and multiple linear regression analysis. Results: The study group showed higher miR-29b levels (31.61 ± 3.05 vs. 27.91 ± 1.71 Ct, p < 0.001 and IL-6 levels (3.40 ± 0.67 vs. 2.99 ± 0.37 pg/ml, p < 0.001, compared with the control group. CIMT was positively correlated with miR-29b (r = 0.587, p < 0.001 and IL-6 (r = 0.410, p < 0.001, and miR-29b levels were also correlated with IL-6 (r = 0.242, p = 0.001. Multiple linear regression analysis also showed that CIMT was positively correlated with miR-29b and IL-6. After adjustment for age, body mass index, systolic blood pressure, total cholesterol and C-reactive protein, CIMT was still closely correlated with miR-29b and IL-6. The combination of miR-29b and IL-6 (AUC = 0.901, p < 0.001 offered a better predictive index for atherosclerosis than either miR-29b (AUC = 0.867, p < 0.001 or IL-6 (AUC = 0.747, p < 0.001 alone. Conclusion: Circulating levels of miR-29b and IL-6 may be independently correlated with subclinical atherosclerosis, and may serve as novel biomarkers for the identification of atherosclerosis.

8. MicroRNAs miR-17 and miR-20a inhibit T cell activation genes and are under-expressed in MS whole blood.

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Mathew B Cox

Full Text Available It is well established that Multiple Sclerosis (MS is an immune mediated disease. Little is known about what drives the differential control of the immune system in MS patients compared to unaffected individuals. MicroRNAs (miRNAs are small non-coding nucleic acids that are involved in the control of gene expression. Their potential role in T cell activation and neurodegenerative disease has recently been recognised and they are therefore excellent candidates for further studies in MS. We investigated the transcriptome of currently known miRNAs using miRNA microarray analysis in peripheral blood samples of 59 treatment naïve MS patients and 37 controls. Of these 59, 18 had a primary progressive, 17 a secondary progressive and 24 a relapsing remitting disease course. In all MS subtypes miR-17 and miR-20a were significantly under-expressed in MS, confirmed by RT-PCR. We demonstrate that these miRNAs modulate T cell activation genes in a knock-in and knock-down T cell model. The same T cell activation genes are also up-regulated in MS whole blood mRNA, suggesting these miRNAs or their analogues may provide useful targets for new therapeutic approaches.

9. miR-199a-3p displays tumor suppressor functions in papillary thyroid carcinoma.

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Minna, Emanuela; Romeo, Paola; De Cecco, Loris; Dugo, Matteo; Cassinelli, Giuliana; Pilotti, Silvana; Degl'Innocenti, Debora; Lanzi, Cinzia; Casalini, Patrizia; Pierotti, Marco A; Greco, Angela; Borrello, Maria Grazia

2014-05-15

Thyroid cancer incidence is rapidly increasing. Papillary Thyroid Carcinoma (PTC), the most frequent hystotype, usually displays good prognosis, but no effective therapeutic options are available for the fraction of progressive PTC patients. BRAF and RET/PTC are the most frequent driving genetic lesions identified in PTC. We developed two complementary in vitro models based on RET/PTC1 oncogene, starting from the hypothesis that miRNAs modulated by a driving PTC-oncogene are likely to have a role in thyroid neoplastic processes. Through this strategy, we identified a panel of deregulated miRNAs. Among these we focused on miR-199a-3p and showed its under-expression in PTC specimens and cell lines. We demonstrated that miR-199a-3p restoration in PTC cells reduces MET and mTOR protein levels, impairs migration and proliferation and, more interesting, induces lethality through an unusual form of cell death similar to methuosis, caused by macropinocytosis dysregulation. Silencing MET or mTOR, both involved in survival pathways, does not recapitulate miR-199a-3p-induced cell lethality, thus suggesting that the cooperative regulation of multiple gene targets is necessary. Integrated analysis of miR-199a-3p targets unveils interesting networks including HGF and macropinocytosis pathways. Overall our results indicate miR-199a-3p as a tumor suppressor miRNA in PTC.

10. A Meta-Path-Based Prediction Method for Human miRNA-Target Association

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Jiawei Luo

2016-01-01

Full Text Available MicroRNAs (miRNAs are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

11. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

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Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

12. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

13. FCMPSO: An Imputation for Missing Data Features in Heart Disease Classification

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Salleh, Mohd Najib Mohd; Ashikin Samat, Nurul

2017-08-01

The application of data mining and machine learning in directing clinical research into possible hidden knowledge is becoming greatly influential in medical areas. Heart Disease is a killer disease around the world, and early prevention through efficient methods can help to reduce the mortality number. Medical data may contain many uncertainties, as they are fuzzy and vague in nature. Nonetheless, imprecise features data such as no values and missing values can affect quality of classification results. Nevertheless, the other complete features are still capable to give information in certain features. Therefore, an imputation approach based on Fuzzy C-Means and Particle Swarm Optimization (FCMPSO) is developed in preprocessing stage to help fill in the missing values. Then, the complete dataset is trained in classification algorithm, Decision Tree. The experiment is trained with Heart Disease dataset and the performance is analysed using accuracy, precision, and ROC values. Results show that the performance of Decision Tree is increased after the application of FCMSPO for imputation.

14. Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

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Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

15. Local exome sequences facilitate imputation of less common variants and increase power of genome wide association studies.

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Peter K Joshi

Full Text Available The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10% in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.

16. Random Forest as an Imputation Method for Education and Psychology Research: Its Impact on Item Fit and Difficulty of the Rasch Model

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Golino, Hudson F.; Gomes, Cristiano M. A.

2016-01-01

This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

17. miRNAs in brain development

International Nuclear Information System (INIS)

Petri, Rebecca; Malmevik, Josephine; Fasching, Liana; Åkerblom, Malin; Jakobsson, Johan

2014-01-01

MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. In the brain, a large number of miRNAs are expressed and there is a growing body of evidence demonstrating that miRNAs are essential for brain development and neuronal function. Conditional knockout studies of the core components in the miRNA biogenesis pathway, such as Dicer and DGCR8, have demonstrated a crucial role for miRNAs during the development of the central nervous system. Furthermore, mice deleted for specific miRNAs and miRNA-clusters demonstrate diverse functional roles for different miRNAs during the development of different brain structures. miRNAs have been proposed to regulate cellular functions such as differentiation, proliferation and fate-determination of neural progenitors. In this review we summarise the findings from recent studies that highlight the importance of miRNAs in brain development with a focus on the mouse model. We also discuss the technical limitations of current miRNA studies that still limit our understanding of this family of non-coding RNAs and propose the use of novel and refined technologies that are needed in order to fully determine the impact of specific miRNAs in brain development. - Highlights: • miRNAs are essential for brain development and neuronal function. • KO of Dicer is embryonically lethal. • Conditional Dicer KO results in defective proliferation or increased apoptosis. • KO of individual miRNAs or miRNA families is necessary to determine function

18. Multiple Intelligences and quotient spaces

OpenAIRE

Malatesta, Mike; Quintana, Yamilet

2006-01-01

The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

19. The regulatory effect of miRNAs is a heritable genetic trait in humans

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Geeleher Paul

2012-08-01

Full Text Available Abstract Background microRNAs (miRNAs have been shown to regulate the expression of a large number of genes and play key roles in many biological processes. Several previous studies have quantified the inhibitory effect of a miRNA indirectly by considering the expression levels of genes that are predicted to be targeted by the miRNA and this approach has been shown to be robust to the choice of prediction algorithm. Given a gene expression dataset, Cheng et al. defined the regulatory effect score (RE-score of a miRNA as the difference in the gene expression rank of targets of the miRNA compared to non-targeted genes. Results Using microarray data from parent-offspring trios from the International HapMap project, we show that the RE-score of most miRNAs is correlated between parents and offspring and, thus, inter-individual variation in RE-score has a genetic component in humans. Indeed, the mean RE-score across miRNAs is correlated between parents and offspring, suggesting genetic differences in the overall efficiency of the miRNA biogenesis pathway between individuals. To explore the genetics of this quantitative trait further, we carried out a genome-wide association study of the mean RE-score separately in two HapMap populations (CEU and YRI. No genome-wide significant associations were discovered; however, a SNP rs17409624, in an intron of DROSHA, was significantly associated with mean RE-score in the CEU population following permutation-based control for multiple testing based on all SNPs mapped to the canonical miRNA biogenesis pathway; of 244 individual miRNA RE-scores assessed in the CEU, 214 were associated (p p = 0.04 with mean RE-score in the YRI population. Interestingly, the same SNP was associated with 17 (8.5% of all expressed miRNA expression levels in the CEU. We also show here that the expression of the targets of most miRNAs is more highly correlated with global changes in miRNA regulatory effect than with the expression of

20. Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density.

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Claudia Coronnello

Full Text Available MicroRNAs (miRNAs are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting, a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential

1. Glatiramer acetate treatment normalizes deregulated microRNA expression in relapsing remitting multiple sclerosis.

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Anne Waschbisch

Full Text Available The expression of selected microRNAs (miRNAs known to be involved in the regulation of immune responses was analyzed in 74 patients with relapsing remitting multiple sclerosis (RRMS and 32 healthy controls. Four miRNAs (miR-326, miR-155, miR-146a, miR-142-3p were aberrantly expressed in peripheral blood mononuclear cells from RRMS patients compared to controls. Although expression of these selected miRNAs did not differ between treatment-naïve (n = 36 and interferon-beta treated RRMS patients (n = 18, expression of miR-146a and miR-142-3p was significantly lower in glatiramer acetate (GA treated RRMS patients (n = 20 suggesting that GA, at least in part, restores the expression of deregulated miRNAs in MS.

2. Regulation of Pattern Formation and Gene Amplification During Drosophila Oogenesis by the miR-318 microRNA

DEFF Research Database (Denmark)

Ge, Wanzhong; Deng, Qiannan; Guo, Ting

2015-01-01

Pattern formation during epithelial development requires the coordination of multiple signaling pathways. Here, we investigate the functions of an ovary-enriched miRNA, miR-318, in epithelial development during Drosophila oogenesis. miR-318 maternal loss-of-function mutants were female sterile...... and laid eggs with abnormal morphology. Removal of miR-318 disrupted the dorsal-anterior follicle cell patterning, resulting in abnormal dorsal appendages. miR-318 mutant females also produced thin and fragile eggshells, due to impaired chorion gene amplification. We provide evidence that the ecdysone......RNAs in maintaining cell fate and promoting the developmental transition in the female follicular epithelium....

3. miR-150 suppresses the proliferation and tumorigenicity of leukemia stem cells by targeting the Nanog signaling pathway

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Dan-dan Xu

2016-11-01

Full Text Available Proliferation, a key feature of cancer cells, accounts for the majority of cancer-related diseases resulting in mortality. MicroRNAs (miRNAs plays important post-transcriptional modulation roles by acting on multiple signaling pathways, but the underlying mechanism in proliferation and tumorigenicity is unclear. Here, we identified the role of miR-150 in proliferation and tumorigenicity in leukemia stem cells (LSCs (CD34+CD38- cells. miR-150 expression was significantly down-regulated in LSCs from leukemia cell lines and clinical samples. Functional assays demonstrated that increased miR-150 expression inhibited proliferation and clonal and clonogenic growth, enhanced chemosensitivity, and attenuated tumorigenic activity of LSCs in vitro. Transplantation animal studies revealed that miR-150 overexpression progressively abrogates tumour growth. Immunohistochemistry assays demonstrated that miR-150 overexpression enhanced caspase-3 level and reduced Ki-67 level. Moreover, luciferase reporter assays indicated Nanog is a direct and functional target of miR-150. Nanog silencing using small interfering RNA recapitulated anti-proliferation and tumorigenicity inhibition effects. Furthermore, miR-150 directly down-regulated the expression of other cancer stem cell factors including Notch2 and CTNNB1. These results provide insights into the specific biological behaviour of miR-150 in regulating LSC proliferation and tumorigenicity. Targeting this miR-150/Nanog axis would be a helpful therapeutic strategy to treat acute myeloid leukemia.

4. Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human Squamous Cell Carcinoma Metastasis

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Nathan Benaich

2014-10-01

Full Text Available Summary: Metastatic colonization of distant organs underpins the majority of human-cancer-related deaths, including deaths from head and neck squamous cell carcinoma (HNSCC. We report that miR-203, a miRNA that triggers differentiation in multilayered epithelia, inhibits multiple postextravasation events during HNSCC lung metastasis. Inducible reactivation of miR-203 in already established lung metastases reduces the overall metastatic burden. Using an integrated approach, we reveal that miR-203 inhibits metastasis independently of its effects on differentiation. In vivo genetic reconstitution experiments show that miR-203 inhibits lung metastasis by suppressing the prometastatic activities of three factors involved in cytoskeletal dynamics (LASP1, extracellular matrix remodeling (SPARC, and cell metabolism (NUAK1. Expression of miR-203 and its downstream effectors correlates with HNSCC overall survival outcomes, indicating the therapeutic potential of targeting this signaling axis. : Benaich et al. have identified miR-203, a microRNA that triggers differentiation in multilayered epithelia, as an inhibitor of lung metastasis in head and neck squamous cell carcinoma (HNSCC cells. They show that miR-203 inhibits metastasis independently of its effects on differentiation. Rather, miR-203 suppresses the prometastatic activities of three factors involved in cytoskeletal dynamics (LASP1, extracellular matrix remodeling (SPARC, and cell metabolism (NUAK1. Expression of miR-203 and its downstream effectors correlates with survival in HNSCC patients.

5. Potential role of miR-9 and miR-223 in recurrent ovarian cancer

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McGuinness Eamonn

2008-04-01

Full Text Available Abstract Background MicroRNAs (miRNAs are small, noncoding RNAs that negatively regulate gene expression by binding to target mRNAs. miRNAs have not been comprehensively studied in recurrent ovarian cancer, yet an incurable disease. Results Using real-time RT-PCR, we obtained distinct miRNA expression profiles between primary and recurrent serous papillary ovarian adenocarcinomas (n = 6 in a subset of samples previously used in a transcriptome approach. Expression levels of top dysregulated miRNA genes, miR-223 and miR-9, were examined using TaqMan PCR in independent cohorts of fresh frozen (n = 18 and FFPE serous ovarian tumours (n = 22. Concordance was observed on TaqMan analysis for miR-223 and miR-9 between the training cohort and the independent test cohorts. Target prediction analysis for the above miRNA "recurrent metastatic signature" identified genes previously validated in our transcriptome study. Common biological pathways well characterised in ovarian cancer were shared by miR-9 and miR-223 lists of predicted target genes. We provide strong evidence that miR-9 acts as a putative tumour suppressor gene in recurrent ovarian cancer. Components of the miRNA processing machinery, such as Dicer and Drosha are not responsible for miRNA deregulation in recurrent ovarian cancer, as deluded by TaqMan and immunohistochemistry. Conclusion We propose a miRNA model for the molecular pathogenesis of recurrent ovarian cancer. Some of the differentially deregulated miRNAs identified correlate with our previous transcriptome findings. Based on integrated transcriptome and miRNA analysis, miR-9 and miR-223 can be of potential importance as biomarkers in recurrent ovarian cancer.

6. Imputation of missing genotypes within LD-blocks relying on the basic coalescent and beyond: consideration of population growth and structure.

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Kabisch, Maria; Hamann, Ute; Lorenzo Bermejo, Justo

2017-10-17

Genotypes not directly measured in genetic studies are often imputed to improve statistical power and to increase mapping resolution. The accuracy of standard imputation techniques strongly depends on the similarity of linkage disequilibrium (LD) patterns in the study and reference populations. Here we develop a novel approach for genotype imputation in low-recombination regions that relies on the coalescent and permits to explicitly account for population demographic factors. To test the new method, study and reference haplotypes were simulated and gene trees were inferred under the basic coalescent and also considering population growth and structure. The reference haplotypes that first coalesced with study haplotypes were used as templates for genotype imputation. Computer simulations were complemented with the analysis of real data. Genotype concordance rates were used to compare the accuracies of coalescent-based and standard (IMPUTE2) imputation. Simulations revealed that, in LD-blocks, imputation accuracy relying on the basic coalescent was higher and less variable than with IMPUTE2. Explicit consideration of population growth and structure, even if present, did not practically improve accuracy. The advantage of coalescent-based over standard imputation increased with the minor allele frequency and it decreased with population stratification. Results based on real data indicated that, even in low-recombination regions, further research is needed to incorporate recombination in coalescence inference, in particular for studies with genetically diverse and admixed individuals. To exploit the full potential of coalescent-based methods for the imputation of missing genotypes in genetic studies, further methodological research is needed to reduce computer time, to take into account recombination, and to implement these methods in user-friendly computer programs. Here we provide reproducible code which takes advantage of publicly available software to facilitate

7. Imputation by the mean score should be avoided when validating a Patient Reported Outcomes questionnaire by a Rasch model in presence of informative missing data

LENUS (Irish Health Repository)

Hardouin, Jean-Benoit

2011-07-14

Abstract Background Nowadays, more and more clinical scales consisting in responses given by the patients to some items (Patient Reported Outcomes - PRO), are validated with models based on Item Response Theory, and more specifically, with a Rasch model. In the validation sample, presence of missing data is frequent. The aim of this paper is to compare sixteen methods for handling the missing data (mainly based on simple imputation) in the context of psychometric validation of PRO by a Rasch model. The main indexes used for validation by a Rasch model are compared. Methods A simulation study was performed allowing to consider several cases, notably the possibility for the missing values to be informative or not and the rate of missing data. Results Several imputations methods produce bias on psychometrical indexes (generally, the imputation methods artificially improve the psychometric qualities of the scale). In particular, this is the case with the method based on the Personal Mean Score (PMS) which is the most commonly used imputation method in practice. Conclusions Several imputation methods should be avoided, in particular PMS imputation. From a general point of view, it is important to use an imputation method that considers both the ability of the patient (measured for example by his\\/her score), and the difficulty of the item (measured for example by its rate of favourable responses). Another recommendation is to always consider the addition of a random process in the imputation method, because such a process allows reducing the bias. Last, the analysis realized without imputation of the missing data (available case analyses) is an interesting alternative to the simple imputation in this context.

8. Bioinformatics of cardiovascular miRNA biology.

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Kunz, Meik; Xiao, Ke; Liang, Chunguang; Viereck, Janika; Pachel, Christina; Frantz, Stefan; Thum, Thomas; Dandekar, Thomas

2015-12-01

9. Functional analysis of neuronal microRNAs in Caenorhabditis elegans dauer formation by combinational genetics and Neuronal miRISC immunoprecipitation.

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Minh T Than

2013-06-01

Full Text Available Identifying the physiological functions of microRNAs (miRNAs is often challenging because miRNAs commonly impact gene expression under specific physiological conditions through complex miRNA::mRNA interaction networks and in coordination with other means of gene regulation, such as transcriptional regulation and protein degradation. Such complexity creates difficulties in dissecting miRNA functions through traditional genetic methods using individual miRNA mutations. To investigate the physiological functions of miRNAs in neurons, we combined a genetic "enhancer" approach complemented by biochemical analysis of neuronal miRNA-induced silencing complexes (miRISCs in C. elegans. Total miRNA function can be compromised by mutating one of the two GW182 proteins (AIN-1, an important component of miRISC. We found that combining an ain-1 mutation with a mutation in unc-3, a neuronal transcription factor, resulted in an inappropriate entrance into the stress-induced, alternative larval stage known as dauer, indicating a role of miRNAs in preventing aberrant dauer formation. Analysis of this genetic interaction suggests that neuronal miRNAs perform such a role partly by regulating endogenous cyclic guanosine monophosphate (cGMP signaling, potentially influencing two other dauer-regulating pathways. Through tissue-specific immunoprecipitations of miRISC, we identified miRNAs and their likely target mRNAs within neuronal tissue. We verified the biological relevance of several of these miRNAs and found that many miRNAs likely regulate dauer formation through multiple dauer-related targets. Further analysis of target mRNAs suggests potential miRNA involvement in various neuronal processes, but the importance of these miRNA::mRNA interactions remains unclear. Finally, we found that neuronal genes may be more highly regulated by miRNAs than intestinal genes. Overall, our study identifies miRNAs and their targets, and a physiological function of these miRNAs in

10. Measurement of target and double-spin asymmetries for the $\stackrel{}{}$mi>e><mi>pmi><mi>emi><mimi>+(<mi>n>) reaction in the nucleon resonance region at low ${}^{}$mi>Q>2

Energy Technology Data Exchange (ETDEWEB)

Zheng, X.; Adhikari, K. P.; Bosted, P.; Deur, A.; Drozdov, V.; El Fassi, L.; Kang, Hyekoo; Kovacs, K.; Kuhn, S.; Long, E.; Phillips, S. K.; Ripani, M.; Slifer, K.; Smith, L. C.; Adikaram, D.; Akbar, Z.; Amaryan, M. J.; Anefalos Pereira, S.; Asryan, G.; Avakian, H.; Badui, R. A.; Ball, J.; Baltzell, N. A.; Battaglieri, M.; Batourine, V.; Bedlinskiy, I.; Biselli, A. S.; Briscoe, W. J.; Bültmann, S.; Burkert, V. D.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Chen, J. -P.; Chetry, T.; Choi, Seonho; Ciullo, G.; Clark, L.; Colaneri, L.; Cole, P. L.; Compton, N.; Contalbrigo, M.; Crede, V.; D' Angelo, A.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Djalali, C.; Dodge, G. E.; Dupre, R.; Egiyan, H.; El Alaoui, A.; Elouadrhiri, L.; Eugenio, P.; Fanchini, E.; Fedotov, G.; Fersch, R.; Filippi, A.; Fleming, J. A.; Gevorgyan, N.; Ghandilyan, Y.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gleason, C.; Golovach, E.; Gothe, R. W.; Griffioen, K. A.; Guidal, M.; Guler, N.; Guo, L.; Hanretty, C.; Harrison, N.; Hattawy, M.; Hicks, K.; Holtrop, M.; Hughes, S. M.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Isupov, E. L.; Jenkins, D.; Jiang, H.; Jo, H. S.; Joosten, S.; Keller, D.; Khachatryan, G.; Khandaker, M.; Kim, A.; Kim, W.; Klein, F. J.; Kubarovsky, V.; Lanza, L.; Lenisa, P.; Livingston, K.; MacGregor, I. J. D.; Markov, N.; McKinnon, B.; Mirazita, M.; Mokeev, V.; Movsisyan, A.; Munevar, E.; Munoz Camacho, C.; Murdoch, G.; Nadel-Turonski, P.; Net, L. A.; Ni, A.; Niccolai, S.; Niculescu, G.; Niculescu, I.; Osipenko, M.; Ostrovidov, A. I.; Paolone, M.; Paremuzyan, R.; Park, K.; Pasyuk, E.; Peng, P.; Pisano, S.; Pogorelko, O.; Price, J. W.; Puckett, A. J. R.; Raue, B. A.; Rizzo, A.; Rosner, G.; Rossi, P.; Roy, P.; Sabatié, F.; Salgado, C.; Schumacher, R. A.; Sharabian, Y. G.; Skorodumina, Iu.; Smith, G. D.; Sokhan, D.; Sparveris, N.; Stankovic, I.; Strakovsky, I. I.; Strauch, S.; Taiuti, M.; Tian, Ye; Ungaro, M.; Voskanyan, H.; Voutier, E.; Walford, N. K.; Watts, D. P.; Wei, X.; Weinstein, L. B.; Wood, M. H.; Zachariou, N.; Zhang, J.; Zonta, I.

2016-10-01

We report measurements of target- and double-spin asymmetries for the exclusive channel $\stackrel{}{}$mi>e><mi>pmi><mi>emi><mimi>+(<mi>n>) in the nucleon resonance region at Jefferson Lab using the CEBAF Large Acceptance Spectrometer (CLAS). These asymmetries were extracted from data obtained using a longitudinally polarized NH3 target and a longitudinally polarized electron beam with energies 1.1, 1.3, 2.0, 2.3, and 3.0 GeV. The new results are consistent with previous CLAS publications but are extended to a low Q2 range from 0.0065 to 0.35 (GeV/c)2. The Q2 access was made possible by a custom-built Cherenkov detector that allowed the detection of electrons for scattering angles as low as 6 degrees. These results are compared with the unitary isobar models JANR and MAID, the partial-wave analysis prediction from SAID, and the dynamic model DMT. In many kinematic regions our results, in particular results on the target asymmetry, help to constrain the polarization-dependent components of these models.

11. Inhibition of bromodomain and extra-terminal (BET) proteins increases NKG2D ligand MICA expression and sensitivity to NK cell-mediated cytotoxicity in multiple myeloma cells: role of cMYC-IRF4-miR-125b interplay.

Science.gov (United States)

Abruzzese, Maria Pia; Bilotta, Maria Teresa; Fionda, Cinzia; Zingoni, Alessandra; Soriani, Alessandra; Vulpis, Elisabetta; Borrelli, Cristiana; Zitti, Beatrice; Petrucci, Maria Teresa; Ricciardi, Maria Rosaria; Molfetta, Rosa; Paolini, Rossella; Santoni, Angela; Cippitelli, Marco

2016-12-01

Anti-cancer immune responses may contribute to the control of tumors after conventional chemotherapy, and different observations have indicated that chemotherapeutic agents can induce immune responses resulting in cancer cell death and immune-stimulatory side effects. Increasing experimental and clinical evidence highlight the importance of natural killer (NK) cells in immune responses toward multiple myeloma (MM), and combination therapies able to enhance the activity of NK cells against MM are showing promise in treating this hematologic cancer. The epigenetic readers of acetylated histones bromodomain and extra-terminal (BET) proteins are critical regulators of gene expression. In cancer, they can upregulate transcription of key oncogenes such as cMYC, IRF4, and BCL-2. In addition, the activity of these proteins can regulate the expression of osteoclastogenic cytokines during cancer progression. Here, we investigated the effect of BET bromodomain protein inhibition, on the expression of NK cell-activating ligands in MM cells. Five MM cell lines [SKO-007(J3), U266, RPMI-8226, ARP-1, JJN3] and CD138 + MM cells isolated from MM patients were used to investigate the activity of BET bromodomain inhibitors (BETi) (JQ1 and I-BET151) and of the selective BRD4-degrader proteolysis targeting chimera (PROTAC) (ARV-825), on the expression and function of several NK cell-activating ligands (NKG2DLs and DNAM-1Ls), using flow cytometry, real-time PCR, transient transfections, and degranulation assays. Our results indicate that inhibition of BET proteins via small molecule inhibitors or their degradation via a hetero-bifunctional PROTAC probe can enhance the expression of MICA, a ligand of the NKG2D receptor, in human MM cell lines and primary malignant plasma cells, rendering myeloma cells more efficient to activate NK cell degranulation. Noteworthy, similar results were obtained using selective CBP/EP300 bromodomain inhibition. Mechanistically, we found that BETi

12. Plant growth retardation and conserved miRNAs are correlated to Hibiscus chlorotic ringspot virus infection.

Science.gov (United States)

Gao, Ruimin; Wan, Zi Yi; Wong, Sek-Man

2013-01-01

Virus infection may cause a multiplicity of symptoms in their host including discoloration, distortion and growth retardation. Hibiscus chlorotic ringspot virus (HCRSV) infection was studied using kenaf (Hibiscus cannabinus L.), a non-wood fiber-producing crop in this study. Infection by HCRSV reduced the fiber yield and concomitant economic value of kenaf. We investigated kenaf growth retardation and fluctuations of four selected miRNAs after HCRSV infection. Vegetative growth (including plant height, leaf size and root development) was severely retarded. From the transverse and radial sections of the mock and HCRSV-infected kenaf stem, the vascular bundles of HCRSV-infected plants were severely disrupted. In addition, four conserved plant developmental and defence related microRNAs (miRNAs) (miR165, miR167, miR168 and miR171) and their respective target genes phabulosa (PHB), auxin response factor 8 (ARF8), argonaute 1 (AGO1) and scarecrow-like protein 1 (SCL1) displayed variation in expression levels after HCRSV infection. Compared with the mock inoculated kenaf plants, miR171 and miR168 and their targets SCL1 and AGO1 showed greater fluctuations after HCRSV infection. As HCRSV upregulates plant SO transcript in kenaf and upregulated AGO1 in HCRSV-infected plants, the expression level of AGO1 transcript was further investigated under sulfite oxidase (SO) overexpression or silencing condition. Interestingly, the four selected miRNAs were also up- or down-regulated upon overexpression or silencing of SO. Plant growth retardation and fluctuation of four conserved miRNAs are correlated to HCRSV infection.

13. miR-326 targets antiapoptotic Bcl-xL and mediates apoptosis in human platelets.

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Shifang Yu

Full Text Available Platelets play crucial roles in hemostasis, thrombosis, wound healing, inflammation, angiogenesis, and tumor metastases. Because they are anucleated blood cells, platelets lack nuclear DNA, but they do contain mitochondrial DNA, which plays a key role in regulating apoptosis. Recent evidence has suggested that miRNAs are also involved in regulating gene expression and apoptosis in platelets. Our previous study showed that the expression of miR-326 increased visibly when apheresis platelets were stored in vitro. The antiapoptotic Bcl-2 family regulator Bcl-xL has been identified as a putative target of miR-326. In the present study, dual reporter luciferase assays were used to characterize the function of miR-326 in the regulation of the apoptosis of platelet cells. These assays demonstrated that miR-326 bound to the 3'-translated region of Bcl-xL. To directly assess the functional effects of miR-326 expression, levels of Bcl-xL and the apoptotic status of stored apheresis platelets were measured after transfection of miR-326 mimic or inhibitor. Results indicated that miR-326 inhibited Bcl-xL expression and induced apoptosis in stored platelets. Additionally, miR-326 inhibited Bcl-2 protein expression and enhanced Bak expression, possibly through an indirect mechanism, though there was no effect on the expression of Bax. The effect of miR-326 appeared to be limited to apoptosis, with no significant effect on platelet activation. These results provide new insight into the molecular mechanisms affecting differential platelet gene regulation, which may increase understanding of the role of platelet apoptosis in multiple diseases.

14. MiR-34a regulates the invasive capacity of canine osteosarcoma cell lines.

Directory of Open Access Journals (Sweden)

Cecilia M Lopez

Full Text Available Osteosarcoma (OSA is the most common bone tumor in children and dogs; however, no substantial improvement in clinical outcome has occurred in either species over the past 30 years. MicroRNAs (miRNAs are small non-coding RNAs that regulate gene expression and play a fundamental role in cancer. The purpose of this study was to investigate the potential contribution of miR-34a loss to the biology of canine OSA, a well-established spontaneous model of the human disease.RT-qPCR demonstrated that miR-34a expression levels were significantly reduced in primary canine OSA tumors and canine OSA cell lines as compared to normal canine osteoblasts. In canine OSA cell lines stably transduced with empty vector or pre-miR-34a lentiviral constructs, overexpression of miR-34a inhibited cellular invasion and migration but had no effect on cell proliferation or cell cycle distribution. Transcriptional profiling of canine OSA8 cells possessing enforced miR-34a expression demonstrated dysregulation of numerous genes, including significant down-regulation of multiple putative targets of miR-34a. Moreover, gene ontology analysis of down-regulated miR-34a target genes showed enrichment of several biological processes related to cell invasion and motility. Lastly, we validated changes in miR-34a putative target gene expression, including decreased expression of KLF4, SEM3A, and VEGFA transcripts in canine OSA cells overexpressing miR-34a and identified KLF4 and VEGFA as direct target genes of miR-34a. Concordant with these data, primary canine OSA tumor tissues demonstrated increased expression levels of putative miR-34a target genes.These data demonstrate that miR-34a contributes to invasion and migration in canine OSA cells and suggest that loss of miR-34a may promote a pattern of gene expression contributing to the metastatic phenotype in canine OSA.

15. MiR-34a regulates the invasive capacity of canine osteosarcoma cell lines.

Science.gov (United States)

Lopez, Cecilia M; Yu, Peter Y; Zhang, Xiaoli; Yilmaz, Ayse Selen; London, Cheryl A; Fenger, Joelle M

2018-01-01

Osteosarcoma (OSA) is the most common bone tumor in children and dogs; however, no substantial improvement in clinical outcome has occurred in either species over the past 30 years. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and play a fundamental role in cancer. The purpose of this study was to investigate the potential contribution of miR-34a loss to the biology of canine OSA, a well-established spontaneous model of the human disease. RT-qPCR demonstrated that miR-34a expression levels were significantly reduced in primary canine OSA tumors and canine OSA cell lines as compared to normal canine osteoblasts. In canine OSA cell lines stably transduced with empty vector or pre-miR-34a lentiviral constructs, overexpression of miR-34a inhibited cellular invasion and migration but had no effect on cell proliferation or cell cycle distribution. Transcriptional profiling of canine OSA8 cells possessing enforced miR-34a expression demonstrated dysregulation of numerous genes, including significant down-regulation of multiple putative targets of miR-34a. Moreover, gene ontology analysis of down-regulated miR-34a target genes showed enrichment of several biological processes related to cell invasion and motility. Lastly, we validated changes in miR-34a putative target gene expression, including decreased expression of KLF4, SEM3A, and VEGFA transcripts in canine OSA cells overexpressing miR-34a and identified KLF4 and VEGFA as direct target genes of miR-34a. Concordant with these data, primary canine OSA tumor tissues demonstrated increased expression levels of putative miR-34a target genes. These data demonstrate that miR-34a contributes to invasion and migration in canine OSA cells and suggest that loss of miR-34a may promote a pattern of gene expression contributing to the metastatic phenotype in canine OSA.

16. Imputation of single nucleotide polymorhpism genotypes of Hereford cattle: reference panel size, family relationship and population structure

Science.gov (United States)

The objective of this study is to investigate single nucleotide polymorphism (SNP) genotypes imputation of Hereford cattle. Purebred Herefords were from two sources, Line 1 Hereford (N=240) and representatives of Industry Herefords (N=311). Using different reference panels of 62 and 494 males with 1...

17. 21 CFR 1404.630 - May the Office of National Drug Control Policy impute conduct of one person to another?

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 9 2010-04-01 2010-04-01 false May the Office of National Drug Control Policy impute conduct of one person to another? 1404.630 Section 1404.630 Food and Drugs OFFICE OF NATIONAL DRUG CONTROL POLICY GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles Relating to Suspension and Debarment Actions § 1404.630...

18. The Use of Imputed Sibling Genotypes in Sibship-Based Association Analysis: On Modeling Alternatives, Power and Model Misspecification

NARCIS (Netherlands)

Minica, C.C.; Dolan, C.V.; Willemsen, G.; Vink, J.M.; Boomsma, D.I.

2013-01-01

When phenotypic, but no genotypic data are available for relatives of participants in genetic association studies, previous research has shown that family-based imputed genotypes can boost the statistical power when included in such studies. Here, using simulations, we compared the performance of

19. Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods

Science.gov (United States)

Kenneth B. Pierce; Janet L. Ohmann; Michael C. Wimberly; Matthew J. Gregory; Jeremy S. Fried

2009-01-01

Land managers need consistent information about the geographic distribution of wildland fuels and forest structure over large areas to evaluate fire risk and plan fuel treatments. We compared spatial predictions for 12 fuel and forest structure variables across three regions in the western United States using gradient nearest neighbor (GNN) imputation, linear models (...

20. Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

DEFF Research Database (Denmark)

Huang, Jie; Howie, Bryan; Mccarthy, Shane

2015-01-01

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low de...

1. 29 CFR 1471.630 - May the Federal Mediation and Conciliation Service impute conduct of one person to another?

Science.gov (United States)

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false May the Federal Mediation and Conciliation Service impute...) FEDERAL MEDIATION AND CONCILIATION SERVICE GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles Relating to Suspension and Debarment Actions § 1471.630 May the Federal Mediation and...

2. Age at menopause: imputing age at menopause for women with a hysterectomy with application to risk of postmenopausal breast cancer

Science.gov (United States)

Rosner, Bernard; Colditz, Graham A.

2011-01-01

Purpose Age at menopause, a major marker in the reproductive life, may bias results for evaluation of breast cancer risk after menopause. Methods We follow 38,948 premenopausal women in 1980 and identify 2,586 who reported hysterectomy without bilateral oophorectomy, and 31,626 who reported natural menopause during 22 years of follow-up. We evaluate risk factors for natural menopause, impute age at natural menopause for women reporting hysterectomy without bilateral oophorectomy and estimate the hazard of reaching natural menopause in the next 2 years. We apply this imputed age at menopause to both increase sample size and to evaluate the relation between postmenopausal exposures and risk of breast cancer. Results Age, cigarette smoking, age at menarche, pregnancy history, body mass index, history of benign breast disease, and history of breast cancer were each significantly related to age at natural menopause; duration of oral contraceptive use and family history of breast cancer were not. The imputation increased sample size substantially and although some risk factors after menopause were weaker in the expanded model (height, and alcohol use), use of hormone therapy is less biased. Conclusions Imputing age at menopause increases sample size, broadens generalizability making it applicable to women with hysterectomy, and reduces bias. PMID:21441037

3. Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

NARCIS (Netherlands)

J. Huang (Jie); B. Howie (Bryan); S. McCarthy (Shane); Y. Memari (Yasin); K. Walter (Klaudia); J.L. Min (Josine L.); P. Danecek (Petr); G. Malerba (Giovanni); E. Trabetti (Elisabetta); H.-F. Zheng (Hou-Feng); G. Gambaro (Giovanni); J.B. Richards (Brent); R. Durbin (Richard); N.J. Timpson (Nicholas); J. Marchini (Jonathan); N. Soranzo (Nicole); S.H. Al Turki (Saeed); A. Amuzu (Antoinette); C. Anderson (Carl); R. Anney (Richard); D. Antony (Dinu); M.S. Artigas; M. Ayub (Muhammad); S. Bala (Senduran); J.C. Barrett (Jeffrey); I.E. Barroso (Inês); P.L. Beales (Philip); M. Benn (Marianne); J. Bentham (Jamie); S. Bhattacharya (Shoumo); E. Birney (Ewan); D.H.R. Blackwood (Douglas); M. Bobrow (Martin); E. Bochukova (Elena); P.F. Bolton (Patrick F.); R. Bounds (Rebecca); C. Boustred (Chris); G. Breen (Gerome); M. Calissano (Mattia); K. Carss (Keren); J.P. Casas (Juan Pablo); J.C. Chambers (John C.); R. Charlton (Ruth); K. Chatterjee (Krishna); L. Chen (Lu); A. Ciampi (Antonio); S. Cirak (Sebahattin); P. Clapham (Peter); G. Clement (Gail); G. Coates (Guy); M. Cocca (Massimiliano); D.A. Collier (David); C. Cosgrove (Catherine); T. Cox (Tony); N.J. Craddock (Nick); L. Crooks (Lucy); S. Curran (Sarah); D. Curtis (David); A. Daly (Allan); I.N.M. Day (Ian N.M.); A.G. Day-Williams (Aaron); G.V. Dedoussis (George); T. Down (Thomas); Y. Du (Yuanping); C.M. van Duijn (Cornelia); I. Dunham (Ian); T. Edkins (Ted); R. Ekong (Rosemary); P. Ellis (Peter); D.M. Evans (David); I.S. Farooqi (I. Sadaf); D.R. Fitzpatrick (David R.); P. Flicek (Paul); J. Floyd (James); A.R. Foley (A. Reghan); C.S. Franklin (Christopher S.); M. Futema (Marta); L. Gallagher (Louise); P. Gasparini (Paolo); T.R. Gaunt (Tom); M. Geihs (Matthias); D. Geschwind (Daniel); C.M.T. Greenwood (Celia); H. Griffin (Heather); D. Grozeva (Detelina); X. Guo (Xiaosen); X. Guo (Xueqin); H. Gurling (Hugh); D. Hart (Deborah); A.E. Hendricks (Audrey E.); P.A. Holmans (Peter A.); L. Huang (Liren); T. Hubbard (Tim); S.E. Humphries (Steve E.); M.E. Hurles (Matthew); P.G. Hysi (Pirro); V. Iotchkova (Valentina); A. Isaacs (Aaron); D.K. Jackson (David K.); Y. Jamshidi (Yalda); J. Johnson (Jon); C. Joyce (Chris); K.J. Karczewski (Konrad); J. Kaye (Jane); T. Keane (Thomas); J.P. Kemp (John); K. Kennedy (Karen); A. Kent (Alastair); J. Keogh (Julia); F. Khawaja (Farrah); M.E. Kleber (Marcus); M. Van Kogelenberg (Margriet); A. Kolb-Kokocinski (Anja); J.S. Kooner (Jaspal S.); G. Lachance (Genevieve); C. Langenberg (Claudia); C. Langford (Cordelia); D. Lawson (Daniel); I. Lee (Irene); E.M. van Leeuwen (Elisa); M. Lek (Monkol); R. Li (Rui); Y. Li (Yingrui); J. Liang (Jieqin); H. Lin (Hong); R. Liu (Ryan); J. Lönnqvist (Jouko); L.R. Lopes (Luis R.); M.C. Lopes (Margarida); J. Luan; D.G. MacArthur (Daniel G.); M. Mangino (Massimo); G. Marenne (Gaëlle); W. März (Winfried); J. Maslen (John); A. Matchan (Angela); I. Mathieson (Iain); P. McGuffin (Peter); A.M. McIntosh (Andrew); A.G. McKechanie (Andrew G.); A. McQuillin (Andrew); S. Metrustry (Sarah); N. Migone (Nicola); H.M. Mitchison (Hannah M.); A. Moayyeri (Alireza); J. Morris (James); R. Morris (Richard); D. Muddyman (Dawn); F. Muntoni; B.G. Nordestgaard (Børge G.); K. Northstone (Kate); M.C. O'donovan (Michael); S. O'Rahilly (Stephen); A. Onoufriadis (Alexandros); K. Oualkacha (Karim); M.J. Owen (Michael J.); A. Palotie (Aarno); K. Panoutsopoulou (Kalliope); V. Parker (Victoria); J.R. Parr (Jeremy R.); L. Paternoster (Lavinia); T. Paunio (Tiina); F. Payne (Felicity); S.J. Payne (Stewart J.); J.R.B. Perry (John); O.P.H. Pietiläinen (Olli); V. Plagnol (Vincent); R.C. Pollitt (Rebecca C.); S. Povey (Sue); M.A. Quail (Michael A.); L. Quaye (Lydia); L. Raymond (Lucy); K. Rehnström (Karola); C.K. Ridout (Cheryl K.); S.M. Ring (Susan); G.R.S. Ritchie (Graham R.S.); N. Roberts (Nicola); R.L. Robinson (Rachel L.); D.B. Savage (David); P.J. Scambler (Peter); S. Schiffels (Stephan); M. Schmidts (Miriam); N. Schoenmakers (Nadia); R.H. Scott (Richard H.); R.A. Scott (Robert); R.K. Semple (Robert K.); E. Serra (Eva); S.I. Sharp (Sally I.); A.C. Shaw (Adam C.); H.A. Shihab (Hashem A.); S.-Y. Shin (So-Youn); D. Skuse (David); K.S. Small (Kerrin); C. Smee (Carol); G.D. Smith; L. Southam (Lorraine); O. Spasic-Boskovic (Olivera); T.D. Spector (Timothy); D. St. Clair (David); B. St Pourcain (Beate); J. Stalker (Jim); E. Stevens (Elizabeth); J. Sun (Jianping); G. Surdulescu (Gabriela); J. Suvisaari (Jaana); P. Syrris (Petros); I. Tachmazidou (Ioanna); R. Taylor (Rohan); J. Tian (Jing); M.D. Tobin (Martin); D. Toniolo (Daniela); M. Traglia (Michela); A. Tybjaerg-Hansen; A.M. Valdes; A.M. Vandersteen (Anthony M.); A. Varbo (Anette); P. Vijayarangakannan (Parthiban); P.M. Visscher (Peter); L.V. Wain (Louise); J.T. Walters (James); G. Wang (Guangbiao); J. Wang (Jun); Y. Wang (Yu); K. Ward (Kirsten); E. Wheeler (Eleanor); P.H. Whincup (Peter); T. Whyte (Tamieka); H.J. Williams (Hywel J.); K.A. Williamson (Kathleen); C. Wilson (Crispian); S.G. Wilson (Scott); K. Wong (Kim); C. Xu (Changjiang); J. Yang (Jian); G. Zaza (Gianluigi); E. Zeggini (Eleftheria); F. Zhang (Feng); P. Zhang (Pingbo); W. Zhang (Weihua)

2015-01-01

textabstractImputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced

4. Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

NARCIS (Netherlands)

van Leeuwen, E.M.; Karssen, L.C.; Deelen, J.; Isaacs, A.; Medina-Gomez, C.; Mbarek, H.; Kanterakis, A.; Trompet, S.; Postmus, I.; Verweij, N.; van Enckevort, D.; Huffman, J.E.; White, C.C.; Feitosa, M.F.; Bartz, T.M.; Manichaikul, A.; Joshi, P.K.; Peloso, G.M.; Deelen, P.; Dijk, F.; Willemsen, G.; de Geus, E.J.C.; Milaneschi, Y.; Penninx, B.W.J.H.; Francioli, L.C.; Menelaou, A.; Pulit, S.L.; Rivadeneira, F.; Hofman, A.; Oostra, B.A.; Franco, O.H.; Mateo Leach, I.; Beekman, M.; de Craen, A.J.; Uh, H.W.; Trochet, H.; Hocking, L.J.; Porteous, D.J.; Sattar, N.; Packard, C.J.; Buckley, B.M.; Brody, J.A.; Bis, J.C.; Rotter, J.I.; Mychaleckyj, J.C.; Campbell, H.; Duan, Q.; Lange, L.A.; Wilson, J.F.; Hayward, C.; Polasek, O.; Vitart, V.; Rudan, I.; Wright, A.F.; Rich, S.S.; Psaty, B.M.; Borecki, I.B.; Kearney, P.M.; Stott, D.J.; Cupples, L.A.; Jukema, J.W.; van der Harst, P.; Sijbrands, E.J.; Hottenga, J.J.; Uitterlinden, A.G.; Swertz, M.A.; van Ommen, G.J.B; Bakker, P.I.W.; Slagboom, P.E.; Boomsma, D.I.; Wijmenga, C.; van Duijn, C.M.

2015-01-01

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (∼35,000 samples) with the population-specific reference panel created

5. 31 CFR 19.630 - May the Department of the Treasury impute conduct of one person to another?

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false May the Department of the Treasury impute conduct of one person to another? 19.630 Section 19.630 Money and Finance: Treasury Office of the Secretary of the Treasury GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) General Principles...

6. Differential expression of miR-1, a putative tumor suppressing microRNA, in cancer resistant and cancer susceptible mice

Directory of Open Access Journals (Sweden)

Jessica L. Fleming

2013-04-01

Full Text Available Mus spretus mice are highly resistant to several types of cancer compared to Mus musculus mice. To determine whether differences in microRNA (miRNA expression account for some of the differences in observed skin cancer susceptibility between the strains, we performed miRNA expression profiling of skin RNA for over 300 miRNAs. Five miRNAs, miR-1, miR-124a-3, miR-133a, miR-134, miR-206, were differentially expressed by array and/or qPCR. miR-1 was previously shown to have tumor suppressing abilities in multiple tumor types. We found miR-1 expression to be lower in mouse cutaneous squamous cell carcinomas (cSCCs compared to normal skin. Based on the literature and our expression data, we performed detailed studies on predicted miR-1 targets and evaluated the effect of miR-1 expression on two murine cSCC cell lines, A5 and B9. Following transfection of miR-1, we found decreased mRNA expression of three validated miR-1 targets, Met, Twf1 and Ets1 and one novel target Bag4. Decreased expression of Ets1 was confirmed by Western analysis and by 3’ reporter luciferase assays containing wildtype and mutated Ets1 3’UTR. We evaluated the effect of miR-1 on multiple tumor phenotypes including apoptosis, proliferation, cell cycle and migration. In A5 cells, expression of miR-1 led to decreased proliferation compared to a control miR. miR-1 expression also led to increased apoptosis at later time points (72 and 96 h and to a decrease in cells in S-phase. In summary, we identified five miRNAs with differential expression between cancer resistant and cancer susceptible mice and found that miR-1, a candidate tumor suppressor, has targets with defined roles in tumorigenesis.

7. MicroRNA expression profiles in chronic epilepsy rats and neuroprotection from seizures by targeting miR-344a

Directory of Open Access Journals (Sweden)

Liu XX

2017-07-01

Full Text Available Xixia Liu,1,2 Yuhan Liao,1 Xiuxiu Wang,1 Donghua Zou,1 Chun Luo,1 Chongdong Jian,1 Yuan Wu1 1Department of Neurology, First Affiliated Hospital of Guangxi Medical University, 2Department of Rehabilitation, People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning, China Abstract: MicroRNA (miRNA is believed to play a crucial role in the cause and treatment of epilepsy by controlling gene expression. However, it is still unclear how miRNA profiles change after multiple prolonged seizures and aggravation of brain injury in chronic epilepsy (CE. To investigate the role of miRNA in epilepsy, we utilized the CE rat models with pentylenetetrazol (PTZ and miRNA profiles in the hippocampus. miRNA profiles were characterized using miRNA microarray analysis and were compared with the rats in the sham group, which received 0.9% physiological saline treatment at the same dose. Four up-regulated miRNAs (miR-139–3p, -770–5p, -127–5p, -331–3p and 5 down-regulated miRNAs (miR-802–5p, -380–5p, -183–5p, -547–5p, -344a/-344a–5p were found in the CE rats (fold change >1.5, P<0.05. Three of the dysregulated miRNAs were validated by quantitative real-time polymerase chain reaction, which revealed an outcome consistent with the initial results of the miRNA microarray analyses. Then, miR-344a agomir was intracerebroventricularly injected and followed by PTZ induction of CE models to investigate the effect of miR-344a in chronic neocortical epileptogenesis. After miRNA-344a agomir and scramble treatment, results showed a restoration of seizure behavior and a reduction in neuron damage in the cortex in miRNA-334a agomir treated rats. These data suggest that miRNA-344a might have a small modulatory effect on seizure-induced apoptosis signaling pathways in the cortex. Keywords: microRNA, chronic epilepsy, miR-344a, epigenetics, apoptosis

8. Multiple Intelligences or Multiply Misleading: The Critic's View of the Multiple Intelligences Theory

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Peariso, Jamon F.

2008-01-01

Howard Gardner's Multiple Intelligences (MI) theory has been widely accepted in the field of education for the past two decades. Most educators have been subjugated to the MI theory and to the many issues that its implementation in the classroom brings. This is often done without ever looking at or being presented the critic's view or research on…

9. Perspectives on Sámi historiography

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Lars Ivar Hansen

2017-09-01

Full Text Available The article focuses on Sámi history and historical methods. The main results and central aspects of Sámi history, in its relational context, are gone through. What effects and consequences — regarding both methodology and narrative styles — these aspects have had, and ought to have, for the processes of doing research on and writing Sámi history? The focus is on the politics of Sámi history and research. The issues, who is “allowed” to write Sámi history and the way Sámi research is demanded to stand in the service of different societal-cultural needs of the Sámi is dealt with. This expectation of applicability concerns Sámi history in general, and the more delimited efforts of presenting situated accounts of Sámi cultural practices, traditions and experience with relations to other folk groups. Finally, methodological considerations and recommendations of Sámi history are presented, in which a number of methodological competences and in-depth usage of numerous source categories are called for.

10. Impute DC link (IDCL) cell based power converters and control thereof

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Divan, Deepakraj M.; Prasai, Anish; Hernendez, Jorge; Moghe, Rohit; Iyer, Amrit; Kandula, Rajendra Prasad

2016-04-26

Power flow controllers based on Imputed DC Link (IDCL) cells are provided. The IDCL cell is a self-contained power electronic building block (PEBB). The IDCL cell may be stacked in series and parallel to achieve power flow control at higher voltage and current levels. Each IDCL cell may comprise a gate drive, a voltage sharing module, and a thermal management component in order to facilitate easy integration of the cell into a variety of applications. By providing direct AC conversion, the IDCL cell based AC/AC converters reduce device count, eliminate the use of electrolytic capacitors that have life and reliability issues, and improve system efficiency compared with similarly rated back-to-back inverter system.

11. Integrated analysis of miRNA and mRNA expression profiles in tilapia gonads at an early stage of sex differentiation.

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Tao, Wenjing; Sun, Lina; Shi, Hongjuan; Cheng, Yunying; Jiang, Dongneng; Fu, Beide; Conte, Matthew A; Gammerdinger, William J; Kocher, Thomas D; Wang, Deshou

2016-05-04

MicroRNAs (miRNAs) represent a second regulatory network that has important effects on gene expression and protein translation during biological process. However, the possible role of miRNAs in the early stages of fish sex differentiation is not well understood. In this study, we carried an integrated analysis of miRNA and mRNA expression profiles to explore their possibly regulatory patterns at the critical stage of sex differentiation in tilapia. We identified 279 pre-miRNA genes in tilapia genome, which were highly conserved in other fish species. Based on small RNA library sequencing, we identified 635 mature miRNAs in tilapia gonads, in which 62 and 49 miRNAs showed higher expression in XX and XY gonads, respectively. The predicted targets of these sex-biased miRNAs (e.g., miR-9, miR-21, miR-30a, miR-96, miR-200b, miR-212 and miR-7977) included genes encoding key enzymes in steroidogenic pathways (Cyp11a1, Hsd3b, Cyp19a1a, Hsd11b) and key molecules involved in vertebrate sex differentiation (Foxl2, Amh, Star1, Sf1, Dmrt1, and Gsdf). These genes also showed sex-biased expression in tilapia gonads at 5 dah. Some miRNAs (e.g., miR-96 and miR-737) targeted multiple genes involved in steroid synthesis, suggesting a complex miRNA regulatory network during early sex differentiation in this fish. The sequence and expression patterns of most miRNAs in tilapia are conserved in fishes, indicating the basic functions of vertebrate miRNAs might share a common evolutionary origin. This comprehensive analysis of miRNA and mRNA at the early stage of molecular sex differentiation in tilapia XX and XY gonads lead to the discovery of differentially expressed miRNAs and their putative targets, which will facilitate studies of the regulatory network of molecular sex determination and differentiation in fishes.

12. Functional miRNAs in breast cancer drug resistance

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Hu WZ

2018-03-01

Full Text Available Weizi Hu,1–3,* Chunli Tan,1–3,* Yunjie He,4 Guangqin Zhang,2 Yong Xu,3,5 Jinhai Tang1 1Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, 2School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, 3Nanjing Medical University Affiliated Cancer Hospital, 4The First Clinical School of Nanjing Medical University, 5Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Nanjing Medical University, Nanjing, People’s Republic of China *These authors contributed equally to this work Abstract: Owing to improved early surveillance and advanced therapy strategies, the current death rate due to breast cancer has decreased; nevertheless, drug resistance and relapse remain obstacles on the path to successful systematic treatment. Multiple mechanisms responsible for drug resistance have been elucidated, and miRNAs seem to play a major part in almost every aspect of cancer progression, including tumorigenesis, metastasis, and drug resistance. In recent years, exosomes have emerged as novel modes of intercellular signaling vehicles, initiating cell–cell communication through their fusion with target cell membranes, delivering functional molecules including miRNAs and proteins. This review particularly focuses on enumerating functional miRNAs involved in breast cancer drug resistance as well as their targets and related mechanisms. Subsequently, we discuss the prospects and challenges of miRNA function in drug resistance and highlight valuable approaches for the investigation of the role of exosomal miRNAs in breast cancer progression and drug resistance. Keywords: microRNA, exosome, breast cancer, drug resistance

13. miRiadne: a web tool for consistent integration of miRNA nomenclature.

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Bonnal, Raoul J P; Rossi, Riccardo L; Carpi, Donatella; Ranzani, Valeria; Abrignani, Sergio; Pagani, Massimiliano

2015-07-01

14. Missing in space: an evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes.

Science.gov (United States)

Baker, Jannah; White, Nicole; Mengersen, Kerrie

2014-11-20

Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.

15. ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing

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Kamatani Naoyuki

2011-05-01

Full Text Available Abstract Background Use of missing genotype imputations and haplotype reconstructions are valuable in genome-wide association studies (GWASs. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and used for GWASs. Since millions of single nucleotide polymorphisms need to be imputed in a GWAS, faster methods for genotype imputation and haplotype reconstruction are required. Results We developed a program package for parallel computation of genotype imputation and haplotype reconstruction. Our program package, ParaHaplo 3.0, is intended for use in workstation clusters using the Intel Message Passing Interface. We compared the performance of ParaHaplo 3.0 on the Japanese in Tokyo, Japan and Han Chinese in Beijing, and Chinese in the HapMap dataset. A parallel version of ParaHaplo 3.0 can conduct genotype imputation 20 times faster than a non-parallel version of ParaHaplo. Conclusions ParaHaplo 3.0 is an invaluable tool for conducting haplotype-based GWASs. The need for faster genotype imputation and haplotype reconstruction using parallel computing will become increasingly important as the data sizes of such projects continue to increase. ParaHaplo executable binaries and program sources are available at http://en.sourceforge.jp/projects/parallelgwas/releases/.

16. Advances in Roles of miR-132 in the Nervous System

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Yun Qian

2017-10-01

Full Text Available miR-132 is an endogenous small RNA and controls post-transcriptional regulation of gene expression via controlled degradation of mRNA or transcription inhibition. In the nervous system, miR-132 is significant for regulating neuronal differentiation, maturation and functioning, and widely participates in axon growth, neural migration, and plasticity. The miR-132 is affected by factors like mRNA expression, functional redundancy, and signaling cascades. It targets multiple downstream molecules to influence physiological and pathological neuronal activities. MiR-132 can influence the pathogenesis of many diseases, especially in the nervous system. The dysregulation of miR-132 results in the occurrence and exacerbation of neural developmental, degenerative diseases, like Alzheimer’s disease, Parkinson’s disease and epilepsy, neural infection and psychiatric disorders including disturbance of consciousness, cognition and memory, depression and schizophrenia. Regulation of miR-132 expression relieves symptoms, alleviates severity and finally effects a cure. This review aims to discuss the clinical potentials of miR-132 in the nervous system.

17. Selective inhibition of miR-92 in hippocampal neurons alters contextual fear memory.

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Vetere, Gisella; Barbato, Christian; Pezzola, Silvia; Frisone, Paola; Aceti, Massimiliano; Ciotti, MariaTeresa; Cogoni, Carlo; Ammassari-Teule, Martine; Ruberti, Francesca

2014-12-01

Post-transcriptional gene regulation mediated by microRNAs (miRNAs) is implicated in memory formation; however, the function of miR-92 in this regulation is uncharacterized. The present study shows that training mice in contextual fear conditioning produces a transient increase in miR-92 levels in the hippocampus and decreases several miR-92 gene targets, including: (i) the neuronal Cl(-) extruding K(+) Cl(-) co-transporter 2 (KCC2) protein; (ii) the cytoplasmic polyadenylation protein (CPEB3), an RNA-binding protein regulator of protein synthesis in neurons; and (iii) the transcription factor myocyte enhancer factor 2D (MEF2D), one of the MEF2 genes which negatively regulates memory-induced structural plasticity. Selective inhibition of endogenous miR-92 in CA1 hippocampal neurons, by a sponge lentiviral vector expressing multiple sequences imperfectly complementary to mature miR-92 under the control of the neuronal specific synapsin promoter, leads to up-regulation of KCC2, CPEB3 and MEF2D, impairs contextual fear conditioning, and prevents a memory-induced increase in the spine density. Taken together, the results indicate that neuronal-expressed miR-92 is an endogenous fine regulator of contextual fear memory in mice. © 2014 Wiley Periodicals, Inc.

18. Neurotrophin-3 mRNA a putative target of miR21 following status epilepticus.

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Risbud, Rashmi M; Lee, Carolyn; Porter, Brenda E

2011-11-18

Status epilepticus induces a cascade of protein expression changes contributing to the subsequent development of epilepsy. By identifying the cascade of molecular changes that contribute to the development of epilepsy we hope to be able to design therapeutics for preventing epilepsy. MicroRNAs influence gene expression by altering mRNA stability and/or translation and have been implicated in the pathology of multiple diseases. MiR21 and its co-transcript miR21, microRNAs produced from either the 5' or 3' ends of the same precursor RNA strand, are increased in the hippocampus following status epilepticus. We have identified a miR21 binding site, in the 3' UTR of neurotrophin-3 that inhibits translation. Neurotrophin-3 mRNA levels decrease in the hippocampus following SE concurrent with the increase in miR21. MiR21 levels in cultured hippocampal neurons inversely correlate with neurotrophin-3 mRNA levels. Treatment of hippocampal neuronal cultures with excess K(+)Cl(-), a depolarizing agent mimicking the episode of status epilepticus, also results in an increase in miR21 and a decrease in neurotrophin-3 mRNA. MiR21 is a candidate for regulating neurotrophin-3 signaling in the hippocampus following status epilepticus. Copyright Â© 2011 Elsevier B.V. All rights reserved.

19. Synergic Functions of miRNAs Determine Neuronal Fate of Adult Neural Stem Cells

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Meritxell Pons-Espinal

2017-04-01

Full Text Available Summary: Adult neurogenesis requires the precise control of neuronal versus astrocyte lineage determination in neural stem cells. While microRNAs (miRNAs are critically involved in this step during development, their actions in adult hippocampal neural stem cells (aNSCs has been unclear. As entry point to address that question we chose DICER, an endoribonuclease essential for miRNA biogenesis and other RNAi-related processes. By specific ablation of Dicer in aNSCs in vivo and in vitro, we demonstrate that miRNAs are required for the generation of new neurons, but not astrocytes, in the adult murine hippocampus. Moreover, we identify 11 miRNAs, of which 9 have not been previously characterized in neurogenesis, that determine neurogenic lineage fate choice of aNSCs at the expense of astrogliogenesis. Finally, we propose that the 11 miRNAs sustain adult hippocampal neurogenesis through synergistic modulation of 26 putative targets from different pathways. : In this article, the authors demonstrate that Dicer-dependent miRNAs are required for the generation of new neurons, but not astrocytes, in the adult hippocampus in vivo and in vitro. The authors identify a new set of 11 miRNAs that synergistically converge on multiple targets in different pathways to sustain neurogenic lineage fate commitment in aNSCs. Keywords: mouse, hippocampus, neural stem cells, fate choice, adult neurogenesis, astrogliogenesis, DICER, microRNAs, synergy

20. Comprehensive analysis of miRNAs expression profiles revealed potential key miRNA/mRNAs regulating colorectal cancer stem cell self-renewal.

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Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-05-20

Self-renewal is essential for the malignant biological behaviors of colorectal cancer stem cells. While the self-renewal molecular mechanisms of colorectal cancer stem cells are not yet fully understood. Recently, miRNAs are reported to be relevant to the self-renewal ability of cancer stem cells. In this study, we first isolated colorectal cancer stem cell from colorectal cancer cell line HCT-116 by 1% low serum culture. Then we conducted a comprehensive analysis based on the miRNAs profiles data of both colorectal cancer stem cells and normal cultured colorectal cancer cells. Pathway analysis revealed multiple pathways including Jak-STAT, TGF-beta, PI3K-Akt and MAPK signaling pathway that are correlated to colorectal cancer. Further, we constructed a miRNA-mRNA network, based on which, several miRNA/mRNA pairs were ranked according to their impact index to the self-renewal of colorectal cancer stem cells. Further biological experiment showed that up-regulation of miR-92a-3p led to cell cycle arrest and reduced colony formation. This work provides clues to find the new potential biomarkers for colorectal cancer stem cell diagnosis and select effective miRNAs for targeted therapy. Copyright © 2018 Elsevier B.V. All rights reserved.

1. miR-19, a component of the oncogenic miR-17∼92 cluster, targets the DNA-end resection factor CtIP

DEFF Research Database (Denmark)

Hühn, D; Kousholt, A N; Sørensen, Claus Storgaard

2014-01-01

MicroRNA-19 (miR-19) was recently identified as the key oncogenic component of the polycistronic miR-17∼92 cluster, also known as oncomiR-1, which is frequently upregulated or amplified in multiple tumor types. However, the gene targets and the pathways underlying the tumor-promoting activity of mi......R-19 still remain largely elusive. CtIP/RBBP8 promotes DNA-end resection, a critical step in the repair of DNA double-strand breaks (DSBs) by homologous recombination (HR), and is considered to function as a tumor suppressor. In this study, we show that miR-19 downregulates CtIP expression by binding...... to two highly conserved sequences located in the 3'-untranslated region of CtIP mRNA. We further demonstrate that CtIP expression is repressed by miR-19 during continuous genotoxic stress in a p53-dependent manner. Finally, we report that miR-19 impairs CtIP-mediated DNA-end resection, which results...

2. The miRNome of bipolar disorder.

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Fries, Gabriel R; Carvalho, Andre F; Quevedo, Joao

2018-06-01

Epigenetic mechanisms have been suggested to play a key role in the pathophysiology of bipolar disorder (BD), among which microRNAs (miRNAs) may be of particular significance according to recent studies. We aimed to summarize miRNA studies in BD to identify consistent findings, limitations, and future directions of this emerging field. We performed a comprehensive search on PUBMED and Medline for studies investigating an association between BD and miRNAs. The included studies report miRNA alterations in postmortem brain tissues and in the periphery, cell culture and preclinical findings, genetic associations, and the effects of medications. Several studies report changes in miRNA expression levels in postmortem brain and in the periphery of patients, although most of the results so far have not been replicated and are not concordant between different populations. Genetic studies also suggest that miRNA genes are located within susceptibility loci of BD, and also a putative role of miRNAs in modulating genes previously shown to confer risk of BD. We did not perform a systematic review of the literature, and miRNAs represent only one facet of the plethora of epigenetic mechanisms that might be involved in BD's pathophysiology. miRNA findings in BD significantly vary between studies, but are consistent to suggest a key role for these molecules in BD's pathophysiology and treatment, particularly miR-34a and miR-137. Accordingly, miRNA might represent important biomarkers of illness to be used in the clinical settings, and potentially also for the development of novel therapeutics for BD in the near future. Copyright © 2017 Elsevier B.V. All rights reserved.

3. Silencing of Stress-Regulated miRNAs in Plants by Short Tandem Target Mimic (STTM) Approach.

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Teotia, Sachin; Tang, Guiliang

2017-01-01

In plants, microRNAs (miRNAs) regulate more than hundred target genes comprising largely transcription factors that control growth and development as well as stress responses. However, the exact functions of miRNA families could not be deciphered because each miRNA family has multiple loci in the genome, thus are functionally redundant. Therefore, an ideal approach to study the function of a miRNA family is to silence the expression of all members simultaneously, which is a daunting task. However, this can be partly overcome by Target Mimic (TM) approach that can knockdown an entire miRNA family. STTM is a modification of TM approach and complements it. STTMs have been successfully used in monocots and dicots to block miRNA functions. miR159 has been shown to be differentially regulated by various abiotic stresses including ABA in various plant species. Here, we describe in detail the protocol for designing STTM construct to block miR159 functions in Arabidopsis, with the potential to apply this technique on a number of other stress-regulated miRNAs in plants.

4. Alu-miRNA interactions modulate transcript isoform diversity in stress response and reveal signatures of positive selection

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Pandey, Rajesh; Bhattacharya, Aniket; Bhardwaj, Vivek; Jha, Vineet; Mandal, Amit K.; Mukerji, Mitali

2016-09-01

Primate-specific Alus harbor different regulatory features, including miRNA targets. In this study, we provide evidence for miRNA-mediated modulation of transcript isoform levels during heat-shock response through exaptation of Alu-miRNA sites in mature mRNA. We performed genome-wide expression profiling coupled with functional validation of miRNA target sites within exonized Alus, and analyzed conservation of these targets across primates. We observed that two miRNAs (miR-15a-3p and miR-302d-3p) elevated in stress response, target RAD1, GTSE1, NR2C1, FKBP9 and UBE2I exclusively within Alu. These genes map onto the p53 regulatory network. Ectopic overexpression of miR-15a-3p downregulates GTSE1 and RAD1 at the protein level and enhances cell survival. This Alu-mediated fine-tuning seems to be unique to humans as evident from the absence of orthologous sites in other primate lineages. We further analyzed signatures of selection on Alu-miRNA targets in the genome, using 1000 Genomes Phase-I data. We found that 198 out of 3177 Alu-exonized genes exhibit signatures of selection within Alu-miRNA sites, with 60 of them containing SNPs supported by multiple evidences (global-FST > 0.3, pair-wise-FST > 0.5, Fay-Wu’s H  2.0, high ΔDAF) and implicated in p53 network. We propose that by affecting multiple genes, Alu-miRNA interactions have the potential to facilitate population-level adaptations in response to environmental challenges.

5. Shrimp miR-12 Suppresses White Spot Syndrome Virus Infection by Synchronously Triggering Antiviral Phagocytosis and Apoptosis Pathways

Science.gov (United States)

Shu, Le; Zhang, Xiaobo

2017-01-01

Growing evidence has indicated that the innate immune system can be regulated by microRNAs (miRNAs). However, the mechanism underlying miRNA-mediated simultaneous activation of multiple immune pathways remains unknown. To address this issue, the role of host miR-12 in shrimp (Marsupenaeus japonicus) antiviral immune responses was characterized in the present study. The results indicated that miR-12 participated in virus infection, host phagocytosis, and apoptosis in defense against white spot syndrome virus invasion. miR-12 could simultaneously trigger phagocytosis, apoptosis, and antiviral immunity through the synchronous downregulation of the expression of shrimp genes [PTEN (phosphatase and tensin homolog) and BI-1(transmembrane BAX inhibitor motif containing 6)] and the viral gene (wsv024). Further analysis showed that miR-12 could synchronously mediate the 5′–3′ exonucleolytic degradation of its target mRNAs, and this degradation terminated in the vicinity of the 3′ untranslated region sequence complementary to the seed sequence of miR-12. Therefore, the present study showed novel aspects of the miRNA-mediated simultaneous regulation of multiple immune pathways. PMID:28824612

6. Turning 21: Induction of miR-21 as a key switch in the inflammatory response

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Frederick J Sheedy

2015-01-01

Full Text Available miR-21 is one of the most highly expressed members of the small non-coding microRNA family in many mammalian cell types. Its expression is further enhanced in many diseased states including solid tumors, cardiac injury and inflamed tissue. Whilst the induction of miR-21 by inflammatory stimuli cells has been well documented in both hematopoietic cells of the immune system (particularly monocytes/macrophages but also dendritic and T-cells and non-hematopoietic tumorigenic cells, the exact functional outcome of this elevated miR-21 is less obvious. Recent studies have confirmed a key role for miR-21 in the resolution of inflammation and in negatively regulating the proinflammatory response induced by many of the same stimuli that trigger miR-21 induction itself. In particular, miR-21 has emerged as a key mediator of the anti-inflammatory response in macrophages. This suggests that miR-21 inhibition in leukocytes will promote inflammation and may enhance current therapies for defective immune responses such as cancer, mycobacterial vaccines or Th2-associated allergic inflammation. At the same time, miR-21 has been shown to promote inflammatory mediators in non-hematopoietic cells resulting in neoplastic transformation. This review will focus on functional studies of miR-21 during inflammation which are complicated by the numerous molecular targets and processes that have emerged as miR-21 sensitive. It may be that the exact functional outcome of miR-21 is determined by multiple features including the cell type affected, the inducing signal, the transcriptomic profile of the cell, which ultimately affect the availability and ability to engage different target mRNAs and bring about its unique responses. Reviewing this data may illustrate that RNA-based oligonucleotide therapies for different diseases based upon miR-21 may have to target the unique and operative miRNA:mRNA interactions functionally active disease.

7. About miRNAs, miRNA seeds, target genes and target pathways.

Science.gov (United States)

Kehl, Tim; Backes, Christina; Kern, Fabian; Fehlmann, Tobias; Ludwig, Nicole; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas

2017-12-05

miRNAs are typically repressing gene expression by binding to the 3' UTR, leading to degradation of the mRNA. This process is dominated by the eight-base seed region of the miRNA. Further, miRNAs are known not only to target genes but also to target significant parts of pathways. A logical line of thoughts is: miRNAs with similar (seed) sequence target similar sets of genes and thus similar sets of pathways. By calculating similarity scores for all 3.25 million pairs of 2,550 human miRNAs, we found that this pattern frequently holds, while we also observed exceptions. Respective results were obtained for both, predicted target genes as well as experimentally validated targets. We note that miRNAs target gene set similarity follows a bimodal distribution, pointing at a set of 282 miRNAs that seems to target genes with very high specificity. Further, we discuss miRNAs with different (seed) sequences that nonetheless regulate similar gene sets or pathways. Most intriguingly, we found miRNA pairs that regulate different gene sets but similar pathways such as miR-6886-5p and miR-3529-5p. These are jointly targeting different parts of the MAPK signaling cascade. The main goal of this study is to provide a general overview on the results, to highlight a selection of relevant results on miRNAs, miRNA seeds, target genes and target pathways and to raise awareness for artifacts in respective comparisons. The full set of information that allows to infer detailed results on each miRNA has been included in miRPathDB, the miRNA target pathway database (https://mpd.bioinf.uni-sb.de).

8. Shoot bending promotes flower bud formation by miRNA-mediated regulation in apple (Malus domestica Borkh.).

Science.gov (United States)

Xing, Libo; Zhang, Dong; Zhao, Caiping; Li, Youmei; Ma, Juanjuan; An, Na; Han, Mingyu

2016-02-01

Flower induction in apple (Malus domestica Borkh.) trees plays an important life cycle role, but young trees produce fewer and inferior quality flower buds. Therefore, shoot bending has become an important cultural practice, significantly promoting the capacity to develop more flower buds during the growing seasons. Additionally, microRNAs (miRNAs) play essential roles in plant growth, flower induction and stress responses. In this study, we identified miRNAs potentially involved in the regulation of bud growth, and flower induction and development, as well as in the response to shoot bending. Of the 195 miRNAs identified, 137 were novel miRNAs. The miRNA expression profiles revealed that the expression levels of 68 and 27 known miRNAs were down-regulated and up-regulated, respectively, in response to shoot bending, and that the 31 differentially expressed novel miRNAs between them formed five major clusters. Additionally, a complex regulatory network associated with auxin, cytokinin, abscisic acid (ABA) and gibberellic acid (GA) plays important roles in cell division, bud growth and flower induction, in which related miRNAs and targets mediated regulation. Among them, miR396, 160, 393, and their targets associated with AUX, miR159, 319, 164, and their targets associated with ABA and GA, and flowering-related miRNAs and genes, regulate bud growth and flower bud formation in response to shoot bending. Meanwhile, the flowering genes had significantly higher expression levels during shoot bending, suggesting that they are involved in this regulatory process. This study provides a framework for the future analysis of miRNAs associated with multiple hormones and their roles in the regulation of bud growth, and flower induction and formation in response to shoot bending in apple trees. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

9. miRNAs in human subcutaneous adipose tissue: Effects of weight loss induced by hypocaloric diet and exercise.

Science.gov (United States)

Kristensen, Malene M; Davidsen, Peter K; Vigelsø, Andreas; Hansen, Christina N; Jensen, Lars J; Jessen, Niels; Bruun, Jens M; Dela, Flemming; Helge, Jørn W

2017-03-01

Obesity is central in the development of insulin resistance. However, the underlying mechanisms still need elucidation. Dysregulated microRNAs (miRNAs; post-transcriptional regulators) in adipose tissue may present an important link. The miRNA expression in subcutaneous adipose tissue from 19 individuals with severe obesity (10 women and 9 men) before and after a 15-week weight loss intervention was studied using genome-wide microarray analysis. The microarray results were validated with RT-qPCR, and pathway enrichment analysis of in silico predicted targets was performed to elucidate the biological consequences of the miRNA dysregulation. Lastly, the messenger RNA (mRNA) and/or protein expression of multiple predicted targets as well as several proteins involved in lipolysis were investigated. The intervention led to upregulation of miR-29a-3p and miR-29a-5p and downregulation of miR-20b-5p. The mRNA and protein expression of predicted targets was not significantly affected by the intervention. However, negative correlations between miR-20b-5p and the protein levels of its predicted target, acyl-CoA synthetase long-chain family member 1, were observed. Several other miRNA-target relationships correlated negatively, indicating possible miRNA regulation, including miR-29a-3p and lipoprotein lipase mRNA levels. Proteins involved in lipolysis were not affected by the intervention. Weight loss influenced several miRNAs, some of which were negatively correlated with predicted targets. These dysregulated miRNAs may affect adipocytokine signaling and forkhead box protein O signaling. © 2017 The Obesity Society.

10. Differential expression of miRNAs in the serum of patients with high-risk oral lesions

International Nuclear Information System (INIS)

MacLellan, Sara Ann; Lawson, James; Baik, Jonathan; Guillaud, Martial; Poh, Catherine Fang-Yeu; Garnis, Cathie

2012-01-01

Oral cancer is one of the most commonly diagnosed cancers worldwide. Disease is often diagnosed at later stages, which is associated with a poor 5-year survival rate and a high rate of local recurrence. MicroRNAs (miRNAs), a group of small, noncoding RNAs, can be isolated from blood serum samples and have demonstrated utility as biomarkers in multiple cancer types. The aim of this study was to examine the expression profiles of circulating miRNAs in the serum of patients with high-risk oral lesions (HRLs; oral cancer or carcinoma in situ) and to explore their utility as potential oral cancer biomarkers. Global serum miRNA profiles were generated using quantitative PCR method from 1) patients diagnosed with HRLs and undergoing intent-to-cure surgical treatment (N = 30) and 2) a demographically matched, noncancer control group (N = 26). We next honed our list of serum miRNAs associated with disease by reducing the effects of interpatient variability; we compared serum miRNA profiles from samples taken both before and after tumor resections (N = 10). Based on these analyses, fifteen miRNAs were significantly upregulated and five were significantly downregulated based on presence of disease (minimum fold-change >2 in at least 50% of samples, P < 0.05, permutation). Five of these miRNAs (miR-16, let-7b, miR-338-3p, miR-223, and miR-29a) yielded an area under the ROC curve (AUC) >0.8, suggesting utility as noninvasive biomarkers for detection of oral cancer or high-grade lesions. Combining these serum miRNA profiles with other screening techniques could greatly improve the sensitivity in oral cancer detection

11. MiR-132 prohibits proliferation, invasion, migration, and metastasis in breast cancer by targeting HN1

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhan-Guo, E-mail: zhang_zhanguo@hotmail.com; Chen, Wei-Xun, E-mail: chenweixunclark@163.com; Wu, Yan-Hui, E-mail: wuyanhui84@126.com; Liang, Hui-Fang, E-mail: lianghuifang1997@126.com; Zhang, Bi-Xiang, E-mail: bixiangzhang@163.com

2014-11-07

Highlights: • MiR-132 is down-regulated in breast cancer tissues and cell lines. • MiR-132 directly regulates HN1 by binding its 3′ UTR. • MiR-132 shows regulatory role in proliferation, invasion, migration and metastasis. • HN1 is involved in miR-132-mediated cell behavior. • Aberrant HN1 is associated with worse overall survival of breast cancer patients. - Abstract: Accumulating evidence indicates that miRNAs play critical roles in tumorigenesis and cancer progression. This study aims to investigate the role and the underlying mechanism of miR-132 in breast cancer. Here, we report that miR-132 is significantly down-regulated in breast cancer tissues and cancer cell lines. Additional study identifies HN1 as a novel direct target of miR-132. MiR-132 down-regulates HN1 expression by binding to the 3′ UTR of HN1 transcript, thereby, suppressing multiple oncogenic traits such as cancer cell proliferation, invasion, migration and metastasis in vivo and in vitro. Overexpression of HN1 restores miR-132-suppressed malignancy. Importantly, higher HN1 expression is significantly associated with worse overall survival of breast cancer patients. Taken together, our data demonstrate a critical role of miR-132 in prohibiting cell proliferation, invasion, migration and metastasis in breast cancer through direct suppression of HN1, supporting the potential utility of miR-132 as a novel therapeutic strategy against breast cancer.

12. [SATLC- Initiative] Uses of SATL & multiple intelligences [MI] for ...

African Journals Online (AJOL)

So, we introduce this activity as an applicable outdoor model which displays innovations in teaching and learning and demonstrates one of the methods of surpassing the traditional indoor methods. It could be extended to other topics of organic chemistry or other branches of chemistry. [AJCE, 3(1), January 2013] ...

13. Evaluating geographic imputation approaches for zip code level data: an application to a study of pediatric diabetes

Directory of Open Access Journals (Sweden)

Puett Robin C

2009-10-01

Full Text Available Abstract Background There is increasing interest in the study of place effects on health, facilitated in part by geographic information systems. Incomplete or missing address information reduces geocoding success. Several geographic imputation methods have been suggested to overcome this limitation. Accuracy evaluation of these methods can be focused at the level of individuals and at higher group-levels (e.g., spatial distribution. Methods We evaluated the accuracy of eight geo-imputation methods for address allocation from ZIP codes to census tracts at the individual and group level. The spatial apportioning approaches underlying the imputation methods included four fixed (deterministic and four random (stochastic allocation methods using land area, total population, population under age 20, and race/ethnicity as weighting factors. Data included more than 2,000 geocoded cases of diabetes mellitus among youth aged 0-19 in four U.S. regions. The imputed distribution of cases across tracts was compared to the true distribution using a chi-squared statistic. Results At the individual level, population-weighted (total or under age 20 fixed allocation showed the greatest level of accuracy, with correct census tract assignments averaging 30.01% across all regions, followed by the race/ethnicity-weighted random method (23.83%. The true distribution of cases across census tracts was that 58.2% of tracts exhibited no cases, 26.2% had one case, 9.5% had two cases, and less than 3% had three or more. This distribution was best captured by random allocation methods, with no significant differences (p-value > 0.90. However, significant differences in distributions based on fixed allocation methods were found (p-value Conclusion Fixed imputation methods seemed to yield greatest accuracy at the individual level, suggesting use for studies on area-level environmental exposures. Fixed methods result in artificial clusters in single census tracts. For studies

14. Diagnostic potential of miR-126, miR-143, miR-145, and miR-652 in malignant pleural mesothelioma

DEFF Research Database (Denmark)

Andersen, Morten; Grauslund, Morten; Ravn, Jesper

2014-01-01

Malignant pleural mesothelioma (MPM) is difficult to distinguish from reactive mesothelial proliferations (RMPs). It is uncertain whether miRNAs are useful biomarkers for differentiating MPM from RMPs. Thus, we screened with a quantitative RT-PCR (RT-qPCR)-based platform the expression of 742 miR...

15. Miércoles al cine

OpenAIRE

2014-01-01

Se analiza un caso concreto de demanda ante una iniciativa empresarial: los miércoles al cine. Se analiza un caso concreto de demanda ante una iniciativa empresarial: los miércoles al cine. Fundamentos del Análisis Económico

16. Expression and Genetic Analysis of MicroRNAs Involved in Multiple Sclerosis

Directory of Open Access Journals (Sweden)

Daniela Galimberti

2013-02-01

Full Text Available Evidence underlines the importance of microRNAs (miRNAs in the pathogenesis of multiple sclerosis (MS. Based on the fact that miRNAs are present in human biological fluids, we previously showed that miR-223, miR-23a and miR-15b levels were downregulated in the sera of MS patients versus controls. Here, the expression levels of these candidate miRNAs were determined in peripheral blood mononuclear cells (PBMCs and the serum of MS patients, in addition to three genotyped single nucleotide polymorphisms (SNPs. Mapping in the genomic regions of miR-223, miR-23a and miR-15b genes, 399 cases and 420 controls were tested. Expression levels of miR-223 and miR-23a were altered in PBMCs from MS patients versus controls. Conversely, there were no differences in the expression levels of miR-15b. A significantly decreased genotypic frequency of miR-223 rs1044165 T/T genotype was observed in MS patients. Moreover, the allelic frequency of miR-23a rs3745453 C allele was significantly increased in patients versus controls. In contrast, there were no differences in the distribution of miR-15b SNP. In conclusion, our results suggest that miR-223 and miR-23a could play a role in the pathogenesis of MS. Moreover, miR-223 rs1044165 polymorphism likely acts as a protective factor, while miR-23a rs3745453 variant seems to act as a risk factor for MS.

17. Expression and Genetic Analysis of MicroRNAs Involved in Multiple Sclerosis.

Science.gov (United States)

Ridolfi, Elisa; Fenoglio, Chiara; Cantoni, Claudia; Calvi, Alberto; De Riz, Milena; Pietroboni, Anna; Villa, Chiara; Serpente, Maria; Bonsi, Rossana; Vercellino, Marco; Cavalla, Paola; Galimberti, Daniela; Scarpini, Elio

2013-02-25

Evidence underlines the importance of microRNAs (miRNAs) in the pathogenesis of multiple sclerosis (MS). Based on the fact that miRNAs are present in human biological fluids, we previously showed that miR-223, miR-23a and miR-15b levels were downregulated in the sera of MS patients versus controls. Here, the expression levels of these candidate miRNAs were determined in peripheral blood mononuclear cells (PBMCs) and the serum of MS patients, in addition to three genotyped single nucleotide polymorphisms (SNPs). Mapping in the genomic regions of miR-223, miR-23a and miR-15b genes, 399 cases and 420 controls were tested. Expression levels of miR-223 and miR-23a were altered in PBMCs from MS patients versus controls. Conversely, there were no differences in the expression levels of miR-15b. A significantly decreased genotypic frequency of miR-223 rs1044165 T/T genotype was observed in MS patients. Moreover, the allelic frequency of miR-23a rs3745453 C allele was significantly increased in patients versus controls. In contrast, there were no differences in the distribution of miR-15b SNP. In conclusion, our results suggest that miR-223 and miR-23a could play a role in the pathogenesis of MS. Moreover, miR-223 rs1044165 polymorphism likely acts as a protective factor, while miR-23a rs3745453 variant seems to act as a risk factor for MS.

18. miRNAFold: a web server for fast miRNA precursor prediction in genomes.

Science.gov (United States)

Tav, Christophe; Tempel, Sébastien; Poligny, Laurent; Tahi, Fariza

2016-07-08

Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

19. Nearest neighbor imputation using spatial-temporal correlations in wireless sensor networks.

Science.gov (United States)

Li, YuanYuan; Parker, Lynne E

2014-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network's performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a k d-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for k d-tree construction, and Euclidean distance for k d-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental

20. Estimating Classification Errors under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC)

NARCIS (Netherlands)

Boeschoten, Laura; Oberski, Daniel; De Waal, Ton

2017-01-01

Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible

1. EBV-encoded miRNAs target ATM-mediated response in nasopharyngeal carcinoma.

Science.gov (United States)

Lung, Raymond W-M; Hau, Pok-Man; Yu, Ken H-O; Yip, Kevin Y; Tong, Joanna H-M; Chak, Wing-Po; Chan, Anthony W-H; Lam, Ka-Hei; Lo, Angela Kwok-Fung; Tin, Edith K-Y; Chau, Shuk-Ling; Pang, Jesse C-S; Kwan, Johnny S-H; Busson, Pierre; Young, Lawrence S; Yap, Lee-Fah; Tsao, Sai-Wah; To, Ka-Fai; Lo, Kwok-Wai

2018-04-01

Nasopharyngeal carcinoma (NPC) is a highly invasive epithelial malignancy that is prevalent in southern China and Southeast Asia. It is consistently associated with latent Epstein-Barr virus (EBV) infection. In NPC, miR-BARTs, the EBV-encoded miRNAs derived from BamH1-A rightward transcripts, are abundantly expressed and contribute to cancer development by targeting various cellular and viral genes. In this study, we establish a comprehensive transcriptional profile of EBV-encoded miRNAs in a panel of NPC patient-derived xenografts and an EBV-positive NPC cell line by small RNA sequencing. Among the 40 miR-BARTs, predominant expression of 22 miRNAs was consistently detected in these tumors. Among the abundantly expressed EBV-miRNAs, BART5-5p, BART7-3p, BART9-3p, and BART14-3p could negatively regulate the expression of a key DNA double-strand break (DSB) repair gene, ataxia telangiectasia mutated (ATM), by binding to multiple sites on its 3'-UTR. Notably, the expression of these four miR-BARTs represented more than 10% of all EBV-encoded miRNAs in tumor cells, while downregulation of ATM expression was commonly detected in all of our tested sequenced samples. In addition, downregulation of ATM was also observed in primary NPC tissues in both qRT-PCR (16 NP and 45 NPC cases) and immunohistochemical staining (35 NP and 46 NPC cases) analysis. Modulation of ATM expression by BART5-5p, BART7-3p, BART9-3p, and BART14-3p was demonstrated in the transient transfection assays. These findings suggest that EBV uses miRNA machinery as a key mechanism to control the ATM signaling pathway in NPC cells. By suppressing these endogenous miR-BARTs in EBV-positive NPC cells, we further demonstrated the novel function of miR-BARTs in inhibiting Zta-induced lytic reactivation. These findings imply that the four viral miRNAs work co-operatively to modulate ATM activity in response to DNA damage and to maintain viral latency, contributing to the tumorigenesis of NPC. © 2017 The Authors

2. EBV‐encoded miRNAs target ATM‐mediated response in nasopharyngeal carcinoma

Science.gov (United States)

Lung, Raymond W‐M; Hau, Pok‐Man; Yu, Ken H‐O; Yip, Kevin Y; Tong, Joanna H‐M; Chak, Wing‐Po; Chan, Anthony W‐H; Lam, Ka‐Hei; Lo, Angela Kwok‐Fung; Tin, Edith K‐Y; Chau, Shuk‐Ling; Pang, Jesse C‐S; Kwan, Johnny S‐H; Busson, Pierre; Young, Lawrence S; Yap, Lee‐Fah; Tsao, Sai‐Wah

2018-01-01

Abstract Nasopharyngeal carcinoma (NPC) is a highly invasive epithelial malignancy that is prevalent in southern China and Southeast Asia. It is consistently associated with latent Epstein–Barr virus (EBV) infection. In NPC, miR‐BARTs, the EBV‐encoded miRNAs derived from BamH1‐A rightward transcripts, are abundantly expressed and contribute to cancer development by targeting various cellular and viral genes. In this study, we establish a comprehensive transcriptional profile of EBV‐encoded miRNAs in a panel of NPC patient‐derived xenografts and an EBV‐positive NPC cell line by small RNA sequencing. Among the 40 miR‐BARTs, predominant expression of 22 miRNAs was consistently detected in these tumors. Among the abundantly expressed EBV‐miRNAs, BART5‐5p, BART7‐3p, BART9‐3p, and BART14‐3p could negatively regulate the expression of a key DNA double‐strand break (DSB) repair gene, ataxia telangiectasia mutated (ATM), by binding to multiple sites on its 3'‐UTR. Notably, the expression of these four miR‐BARTs represented more than 10% of all EBV‐encoded miRNAs in tumor cells, while downregulation of ATM expression was commonly detected in all of our tested sequenced samples. In addition, downregulation of ATM was also observed in primary NPC tissues in both qRT‐PCR (16 NP and 45 NPC cases) and immunohistochemical staining (35 NP and 46 NPC cases) analysis. Modulation of ATM expression by BART5‐5p, BART7‐3p, BART9‐3p, and BART14‐3p was demonstrated in the transient transfection assays. These findings suggest that EBV uses miRNA machinery as a key mechanism to control the ATM signaling pathway in NPC cells. By suppressing these endogenous miR‐BARTs in EBV‐positive NPC cells, we further demonstrated the novel function of miR‐BARTs in inhibiting Zta‐induced lytic reactivation. These findings imply that the four viral miRNAs work co‐operatively to modulate ATM activity in response to DNA damage and to maintain viral latency

3. A multiplexed miRNA and transgene expression platform for simultaneous repression and expression of protein coding sequences.

Science.gov (United States)

Seyhan, Attila A

2016-01-01

Knockdown of single or multiple gene targets by RNA interference (RNAi) is necessary to overcome escape mutants or isoform redundancy. It is also necessary to use multiple RNAi reagents to knockdown multiple targets. It is also desirable to express a transgene or positive regulatory elements and inhibit a target gene in a coordinated fashion. This study reports a flexible multiplexed RNAi and transgene platform using endogenous intronic primary microRNAs (pri-miRNAs) as a scaffold located in the green fluorescent protein (GFP) as a model for any functional transgene. The multiplexed intronic miRNA - GFP transgene platform was designed to co-express multiple small RNAs within the polycistronic cluster from a Pol II promoter at more moderate levels to reduce potential vector toxicity. The native intronic miRNAs are co-transcribed with a precursor GFP mRNA as a single transcript and presumably cleaved out of the precursor-(pre) mRNA by the RNA splicing machinery, spliceosome. The spliced intron with miRNA hairpins will be further processed into mature miRNAs or small interfering RNAs (siRNAs) capable of triggering RNAi effects, while the ligated exons become a mature messenger RNA for the translation of the functional GFP protein. Data show that this approach led to robust RNAi-mediated silencing of multiple Renilla Luciferase (R-Luc)-tagged target genes and coordinated expression of functional GFP from a single transcript in transiently transfected HeLa cells. The results demonstrated that this design facilitates the coordinated expression of all mature miRNAs either as individual miRNAs or as multiple miRNAs and the associated protein. The data suggest that, it is possible to simultaneously deliver multiple negative (miRNA or shRNA) and positive (transgene) regulatory elements. Because many cellular processes require simultaneous repression and activation of downstream pathways, this approach offers a platform technology to achieve that dual manipulation efficiently

4. Mi oíslo

Directory of Open Access Journals (Sweden)

Mitja Skubic

2006-12-01

Full Text Available Hablando Sancho en su primer encuentro con don Quijote de su mujer Juana Gutiérrez, llamada en seguida Teresa Panza o simplemente Teresa, la nombra mi oíslo y repite lo mismo otras dos veces. Conviene tener presente que de su mujer Sancho habla siempre respetuosamente y con mucho cariño, con excepción de una conversación que llega a ser un litigio, II, 5. Allí, Sancho expresa su idea de cómo y con quién casar a la hija Sanchica y por fin impone su voluntad. Teresa se le opone vigorosamente y esto induce a Sancho, sobreexcitado, a formular una gradación sorprendente: mujer mía; mirad, Teresa; mujer; calla, boba; bestia y mujer de Barrabás; animalia; mentecata e ignorante.

5. Avoid Filling Swiss Cheese with Whipped Cream; Imputation Techniques and Evaluation Procedures for Cross-Country Time Series

OpenAIRE

Michael Weber; Michaela Denk

2011-01-01

International organizations collect data from national authorities to create multivariate cross-sectional time series for their analyses. As data from countries with not yet well-established statistical systems may be incomplete, the bridging of data gaps is a crucial challenge. This paper investigates data structures and missing data patterns in the cross-sectional time series framework, reviews missing value imputation techniques used for micro data in official statistics, and discusses the...

6. Defining, evaluating, and removing bias induced by linear imputation in longitudinal clinical trials with MNAR missing data.

Science.gov (United States)

Helms, Ronald W; Reece, Laura Helms; Helms, Russell W; Helms, Mary W

2011-03-01

Missing not at random (MNAR) post-dropout missing data from a longitudinal clinical trial result in the collection of "biased data," which leads to biased estimators and tests of corrupted hypotheses. In a full rank linear model analysis the model equation, E[Y] = Xβ, leads to the definition of the primary parameter β = (X'X)(-1)X'E[Y], and the definition of linear secondary parameters of the form θ = Lβ = L(X'X)(-1)X'E[Y], including, for example, a parameter representing a "treatment effect." These parameters depend explicitly on E[Y], which raises the questions: What is E[Y] when some elements of the incomplete random vector Y are not observed and MNAR, or when such a Y is "completed" via imputation? We develop a rigorous, readily interpretable definition of E[Y] in this context that leads directly to definitions of β, Bias(β) = E[β] - β, Bias(θ) = E[θ] - Lβ, and the extent of hypothesis corruption. These definitions provide a basis for evaluating, comparing, and removing biases induced by various linear imputation methods for MNAR incomplete data from longitudinal clinical trials. Linear imputation methods use earlier data from a subject to impute values for post-dropout missing values and include "Last Observation Carried Forward" (LOCF) and "Baseline Observation Carried Forward" (BOCF), among others. We illustrate the methods of evaluating, comparing, and removing biases and the effects of testing corresponding corrupted hypotheses via a hypothetical but very realistic longitudinal analgesic clinical trial.

7. Assessment of Consequences of Replacement of System of the Uniform Tax on Imputed Income Patent System of the Taxation

Directory of Open Access Journals (Sweden)

Galina A. Manokhina

2012-11-01

Full Text Available The article highlights the main questions concerning possible consequences of replacement of nowadays operating system in the form of a single tax in reference to imputed income with patent system of the taxation. The main advantages and drawbacks of new system of the taxation are shown, including the opinion that not the replacement of one special mode of the taxation with another is more effective, but the introduction of patent a taxation system as an auxilary system.

8. An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network

Directory of Open Access Journals (Sweden)

John A. KershawJr

2017-09-01

Full Text Available Background A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design.

9. Inhibition of miR-155 Protects Against LPS-induced Cardiac Dysfunction and Apoptosis in Mice

Directory of Open Access Journals (Sweden)

Hui Wang

2016-01-01

Full Text Available Sepsis-induced myocardial dysfunction represents a major cause of death in intensive care units. Dysregulated microRNAs (miR-155 has been implicated in multiple cardiovascular diseases and miR-155 can be induced by lipopolysaccharide (LPS. However, the role of miR-155 in LPS-induced cardiac dysfunction is unclear. Septic cardiac dysfunction in mice was induced by intraperitoneal injection of LPS (5 mg/kg and miR-155 was found to be significantly increased in heart challenged with LPS. Pharmacological inhibition of miR-155 using antagomiR improved cardiac function and suppressed cardiac apoptosis induced by LPS in mice as determined by echocardiography, terminal deoxynucleotidyl transferase nick-end labeling (TUNEL assay, and Western blot for Bax and Bcl-2, while overexpression of miR-155 using agomiR had inverse effects. Pea15a was identified as a target gene of miR-155, mediating its effects in controlling apoptosis of cardiomyocytes as evidenced by luciferase reporter assays, quantitative real time-polymerase chain reaction, Western blot, and TUNEL staining. Noteworthy, miR-155 was also found to be upregulated in the plasma of patients with septic cardiac dysfunction compared to sepsis patients without cardiac dysfunction, indicating a potential clinical relevance of miR-155. The receiver-operator characteristic curve indicated that plasma miR-155 might be a biomarker for sepsis patients developing cardiac dysfunction. Therefore, inhibition of miR-155 represents a novel therapy for septic myocardial dysfunction.

10. Inhibition of miR-142-5P ameliorates disease in mouse models of experimental colitis.

Directory of Open Access Journals (Sweden)

Nicolette W Duijvis

Full Text Available MicroRNAs (miRNAs are epigenetically involved in regulating gene expression. They may be of importance in the pathogenesis of inflammatory bowel disease (IBD. The aim of this study was to determine the role of miRNAs by their specific blocking in the CD4+CB45RBhi T-cell transfer model of chronic experimental colitis.Colitis caused by transfer of WT CD4+CD45RBhi T cells in severe combined immunodeficiency (SCID mice shares many features with human IBD. Colonic miRNA expression levels were measured at three time points in colitic mice, where a time-dependent upregulation of multiple miRNAs was seen. To inhibit these miRNAs, specific locked-nucleic-acid-modified (LNA oligonucleotides were administered in further experiments at the moment the mice demonstrated the first signs of colitis. As controls, PBS and a scrambled sequence of anti-miRNA were used. Genome-wide expression analyses were also performed in order to detect candidate target genes of miR-142-5p, of which inhibition resulted in most effective amelioration of colitis.Anti-miR-142-5p reduced colitis and related wasting disease when administered in the T-cell transfer model, reflected in reduced weight loss and a lower disease activity index (DAI. In further validation experiments we also observed a higher survival rate and less colonic histological inflammation in the antagomir-treated mice. Moreover, by genome-wide expression analyses, we found downstream activation of the anti-inflammatory IL10RA pathway, including three genes also found in the top-20 candidate target genes of miR-142-5p.In conclusion, CD4+CD45RBhi-transfer colitis induces miR-142-5p. Blocking miR-142-5p reduced colitis and prevented wasting disease, possibly by activation of the IL10RA pathway.

11. Altering β-cell number through stable alteration of miR-21 and miR-34a expression

DEFF Research Database (Denmark)

Backe, Marie Balslev; Novotny, Guy Wayne; Christensen, Dan Ploug

2014-01-01

RNAs, miR-21 and miR-34a, may be involved in mediating cytokine-induced β-cell dysfunction. Therefore, manipulation of miR-21 and miR-34a levels may potentially be beneficial to β cells. To study the effect of long-term alterations of miR-21 or miR-34a levels upon net β-cell number, we stably overexpressed...

12. RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning.

Directory of Open Access Journals (Sweden)

Ji-Sung Kim

2018-04-01

Full Text Available Anonymized electronic medical records are an increasingly popular source of research data. However, these datasets often lack race and ethnicity information. This creates problems for researchers modeling human disease, as race and ethnicity are powerful confounders for many health exposures and treatment outcomes; race and ethnicity are closely linked to population-specific genetic variation. We showed that deep neural networks generate more accurate estimates for missing racial and ethnic information than competing methods (e.g., logistic regression, random forest, support vector machines, and gradient-boosted decision trees. RIDDLE yielded significantly better classification performance across all metrics that were considered: accuracy, cross-entropy loss (error, precision, recall, and area under the curve for receiver operating characteristic plots (all p < 10-9. We made specific efforts to interpret the trained neural network models to identify, quantify, and visualize medical features which are predictive of race and ethnicity. We used these characterizations of informative features to perform a systematic comparison of differential disease patterns by race and ethnicity. The fact that clinical histories are informative for imputing race and ethnicity could reflect (1 a skewed distribution of blue- and white-collar professions across racial and ethnic groups, (2 uneven accessibility and subjective importance of prophylactic health, (3 possible variation in lifestyle, such as dietary habits, and (4 differences in background genetic variation which predispose to diseases.

13. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Science.gov (United States)

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

14. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

Directory of Open Access Journals (Sweden)

Jun-He Yang

2017-01-01

Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

15. Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes

KAUST Repository

Chatterjee, Nilanjan

2009-11-01

Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.

16. Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes

KAUST Repository

Chatterjee, Nilanjan; Chen, Yi-Hau; Luo, Sheng; Carroll, Raymond J.

2009-01-01

Although prospective logistic regression is the standard method of analysis for case-control data, it has been recently noted that in genetic epidemiologic studies one can use the "retrospective" likelihood to gain major power by incorporating various population genetics model assumptions such as Hardy-Weinberg-Equilibrium (HWE), gene-gene and gene-environment independence. In this article we review these modern methods and contrast them with the more classical approaches through two types of applications (i) association tests for typed and untyped single nucleotide polymorphisms (SNPs) and (ii) estimation of haplotype effects and haplotype-environment interactions in the presence of haplotype-phase ambiguity. We provide novel insights to existing methods by construction of various score-tests and pseudo-likelihoods. In addition, we describe a novel two-stage method for analysis of untyped SNPs that can use any flexible external algorithm for genotype imputation followed by a powerful association test based on the retrospective likelihood. We illustrate applications of the methods using simulated and real data. © Institute of Mathematical Statistics, 2009.

17. RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning

KAUST Repository

Kim, Ji-Sung

2018-04-26

Anonymized electronic medical records are an increasingly popular source of research data. However, these datasets often lack race and ethnicity information. This creates problems for researchers modeling human disease, as race and ethnicity are powerful confounders for many health exposures and treatment outcomes; race and ethnicity are closely linked to population-specific genetic variation. We showed that deep neural networks generate more accurate estimates for missing racial and ethnic information than competing methods (e.g., logistic regression, random forest, support vector machines, and gradient-boosted decision trees). RIDDLE yielded significantly better classification performance across all metrics that were considered: accuracy, cross-entropy loss (error), precision, recall, and area under the curve for receiver operating characteristic plots (all p < 10-9). We made specific efforts to interpret the trained neural network models to identify, quantify, and visualize medical features which are predictive of race and ethnicity. We used these characterizations of informative features to perform a systematic comparison of differential disease patterns by race and ethnicity. The fact that clinical histories are informative for imputing race and ethnicity could reflect (1) a skewed distribution of blue- and white-collar professions across racial and ethnic groups, (2) uneven accessibility and subjective importance of prophylactic health, (3) possible variation in lifestyle, such as dietary habits, and (4) differences in background genetic variation which predispose to diseases.

18. MicroRNAs regulate human adipocyte lipolysis: effects of miR-145 are linked to TNF-α.

Directory of Open Access Journals (Sweden)

Silvia Lorente-Cebrián

Full Text Available MicroRNAs (miRNAs are small non-coding RNAs that regulate gene expression and have multiple effects in various tissues including adipose inflammation, a condition characterized by increased local release of the pro-lipolytic cytokine tumor necrosis factor-alpha (TNF-α. Whether miRNAs regulate adipocyte lipolysis is unknown. We set out to determine whether miRNAs affect adipocyte lipolysis in human fat cells. To this end, eleven miRNAs known to be present in human adipose tissue were over-expressed in human in vitro differentiated adipocytes followed by assessments of TNF-α and glycerol levels in conditioned media after 48 h. Three miRNAs (miR-145, -26a and let-7d modulated both parameters in parallel. However, while miR-26a and let-7d decreased, miR-145 increased both glycerol release and TNF-α secretion. Further studies were focused therefore on miR-145 since this was the only stimulator of lipolysis and TNF-α secretion. Time-course analysis demonstrated that miR-145 over-expression up-regulated TNF-α expression/secretion followed by increased glycerol release. Increase in TNF-α production by miR-145 was mediated via activation of p65, a member of the NF-κB complex. In addition, miR-145 down-regulated the expression of the protease ADAM17, resulting in an increased fraction of membrane bound TNF-α, which is the more biologically active form of TNF-α. MiR-145 overexpression also increased the phosphorylation of activating serine residues in hormone sensitive lipase and decreased the mRNA expression of phosphodiesterase 3B, effects which are also observed upon TNF-α treatment in human adipocytes. We conclude that miR-145 regulates adipocyte lipolysis via multiple mechanisms involving increased production and processing of TNF-α in fat cells.

19. Emerging roles and regulation of MiT/TFE transcriptional factors.

Science.gov (United States)

Yang, Min; Liu, En; Tang, Li; Lei, Yuanyuan; Sun, Xuemei; Hu, Jiaxi; Dong, Hui; Yang, Shi-Ming; Gao, Mingfa; Tang, Bo

2018-06-15

The MiT/TFE transcription factors play a pivotal role in the regulation of autophagy and lysosomal biogenesis. The subcellular localization and activity of MiT/TFE proteins are primarily regulated through phosphorylation. And the phosphorylated protein is retained in the cytoplasm and subsequently translocates to the nucleus upon dephosphorylation, where it stimulates the expression of hundreds of genes, leading to lysosomal biogenesis and autophagy induction. The transcription factor-mediated lysosome-to-nucleus signaling can be directly controlled by several signaling molecules involved in the mTORC1, PKC, and AKT pathways. MiT/TFE family members have attracted much attention owing to their intracellular clearance of pathogenic factors in numerous diseases. Recently, multiple studies have also revealed the MiT/TFE proteins as master regulators of cellular metabolic reprogramming, converging on autophagic and lysosomal function and playing a critical role in cancer, suggesting that novel therapeutic strategies could be based on the modulation of MiT/TFE family member activity. Here, we present an overview of the latest research on MiT/TFE transcriptional factors and their potential mechanisms in cancer.

20. Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

Science.gov (United States)

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

1. Human disease MiRNA inference by combining target information based on heterogeneous manifolds.

Science.gov (United States)

Ding, Pingjian; Luo, Jiawei; Liang, Cheng; Xiao, Qiu; Cao, Buwen

2018-04-01

The emergence of network medicine has provided great insight into the identification of disease-related molecules, which could help with the development of personalized medicine. However, the state-of-the-art methods could neither simultaneously consider target information and the known miRNA-disease associations nor effectively explore novel gene-disease associations as a by-product during the process of inferring disease-related miRNAs. Computational methods incorporating multiple sources of information offer more opportunities to infer disease-related molecules, including miRNAs and genes in heterogeneous networks at a system level. In this study, we developed a novel algorithm, named inference of Disease-related MiRNAs based on Heterogeneous Manifold (DMHM), to accurately and efficiently identify miRNA-disease associations by integrating multi-omics data. Graph-based regularization was utilized to obtain a smooth function on the data manifold, which constitutes the main principle of DMHM. The novelty of this framework lies in the relatedness between diseases and miRNAs, which are measured via heterogeneous manifolds on heterogeneous networks integrating target information. To demonstrate the effectiveness of DMHM, we conducted comprehensive experiments based on HMDD datasets and compared DMHM with six state-of-the-art methods. Experimental results indicated that DMHM significantly outperformed the other six methods under fivefold cross validation and de novo prediction tests. Case studies have further confirmed the practical usefulness of DMHM. Copyright © 2018 Elsevier Inc. All rights reserved.

2. MiMiR: a comprehensive solution for storage, annotation and exchange of microarray data

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Rahman Fatimah

2005-11-01

Full Text Available Abstract Background The generation of large amounts of microarray data presents challenges for data collection, annotation, exchange and analysis. Although there are now widely accepted formats, minimum standards for data content and ontologies for microarray data, only a few groups are using them together to build and populate large-scale databases. Structured environments for data management are crucial for making full use of these data. Description The MiMiR database provides a comprehensive infrastructure for microarray data annotation, storage and exchange and is based on the MAGE format. MiMiR is MIAME-supportive, customised for use with data generated on the Affymetrix platform and includes a tool for data annotation using ontologies. Detailed information on the experiment, methods, reagents and signal intensity data can be captured in a systematic format. Reports screens permit the user to query the database, to view annotation on individual experiments and provide summary statistics. MiMiR has tools for automatic upload of the data from the microarray scanner and export to databases using MAGE-ML. Conclusion MiMiR facilitates microarray data management, annotation and exchange, in line with international guidelines. The database is valuable for underpinning research activities and promotes a systematic approach to data handling. Copies of MiMiR are freely available to academic groups under licence.

3. Mitigation of arsenic-induced acquired cancer phenotype in prostate cancer stem cells by miR-143 restoration

Energy Technology Data Exchange (ETDEWEB)

Ngalame, Ntube N.O., E-mail: ngalamenn@niehs.nih.gov; Makia, Ngome L., E-mail: makianl@niehs.nih.gov; Waalkes, Michael P., E-mail: waalkes@niehs.nih.gov; Tokar, Erik J., E-mail: tokare@mail.nih.gov

2016-12-01

Inorganic arsenic, an environmental contaminant and a human carcinogen is associated with prostate cancer. Emerging evidence suggests that cancer stem cells (CSCs) are the driving force of carcinogenesis. Chronic arsenic exposure malignantly transforms the human normal prostate stem/progenitor cell (SC) line, WPE-stem to arsenic-cancer SCs (As-CSCs), through unknown mechanisms. MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate gene expression at the posttranscriptional level. In prior work, miR-143 was markedly downregulated in As-CSCs, suggesting a role in arsenic-induced malignant transformation. In the present study, we investigated whether loss of miR-143 expression is important in arsenic-induced transformation of prostate SCs. Restoration of miR-143 in As-CSCs was achieved by lentivirus-mediated miR-143 overexpression. Cells were assessed bi-weekly for up to 30 weeks to examine mitigation of cancer phenotype. Secreted matrix metalloproteinase (MMP) activity was increased by arsenic-induced malignant transformation, but miR-143 restoration decreased secreted MMP-2 and MMP-9 enzyme activities compared with scramble controls. Increased cell proliferation and apoptotic resistance, two hallmarks of cancer, were decreased upon miR-143 restoration. Increased apoptosis was associated with decreased BCL2 and BCL-XL expression. miR-143 restoration dysregulated the expression of SC/CSC self-renewal genes including NOTCH-1, BMI-1, OCT4 and ABCG2. The anticancer effects of miR-143 overexpression appeared to be mediated by targeting and inhibiting LIMK1 protein, and the phosphorylation of cofilin, a LIMK1 substrate. These findings clearly show that miR-143 restoration mitigated multiple cancer characteristics in the As-CSCs, suggesting a potential role in arsenic-induced transformation of prostate SCs. Thus, miR-143 is a potential biomarker and therapeutic target for arsenic-induced prostate cancer. - Highlights: • Chronic arsenic exposure

4. Mitigation of arsenic-induced acquired cancer phenotype in prostate cancer stem cells by miR-143 restoration

International Nuclear Information System (INIS)

Ngalame, Ntube N.O.; Makia, Ngome L.; Waalkes, Michael P.; Tokar, Erik J.

2016-01-01

Inorganic arsenic, an environmental contaminant and a human carcinogen is associated with prostate cancer. Emerging evidence suggests that cancer stem cells (CSCs) are the driving force of carcinogenesis. Chronic arsenic exposure malignantly transforms the human normal prostate stem/progenitor cell (SC) line, WPE-stem to arsenic-cancer SCs (As-CSCs), through unknown mechanisms. MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate gene expression at the posttranscriptional level. In prior work, miR-143 was markedly downregulated in As-CSCs, suggesting a role in arsenic-induced malignant transformation. In the present study, we investigated whether loss of miR-143 expression is important in arsenic-induced transformation of prostate SCs. Restoration of miR-143 in As-CSCs was achieved by lentivirus-mediated miR-143 overexpression. Cells were assessed bi-weekly for up to 30 weeks to examine mitigation of cancer phenotype. Secreted matrix metalloproteinase (MMP) activity was increased by arsenic-induced malignant transformation, but miR-143 restoration decreased secreted MMP-2 and MMP-9 enzyme activities compared with scramble controls. Increased cell proliferation and apoptotic resistance, two hallmarks of cancer, were decreased upon miR-143 restoration. Increased apoptosis was associated with decreased BCL2 and BCL-XL expression. miR-143 restoration dysregulated the expression of SC/CSC self-renewal genes including NOTCH-1, BMI-1, OCT4 and ABCG2. The anticancer effects of miR-143 overexpression appeared to be mediated by targeting and inhibiting LIMK1 protein, and the phosphorylation of cofilin, a LIMK1 substrate. These findings clearly show that miR-143 restoration mitigated multiple cancer characteristics in the As-CSCs, suggesting a potential role in arsenic-induced transformation of prostate SCs. Thus, miR-143 is a potential biomarker and therapeutic target for arsenic-induced prostate cancer. - Highlights: • Chronic arsenic exposure

5. Arabidopsis mutant sk156 reveals complex regulation of SPL15 in a miR156-controlled gene network.

Science.gov (United States)

Wei, Shu; Gruber, Margaret Y; Yu, Bianyun; Gao, Ming-Jun; Khachatourians, George G; Hegedus, Dwayne D; Parkin, Isobel A P; Hannoufa, Abdelali

2012-09-18

The Arabidopsis microRNA156 (miR156) regulates 11 members of the SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL) family by base pairing to complementary target mRNAs. Each SPL gene further regulates a set of other genes; thus, miR156 controls numerous genes through a complex gene regulation network. Increased axillary branching occurs in transgenic Arabidopsis overexpressing miR156b, similar to that observed in loss-of-function max3 and max4 mutants with lesions in carotenoid cleavage dioxygenases. Arabidopsis miR156b was found to enhance carotenoid levels and reproductive shoot branching when expressed in Brassica napus, suggesting a link between miR156b expression and carotenoid metabolism. However, details of the miR156 regulatory network of SPL genes related to carotenoid metabolism are not known. In this study, an Arabidopsis T-DNA enhancer mutant, sk156, was identified due to its altered branching and trichome morphology and increased seed carotenoid levels compared to wild type (WT) ecovar Columbia. Enhanced miR156b expression due to the 35S enhancers present on the T-DNA insert was responsible for these phenotypes. Constitutive and leaf primodium-specific expression of a miR156-insensitive (mutated) SPL15 (SPL15m) largely restored WT seed carotenoid levels and plant morphology when expressed in sk156. The Arabidopsis native miR156-sensitive SPL15 (SPL15n) and SPL15m driven by a native SPL15 promoter did not restore the WT phenotype in sk156. Our findings suggest that SPL15 function is somewhat redundant with other SPL family members, which collectively affect plant phenotypes. Moreover, substantially decreased miR156b transcript levels in sk156 expressing SPL15m, together with the presence of multiple repeats of SPL-binding GTAC core sequence close to the miR156b transcription start site, suggested feedback regulation of miR156b expression by SPL15. This was supported by the demonstration of specific in vitro interaction between DNA-binding SBP domain of SPL15

6. Arabidopsis mutant sk156 reveals complex regulation of SPL15 in a miR156-controlled gene network

Directory of Open Access Journals (Sweden)

Wei Shu

2012-09-01

Full Text Available Abstract Background The Arabidopsis microRNA156 (miR156 regulates 11 members of the SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL family by base pairing to complementary target mRNAs. Each SPL gene further regulates a set of other genes; thus, miR156 controls numerous genes through a complex gene regulation network. Increased axillary branching occurs in transgenic Arabidopsis overexpressing miR156b, similar to that observed in loss-of-function max3 and max4 mutants with lesions in carotenoid cleavage dioxygenases. Arabidopsis miR156b was found to enhance carotenoid levels and reproductive shoot branching when expressed in Brassica napus, suggesting a link between miR156b expression and carotenoid metabolism. However, details of the miR156 regulatory network of SPL genes related to carotenoid metabolism are not known. Results In this study, an Arabidopsis T-DNA enhancer mutant, sk156, was identified due to its altered branching and trichome morphology and increased seed carotenoid levels compared to wild type (WT ecovar Columbia. Enhanced miR156b expression due to the 35S enhancers present on the T-DNA insert was responsible for these phenotypes. Constitutive and leaf primodium-specific expression of a miR156-insensitive (mutated SPL15 (SPL15m largely restored WT seed carotenoid levels and plant morphology when expressed in sk156. The Arabidopsis native miR156-sensitive SPL15 (SPL15n and SPL15m driven by a native SPL15 promoter did not restore the WT phenotype in sk156. Our findings suggest that SPL15 function is somewhat redundant with other SPL family members, which collectively affect plant phenotypes. Moreover, substantially decreased miR156b transcript levels in sk156 expressing SPL15m, together with the presence of multiple repeats of SPL-binding GTAC core sequence close to the miR156b transcription start site, suggested feedback regulation of miR156b expression by SPL15. This was supported by the demonstration of specific in vitro

7. Potential impact of miR-137 and its targets in schizophrenia

Directory of Open Access Journals (Sweden)

Carrie eWright

2013-04-01

Full Text Available The significant impact of microRNAs (miRNAs on disease pathology is becoming increasingly evident. These small non-coding RNAs have the ability to post-transcriptionally silence the expression of thousands of genes. Therefore, dysregulation of even a single miRNA could confer a large polygenic effect. Schizophrenia is a genetically complex illness thought to involve multiple genes each contributing a small risk. Large genome-wide association studies identified miR-137, a miRNA shown to be involved in neuronal maturation, as one of the top risk genes. To assess the potential mechanism of impact of miR-137 in this disorder and identify its targets, we used a combination of literature searches, Ingenuity Pathway Analysis (IPA, and freely accessible bioinformatics resources. Using TargetScan and the Schizophrenia Gene Resource (SZGR database, we found that in addition to CSMD1, C10orf26, CACNA1C, TCF4, and ZNF804A, five schizophrenia risk genes whose transcripts are also validated miR-137 targets, there are other schizophrenia-associated genes that may be targets of miR-137, including ERBB4, GABRA1, GRIN2A, GRM5, GSK3B, NRG2 and HTR2C. IPA analyses of all the potential targets identified several nervous system functions as the top canonical pathways including synaptic long-term potentiation, a process implicated in learning and memory mechanisms and recently shown to be altered in patients with schizophrenia. Among the subset of targets involved in nervous system development and function, the top scoring pathways were ephrin receptor signaling and axonal guidance, processes that are critical for proper circuitry formation and were shown to be disrupted in schizophrenia. These results suggest that miR-137 may indeed play a substantial role in the genetic etiology of schizophrenia by regulating networks involved in neural development and brain function.

8. Identification of miR-93 as a suitable miR for normalizing miRNA in plasma of tuberculosis patients.

Science.gov (United States)

Barry, Simone E; Chan, Brian; Ellis, Magda; Yang, YuRong; Plit, Marshall L; Guan, Guangyu; Wang, Xiaolin; Britton, Warwick J; Saunders, Bernadette M

2015-07-01

Tuberculosis (TB) remains a major public health issue. New tests to aid diagnoses and monitor the response to therapy are urgently required. There is growing interest in the use of microRNA (miRNA) profiles as diagnostic, prognostic or predictive markers in a range of clinical and infectious diseases, including Mycobacterium tuberculosis infection, however, challenges exist to accurately normalise miRNA levels in cohorts. This study examined the appropriateness of 12 miRs and RNU6B to normalise circulating plasma miRNA levels in individuals with active TB from 2 different geographical and ethnic regions. Twelve miRs (let-7, miR-16, miR-22, miR-26, miR-93, miR-103, miR-191, miR-192, miR-221, miR-423, miR-425 and miR-451) and RNU6B were selected based on their reported production by lung cells, expression in blood and previous use as a reference miRNA. Expression levels were analysed in the plasma of newly diagnosed TB patients from Australia and China compared with individuals with latent TB infection and healthy volunteers. Analysis with both geNorm and NormFinder software identified miR-93 as the most suitable reference miR in both cohorts, either when analysed separately or collectively. Interestingly, there were large variations in the expression levels of some miRs, in particular miR-192 and let-7, between the two cohorts, independent of disease status. These data identify miR-93 is a suitable reference miR for normalizing miRNA levels in TB patients, and highlight how environmental, and possibly ethnic, factors influence miRNA expression levels, demonstrating the necessity of assessing the suitability of reference miRs within the study population. © 2015 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

9. Does Multiple Intelligence Improve Performance? Evidence from a ...

African Journals Online (AJOL)

This study reports the findings of a study that investigated the relationship between multiple intelligence (MI) and academic performance in higher education. It addresses one question: does MI improve academic performance? Taking the case of the finalist cohort of the university's Faculty of Education of the academic year ...

10. miRNA Signatures of Insulin Resistance in Obesity.

Science.gov (United States)

Jones, Angela; Danielson, Kirsty M; Benton, Miles C; Ziegler, Olivia; Shah, Ravi; Stubbs, Richard S; Das, Saumya; Macartney-Coxson, Donia

2017-10-01

Extracellular microRNAs (miRNAs) represent functional biomarkers for obesity and related disorders; this study investigated plasma miRNAs in insulin resistance phenotypes in obesity. One hundred seventy-five miRNAs were analyzed in females with obesity (insulin sensitivity, n = 11; insulin resistance, n = 19; type 2 diabetes, n = 15) and without obesity (n = 12). Correlations between miRNA level and clinical parameters and levels of 15 miRNAs in a murine obesity model were investigated. One hundred six miRNAs were significantly (adjusted P ≤ 0.05) different between controls and at least one obesity phenotype, including miRNAs with the following attributes: previously reported roles in obesity and altered circulating levels (e.g., miR-122, miR-192); known roles in obesity but no reported changes in circulating levels (e.g., miR-378a); and no current reported role in, or association with, obesity (e.g., miR-28-5p, miR-374b, miR-32). The miRNAs in the latter group were found to be associated with extracellular vesicles. Forty-eight miRNAs showed significant correlations with clinical parameters; stepwise regression retained let-7b, miR-144-5p, miR-34a, and miR-532-5p in a model predictive of insulin resistance (R 2  = 0.57, P = 7.5 × 10 -8 ). Both miR-378a and miR-122 were perturbed in metabolically relevant tissues in a murine model of obesity. This study expands on the role of extracellular miRNAs in insulin-resistant phenotypes of obesity and identifies candidate miRNAs not previously associated with obesity. © 2017 The Obesity Society.

11. Development of a Low-Cost Stem-Loop Real-Time Quantification PCR Technique for EBV miRNA Expression Analysis.

Science.gov (United States)

Bergallo, Massimiliano; Merlino, Chiara; Montin, Davide; Galliano, Ilaria; Gambarino, Stefano; Mareschi, Katia; Fagioli, Franca; Montanari, Paola; Martino, Silvana; Tovo, Pier-Angelo

2016-09-01

MicroRNAs (miRNAs) are short, single stranded, non-coding RNA molecules. They are produced by many different species and are key regulators of several physiological processes. miRNAs are also encoded by the genomes of multiple virus families, such as herpesvirus family. In particular, miRNAs from Epstein Barr virus were found at high concentrations in different associated pathologies, such as Burkitt's lymphoma, Hodgkin disease, and nasopharyngeal carcinoma. Thanks to their stability, these molecules could possibly serve as biomarkers for EBV-associated diseases. In this study, a stem-loop real-time PCR for miR-BART2-5p, miR-BART15, and miR-BART22 EBV miRNAs detection and quantification has been developed. Evaluation of these miRNAs in 31 serum samples (12 from patients affected by primary immunodeficiency, 9 from X-linked agammaglobulinemia and 10 from healthy subjects) has been carried out. The amplification performance showed a wide dynamic range (10(8)-10(2) copies/reaction) and sensibility equal to 10(2) copies/reaction for all the target tested. Serum samples analysis, on the other hand, showed a statistical significant higher level of miR-BART22 in primary immunodeficiency patients (P = 0.0001) compared to other groups and targets. The results confirmed the potential use of this assay as a tool for monitoring EBV-associated disease and for miRNAs expression profile analysis.

12. Simultaneous Treatment of Missing Data and Measurement Error in HIV Research Using Multiple Overimputation.

Science.gov (United States)

Schomaker, Michael; Hogger, Sara; Johnson, Leigh F; Hoffmann, Christopher J; Bärnighausen, Till; Heumann, Christian

2015-09-01

Both CD4 count and viral load in HIV-infected persons are measured with error. There is no clear guidance on how to deal with this measurement error in the presence of missing data. We used multiple overimputation, a method recently developed in the political sciences, to account for both measurement error and missing data in CD4 count and viral load measurements from four South African cohorts of a Southern African HIV cohort collaboration. Our knowledge about the measurement error of ln CD4 and log10 viral load is part of an imputation model that imputes both missing and mismeasured data. In an illustrative example, we estimate the association of CD4 count and viral load with the hazard of death among patients on highly active antiretroviral therapy by means of a Cox model. Simulation studies evaluate the extent to which multiple overimputation is able to reduce bias in survival analyses. Multiple overimputation emphasizes more strongly the influence of having high baseline CD4 counts compared to both a complete case analysis and multiple imputation (hazard ratio for >200 cells/mm vs. <25 cells/mm: 0.21 [95% confidence interval: 0.18, 0.24] vs. 0.38 [0.29, 0.48], and 0.29 [0.25, 0.34], respectively). Similar results are obtained when varying assumptions about measurement error, when using p-splines, and when evaluating time-updated CD4 count in a longitudinal analysis. The estimates of the association with viral load are slightly more attenuated when using multiple imputation instead of multiple overimputation. Our simulation studies suggest that multiple overimputation is able to reduce bias and mean squared error in survival analyses. Multiple overimputation, which can be used with existing software, offers a convenient approach to account for both missing and mismeasured data in HIV research.

13. Cointegrating MiDaS Regressions and a MiDaS Test

OpenAIRE

J. Isaac Miller

2011-01-01

This paper introduces cointegrating mixed data sampling (CoMiDaS) regressions, generalizing nonlinear MiDaS regressions in the extant literature. Under a linear mixed-frequency data-generating process, MiDaS regressions provide a parsimoniously parameterized nonlinear alternative when the linear forecasting model is over-parameterized and may be infeasible. In spite of potential correlation of the error term both serially and with the regressors, I find that nonlinear least squares consistent...

14. The regulatory epicenter of miRNAs

Bioresource Technology, Council of Scientific & Industrial Research, Palampur 176 061, HP, India. *Corresponding .... miRNA stem and loop regions, interacting with Drosha for .... a double-stranded element, having one strand from the 5′.

15. Universal MI definition update for cardiovascular disease.

Science.gov (United States)

White, Harvey; Thygesen, Kristian; Alpert, Joseph S; Jaffe, Allan

2014-01-01

The new third universal definition of myocardial infarction (MI) is based on troponin elevation together with ischemic symptoms, ischemic ECG changes, and imaging evidence. MIs are classified into five types as to whether they are spontaneous, secondary to imbalance between coronary artery blood supply and demand, related to sudden death, or related to revascularization procedures. The definition is based on a rise and/or fall in troponin levels occurring in a clinical setting. There have been modifications over previous definitions with adding intracoronary thrombus as a criterion, adding a new type of MI type 4c, and raising the cutpoint for the diagnosis of MI related to percutaneous coronary intervention to five times the 99(th) percentile upper reference limit and requiring evidence of ischemia or angiographic complications. In clinical practice, trials, and registries, different definitions are used. There is a need for consistency with regard to the definition of MI and the universal definition should be implemented.

16. miRNAting control of DNA methylation

miRNAting control of DNA methylation. ASHWANI ... function and biological process ... Enrichment analysis of the genes methylated by DRM2 for molecular function and biological ... 39(3), June 2014, 365–380, © Indian Academy of Sciences.

17. miRNAtools: Advanced Training Using the miRNA Web of Knowledge.

Science.gov (United States)

Stępień, Ewa Ł; Costa, Marina C; Enguita, Francisco J

2018-02-16

Micro-RNAs (miRNAs) are small non-coding RNAs that act as negative regulators of the genomic output. Their intrinsic importance within cell biology and human disease is well known. Their mechanism of action based on the base pairing binding to their cognate targets have helped the development not only of many computer applications for the prediction of miRNA target recognition but also of specific applications for functional assessment and analysis. Learning about miRNA function requires practical training in the use of specific computer and web-based applications that are complementary to wet-lab studies. In order to guide the learning process about miRNAs, we have created miRNAtools (http://mirnatools.eu), a web repository of miRNA tools and tutorials. This article compiles tools with which miRNAs and their regulatory action can be analyzed and that function to collect and organize information dispersed on the web. The miRNAtools website contains a collection of tutorials that can be used by students and tutors engaged in advanced training courses. The tutorials engage in analyses of the functions of selected miRNAs, starting with their nomenclature and genomic localization and finishing with their involvement in specific cellular functions.

18. Circulating miR-1, miR-133a, and miR-206 levels are increased after a half-marathon run.

Science.gov (United States)

Gomes, Clarissa P C; Oliveira, Getúlio P; Madrid, Bibiano; Almeida, Jeeser A; Franco, Octávio L; Pereira, Rinaldo W

2014-11-01

Circulating miRNAs are potential biomarkers that can be important molecules driving cell-to-cell communication. To investigate circulating muscle-specific miRNAs in recreational athletes. Three miRNAs from whole plasma before and after a half-marathon were analyzed by qPCR. MiR-1, -133a, and -206 significantly increased after the race. Increased levels of miRNAs after exercise point to potential biomarkers and to the possibility of being functional players following endurance training. These miRNAs are potential biomarkers of muscle damage or adaptation to exercise.

19. miR-20b, miR-98, miR-125b-1*, and let-7e* as new potential diagnostic biomarkers in ulcerative colitis

DEFF Research Database (Denmark)

Coskun, Mehmet; Bjerrum, Jacob Tveiten; Seidelin, Jakob Benedict

2013-01-01

were obtained endoscopically from patients with active UC or CD, quiescent UC or CD, as well as healthy controls. Total RNA was isolated and miRNA expression assessed using the miRNA microarray Geniom Biochip miRNA Homo sapiens (Febit GmbH, Heidelberg, Germany). Data analysis was carried out...... genes involved in various pathways, such as mitogen-activated protein kinase and cytokine signaling, which are both key signaling pathways in UC. CONCLUSION: The present study provides the first evidence that miR-20b, miR-98, miR-125b-1*, and let-7e* are deregulated in patients with UC. The level...

20. Evolutionary conservation and expression of miR-10a-3p in olive flounder and rock bream.

Science.gov (United States)

Jo, Ara; Im, Jennifer; Lee, Hee-Eun; Jang, Dongmin; Nam, Gyu-Hwi; Mishra, Anshuman; Kim, Woo-Jin; Kim, Won; Cha, Hee-Jae; Kim, Heui-Soo

2017-09-10

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) that mainly bind to the seed sequences located within the 3' untranslated region (3' UTR) of target genes. They perform an important biological function as regulators of gene expression. Different genes can be regulated by the same miRNA, whilst different miRNAs can be regulated by the same genes. Here, the evolutionary conservation and expression pattern of miR-10a-3p in olive flounder and rock bream was examined. Binding sites (AAAUUC) to seed region of the 3' UTR of target genes were highly conserved in various species. The expression pattern of miR-10a-3p was ubiquitous in the examined tissues, whilst its expression level was decreased in gill tissues infected by viral hemorrhagic septicemia virus (VHSV) compared to the normal control. In the case of rock bream, the spleen, kidney, and liver tissues showed dominant expression levels of miR-10a-3p. Only the liver tissues in the rock bream samples infected by the iridovirus indicated a dominant miR-10a-3p expression. The gene ontology (GO) analysis of predicted target genes for miR-10a-3p revealed that multiple genes are related to binding activity, catalytic activity, cell components as well as cellular and metabolic process. Overall the results imply that the miR-10a-3p could be used as a biomarker to detect VHSV infection in olive flounder and iridovirus infection in rock bream. In addition, the data provides fundamental information for further study of the complex interaction between miR-10a-3p and gene expression. Copyright © 2017 Elsevier B.V. All rights reserved.

1. Roles for miR-375 in Neuroendocrine Differentiation and Tumor Suppression via Notch Pathway Suppression in Merkel Cell Carcinoma.

Science.gov (United States)

Abraham, Karan J; Zhang, Xiao; Vidal, Ricardo; Paré, Geneviève C; Feilotter, Harriet E; Tron, Victor A

2016-04-01

Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

2. Evaluation of miR-182/miR-100 Ratio for Diagnosis and Survival Prediction in Bladder Cancer.

Science.gov (United States)

Chen, Zhanguo; Wu, Lili; Lin, Qi; Shi, Jing; Lin, Xiangyang; Shi, Liang

2016-09-01

Abnormal expression of microRNAs (miRNAs) plays an important role in development of several cancer types, including bladder cancer (BCa). However, the relationship between the ratio of miR-181/miR-100 and the prognosis of BCa has not been studied yet. The aim of this study was to evaluate the expression of miR-182, miR-100 and their clinical significance in BCa. Upregulation of miR-182 and down-regulation of miR-100 were validated in tissue specimens of 134 BCa cases compared with 148 normal bladder epithelia (NBE) specimens  using TaqMan-based real-time reverse transcription quantitative PCR (RT-qPCR). The diagnostic and prognostic evaluation of miR-182, miR-100, and miR-182/miR-100 ratio was also performed. miR-182 was upregulated in BCa and miR-100 was down-regulated in BCa compared with NBE (P ratio increased the diagnostic performance, yielding an AUC of 0.981 (97.01% sensitivity and 90.54% specificity). Moreover, miR-182/miR-100 ratio was associated with pT-stage, histological grade, BCa recurrence and carcinoma in situ (P analysis indicated that miR-182/miR-100 ratio was an independent prognostic factor for overall survival (Hazard ratio: 7.142; 95% CI: 2.106 - 9.891; P analysis revealed that high-level of miR-182/miR-100 ratio was significantly correlated with shortened survival time for BCa patients (P ratio may serve as a novel promising biomarker for diagnosis and survival prediction in BCa. Further studies are needed to elucidate the role of miR-182/miR-100 ratio as a non‑invasive diagnostic tool for BCa.

3. Knock-down of miR-221 and miR-222 in the radiosensitization of breast cancer cells

International Nuclear Information System (INIS)

Zhang Chunzhi; Kang Chunsheng; Cao Yongzhen; Pu Peiyu; Lu Zhonghong; Du Yue

2009-01-01

Objective: To investigate the radiosensitizing effect of knock-down of miR-221 miR-222 on MCF-7 human breast cancer cells and explore the possible mechanism. Methods: Antisense oligonucleotides of miR-221 and miR-222 (AS-miR-221 and AS-miR-222), mediated by lipofectamine, were transfected to MCF-7 cells to knock down miR-221 and miR-222, Northern blotting was conducted to detect the expression of miR-221 and miR-222 in transfected cells. The cell apoptosis was detected by flow cytometry and Caspase-3 and Caspase-7 activity assay. Clonogenic assay was used to measure the sensitizing enhancement ratio. Target genes of miR-221 and miR-222 relevant to radio-sensitivity were searched using bioinformatics analysis. The targeted protein expression was determined by Western blot analysis. Results: The expression of miR-221 and miR-222 in the AS-miR-221/222 cells determined by Northern blotting was significantly reduced. Compared with the control group, the cell apoptosis and mitotic cell death after the radiation were significantly higher in AS-miR-221/222 cells. The sensitizing enhancement ratio was 1.87. Based on bioinformatics analysis, PTEN was a target gene of miR-221 and miR-222 which could enhance the radiosensitivity of MCF-7 cells. In AS-miR-221/222 cells, the expression of PTEN was up-regulated while pAkt down-regulated. Conclusions: AS-miR-221 and AS-miR-222 may enhance the radiosensitivity of MCF-7 breast cancer cells by up-regulating the expression of PTEN. (authors)

4. Cortical Morphogenesis during Embryonic Development Is Regulated by miR-34c and miR-204

DEFF Research Database (Denmark)

Veno, Morten T.; Veno, Susanne T.; Rehberg, Kati

2017-01-01

The porcine brain closely resembles the human brain in aspects such as development and morphology. Temporal miRNA profiling in the developing embryonic porcine cortex revealed a distinct set of miRNAs, including miR-34c and miR-204, which exhibited a highly specific expression profile across...

5. Decreased miR-128 and increased miR-21 synergistically cause podocyte injury in sepsis.

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Wang, Shanshan; Wang, Jun; Zhang, Zengdi; Miao, Hongjun

2017-08-01

Glomerular podocytes are injured in sepsis. We studied, in a sepsis patient, whether microRNAs (miRNAs) play a role in the podocyte injury. Podocytes were cultured and treated with lipopolysaccharide (LPS). Filtration barrier function of podocyte was analyzed with albumin influx assay. Nephrin level was analyzed with reverse transcription polymerase chain reaction (RT-PCR) and western blot. MiRNAs were detected using miRNAs PCR Array and in situ hybridization. MiRNA target sites were evaluated with luciferase reporter assays. LPS impaired the filtration barrier function of podocytes. MiR-128 level was decreased and miR-21 level was increased in podocytes in vitro and in the sepsis patient. The decrease in miR-128 was sufficient to induce the loss of nephrin and the impairment of filtration barrier function, while the increase of miR-21 exacerbated the process. Snail and phosphatase and tensin homolog (PTEN) were identified as the targets of miR-128 and miR-21. Decreased miR-128 induced Snail expression, and the increased miR-21 stabilized Snail by regulating the PTEN/Akt/GSK3β pathway. Supplementation of miR-128 and inhibition of miR-21 suppressed Snail expression and prevented the podocyte injury induced by LPS. Our study suggests that decreased miR-128 and increased miR-21 synergistically cause podocyte injury and are the potential therapeutic targets in sepsis.

6. Structural profiles of human miRNA families from pairwise clustering

DEFF Research Database (Denmark)

Kaczkowski, Bogumil; Þórarinsson, Elfar; Reiche, Kristin

2009-01-01

secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment...... of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures. Availability: http://genome.ku.dk/resources/mirclust...

7. Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

Science.gov (United States)

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

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.

8. Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

Science.gov (United States)

Lopes, F B; Wu, X-L; Li, H; Xu, J; Perkins, T; Genho, J; Ferretti, R; Tait, R G; Bauck, S; Rosa, G J M

2018-02-01

Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP-LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP-LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de-regressed EBV was slightly small (i.e. 0.87%-18.75%). The present study also compared the performance of five genomic prediction models and two cross-validation methods. The five genomic models predicted EBV and de-regressed EBV of the ten traits similarly well. Of the two cross-validation methods, leave-one-out cross-validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle. © 2018 Blackwell Verlag GmbH.

9. A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods.

Science.gov (United States)

Ratcliffe, B; El-Dien, O G; Klápště, J; Porth, I; Chen, C; Jaquish, B; El-Kassaby, Y A

2015-12-01

Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3-40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31-0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04-0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.

10. Differential expression of miR-139, miR-486 and miR-21 in breast cancer patients sub-classified according to lymph node status

DEFF Research Database (Denmark)

Rask, Lene; Balslev, Eva; Søkilde, Rolf

2014-01-01

PURPOSE: Therapeutic decisions in breast cancer are increasingly guided by prognostic and predictive biomarkers. Non-protein-coding microRNAs (miRNAs) have recently been found to be deregulated in breast cancers and, in addition, to be correlated with several clinico-pathological features. One...... of the most consistently up-regulated miRNAs is miR-21. Here, we specifically searched for differentially expressed miRNAs in high-risk breast cancer patients as compared to low-risk breast cancer patients. In the same patients, we also compared miR-21 expression with the expression of its presumed target...... PTEN. METHODS: Both microarray and RT-qPCR techniques were used to assess miRNA expression levels in lymph node-positive and -negative human invasive ductal carcinoma tissues. Simultaneously, PTEN protein expression levels were assessed using immunohistochemistry. RESULTS: miR-486-5p and miR-139-5p...

11. Cellular microRNA-miR-548g-3p modulates the replication of dengue virus.

Science.gov (United States)

Wen, Weitao; He, Zhenjian; Jing, Qinlong; Hu, Yiwen; Lin, Cuiji; Zhou, Rui; Wang, Xiaoqun; Su, Yangfan; Yuan, Jiehao; Chen, Zhenxin; Yuan, Jie; Wu, Jueheng; Li, Jun; Zhu, Xun; Li, Mengfeng

2015-06-01

It has been well recognized that microRNA plays a role in the host-pathogen interaction network. The significance of microRNA in the regulation of dengue virus (DENV) replication, however, remains unknown. The objective of our study was to determine the biological function of miR-548g-3p in modulating the replication of dengue virus. Here we report that employment of a microRNA target search algorithm to analyze the 5' untranslated region (5'UTR) consensus sequences of DENV (DENV serotypes 1-4) led to a discovery that miR-548g-3p directly targets the stem loop A promoter element within the 5'UTR, a region essential for DENV replication. Real-time PCR was used to measure the expression levels of miR-548g-3p under DENV infection. We performed overexpression and inhibition assays to test the role of miR-548g-3p on DENV replication. The protein and mRNA levels of interferon were measured by ELISA and real-time PCR respectively. We found that overexpression of miR-548g-3p suppressed multiplication of DENV 1, 2, 3 and 4, and that miR-548g-3p was also found to interfere with DENV translation, thereby suppressing the expression of viral proteins. Our results suggest that miR-548g-3p directly regulates DENV replication and warrant further study to investigate the feasibility of microRNA-based anti-DENV approaches. Copyright © 2014 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

12. NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

Science.gov (United States)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and

13. Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms.

Science.gov (United States)

Gaur, Pallavi; Chaturvedi, Anoop

2017-07-22

The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Recent progress in the field of exosome research and more particularly regarding exosomal miRNAs has led much bioinformatic-based research to come into existence. The information on clustering pattern and candidate motifs in miRNAs of exosomal origin would help in analyzing existing, as well as newly discovered miRNAs within exosomes. Along with obtaining clustering pattern and candidate motifs in exosomal miRNAs, this work also elaborates the usefulness of the machine learning algorithms that can be efficiently used and executed on various programming languages/platforms. Data were clustered and sequence candidate motifs were detected successfully. The results were compared and validated with some available web tools such as 'BLASTN' and 'MEME suite'. The machine learning algorithms for aforementioned objectives were applied successfully. This work elaborated utility of machine learning algorithms and language platforms to achieve the tasks of clustering and candidate motif detection in exosomal miRNAs. With the information on mentioned objectives, deeper insight would be gained for analyses of newly discovered miRNAs in exosomes which are considered to be circulating biomarkers. In addition, the execution of machine learning algorithms on various language platforms gives more flexibility to users to try multiple iterations according to their requirements. This approach can be applied to other biological data-mining tasks as well.

14. Oligoasthenoteratozoospermia and infertility in mice deficient for miR-34b/c and miR-449 loci.

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Stefano Comazzetto

2014-10-01

Full Text Available Male fertility requires the continuous production of high quality motile spermatozoa in abundance. Alterations in all three metrics cause oligoasthenoteratozoospermia, the leading cause of human sub/infertility. Post-mitotic spermatogenesis inclusive of several meiotic stages and spermiogenesis (terminal spermatozoa differentiation are transcriptionally inert, indicating the potential importance for the post-transcriptional microRNA (miRNA gene-silencing pathway therein. We found the expression of miRNA generating enzyme Dicer within spermatogenesis peaks in meiosis with critical functions in spermatogenesis. In an expression screen we identified two miRNA loci of the miR-34 family (miR-34b/c and miR-449 that are specifically and highly expressed in post-mitotic male germ cells. A reduction in several miRNAs inclusive of miR-34b/c in spermatozoa has been causally associated with reduced fertility in humans. We found that deletion of both miR34b/c and miR-449 loci resulted in oligoasthenoteratozoospermia in mice. MiR-34bc/449-deficiency impairs both meiosis and the final stages of spermatozoa maturation. Analysis of miR-34bc-/-;449-/- pachytene spermatocytes revealed a small cohort of genes deregulated that were highly enriched for miR-34 family target genes. Our results identify the miR-34 family as the first functionally important miRNAs for spermatogenesis whose deregulation is causal to oligoasthenoteratozoospermia and infertility.

15. Early Sámi visual artists - Western fine art meets Sámi culture

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Tuija Hautala-Hirvioja

2014-04-01

Full Text Available Johan Turi (1854–1936, Nils Nilsson Skum (1872–1951 and John Savio (1902–1938 were among the first Sámi visual artists. The production of their art work occurred between the 1910s and the early 1950s. Sámi aesthetics had its basis in folklore, i.e., handicraft or duodji, which did not follow the principle of art for art’s sake but combined beauty and practicality. Art was part of community life. Not until the 1970s was the word daidda, which is Finnish in origin and which means “art”, adopted into the Sámi language. Turi and Skum became famous through their books. They drew and wrote in order to pass the traditional knowledge of their people on to succeeding generations. They also wanted to introduce Sámi life and culture to non-Sámi people. One typical feature of their work is that they depicted Sáminess in a realistic way and sought to strengthen and preserve the Sámi identity through their art. In Turi and Skum’s work, both the documentation of community life and their own personal expression were strongly present and equally important; for this reason their pictures and texts have both practical and aesthetic dimensions. They did not attend school and were self-taught artists. The third pioneer of Sámi visual arts was John Savio, who, unlike the other two, attended secondary school and studied visual arts both independently and under the guidance of a mentor. He expressively combined Western ways of depiction with Sámi subjects. My article examines what made these early Sámi artists change over from Sámi handicraft, duodji, to Western visual arts, how they used Western pictorial conventions in dealing with their Sámi subjects, and the significance of their art for Sámi identity and culture. They lived and worked under cross pressure: the first few decades of the 20th century were characterized by racial theories that denigrated Sámi people, and the period following World War II was marked by demands for

16. The silkworm (Bombyx mori microRNAs and their expressions in multiple developmental stages.

Directory of Open Access Journals (Sweden)

Xiaomin Yu

multiple developmental stages allowed us to pinpoint molting stages as hotspots of miRNA expression both in sorts and quantities. Based on the analysis of target genes, we hypothesized that miRNAs regulate development through a particular emphasis on complex stages rather than general regulatory mechanisms.

17. A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

Science.gov (United States)

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

18. Capture of microRNA-bound mRNAs identifies the tumor suppressor miR-34a as a regulator of growth factor signaling.

Directory of Open Access Journals (Sweden)

Ashish Lal

2011-11-01

Full Text Available A simple biochemical method to isolate mRNAs pulled down with a transfected, biotinylated microRNA was used to identify direct target genes of miR-34a, a tumor suppressor gene. The method reidentified most of the known miR-34a regulated genes expressed in K562 and HCT116 cancer cell lines. Transcripts for 982 genes were enriched in the pull-down with miR-34a in both cell lines. Despite this large number, validation experiments suggested that ~90% of the genes identified in both cell lines can be directly regulated by miR-34a. Thus miR-34a is capable of regulating hundreds of genes. The transcripts pulled down with miR-34a were highly enriched for their roles in growth factor signaling and cell cycle progression. These genes form a dense network of interacting gene products that regulate multiple signal transduction pathways that orchestrate the proliferative response to external growth stimuli. Multiple candidate miR-34a-regulated genes participate in RAS-RAF-MAPK signaling. Ectopic miR-34a expression reduced basal ERK and AKT phosphorylation and enhanced sensitivity to serum growth factor withdrawal, while cells genetically deficient in miR-34a were less sensitive. Fourteen new direct targets of miR-34a were experimentally validated, including genes that participate in growth factor signaling (ARAF and PIK3R2 as well as genes that regulate cell cycle progression at various phases of the cell cycle (cyclins D3 and G2, MCM2 and MCM5, PLK1 and SMAD4. Thus miR-34a tempers the proliferative and pro-survival effect of growth factor stimulation by interfering with growth factor signal transduction and downstream pathways required for cell division.

19. Capture of microRNA-bound mRNAs identifies the tumor suppressor miR-34a as a regulator of growth factor signaling.

Science.gov (United States)

Lal, Ashish; Thomas, Marshall P; Altschuler, Gabriel; Navarro, Francisco; O'Day, Elizabeth; Li, Xiao Ling; Concepcion, Carla; Han, Yoon-Chi; Thiery, Jerome; Rajani, Danielle K; Deutsch, Aaron; Hofmann, Oliver; Ventura, Andrea; Hide, Winston; Lieberman, Judy

2011-11-01

A simple biochemical method to isolate mRNAs pulled down with a transfected, biotinylated microRNA was used to identify direct target genes of miR-34a, a tumor suppressor gene. The method reidentified most of the known miR-34a regulated genes expressed in K562 and HCT116 cancer cell lines. Transcripts for 982 genes were enriched in the pull-down with miR-34a in both cell lines. Despite this large number, validation experiments suggested that ~90% of the genes identified in both cell lines can be directly regulated by miR-34a. Thus miR-34a is capable of regulating hundreds of genes. The transcripts pulled down with miR-34a were highly enriched for their roles in growth factor signaling and cell cycle progression. These genes form a dense network of interacting gene products that regulate multiple signal transduction pathways that orchestrate the proliferative response to external growth stimuli. Multiple candidate miR-34a-regulated genes participate in RAS-RAF-MAPK signaling. Ectopic miR-34a expression reduced basal ERK and AKT phosphorylation and enhanced sensitivity to serum growth factor withdrawal, while cells genetically deficient in miR-34a were less sensitive. Fourteen new direct targets of miR-34a were experimentally validated, including genes that participate in growth factor signaling (ARAF and PIK3R2) as well as genes that regulate cell cycle progression at various phases of the cell cycle (cyclins D3 and G2, MCM2 and MCM5, PLK1 and SMAD4). Thus miR-34a tempers the proliferative and pro-survival effect of growth factor stimulation by interfering with growth factor signal transduction and downstream pathways required for cell division.

20. Capture of MicroRNA–Bound mRNAs Identifies the Tumor Suppressor miR-34a as a Regulator of Growth Factor Signaling

Science.gov (United States)

O'Day, Elizabeth; Li, Xiao Ling; Concepcion, Carla; Han, Yoon-Chi; Thiery, Jerome; Rajani, Danielle K.; Deutsch, Aaron; Hofmann, Oliver; Ventura, Andrea; Hide, Winston; Lieberman, Judy

2011-01-01

A simple biochemical method to isolate mRNAs pulled down with a transfected, biotinylated microRNA was used to identify direct target genes of miR-34a, a tumor suppressor gene. The method reidentified most of the known miR-34a regulated genes expressed in K562 and HCT116 cancer cell lines. Transcripts for 982 genes were enriched in the pull-down with miR-34a in both cell lines. Despite this large number, validation experiments suggested that ∼90% of the genes identified in both cell lines can be directly regulated by miR-34a. Thus miR-34a is capable of regulating hundreds of genes. The transcripts pulled down with miR-34a were highly enriched for their roles in growth factor signaling and cell cycle progression. These genes form a dense network of interacting gene products that regulate multiple signal transduction pathways that orchestrate the proliferative response to external growth stimuli. Multiple candidate miR-34a–regulated genes participate in RAS-RAF-MAPK signaling. Ectopic miR-34a expression reduced basal ERK and AKT phosphorylation and enhanced sensitivity to serum growth factor withdrawal, while cells genetically deficient in miR-34a were less sensitive. Fourteen new direct targets of miR-34a were experimentally validated, including genes that participate in growth factor signaling (ARAF and PIK3R2) as well as genes that regulate cell cycle progression at various phases of the cell cycle (cyclins D3 and G2, MCM2 and MCM5, PLK1 and SMAD4). Thus miR-34a tempers the proliferative and pro-survival effect of growth factor stimulation by interfering with growth factor signal transduction and downstream pathways required for cell division. PMID:22102825

1. ARMOUR – A Rice miRNA: mRNA Interaction Resource

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Neeti Sanan-Mishra

2018-05-01

Full Text Available ARMOUR was developed as ARice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

2. Polymorphisms in miRNA genes and their involvement in autoimmune diseases susceptibility.

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Latini, Andrea; Ciccacci, Cinzia; Novelli, Giuseppe; Borgiani, Paola

2017-08-01

MicroRNAs (miRNAs) are small non-coding RNA molecules that negatively regulate the expression of multiple protein-encoding genes at the post-transcriptional level. MicroRNAs are involved in different pathways, such as cellular proliferation and differentiation, signal transduction and inflammation, and play crucial roles in the development of several diseases, such as cancer, diabetes, and cardiovascular diseases. They have recently been recognized to play a role also in the pathogenesis of autoimmune diseases. Although the majority of studies are focused on miRNA expression profiles investigation, a growing number of studies have been investigating the role of polymorphisms in miRNA genes in the autoimmune diseases development. Indeed, polymorphisms affecting the miRNA genes can modify the set of targets they regulate or the maturation efficiency. This review is aimed to give an overview about the available studies that have investigated the association of miRNA gene polymorphisms with the susceptibility to various autoimmune diseases and to their clinical phenotypes.

3. ARMOUR - A Rice miRNA: mRNA Interaction Resource.

Science.gov (United States)

Sanan-Mishra, Neeti; Tripathi, Anita; Goswami, Kavita; Shukla, Rohit N; Vasudevan, Madavan; Goswami, Hitesh

2018-01-01

ARMOUR was developed as A Rice miRNA:mRNA interaction resource. This informative and interactive database includes the experimentally validated expression profiles of miRNAs under different developmental and abiotic stress conditions across seven Indian rice cultivars. This comprehensive database covers 689 known and 1664 predicted novel miRNAs and their expression profiles in more than 38 different tissues or conditions along with their predicted/known target transcripts. The understanding of miRNA:mRNA interactome in regulation of functional cellular machinery is supported by the sequence information of the mature and hairpin structures. ARMOUR provides flexibility to users in querying the database using multiple ways like known gene identifiers, gene ontology identifiers, KEGG identifiers and also allows on the fly fold change analysis and sequence search query with inbuilt BLAST algorithm. ARMOUR database provides a cohesive platform for novel and mature miRNAs and their expression in different experimental conditions and allows searching for their interacting mRNA targets, GO annotation and their involvement in various biological pathways. The ARMOUR database includes a provision for adding more experimental data from users, with an aim to develop it as a platform for sharing and comparing experimental data contributed by research groups working on rice.

4. miR482 and Its Isoforms in Plants

Directory of Open Access Journals (Sweden)

Abdil Hakan EREN

2016-09-01

Full Text Available In plants, miR482 family members are generally 22-nucleotide long, distinguishing from other microRNA (miRNA families by their extraordinary and diverse sequence structures. Studies showed that miRNA482 is related to NBLRR (Nucleotide binding-site leucine-rich repeat genes conferring resistance to disease in plants. There are different coded NB-LRR genes which are considered as the part immune response assisting the recognition of pathogens in plant genomes. NB-LRR proteins are mostly related to effector – triggering immune system against pathogens. The main immune receptors in plants are PRR (Pattern recoginition receptor and R (Resistance proteins. R proteins code for immune system proteins by NB-LRR activity. miR482, miR1448, slmiR2118 and ath-miR472 are disease resistance related miRNAs. In several studies, miR482 was found to be a homolog of miR1448 and phylogenetic analyses showed that miR1448 is formed by tandem duplication of miR482. While suppression of miR482 results in plant susceptibility to pathogens, miR482 was considered to play role in nodulation and mycorrhizal processes of soya roots. Increasing evidences exhibit that miR482 is critical in disease resistance against pathogen attacks.

5. MDRL lncRNA regulates the processing of miR-484 primary transcript by targeting miR-361.

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Kun Wang

2014-07-01

Full Text Available Long noncoding RNAs (lncRNAs are emerging as new players in gene regulation, but whether lncRNAs operate in the processing of miRNA primary transcript is unclear. Also, whether lncRNAs are involved in the regulation of the mitochondrial network remains to be elucidated. Here, we report that a long noncoding RNA, named mitochondrial dynamic related lncRNA (MDRL, affects the processing of miR-484 primary transcript in nucleus and regulates the mitochondrial network by targeting miR-361 and miR-484. The results showed that miR-361 that predominantly located in nucleus can directly bind to primary transcript of miR-484 (pri-miR-484 and prevent its processing by Drosha into pre-miR-484. miR-361 is able to regulate mitochondrial fission and apoptosis by regulating miR-484 levels. In exploring the underlying molecular mechanism by which miR-361 is regulated, we identified MDRL and demonstrated that it could directly bind to miR-361 and downregulate its expression levels, which promotes the processing of pri-miR-484. MDRL inhibits mitochondrial fission and apoptosis by downregulating miR-361, which in turn relieves inhibition of miR-484 processing by miR-361. Our present study reveals a novel regulating model of mitochondrial fission program which is composed of MDRL, miR-361 and miR-484. Our work not only expands the function of the lncRNA pathway in gene regulation but also establishes a new mechanism for controlling miRNA expression.

6. Cell type-specific deficiency of c-kit gene expression in mutant mice of mi/mi genotype.

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Isozaki, K.; Tsujimura, T.; Nomura, S.; Morii, E.; Koshimizu, U.; Nishimune, Y.; Kitamura, Y.

1994-01-01

The mi locus of mice encodes a novel member of the basic-helix-loop-helix-leucine zipper protein family of transcription factors (hereafter called mi factor). In addition to microphthalmus, osteopetrosis, and lack of melanocytes, mice of mi/mi genotype are deficient in mast cells. Since the c-kit receptor tyrosine kinase plays an important role in the development of mast cells, and since the c-kit expression by cultured mast cells from mi/mi mice is deficient in both mRNA and protein levels, the mast cell deficiency of mi/mi mice has been attributed at least in part to the deficient expression of c-kit. However, it remained to be examined whether the c-kit expression was also deficient in tissues of mi/mi mice. In the present study, we examined the c-kit expression by mi/mi skin mast cells using in situ hybridization and immunohistochemistry. Moreover, we examined the c-kit expression by various cells other than mast cells in tissues of mi/mi mice. We found that the c-kit expression was deficient in mast cells but not in erythroid precursors, testicular germ cells, and neurons of mi/mi mice. This suggested that the regulation of the c-kit transcription by the mi factor was dependent on cell types. Mice of mi/mi genotype appeared to be a useful model to analyze the function of transcription factors in the whole-animal level. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 PMID:7524330

7. A meta-analytic review of the association between two common SNPs in miRNAs and lung cancer susceptibility.

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Xiao, Sha; Sun, Songzan; Long, Wenfang; Kuang, Shicheng; Liu, Yunru; Huang, Hairong; Zhou, Jing; Zhou, Yongjiang; Lu, Xiaobo

2018-01-01

MicroRNAs (miRNAs) are involved in many biological processes, including tumor suppression. Multiple studies have shown an association between the miRNA-196a2 rs11614913 and miRNA-146a rs2910164 polymorphisms and cancer risk. However, the implications of the reported data are debatable and inconclusive. Relevant articles were retrieved from the PubMed, EMBASE, China National Knowledge Infrastructure, and WanFang databases from January 1, 2007, to April 30, 2017. Studies were assessed based on designated inclusion and exclusion criteria, and data were manually extracted from relevant studies by two investigators. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to explore the association between two single-nucleotide polymorphisms (SNPs) in miRNAs and lung cancer susceptibility. Nine eligible articles were included, consisting of 3,101 cancer cases and 3,234 controls for miRNA-196a2 rs11614913, and 3,483 cases and 3,578 controls for miRNA-146a rs2910164. For studies evaluating miRNA-196a2 rs11614913, significant associations with lung cancer risk were discovered. Overall, the pooled analysis showed that miRNA-196a2 rs11614913 was associated with a decreased cancer risk (CC vs TT: OR = 1.25, 95% CI: 1.09-1.44; CT vs TT: OR = 1.26, 95% CI: 1.03-1.53). For miRNA-146a rs2910164, only the CC genotype was found to be associated with high lung cancer risk (OR = 1.30, 95% CI: 1.13-1.49). Subgroup analyses based on ethnicity, source of control group, and country indicated that there were strong associations between miRNA-146a rs2910164 and cancer risk. The results indicated that lung cancer risk was significantly associated with miRNA-196a2 rs11614913 and miRNA-146a rs2910164. These two common SNPs in miRNAs may be potential biomarkers of lung cancer.

8. In silico identification of miRNAs and their target genes and analysis of gene co-expression network in saffron (Crocus sativus L.) stigma

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Zinati, Zahra; Shamloo-Dashtpagerdi, Roohollah; Behpouri, Ali

2016-01-01

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characterization of miRNAs along with the corresponding target genes in C. sativus might expand our perspectives on the roles of miRNAs in carotenoid/apocarotenoid biosynthetic pathway. A computational analysis was used to identify miRNAs and their targets using EST (Expressed Sequence Tag) library from mature saffron stigmas. Then, a gene co- expression network was constructed to identify genes which are potentially involved in carotenoid/apocarotenoid biosynthetic pathways. EST analysis led to the identification of two putative miRNAs (miR414 and miR837-5p) along with the corresponding stem- looped precursors. To our knowledge, this is the first report on miR414 and miR837-5p in C. sativus. Co-expression network analysis indicated that miR414 and miR837-5p may play roles in C. sativus metabolic pathways and led to identification of candidate genes including six transcription factors and one protein kinase probably involved in carotenoid/apocarotenoid biosynthetic pathway. Presence of transcription factors, miRNAs and protein kinase in the network indicated multiple layers of regulation in saffron stigma. The candidate genes from this study may help unraveling regulatory networks underlying the carotenoid/apocarotenoid biosynthesis in saffron and designing metabolic engineering for enhanced secondary metabolites. PMID:28261627

9. miR-7 and miR-218 epigenetically control tumor suppressor genes RASSF1A and Claudin-6 by targeting HoxB3 in breast cancer

International Nuclear Information System (INIS)

Li, Qiaoyan; Zhu, Fufan; Chen, Puxiang

2012-01-01

Highlights: ► Both miR-7 and miR-218 down-regulates HoxB3 expression by targeting the 3′-UTR of HoxB3 mRNA. ► A reverse correlation between the levels of endogenous miR-7, miR218 and HoxB3 expression. ► Epigenetic changes involve in the reactivation of HoxB3. ► Both miRNAs inhibits the cell cycle and clone formation of breast cancer cells. -- Abstract: Many microRNAs have been implicated as key regulators of cellular growth and differentiation and have been found to dysregulate proliferation in human tumors, including breast cancer. Cancer-linked microRNAs also alter the epigenetic landscape by way of DNA methylation and post-translational modifications of histones. Aberrations in Hox gene expression are important for oncogene or tumor suppressor during abnormal development and malignancy. Although recent studies suggest that HoxB3 is critical in breast cancer, the putative role(s) of microRNAs impinging on HoxB3 is not yet fully understood. In this study, we found that the expression levels of miR-7 and miR-218 were strongly and reversely associated with HoxB3 expression. Stable overexpression of miR-7 and miR-218 was accompanied by reactivation of tumor suppressor genes including RASSF1A and Claudin-6 by means of epigenetic switches in DNA methylation and histone modification, giving rise to inhibition of the cell cycle and clone formation of breast cancer cells. The current study provides a novel link between overexpression of collinear Hox genes and multiple microRNAs in human breast malignancy.

10. Multiple intelligences in school

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Alejandro Castro Solano

2016-02-01

Full Text Available During many years has prevailed the idea of intelligence as a single problem solving ability (factor g considered the best predictor of student’s academic achievement. Recently, researches have begun to take an alternative view of the problem, understanding it is a multidimensional construct. Multiple intelligences (MI theory proposed by Gardner (1983 takes into account seven talents or skills individuals appear to have in certain amount. These latent bio-psychological potentials are stable and they are mantained through life. Theory of MI proposes that every person learns in relation to them. MI theory has many educational applications, however, very few efforts have been made to verify such statements. The main goal of this study is to analyze the IM differential individual profile of high school and university students studying the relation between IM, academic achievement and self efficacy competence on course performance. Two studies were carried out , the first was done with high school students (N=500 and the second with military students (N=362. Based on Armstrong’s proposals to assess IM, an inventory was designed. Main results point out that there is a correspondence between academic attainment, self interest and self perception of competence in different courses students take. MI are good predictors of academic achievement considering specific areas but they don’t provide a better estimation compared to traditional assessment instruments. Students who have failed in school were those with more spatial and corporal abilities, usually relegated by traditional instruction. High achievers were those with more logical and intrapersonal skills. Different relations were found for military students. For these latter students IM theory was not a valuable predictor of successful academic attainment.

11. Characterization of the Merkel Cell Carcinoma miRNome

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Matthew S. Ning

2014-01-01

Full Text Available MicroRNAs have been implicated in various skin cancers, including melanoma, squamous cell carcinoma, and basal cell carcinoma; however, the expression of microRNAs and their role in Merkel cell carcinoma (MCC have yet to be explored in depth. To identify microRNAs specific to MCC (MCC-miRs, next-generation sequencing (NGS of small RNA libraries was performed on different tissue samples including MCCs, other cutaneous tumors, and normal skin. Comparison of the profiles identified several microRNAs upregulated and downregulated in MCC. For validation, their expression was measured via qRT-PCR in a larger group of MCC and in a comparison group of non-MCC cutaneous tumors and normal skin. Eight microRNAs were upregulated in MCC: miR-502-3p, miR-9, miR-7, miR-340, miR-182, miR-190b, miR-873, and miR-183. Three microRNAs were downregulated: miR-3170, miR-125b, and miR-374c. Many of these MCC-miRs, the miR-183/182/96a cistron in particular, have connections to tumorigenic pathways implicated in MCC pathogenesis. In situ hybridization confirmed that the highly expressed MCC-miR, miR-182, is localized within tumor cells. Furthermore, NGS and qRT-PCR reveal that several of these MCC-miRs are highly expressed in the patient-derived MCC cell line, MS-1. These data indicate that we have identified a set of MCC-miRs with important implications for MCC research.

12. Prediction of target genes for miR-140-5p in pulmonary arterial hypertension using bioinformatics methods.

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Li, Fangwei; Shi, Wenhua; Wan, Yixin; Wang, Qingting; Feng, Wei; Yan, Xin; Wang, Jian; Chai, Limin; Zhang, Qianqian; Li, Manxiang

2017-12-01

The expression of microRNA (miR)-140-5p is known to be reduced in both pulmonary arterial hypertension (PAH) patients and monocrotaline-induced PAH models in rat. Identification of target genes for miR-140-5p with bioinformatics analysis may reveal new pathways and connections in PAH. This study aimed to explore downstream target genes and relevant signaling pathways regulated by miR-140-5p to provide theoretical evidences for further researches on role of miR-140-5p in PAH. Multiple downstream target genes and upstream transcription factors (TFs) of miR-140-5p were predicted in the analysis. Gene ontology (GO) enrichment analysis indicated that downstream target genes of miR-140-5p were enriched in many biological processes, such as biological regulation, signal transduction, response to chemical stimulus, stem cell proliferation, cell surface receptor signaling pathways. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis found that downstream target genes were mainly located in Notch, TGF-beta, PI3K/Akt, and Hippo signaling pathway. According to TF-miRNA-mRNA network, the important downstream target genes of miR-140-5p were PPI, TGF-betaR1, smad4, JAG1, ADAM10, FGF9, PDGFRA, VEGFA, LAMC1, TLR4, and CREB. After thoroughly reviewing published literature, we found that 23 target genes and seven signaling pathways were truly inhibited by miR-140-5p in various tissues or cells; most of these verified targets were in accordance with our present prediction. Other predicted targets still need further verification in vivo and in vitro .

13. Hotair mediates hepatocarcinogenesis through suppressing miRNA-218 expression and activating P14 and P16 signaling.

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Fu, Wei-Ming; Zhu, Xiao; Wang, Wei-Mao; Lu, Ying-Fei; Hu, Bao-Guang; Wang, Hua; Liang, Wei-Cheng; Wang, Shan-Shan; Ko, Chun-Hay; Waye, Mary Miu-Yee; Kung, Hsiang-Fu; Li, Gang; Zhang, Jin-Fang

2015-10-01

Long non-coding RNA Hotair has been considered as a pro-oncogene in multiple cancers. Although there is emerging evidence that reveals its biological function and the association with clinical prognosis, the precise mechanism remains largely elusive. We investigated the function and mechanism of Hotair in hepatocellular carcinoma (HCC) cell models and a xenograft mouse model. The regulatory network between miR-218 and Hotair was elucidated by RNA immunoprecipitation and luciferase reporter assays. Finally, the correlation between Hotair, miR-218 and the target gene Bmi-1 were evaluated in 52 paired HCC specimens. In this study, we reported that Hotair negatively regulated miR-218 expression in HCC, which might be mediated through an EZH2-targeting-miR-218-2 promoter regulatory axis. Further investigation revealed that Hotair knockdown dramatically inhibited cell viability and induced G1-phase arrest in vitro and suppressed tumorigenicity in vivo by promoting miR-218 expression. Oncogene Bmi-1 was shown to be a functional target of miR-218, and the main downstream targets signaling, P16(Ink4a) and P14(ARF), were activated in Hotair-suppressed tumorigenesis. In primary human HCC specimens, Hotair and Bmi-1 were concordantly upregulated whereas miR-218 was downregulated in these tissues. Furthermore, Hotair was inversely associated with miR-218 expression and positively correlated with Bmi-1 expression in these clinical tissues. Hotair silence activates P16(Ink4a) and P14(ARF) signaling by enhancing miR-218 expression and suppressing Bmi-1 expression, resulting in the suppression of tumorigenesis in HCC. Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

14. miReg: a resource for microRNA regulation

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Barh Debmalya

2010-03-01

Full Text Available MicroRNAs (miRNAs/miRs are important cellular components that regulate gene expression at posttranscriptional level. Various upstream components regulate miR expression and any deregulation causes disease conditions. Therefore, understanding of miR regulatory network both at upstream and downstream level is crucial and a resource on this aspect will be helpful. Currently available miR databases are mostly related to downstream targets, sequences, or diseases. But as of now, no database is available that provides a complete picture of miR regulation in a specific condition.

15. Evaluation of miR-21 and miR-375 as prognostic biomarkers in esophageal cancer

DEFF Research Database (Denmark)

Winther, Mette; Alsner, Jan; Tramm, Trine

2015-01-01

analyses identified miR-21 as an independent prognostic marker for DSS in EAC [HR 3.52 (95% CI 1.06-11.69)]. High miR-375 was not correlated with improved prognosis in either histology. However, Forest plots demonstrated that both miR-21 and miR-375 were of prognostic impact in ESCC. CONCLUSION...... chemotherapy were analyzed. Expression levels of miR-21 and miR-375 were quantified using Affymetrix GeneChip miRNA 1.0 Array. The Cox proportional hazards model was used to assess the correlation of miR-21 and miR-375 with disease-specific survival (DSS) and overall survival (OS). Forest plots were performed...... to evaluate the prognostic impact of miR-21 and miR-375 in the present study and previously published reports. RESULTS: In ESCC, patients with miR-21 expression levels above median showed a trend towards poorer DSS and OS. When dividing miR-21 expression by tertiles, high levels of miR-21 significantly...

16. Evaluation of miR-122 as a Serum Biomarker for Hepatotoxicity in Investigative Rat Toxicology Studies.

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Sharapova, T; Devanarayan, V; LeRoy, B; Liguori, M J; Blomme, E; Buck, W; Maher, J

2016-01-01

MicroRNAs are short noncoding RNAs involved in regulation of gene expression. Certain microRNAs, including miR-122, seem to have ideal properties as biomarkers due to good stability, high tissue specificity, and ease of detection across multiple species. Recent reports have indicated that miR-122 is a highly liver-specific marker detectable in serum after liver injury. The purpose of the current study was to assess the performance of miR-122 as a serum biomarker for hepatotoxicity in short-term (5-28 days) repeat-dose rat toxicology studies when benchmarked against routine clinical chemistry and histopathology. A total of 23 studies with multiple dose levels of experimental compounds were examined, and they included animals with or without liver injury and with various hepatic histopathologic changes. Serum miR-122 levels were quantified by reverse transcription quantitative polymerase chain reaction. Increases in circulating miR-122 levels highly correlated with serum elevations of liver enzymes, such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) and glutamate dehydrogenase (GLDH). Statistical analysis showed that miR-122 outperformed ALT as a biomarker for histopathologically confirmed liver toxicity and was equivalent in performance to AST and GLDH. Additionally, an increase of 4% in predictive accuracy was obtained using a multiparameter approach incorporating miR-122 with ALT, AST, and GLDH. In conclusion, serum miR-122 levels can be utilized as a biomarker of hepatotoxicity in acute and subacute rat toxicology studies, and its performance can rival or exceed those of standard enzyme biomarkers such as the liver transaminases. © The Author(s) 2015.

17. miR-371, miR-138, miR-544, miR-145, and miR-214 could modulate Th1/Th2 balance in asthma through the combinatorial regulation of Runx3.

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Qiu, Yu-Ying; Zhang, Ying-Wei; Qian, Xiu-Fen; Bian, Tao

2017-01-01

Asthma is tightly related to the imbalance of Th1/Th2 cells, and Runx3 plays a pivotal role in the differentiation of T helper cells. The present study aimed to investigate dysregulated microRNAs that may target Runx3 in CD4 + T cells from asthmatic patients and reveal Runx3 function in Th1/Th2 balance regulation. We detected the levels of Th1- and Th2-related cytokines by ELISA and analyzed the differentiation marker gene of T helper cells by qRT-PCR. Results indicated that an imbalance of Th1/Th2 cells was present in our asthmatic subject. Runx3 expression was reduced in the CD4 + T cells from asthmatic patients. Overexpression of Runx3 could restore the Th1/Th2 balance. After performing microRNA microarray assay, we found a series of microRNAs that were considerably altered in the CD4 + T cells from asthmatic patients. Among these upregulated microRNAs, eight microRNAs that may target Runx3 were selected by bioinformatics prediction. Five microRNAs, namely miR-371, miR-138, miR-544, miR-145, and miR-214, were confirmed by qRT-PCR and selected as candidate microRNAs. Luciferase reporter assay showed that these five microRNAs could directly target the 3'-UTR of Runx3. However, only simultaneous inhibition of these five microRNAs could alter the expression of Runx3. Most importantly, only simultaneous inhibition could improve the Th1/Th2 balance. Thus, we suggest that miR-371, miR-138, miR-544, miR-145, and miR-214 can modulate the Th1/Th2 balance in asthma by regulating Runx3 in a combinatorial manner.

18. miR-24 inhibits cell proliferation by suppressing expression of E2F2, MYC and other cell cycle regulatory genes by binding to “seedless” 3′UTR microRNA recognition elements

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Lal, Ashish; Navarro, Francisco; Maher, Christopher; Maliszewski, Laura E.; Yan, Nan; O'Day, Elizabeth; Chowdhury, Dipanjan; Dykxhoorn, Derek M.; Tsai, Perry; Hofman, Oliver; Becker, Kevin G.; Gorospe, Myriam; Hide, Winston; Lieberman, Judy

2009-01-01

Summary miR-24, up-regulated during terminal differentiation of multiple lineages, inhibits cell cycle progression. Antagonizing miR-24 restores post-mitotic cell proliferation and enhances fibroblast proliferation, while over-expressing miR-24 increases the G1 compartment. The 248 mRNAs down-regulated upon miR-24 over-expression are highly enriched for DNA repair and cell cycle regulatory genes that form a direct interaction network with prominent nodes at genes that enhance (MYC, E2F2, CCNB1, CDC2) or inhibit (p27Kip1, VHL) cell cycle progression. miR-24 directly regulates MYC and E2F2 and some genes they transactivate. Enhanced proliferation from antagonizing miR-24 is abrogated by knocking down E2F2, but not MYC, and cell proliferation, inhibited by miR-24 over-expression, is rescued by miR-24-insensitive E2F2. Therefore, E2F2 is a critical miR-24 target. The E2F2 3′UTR lacks a predicted miR-24 recognition element. In fact, miR-24 regulates expression of E2F2, MYC, AURKB, CCNA2, CDC2, CDK4 and FEN1 by recognizing seedless, but highly complementary, sequences. PMID:19748357

19. A path-based measurement for human miRNA functional similarities using miRNA-disease associations

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Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

20. EL CIRCO Y MI DILEMA

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