Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.
2009-01-01
Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078
A combination test for detection of gene-environment interaction in cohort studies.
Coombes, Brandon; Basu, Saonli; McGue, Matt
2017-07-01
Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.
Confirmatory and Competitive Evaluation of Alternative Gene-Environment Interaction Hypotheses
ERIC Educational Resources Information Center
Belsky, Jay; Pluess, Michael; Widaman, Keith F.
2013-01-01
Background: Most gene-environment interaction (GXE) research, though based on clear, vulnerability-oriented hypotheses, is carried out using exploratory rather than hypothesis-informed statistical tests, limiting power and making formal evaluation of competing GXE propositions difficult. Method: We present and illustrate a new regression technique…
A Nonlinear Model for Gene-Based Gene-Environment Interaction.
Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua
2016-06-04
A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.
Cook, C. Justin; Fletcher, Jason M.
2013-01-01
A large literature links early environments and later outcomes, such as cognition; however, little is known about the mechanisms. One potential mechanism is sensitivity to early environments that is moderated or amplified by the genotype. With this mechanism in mind, a complementary literature outside economics examines the interaction between genes and environments, but often problems of endogeneity and bias in estimation are uncorrected. A key issue in the literature is exploring environmental variation that is not exogenous, which is potentially problematic if there are gene-environment correlation or gene-gene interactions. Using sibling pairs with genetic data in the Wisconsin Longitudinal Study we extend a previous, and widely cited, gene-environment study that explores an interaction between the FADS2 gene, which is associated with the processing of essential fatty acids related to cognitive development, and early life nutrition in explaining later-life IQ. Our base OLS findings suggest that individuals with specific FADS2 variants gain roughly 0.15 standard deviations in IQ for each standard deviation increase in birth weight, our measure of the early nutrition environment; while, individuals with other variants of FADS2 do not have a statistically significant association with early nutrition, implying the genotype is influencing the effects of environmental exposure. When including family-level fixed effects, however, the magnitude of the gene-environment interaction is reduced by half and statistical significance dissipates, implying the interaction between FADS2 and early nutrition in explaining later life IQ may in part be due to unobserved, family-level factors. The example has wider implications for the practice of investigating gene-environment interactions when the environmental exposure is not exogenous and robustness to unobserved variation in the genome is not controlled for in the analysis. PMID:24172871
Gene-Environment Interactions in Cardiovascular Disease
Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.
2011-01-01
Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212
Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.
2008-01-01
Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621
Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C
2009-01-01
Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.
Oh, Behave! Behavior as an Interaction between Genes & the Environment
ERIC Educational Resources Information Center
Weigel, Emily G.; DeNieu, Michael; Gall, Andrew J.
2014-01-01
This lesson is designed to teach students that behavior is a trait shaped by both genes and the environment. Students will read a scientific paper, discuss and generate predictions based on the ideas and data therein, and model the relationships between genes, the environment, and behavior. The lesson is targeted to meet the educational goals of…
Faith, Myles S
2008-12-01
This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.
Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models
USDA-ARS?s Scientific Manuscript database
Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...
Fletcher, Jason M
2014-01-01
This article uses a gene-environment interaction framework to examine the differential responses to an objective external stressor based on genetic variation in the production of depressive symptoms. This article advances the literature by utilizing a quasi-experimental environmental exposure design, as well as a regression discontinuity design, to control for seasonal trends, which limit the potential for gene-environment correlation and allow stronger causal claims. Replications are attempted for two prominent genes (5-HTT and MAOA), and three additional genes are explored (DRD2, DRD4, and DAT1). This article provides evidence of a main effect of 9/11 on reports of feelings of sadness and fails to replicate a common finding of interaction using 5-HTT but does show support for interaction with MAOA in men. It also provides new evidence that variation in the DRD4 gene modifies an individual's response to the exposure, with individuals with no 7-repeats found to have a muted response.
Incorporating gene-environment interaction in testing for association with rare genetic variants.
Chen, Han; Meigs, James B; Dupuis, Josée
2014-01-01
The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.
Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud
2017-12-01
Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes interact differently with particular aspects of parenting. This accentuates the importance of polygenic approaches and the need to accurately assess environmental exposure in G × E. © 2017 Association for Child and Adolescent Mental Health.
Lanktree, Matthew B; Hegele, Robert A
2009-02-26
Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.
Gene-environment studies: any advantage over environmental studies?
Bermejo, Justo Lorenzo; Hemminki, Kari
2007-07-01
Gene-environment studies have been motivated by the likely existence of prevalent low-risk genes that interact with common environmental exposures. The present study assessed the statistical advantage of the simultaneous consideration of genes and environment to investigate the effect of environmental risk factors on disease. In particular, we contemplated the possibility that several genes modulate the environmental effect. Environmental exposures, genotypes and phenotypes were simulated according to a wide range of parameter settings. Different models of gene-gene-environment interaction were considered. For each parameter combination, we estimated the probability of detecting the main environmental effect, the power to identify the gene-environment interaction and the frequency of environmentally affected individuals at which environmental and gene-environment studies show the same statistical power. The proportion of cases in the population attributable to the modeled risk factors was also calculated. Our data indicate that environmental exposures with weak effects may account for a significant proportion of the population prevalence of the disease. A general result was that, if the environmental effect was restricted to rare genotypes, the power to detect the gene-environment interaction was higher than the power to identify the main environmental effect. In other words, when few individuals contribute to the overall environmental effect, individual contributions are large and result in easily identifiable gene-environment interactions. Moreover, when multiple genes interacted with the environment, the statistical benefit of gene-environment studies was limited to those studies that included major contributors to the gene-environment interaction. The advantage of gene-environment over plain environmental studies also depends on the inheritance mode of the involved genes, on the study design and, to some extend, on the disease prevalence.
Environmental confounding in gene-environment interaction studies.
Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar
2013-07-01
We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.
A Penalized Robust Method for Identifying Gene-Environment Interactions
Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge
2015-01-01
In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063
A novel approach to simulate gene-environment interactions in complex diseases.
Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio
2010-01-05
Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.
Cicchetti, Dante; Rogosch, Fred A.
2013-01-01
In this investigation, gene-environment interaction effects in predicting resilience in adaptive functioning among maltreated and nonmaltreated low-income children (N = 595) were examined. A multi-component index of resilient functioning was derived and levels of resilient functioning were identified. Variants in four genes, 5-HTTLPR, CRHR1, DRD4 -521C/T, and OXTR, were investigated. In a series of ANCOVAs, child maltreatment demonstrated a strong negative main effect on children’s resilient functioning, whereas no main effects for any of the genotypes of the respective genes were found. However, gene-environment interactions involving genotypes of each of the respective genes and maltreatment status were obtained. For each respective gene, among children with a specific genotype, the relative advantage in resilient functioning of nonmaltreated compared to maltreated children was stronger than was the case for nonmaltreated and maltreated children with other genotypes of the respective gene. Across the four genes, a composite of the genotypes that more strongly differentiated resilient functioning between nonmaltreated and maltreated children provided further evidence of genetic variations influencing resilient functioning in nonmaltreated children, whereas genetic variation had a negligible effect on promoting resilience among maltreated children. Additional effects were observed for children based on the number of subtypes of maltreatment children experienced, as well as for abuse and neglect subgroups. Finally, maltreated and nonmaltreated children with high levels of resilience differed in their average number of differentiating genotypes. These results suggest that differential resilient outcomes are based on the interaction between genes and developmental experiences. PMID:22559122
Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.
Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar
2014-01-01
Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.
Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice
Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar
2014-01-01
Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945
Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza
2017-09-27
Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.
Gene-environment interactions in mental disorders
Tsuang, Ming T; Bar, Jessica L; Stone, William S; Faraone, Stephen V
2004-01-01
Research clearly shows that both nature and nurture play important roles in the genesis of psychopathology. In this paper, we focus on 'gene-environment interaction' in mental disorders, using genetic control of sensitivity to the environment as our definition of that term. We begin with an examination of methodological issues involving gene-environment interactions, with examples concerning psychiatric and neurological conditions. Then we review the interactions in psychiatric disorders using twin, adoption and association designs. Finally, we consider gene-environment interactions in selected neurodevelopmental disorders (autism and schizophrenia). PMID:16633461
A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies
Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.
2008-01-01
Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969
Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro
2018-02-16
For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p < 0.05), on MTHFR C677T , MTR A2756G , MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05) except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike's information criterion and leave-one-out cross validation methods. Body mass index (BMI) and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene-environment interactions in the prevention of CRC.
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.
Lynch, Michael; Manly, Jody Todd; Cicchetti, Dante
2015-11-01
Physiological response to stress has been linked to a variety of healthy and pathological conditions. The current study conducted a multilevel examination of interactions among environmental toxins (i.e., neighborhood crime and child maltreatment) and specific genetic polymorphisms of the endothelial nitric oxide synthase gene (eNOS) and GABA(A) receptor subunit alpha-6 gene (GABRA6). One hundred eighty-six children were recruited at age 4. The presence or absence of child maltreatment as well as the amount of crime that occurred in their neighborhood during the previous year were determined at that time. At age 9, the children were brought to the lab, where their physiological response to a cognitive challenge (i.e., change in the amplitude of the respiratory sinus arrhythmia) was assessed and DNA samples were collected for subsequent genotyping. The results confirmed that complex Gene × Gene, Environment × Environment, and Gene × Environment interactions were associated with different patterns of respiratory sinus arrhythmia reactivity. The implications for future research and evidence-based intervention are discussed.
Robustness of meta-analyses in finding gene × environment interactions
Shi, Gang; Nehorai, Arye
2017-01-01
Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796
Kitchen, James L.; Allaby, Robin G.
2013-01-01
Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364
Gene-environment interaction and suicidal behavior.
Roy, Alec; Sarchiopone, Marco; Carli, Vladimir
2009-07-01
Studies have increasingly shown that gene-environment interactions are important in psychiatry. Suicidal behavior is a major public health problem. Suicide is generally considered to be a multi-determined act involving various areas of proximal and distal risk. Genetic risk factors are estimated to account for approximately 30% to 40% of the variance in suicidal behavior. In this article, the authors review relevant studies concerning the interaction between the serotonin transporter gene and environmental variables as a model of gene-environment interactions that may have an impact on suicidal behavior. The findings reviewed here suggest that there may be meaningful interactions between distal and proximal suicide risk factors that may amplify the risk of suicidal behavior. Future studies of suicidal behavior should examine both genetic and environmental variables and examine for gene-environment interactions.
Jokela, Markus; Lehtimäki, Terho; Keltikangas-Järvinen, Liisa
2007-10-05
Gene-environment interactions are thought to be involved in the development of depression. Here we examined the interaction effect between urban/rural residency and the serotonin receptor 2A (HTR2A) gene on subclinical depressive symptoms. The participants were 1,224 Finnish men and women being followed in the on-going population-based study of "Cardiovascular Risk in Young Finns". Urban/rural residency was determined on the basis of a (1) subjective report and (2) the population density of the residential area. Depressive symptoms were measured in two test settings four years apart. There was a significant gene-environment interaction, such that the urban residency was associated with low depressive symptoms in individuals carrying the T/T or T/C genotype of the T102C polymorphism, but not in those carrying the C/C genotype. The T allele was associated with high depressive symptoms in remote rural areas, but with low depressive symptoms in urban or suburban areas. The gene-environment interaction was not accounted by level of education, social support, unemployment, or partnership status. The HTR2A gene may be involved in the development of depression by influencing how individuals respond to environmental conditions. (c) 2007 Wiley-Liss, Inc.
Measured Gene-by-Environment Interaction in Relation to Attention-Deficit/Hyperactivity Disorder
ERIC Educational Resources Information Center
Nigg, Joel; Nikolas, Molly; Burt, S. Alexandra
2010-01-01
Objective: To summarize and evaluate the state of knowledge regarding the role of measured gene-by-environment interactions in relation to attention-deficit/hyperactivity disorder. Method: A selective review of methodologic issues was followed by a systematic search for relevant articles on measured gene-by-environment interactions; the search…
Design and analysis issues in gene and environment studies
2012-01-01
Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the “-omics” era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed. PMID:23253229
Design and analysis issues in gene and environment studies.
Liu, Chen-yu; Maity, Arnab; Lin, Xihong; Wright, Robert O; Christiani, David C
2012-12-19
Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.
Detecting regulatory gene-environment interactions with unmeasured environmental factors.
Fusi, Nicoló; Lippert, Christoph; Borgwardt, Karsten; Lawrence, Neil D; Stegle, Oliver
2013-06-01
Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits. In extensive simulation studies, we show that our method is able to accurately reconstruct environmental factors and their interactions with genotype in a variety of settings. We further illustrate the use of our model in a real-world dataset in which one environmental factor has been explicitly experimentally controlled. Our method is able to accurately reconstruct the true underlying environmental factor even if it is not given as an input, allowing to detect genuine genotype-environment interactions. In addition to the known environmental factor, we find unmeasured factors involved in novel genotype-environment interactions. Our results suggest that interactions with both known and unknown environmental factors significantly contribute to gene expression variability. and implementation: Software available at http://pmbio.github.io/envGPLVM/. Supplementary data are available at Bioinformatics online.
Why study gene-environment interactions?
USDA-ARS?s Scientific Manuscript database
PURPOSE OF REVIEW: We examine the reasons for investigating gene-environment interactions and address recent reports evaluating interactions between genes and environmental modulators in relation to cardiovascular disease and its common risk factors. RECENT FINDINGS: Studies focusing on smoking, phy...
Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom
2006-12-01
In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.
Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D
2013-01-01
Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.
A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.
Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying
2015-09-01
Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.
Simons, Ronald L.; Lei, Man Kit; Beach, Steven R.H.; Brody, Gene H.; Philibert, Robert A.; Gibbons, Frederick X.
2011-01-01
Although G×E studies are typically based on the assumption that some individuals possess genetic variants that enhance their vulnerability to environmental adversity, the differential susceptibility perspective posits that these individuals are simply more susceptible to environmental influence than others. An important implication of this model is that those persons most vulnerable to adverse social environments are the same ones who reap the most benefit from environmental support. The present study tested several implications of this proposition. Using longitudinal data from a sample of several hundred African Americans, we found that relatively common variants of the dopamine receptor gene and the serotonin transporter gene interact with social environmental conditions to predict aggression in a manner consonant with differential susceptibility. When the social environment was adverse, individuals with these genetic variants manifested more aggression than other genotypes, whereas when the environment was supportive they demonstrated less aggression than other genotypes. Further, we found that these genetic variants interact with environmental conditions to foster various cognitive schemas and emotions in a manner consistent with differential susceptibility and that a latent construct formed by these schemas and emotions mediated the effect of gene by environment interaction on aggression. PMID:22199399
Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun
2017-01-01
Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
The genetics of human longevity: an intricacy of genes, environment, culture and microbiome.
Dato, Serena; Rose, Giuseppina; Crocco, Paolina; Monti, Daniela; Garagnani, Paolo; Franceschi, Claudio; Passarino, Giuseppe
2017-07-01
Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. However, even large population based studies investigating genetic influence on human lifespan have been disappointing, identifying only a few genes accounting for genetic susceptibility to longevity. Some environmental and lifestyle determinants associated with longevity have been identified, which interplay with genetic factors in an intricate way. The study of gene-environment and gene-gene interactions can significantly improve our chance to disentangle this complex scenario. In this review, we first describe the most recent approaches for genetic studies of longevity, from those enriched with health parameters and frailty measures to pathway-based and SNP-SNP interaction analyses. Then, we go deeper into the concept of "environmental influences" in human aging and longevity, focusing on the contribution of life style changes, social and cultural influences, as important determinants of survival differences among individuals in a population. Finally, we discuss the contribution of the microbiome in human longevity, as an example of complex interaction between organism and environment. In conclusion, evidences collected from the latest studies on human longevity provide a support for the collection of life-long genetic and environmental/lifestyle variables with beneficial or detrimental effects on health, to improve our understanding of the determinants of human lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.
van Os, Jim; Rutten, Bart PF; Poulton, Richie
2008-01-01
Concern is building about high rates of schizophrenia in large cities, and among immigrants, cannabis users, and traumatized individuals, some of which likely reflects the causal influence of environmental exposures. This, in combination with very slow progress in the area of molecular genetics, has generated interest in more complicated models of schizophrenia etiology that explicitly posit gene-environment interactions (EU-GEI. European Network of Schizophrenia Networks for the Study of Gene Environment Interactions. Schizophrenia aetiology: do gene-environment interactions hold the key? [published online ahead of print April 25, 2008] Schizophr Res; S0920-9964(08) 00170–9). Although findings of epidemiological gene-environment interaction (G × E) studies are suggestive of widespread gene-environment interactions in the etiology of schizophrenia, numerous challenges remain. For example, attempts to identify gene-environment interactions cannot be equated with molecular genetic studies with a few putative environmental variables “thrown in”: G × E is a multidisciplinary exercise involving epidemiology, psychology, psychiatry, neuroscience, neuroimaging, pharmacology, biostatistics, and genetics. Epidemiological G × E studies using indirect measures of genetic risk in genetically sensitive designs have the advantage that they are able to model the net, albeit nonspecific, genetic load. In studies using direct molecular measures of genetic variation, a hypothesis-driven approach postulating synergistic effects between genes and environment impacting on a final common pathway, such as “sensitization” of mesolimbic dopamine neurotransmission, while simplistic, may provide initial focus and protection against the numerous false-positive and false-negative results that these investigations engender. Experimental ecogenetic approaches with randomized assignment may help to overcome some of the limitations of observational studies and allow for the additional elucidation of underlying mechanisms using a combination of functional enviromics and functional genomics. PMID:18791076
2010-01-01
Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103
Leighton, Caroline; Botto, Alberto; Silva, Jaime R; Jiménez, Juan Pablo; Luyten, Patrick
2017-01-01
Research on the potential role of gene-environment interactions (GxE) in explaining vulnerability to psychopathology in humans has witnessed a shift from a diathesis-stress perspective to differential susceptibility approaches. This paper critically reviews methodological issues and trends in this body of research. Databases were screened for studies of GxE in the prediction of personality traits, behavior, and mental health disorders in humans published between January 2002 and January 2015. In total, 315 papers were included. Results showed that 34 candidate genes have been included in GxE studies. Independent of the type of environment studied (early or recent life events, positive or negative environments), about 67-83% of studies have reported significant GxE interactions, which is consistent with a social susceptibility model. The percentage of positive results does not seem to differ depending on the gene studied, although publication bias might be involved. However, the number of positive findings differs depending on the population studied (i.e., young adults vs. older adults). Methodological considerations limit the ability to draw strong conclusions, particularly as almost 90% ( n = 283/315) of published papers are based on samples from North America and Europe, and about 70% of published studies (219/315) are based on samples that were also used in other reports. At the same time, there are clear indications of methodological improvements over time, as is shown by a significant increase in longitudinal and experimental studies as well as in improved minimum genotyping. Recommendations for future research, such as minimum quality assessment of genes and environmental factors, specifying theoretical models guiding the study, and taking into account of cultural, ethnic, and lifetime perspectives, are formulated.
Chapter 20: geographic variability in growth of forest trees
Robert Z. Callaham
1962-01-01
Tree growth, like all plant characters, is a product of the interaction of genes and environment; however, the genes, environment, and interaction are not the same for every individual of a species. Genes exert master control over the plant's growth mechanisms. They control mechanisms for responding to environment and for utilizing environment in growth. Usually...
System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks
Miao, Yingbo; Zhang, Liangcai; Wang, Yang; Feng, Rennan; Yang, Lei; Zhang, Shihua; Jiang, Yongshuai; Liu, Guiyou
2014-01-01
Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM. PMID:25243143
Disentangling Gene-Environment Correlations and Interactions on Adolescent Depressive Symptoms
ERIC Educational Resources Information Center
Lau, Jennifer Y. F.; Eley, Thalia C.
2008-01-01
Background: Genetic risks for depression may be expressed through greater exposure towards environmental stressors (gene-environment correlation, rGE) and increased susceptibility to these stressors (gene-environment interaction, G x E). While these effects are often studied independently, evidence supports their co-occurrence on depression.…
McGregor, N W; Hemmings, S M J; Erdman, L; Calmarza-Font, I; Stein, D J; Lochner, C
2016-12-30
The monoamine oxidases (MAOA/B) and catechol-O-methyltransferase (COMT) enzymes break down regulatory components within serotonin and dopamine pathways, and polymorphisms within these genes are candidates for OCD susceptibility. Childhood trauma has been linked OCD psychopathology, but little attention has been paid to the interactions between genes and environment in OCD aetiology. This pilot study investigated gene-by-environment interactions between childhood trauma and polymorphisms in the MAOA, MAOB and COMT genes in OCD. Ten polymorphisms (MAOA: 3 variants, MAOB: 4 variants, COMT: 3 variants) were genotyped in a cohort of OCD patients and controls. Early-life trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Gene-by-gene (GxG) and gene-by-environment interactions (GxE) of the variants and childhood trauma were assessed using logistic regression models. Significant GxG interactions were found between rs362204 (COMT) and two independent polymorphisms in the MAOB gene (rs1799836 and rs6651806). Haplotype associations for OCD susceptibility were found for MAOB. Investigation of GxE interactions indicated that the sexual abuse sub-category was significantly associated with all three genes in haplotype x environment interaction analyses. Preliminary findings indicate that polymorphisms within the MAOB and COMT genes interact resulting in risk for OCD. Childhood trauma interacts with haplotypes in COMT, MAOA and MAOB, increasing risk for OCD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NATURE VERSUS NURTURE: DEATH OF A DOGMA, AND THE ROAD AHEAD
Traynor, Bryan J.; Singleton, Andrew B.
2010-01-01
Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions: First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. PMID:20955927
Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Iacono, William G.; McGue, Matt
2016-01-01
Gene × environment interaction contributes to externalizing disorders in adolescence, but little is known about whether such effects are long-lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a gene × environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This gene × environment interaction was not present for antisocial behavior symptoms after age 17, but was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). Results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of gene × environment interaction may persist through young adulthood for substance use disorders, but is limited to adolescence for antisocial behavior. PMID:27580681
Samek, Diana R; Hicks, Brian M; Keyes, Margaret A; Iacono, William G; McGue, Matt
2017-02-01
Gene × Environment interaction contributes to externalizing disorders in childhood and adolescence, but little is known about whether such effects are long lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a Gene × Environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This Gene × Environment interaction was not present for antisocial behavior symptoms after age 17, but it was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). The results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of Gene × Environment interaction may persist through young adulthood for substance use disorders, but it appears to be limited to adolescence for antisocial behavior.
Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L
2013-04-01
Eating behaviors and obesity are complex phenotypes influenced by genes and the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as "healthy" or "unhealthy" based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4-6 years, recruited from New York City over 2005-2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment ("healthy" vs. "unhealthy"), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (P ≤ 0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (P ≤ 0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. Copyright © 2012 The Obesity Society.
Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L.
2012-01-01
Eating behaviors and obesity are complex phenotypes influenced by genes and access to foods in the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as “healthy” or “unhealthy” based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4–6 years, recruited from New York City over 2005–2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment (“healthy” vs. “unhealthy”), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (p≤0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (p≤0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. PMID:23401219
Lobach, Iryna; Fan, Ruzong; Manga, Prashiela
A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.
ERIC Educational Resources Information Center
Chen, Jie; Li, Xinying; McGue, Matt
2013-01-01
Background: Confounding introduced by gene-environment correlation (rGE) may prevent one from observing a true gene-environment interaction (G × E) effect on psychopathology. The present study investigated the interacting effect of the BDNF Val66Met polymorphism and stressful life events (SLEs) on adolescent depression while controlling for the…
Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions
Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.
2014-01-01
We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630
Nature versus nurture: death of a dogma, and the road ahead.
Traynor, Bryan J; Singleton, Andrew B
2010-10-21
Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions. First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. Copyright © 2010 Elsevier Inc. All rights reserved.
Rava, Marta; Ahmed, Ismail; Kogevinas, Manolis; Le Moual, Nicole; Bouzigon, Emmanuelle; Curjuric, Ivan; Dizier, Marie-Hélène; Dumas, Orianne; Gonzalez, Juan R.; Imboden, Medea; Mehta, Amar J.; Tubert-Bitter, Pascale; Zock, Jan-Paul; Jarvis, Deborah; Probst-Hensch, Nicole M.; Demenais, Florence; Nadif, Rachel
2016-01-01
Background: The biological mechanisms by which cleaning products and disinfectants—an emerging risk factor—affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma. Objectives: We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma. Methods: Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway–based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons. Results: Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking. Conclusions: Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207–214; http://dx.doi.org/10.1289/EHP376 PMID:27504716
Genetic variation in biotransformation enzymes, air pollution exposures, and risk of spina bifida.
Padula, Amy M; Yang, Wei; Schultz, Kathleen; Lurmann, Fred; Hammond, S Katharine; Shaw, Gary M
2018-05-01
Spina bifida is a birth defect characterized by incomplete closure of the embryonic neural tube. Genetic factors as well as environmental factors have been observed to influence risks for spina bifida. Few studies have investigated possible gene-environment interactions that could contribute to spina bifida risk. The aim of this study is to examine the interaction between gene variants in biotransformation enzyme pathways and ambient air pollution exposures and risk of spina bifida. We evaluated the role of air pollution exposure during pregnancy and gene variants of biotransformation enzymes from bloodspots and buccal cells in a California population-based case-control (86 cases of spina bifida and 208 non-malformed controls) study. We considered race/ethnicity and folic acid vitamin use as potential effect modifiers and adjusted for those factors and smoking. We observed gene-environment interactions between each of the five pollutants and several gene variants: NO (ABCC2), NO 2 (ABCC2, SLC01B1), PM 10 (ABCC2, CYP1A1, CYP2B6, CYP2C19, CYP2D6, NAT2, SLC01B1, SLC01B3), PM 2.5 (CYP1A1 and CYP1A2). These analyses show positive interactions between air pollution exposure during early pregnancy and gene variants associated with metabolizing enzymes. These exploratory results suggest that some individuals based on their genetic background may be more susceptible to the adverse effects of pollution. © 2018 Wiley Periodicals, Inc.
Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Ågren, Åsa; Engberg, Elisabeth; Hu, Frank B.; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W.
2014-01-01
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics. PMID:25396097
Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W
2014-12-01
Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.
Lindström, Sara; Yen, Yu-Chun; Spiegelman, Donna; Kraft, Peter
2009-01-01
The possibility of gene-environment interaction can be exploited to identify genetic variants associated with disease using a joint test of genetic main effect and gene-environment interaction. We consider how exposure misclassification and dependence between the true exposure E and the tested genetic variant G affect this joint test in absolute terms and relative to three other tests: the marginal test (G), the standard test for multiplicative gene-environment interaction (GE), and the case-only test for interaction (GE-CO). All tests can have inflated Type I error rate when E and G are correlated in the underlying population. For the GE and G-GE tests this inflation is only noticeable when the gene-environment dependence is unusually strong; the inflation can be large for the GE-CO test even for modest correlation. The joint G-GE test has greater power than the GE test generally, and greater power than the G test when there is no genetic main effect and the measurement error is small to moderate. The joint G-GE test is an attractive test for assessing genetic association when there is limited knowledge about casual mechanisms a priori, even in the presence of misclassification in environmental exposure measurement and correlation between exposure and genetic variants. PMID:19521099
Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh
2018-02-01
There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Windhorst, Dafna A; Mileva-Seitz, Viara R; Rippe, Ralph C A; Tiemeier, Henning; Jaddoe, Vincent W V; Verhulst, Frank C; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J
2016-08-01
In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and gene-set approaches in tests of Gene by Environment (G × E) effects on complex behavior. This approach can offer an important alternative or complement to candidate gene and genome-wide environmental interaction (GWEI) studies in the search for genetic variation underlying individual differences in behavior. Genetic variants in 12 autosomal dopaminergic genes were available in an ethnically homogenous part of a population-based cohort. Harsh parenting was assessed with maternal (n = 1881) and paternal (n = 1710) reports at age 3. Externalizing behavior was assessed with the Child Behavior Checklist (CBCL) at age 5 (71 ± 3.7 months). We conducted gene-set analyses of the association between variation in dopaminergic genes and externalizing behavior, stratified for harsh parenting. The association was statistically significant or approached significance for children without harsh parenting experiences, but was absent in the group with harsh parenting. Similarly, significant associations between single genes and externalizing behavior were only found in the group without harsh parenting. Effect sizes in the groups with and without harsh parenting did not differ significantly. Gene-environment interaction tests were conducted for individual genetic variants, resulting in two significant interaction effects (rs1497023 and rs4922132) after correction for multiple testing. Our findings are suggestive of G × E interplay, with associations between dopamine genes and externalizing behavior present in children without harsh parenting, but not in children with harsh parenting experiences. Harsh parenting may overrule the role of genetic factors in externalizing behavior. Gene-based and gene-set analyses offer promising new alternatives to analyses focusing on single candidate polymorphisms when examining the interplay between genetic and environmental factors.
Wei, Qingyi Wei
2012-01-01
Asbestos exposure is a known risk factor for lung cancer. Although recent genome-wide association studies (GWASs) have identified some novel loci for lung cancer risk, few addressed genome-wide gene–environment interactions. To determine gene–asbestos interactions in lung cancer risk, we conducted genome-wide gene–environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using our published Texas lung cancer GWAS dataset. This dataset included 317 498 SNPs from 1154 lung cancer cases and 1137 cancer-free controls. The initial SNP-level P-values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models with adjustment for age, sex, smoking status and pack-years. The P-value for the most significant SNP rs13383928 was 2.17×10–6, which did not reach the genome-wide statistical significance. Using a versatile gene-based test approach, we found that the top significant gene was C7orf54, located on 7q32.1 (P = 8.90×10–5). Interestingly, most of the other significant genes were located on 11q13. When we used an improved gene-set-enrichment analysis approach, we found that the Fas signaling pathway and the antigen processing and presentation pathway were most significant (nominal P < 0.001; false discovery rate < 0.05) among 250 pathways containing 17 572 genes. We believe that our analysis is a pilot study that first describes the gene–asbestos interaction in lung cancer risk at levels of SNPs, genes and pathways. Our findings suggest that immune function regulation-related pathways may be mechanistically involved in asbestos-associated lung cancer risk. Abbreviations:CIconfidence intervalEenvironmentFDRfalse discovery rateGgeneGSEAgene-set-enrichment analysisGWASgenome-wide association studiesi-GSEAimproved gene-set-enrichment analysis approachORodds ratioSNPsingle nucleotide polymorphism PMID:22637743
Merlo, Domenico F; Filiberti, Rosangela; Kobernus, Michael; Bartonova, Alena; Gamulin, Marija; Ferencic, Zeljko; Dusinska, Maria; Fucic, Aleksandra
2012-06-28
Development of graphical/visual presentations of cancer etiology caused by environmental stressors is a process that requires combining the complex biological interactions between xenobiotics in living and occupational environment with genes (gene-environment interaction) and genomic and non-genomic based disease specific mechanisms in living organisms. Traditionally, presentation of causal relationships includes the statistical association between exposure to one xenobiotic and the disease corrected for the effect of potential confounders. Within the FP6 project HENVINET, we aimed at considering together all known agents and mechanisms involved in development of selected cancer types. Selection of cancer types for causal diagrams was based on the corpus of available data and reported relative risk (RR). In constructing causal diagrams the complexity of the interactions between xenobiotics was considered a priority in the interpretation of cancer risk. Additionally, gene-environment interactions were incorporated such as polymorphisms in genes for repair and for phase I and II enzymes involved in metabolism of xenobiotics and their elimination. Information on possible age or gender susceptibility is also included. Diagrams are user friendly thanks to multistep access to information packages and the possibility of referring to related literature and a glossary of terms. Diagrams cover both chemical and physical agents (ionizing and non-ionizing radiation) and provide basic information on the strength of the association between type of exposure and cancer risk reported by human studies and supported by mechanistic studies. Causal diagrams developed within HENVINET project represent a valuable source of information for professionals working in the field of environmental health and epidemiology, and as educational material for students. Cancer risk results from a complex interaction of environmental exposures with inherited gene polymorphisms, genetic burden collected during development and non genomic capacity of response to environmental insults. In order to adopt effective preventive measures and the associated regulatory actions, a comprehensive investigation of cancer etiology is crucial. Variations and fluctuations of cancer incidence in human populations do not necessarily reflect environmental pollution policies or population distribution of polymorphisms of genes known to be associated with increased cancer risk. Tools which may be used in such a comprehensive research, including molecular biology applied to field studies, require a methodological shift from the reductionism that has been used until recently as a basic axiom in interpretation of data. The complexity of the interactions between cells, genes and the environment, i.e. the resonance of the living matter with the environment, can be synthesized by systems biology. Within the HENVINET project such philosophy was followed in order to develop interactive causal diagrams for the investigation of cancers with possible etiology in environmental exposure. Causal diagrams represent integrated knowledge and seed tool for their future development and development of similar diagrams for other environmentally related diseases such as asthma or sterility. In this paper development and application of causal diagrams for cancer are presented and discussed.
Zhang, Yun; Ming, Qing-sen; Yi, Jin-yao; Wang, Xiang; Chai, Qiao-lian; Yao, Shu-qiao
2017-01-01
Gene-environment interactions that moderate aggressive behavior have been identified independently in the serotonin transporter (5-HTT) gene and monoamine oxidase A gene (MAOA). The aim of the present study was to investigate epistasis interactions between MAOA-variable number tandem repeat (VNTR), 5-HTTlinked polymorphism (LPR) and child abuse and the effects of these on aggressive tendencies in a group of otherwise healthy adolescents. A group of 546 Chinese male adolescents completed the Child Trauma Questionnaire and Youth self-report of the Child Behavior Checklist. Buccal cells were collected for DNA analysis. The effects of childhood abuse, MAOA-VNTR, 5-HTTLPR genotypes and their interactive gene-gene-environmental effects on aggressive behavior were analyzed using a linear regression model. The effect of child maltreatment was significant, and a three-way interaction among MAOA-VNTR, 5-HTTLPR and sexual abuse (SA) relating to aggressive behaviors was identified. Chinese male adolescents with high expression of the MAOA-VNTR allele and 5-HTTLPR “SS” genotype exhibited the highest aggression tendencies with an increase in SA during childhood. The findings reported support aggression being a complex behavior involving the synergistic effects of gene-gene-environment interactions. PMID:28203149
Ma, Jing; Yu, Shun-Ying; Liang, Shan; Ding, Jun; Feng, Zhe; Yang, Fan; Gao, Wei-Jia; Lin, Jia-Ni; Huang, Chun-Xiang; Liu, Xue-Jun; Su, Lin-Yan
2013-07-01
To investigate whether the genetic polymorphism, upstream variable number of tandem repeats (uVNTR), in the monoamine oxidase A (MAOA) gene, is associated with major depressive disorder (MDD) in adolescents and to test whether there is gene-environment interaction between MAOA-uVNTR polymorphism and stressful life events (SLEs). A total of 394 Chinese Han subjects, including 187 adolescent patients with MDD and 207 normal students as a control group, were included in the study. Genotyping was performed by SNaP-shot assay. SLEs in the previous 12 months were evaluated. The groups were compared in terms of the frequency distributions of MAOA-uVNTR genotypes and alleles using statistical software. The binary logistic regression model of gene-environment interaction was established to analyze the association of the gene-environment interaction between MAOA-u VNTR genotypes and SLEs with adolescent MDD. The distribution profiles of MAOA-u VNTR genotypes and alleles were not related to the onset of MDD, severity of depression, comorbid anxiety and suicidal ideation/behavior/attempt in adolescents. The gene-environment interaction between MAOA-u VNTR genotypes and SLEs was not associated with MDD in male or female adolescents. It is not proven that MAOA-u VNTR polymorphism is associated with adolescent MDD. There is also no gene-environment interaction between MAOA-u VNTR polymorphism and SLEs that is associated with adolescent MDD.
Gene-Environment Interactions in Asthma: Genetic and Epigenetic Effects.
Lee, Jong-Uk; Kim, Jeong Dong; Park, Choon-Sik
2015-07-01
Over the past three decades, a large number of genetic studies have been aimed at finding genetic variants associated with the risk of asthma, applying various genetic and genomic approaches including linkage analysis, candidate gene polymorphism studies, and genome-wide association studies (GWAS). However, contrary to general expectation, even single nucleotide polymorphisms (SNPs) discovered by GWAS failed to fully explain the heritability of asthma. Thus, application of rare allele polymorphisms in well defined phenotypes and clarification of environmental factors have been suggested to overcome the problem of 'missing' heritability. Such factors include allergens, cigarette smoke, air pollutants, and infectious agents during pre- and post-natal periods. The first and simplest interaction between a gene and the environment is a candidate interaction of both a well known gene and environmental factor in a direct physical or chemical interaction such as between CD14 and endotoxin or between HLA and allergens. Several GWAS have found environmental interactions with occupational asthma, aspirin exacerbated respiratory disease, tobacco smoke-related airway dysfunction, and farm-related atopic diseases. As one of the mechanisms behind gene-environment interaction is epigenetics, a few studies on DNA CpG methylation have been reported on subphenotypes of asthma, pitching the exciting idea that it may be possible to intervene at the junction between the genome and the environment. Epigenetic studies are starting to include data from clinical samples, which will make them another powerful tool for re-search on gene-environment interactions in asthma.
Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill
2013-02-01
Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.
Gene x Environment Interactions in Reading Disability and Attention-Deficit/Hyperactivity Disorder
ERIC Educational Resources Information Center
Pennington, Bruce F.; McGrath, Lauren M.; Rosenberg, Jenni; Barnard, Holly; Smith, Shelley D.; Willcutt, Erik G.; Friend, Angela; DeFries, John C.; Olson, Richard K.
2009-01-01
This article examines Gene x Environment (G x E) interactions in two comorbid developmental disorders--reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD)--as a window on broader issues on G x E interactions in developmental psychology. The authors first briefly review types of G x E interactions, methods for detecting…
Computational gene network study on antibiotic resistance genes of Acinetobacter baumannii.
Anitha, P; Anbarasu, Anand; Ramaiah, Sudha
2014-05-01
Multi Drug Resistance (MDR) in Acinetobacter baumannii is one of the major threats for emerging nosocomial infections in hospital environment. Multidrug-resistance in A. baumannii may be due to the implementation of multi-combination resistance mechanisms such as β-lactamase synthesis, Penicillin-Binding Proteins (PBPs) changes, alteration in porin proteins and in efflux pumps against various existing classes of antibiotics. Multiple antibiotic resistance genes are involved in MDR. These resistance genes are transferred through plasmids, which are responsible for the dissemination of antibiotic resistance among Acinetobacter spp. In addition, these resistance genes may also have a tendency to interact with each other or with their gene products. Therefore, it becomes necessary to understand the impact of these interactions in antibiotic resistance mechanism. Hence, our study focuses on protein and gene network analysis on various resistance genes, to elucidate the role of the interacting proteins and to study their functional contribution towards antibiotic resistance. From the search tool for the retrieval of interacting gene/protein (STRING), a total of 168 functional partners for 15 resistance genes were extracted based on the confidence scoring system. The network study was then followed up with functional clustering of associated partners using molecular complex detection (MCODE). Later, we selected eight efficient clusters based on score. Interestingly, the associated protein we identified from the network possessed greater functional similarity with known resistance genes. This network-based approach on resistance genes of A. baumannii could help in identifying new genes/proteins and provide clues on their association in antibiotic resistance. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis
Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul
2014-01-01
Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240
Richards, Jennifer S; Hartman, Catharina A; Franke, Barbara; Hoekstra, Pieter J; Heslenfeld, Dirk J; Oosterlaan, Jaap; Arias Vásquez, Alejandro; Buitelaar, Jan K
2015-02-01
The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantaged in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N = 366, M = 17.11 years, 74.9% male). Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour.
Richards, Jennifer S.; Hartman, Catharina A.; Franke, Barbara; Hoekstra, Pieter J.; Heslenfeld, Dirk J.; Oosterlaan, Jaap; Vásquez, Alejandro Arias; Buitelaar, Jan K.
2014-01-01
Background The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantageous in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). Methods The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N=366, M=17.11 years, 74.9 % male). Results Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. Conclusions The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour. PMID:24929324
Dressler, William W; Balieiro, Mauro C; Ferreira de Araújo, Luiza; Silva, Wilson A; Ernesto Dos Santos, José
2016-07-01
Research on gene-environment interaction was facilitated by breakthroughs in molecular biology in the late 20th century, especially in the study of mental health. There is a reliable interaction between candidate genes for depression and childhood adversity in relation to mental health outcomes. The aim of this paper is to explore the role of culture in this process in an urban community in Brazil. The specific cultural factor examined is cultural consonance, or the degree to which individuals are able to successfully incorporate salient cultural models into their own beliefs and behaviors. It was hypothesized that cultural consonance in family life would mediate the interaction of genotype and childhood adversity. In a study of 402 adult Brazilians from diverse socioeconomic backgrounds, conducted from 2011 to 2014, the interaction of reported childhood adversity and a polymorphism in the 2A serotonin receptor was associated with higher depressive symptoms. Further analysis showed that the gene-environment interaction was mediated by cultural consonance in family life, and that these effects were more pronounced in lower social class neighborhoods. The findings reinforce the role of the serotonergic system in the regulation of stress response and learning and memory, and how these processes in turn interact with environmental events and circumstances. Furthermore, these results suggest that gene-environment interaction models should incorporate a wider range of environmental experience and more complex pathways to better understand how genes and the environment combine to influence mental health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Winham, Stacey J.; Biernacka, Joanna M.
2013-01-01
Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…
Rohde, Palle Duun; Gaertner, Bryn; Ward, Kirsty; Sørensen, Peter; Mackay, Trudy F C
2017-08-01
Human psychiatric disorders such as schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder often include adverse behaviors including increased aggressiveness. Individuals with psychiatric disorders often exhibit social withdrawal, which can further increase the probability of conducting a violent act. Here, we used the inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP) to investigate the genetic basis of variation in male aggressive behavior for flies reared in a socialized and socially isolated environment. We identified genetic variation for aggressive behavior, as well as significant genotype-by-social environmental interaction (GSEI); i.e. , variation among DGRP genotypes in the degree to which social isolation affected aggression. We performed genome-wide association (GWA) analyses to identify genetic variants associated with aggression within each environment. We used genomic prediction to partition genetic variants into gene ontology (GO) terms and constituent genes, and identified GO terms and genes with high prediction accuracies in both social environments and for GSEI. The top predictive GO terms significantly increased the proportion of variance explained, compared to prediction models based on all segregating variants. We performed genomic prediction across environments, and identified genes in common between the social environments that turned out to be enriched for genome-wide associated variants. A large proportion of the associated genes have previously been associated with aggressive behavior in Drosophila and mice. Further, many of these genes have human orthologs that have been associated with neurological disorders, indicating partially shared genetic mechanisms underlying aggression in animal models and human psychiatric disorders. Copyright © 2017 by the Genetics Society of America.
Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models
Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John
2016-01-01
The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886
Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H. Hill
2013-01-01
Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e. passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e. gene-environment interaction). The sample comprised 807 twin pairs (M age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high Effortful Control, and this association was genetically mediated. Children with high Extraversion/Surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that Effortful Control and Extraversion/Surgency were more heritable in chaotic homes, and Negative Affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally. PMID:23398752
Genome-wide assessment of gene-by-smoking interactions in COPD.
Park, Boram; Koo, So-My; An, Jaehoon; Lee, MoonGyu; Kang, Hae Yeon; Qiao, Dandi; Cho, Michael H; Sung, Joohon; Silverman, Edwin K; Yang, Hyeon-Jong; Won, Sungho
2018-06-18
Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables-forced expiratory volume in 1 s (FEV 1 ). We found that variations in FEV 1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV 1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.
Bookman, Ebony B.; McAllister, Kimberly; Gillanders, Elizabeth; Wanke, Kay; Balshaw, David; Rutter, Joni; Reedy, Jill; Shaughnessy, Daniel; Agurs-Collins, Tanya; Paltoo, Dina; Atienza, Audie; Bierut, Laura; Kraft, Peter; Fallin, M. Daniele; Perera, Frederica; Turkheimer, Eric; Boardman, Jason; Marazita, Mary L.; Rappaport, Stephen M.; Boerwinkle, Eric; Suomi, Stephen J.; Caporaso, Neil E.; Hertz-Picciotto, Irva; Jacobson, Kristen C.; Lowe, William L.; Goldman, Lynn R.; Duggal, Priya; Gunnar, Megan R.; Manolio, Teri A.; Green, Eric D.; Olster, Deborah H.; Birnbaum, Linda S.
2011-01-01
Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies. PMID:21308768
ERIC Educational Resources Information Center
Price, Thomas S.; Jaffee, Sara R.
2008-01-01
The classical twin study provides a useful resource for testing hypotheses about how the family environment influences children's development, including how genes can influence sensitivity to environmental effects. However, existing statistical models do not account for the possibility that children can inherit exposure to family environments…
Gene-Environment Interplay between Number of Friends and Prosocial Leadership Behavior in Children
ERIC Educational Resources Information Center
Rivizzigno, Alessandra S.; Brendgen, Mara; Feng, Bei; Vitaro, Frank; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel
2014-01-01
Enriched environments may moderate the effect of genetic factors on prosocial leadership (gene-environment interaction, G × E). However, positive environmental experiences may also themselves be influenced by a genetic disposition for prosocial leadership (gene-environment correlation, rGE). Relating these processes to friendships, the present…
USDA-ARS?s Scientific Manuscript database
As the role of the environment – diet, exercise, alcohol and tobacco use and sleep among others – is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate i...
Bunyavanich, S; Boyce, J A; Raby, B A; Weiss, S T
2012-02-01
Distinct receptors likely exist for leukotriene (LT)E(4), a potent mediator of airway inflammation. Purinergic receptor P2Y12 is needed for LTE(4)-induced airways inflammation, and P2Y12 antagonism attenuates house dust mite-induced pulmonary eosinophilia in mice. Although experimental data support a role for P2Y12 in airway inflammation, its role in human asthma has never been studied. To test for association between variants in the P2Y12 gene (P2RY12) and lung function in human subjects with asthma, and to examine for gene-by-environment interaction with house dust mite exposure. Nineteen single nucleotide polymorphisms (SNPs) in P2RY12 were genotyped in 422 children with asthma and their parents (n = 1266). Using family based methods, we tested for associations between these SNPs and five lung function measures. We performed haplotype association analyses and tested for gene-by-environment interactions using house dust mite exposure. We used the false discovery rate to account for multiple comparisons. Five SNPs in P2RY12 were associated with multiple lung function measures (P-values 0.006–0.025). Haplotypes in P2RY12 were also associated with lung function (P-values 0.0055–0.046). House dust mite exposure modulated associations between P2RY12 and lung function, with minor allele homozygotes exposed to house dust mite demonstrating worse lung function than those unexposed (significant interaction P-values 0.0028–0.040). The P2RY12 variants were associated with lung function in a large family-based asthma cohort. House dust mite exposure caused significant gene-by-environment effects. Our findings add the first human evidence to experimental data supporting a role for P2Y12 in lung function. P2Y12 could represent a novel target for asthma treatment.
Slutske, Wendy S; Deutsch, Arielle R; Statham, Dixie J; Martin, Nicholas G
2015-08-01
Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These 2 lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge-from genes to geography-as well as the ways in which such contexts may interact with each other. (c) 2015 APA, all rights reserved).
Slutske, Wendy S.; Deutsch, Arielle R.; Statham, Dixie B.; Martin, Nicholas G.
2015-01-01
Previous research has demonstrated that local area characteristics (such as disadvantage and gambling outlet density) and genetic risk factors are associated with gambling involvement and disordered gambling. These two lines of research were brought together in the present study by examining the extent to which genetic contributions to individual differences in gambling involvement and disorder contributed to being exposed to, and were also accentuated by, local area disadvantage. Participants were members of the national community-based Australian Twin Registry who completed a telephone interview in which the past-year frequency of gambling and symptoms of disordered gambling were assessed. Indicators of local area disadvantage were based on census data matched to the participants' postal codes. Univariate biometric model-fitting revealed that exposure to area disadvantage was partially explained by genetic factors. Bivariate biometric model-fitting was conducted to examine the evidence for gene-environment interaction while accounting for gene-environment correlation. These analyses demonstrated that: (a) a small portion of the genetic propensity to gamble was explained by moving to or remaining in a disadvantaged area, and (b) the remaining genetic and unique environmental variation in the frequency of participating in electronic machine gambling (among men and women) and symptoms of disordered gambling (among women) was greater in more disadvantaged localities. As the gambling industry continues to grow, it will be important to take into account the multiple contexts in which problematic gambling behavior can emerge -- from genes to geography -- as well as the ways in which such contexts may interact with each other. PMID:26147321
Schneider, Susan M
2007-01-01
Nature–nurture views that smack of genetic determinism remain prevalent. Yet, the increasing knowledge base shows ever more clearly that environmental factors and genes form a fully interactional system at all levels. Moore's book covers the major topics of discovery and dispute, including behavior genetics and the twin studies, developmental psychobiology, and developmental systems theory. Knowledge of this larger life-sciences context for behavior principles will become increasingly important as the full complexity of gene–environment relations is revealed. Behavior analysis both contributes to and gains from the larger battle for the recognition of how nature and nurture really work.
Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.
2011-01-01
With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455
Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?
Simonds, Naoko I; Ghazarian, Armen A; Pimentel, Camilla B; Schully, Sheri D; Ellison, Gary L; Gillanders, Elizabeth M; Mechanic, Leah E
2016-07-01
Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature. To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest. Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
Review of the Gene-Environment Interaction Literature in Cancer: What do we know?
Simonds, Naoko I.; Ghazarian, Armen A.; Pimentel, Camilla B.; Schully, Sheri D.; Ellison, Gary L.; Gillanders, Elizabeth M.; Mechanic, Leah E.
2016-01-01
Background Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment (GxE) interactions has been an active area of research, little is reported about the known findings in the literature. Methods To examine the state of the science in GxE research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. Results A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined GxE in colon, rectal, or colorectal cancer types; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index (BMI), diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction p-value, of which a sizable number of p-values were considered statistically significant (i.e., < 0.05). In addition, the magnitudes of interactions reported were modest. Conclusion Observations of published literature suggest that opportunity exists for increased sample size in GxE research, including GWAS identified loci in GxE studies, exploring more GWAS approaches in GxE such as GEWIS, and improving the reporting of GxE findings. PMID:27061572
Distel, M A; Middeldorp, C M; Trull, T J; Derom, C A; Willemsen, G; Boomsma, D I
2011-04-01
Traumatic life events are generally more common in patients with borderline personality disorder (BPD) than in non-patients or patients with other personality disorders. This study investigates whether exposure to life events moderates the genetic architecture of BPD features. As the presence of genotype-environment correlation (rGE) can lead to spurious findings of genotype-environment interaction (G × E), we also test whether BPD features increase the likelihood of exposure to life events. The extent to which an individual is at risk to develop BPD was assessed with the Personality Assessment Inventory - Borderline features scale (PAI-BOR). Life events under study were a divorce/break-up, traffic accident, violent assault, sexual assault, robbery and job loss. Data were available for 5083 twins and 1285 non-twin siblings. Gene-environment interaction and correlation were assessed by using structural equation modelling (SEM) and the co-twin control design. There was evidence for both gene-environment interaction and correlation. Additive genetic influences on BPD features interacted with the exposure to sexual assault, with genetic variance being lower in exposed individuals. In individuals who had experienced a divorce/break-up, violent assault, sexual assault or job loss, environmental variance for BPD features was higher, leading to a lower heritability of BPD features in exposed individuals. Gene-environment correlation was present for some life events. The genes that influence BPD features thus also increased the likelihood of being exposed to certain life events. To our knowledge, this study is the first to test the joint effect of genetic and environmental influences and the exposure to life events on BPD features in the general population. Our results indicate the importance of both genetic vulnerability and life events.
The case-only test for gene-environment interaction is not uniformly powerful: an empirical example
Wu, Chen; Chang, Jiang; Ma, Baoshan; Miao, Xiaoping; Zhou, Yifeng; Liu, Yu; Li, Yun; Wu, Tangchun; Hu, Zhibin; Shen, Hongbing; Jia, Weihua; Zeng, Yixin; Lin, Dongxin; Kraft, Peter
2016-01-01
The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption. PMID:23595356
ERIC Educational Resources Information Center
Wiebe, Sandra A.; Espy, Kimberly Andrews; Stopp, Christian; Respass, Jennifer; Stewart, Peter; Jameson, Travis R.; Gilbert, David G.; Huggenvik, Jodi I.
2009-01-01
Genetic factors dynamically interact with both pre- and postnatal environmental influences to shape development. Considerable attention has been devoted to gene-environment interactions (G x E) on important outcomes (A. Caspi & T. E. Moffitt, 2006). It is also important to consider the possibility that these G x E effects may vary across…
Zhao, Wei; Ware, Erin B; He, Zihuai; Kardia, Sharon L R; Faul, Jessica D; Smith, Jennifer A
2017-09-29
Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).
Zhao, Wei; He, Zihuai; Kardia, Sharon L. R.; Faul, Jessica D.
2017-01-01
Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) (p = 0.07). PMID:28961216
Genes and environment in neonatal intraventricular hemorrhage.
Ment, Laura R; Ådén, Ulrika; Bauer, Charles R; Bada, Henrietta S; Carlo, Waldemar A; Kaiser, Jeffrey R; Lin, Aiping; Cotten, Charles Michael; Murray, Jeffrey; Page, Grier; Hallman, Mikko; Lifton, Richard P; Zhang, Heping
2015-12-01
Emerging data suggest intraventricular hemorrhage (IVH) of the preterm neonate is a complex disorder with contributions from both the environment and the genome. Environmental analyses suggest factors mediating both cerebral blood flow and angiogenesis contribute to IVH, while candidate gene studies report variants in angiogenesis, inflammation, and vascular pathways. Gene-by-environment interactions demonstrate the interaction between the environment and the genome, and a non-replicated genome-wide association study suggests that both environmental and genetic factors contribute to the risk for severe IVH in very low-birth weight preterm neonates. Copyright © 2015 Elsevier Inc. All rights reserved.
Testing for gene-environment interaction under exposure misspecification.
Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong
2017-11-09
Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.
Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L
2017-12-18
Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region ( p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region ( p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.
Genome-Wide Analysis of Gene-Gene and Gene-Environment Interactions Using Closed-Form Wald Tests.
Yu, Zhaoxia; Demetriou, Michael; Gillen, Daniel L
2015-09-01
Despite the successful discovery of hundreds of variants for complex human traits using genome-wide association studies, the degree to which genes and environmental risk factors jointly affect disease risk is largely unknown. One obstacle toward this goal is that the computational effort required for testing gene-gene and gene-environment interactions is enormous. As a result, numerous computationally efficient tests were recently proposed. However, the validity of these methods often relies on unrealistic assumptions such as additive main effects, main effects at only one variable, no linkage disequilibrium between the two single-nucleotide polymorphisms (SNPs) in a pair or gene-environment independence. Here, we derive closed-form and consistent estimates for interaction parameters and propose to use Wald tests for testing interactions. The Wald tests are asymptotically equivalent to the likelihood ratio tests (LRTs), largely considered to be the gold standard tests but generally too computationally demanding for genome-wide interaction analysis. Simulation studies show that the proposed Wald tests have very similar performances with the LRTs but are much more computationally efficient. Applying the proposed tests to a genome-wide study of multiple sclerosis, we identify interactions within the major histocompatibility complex region. In this application, we find that (1) focusing on pairs where both SNPs are marginally significant leads to more significant interactions when compared to focusing on pairs where at least one SNP is marginally significant; and (2) parsimonious parameterization of interaction effects might decrease, rather than increase, statistical power. © 2015 WILEY PERIODICALS, INC.
Hu, Ting; Pan, Qinxin; Andrew, Angeline S; Langer, Jillian M; Cole, Michael D; Tomlinson, Craig R; Karagas, Margaret R; Moore, Jason H
2014-04-11
Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types. The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.
Qian, Airong; Di, Shengmeng; Gao, Xiang; Zhang, Wei; Tian, Zongcheng; Li, Jingbao; Hu, Lifang; Yang, Pengfei; Yin, Dachuan; Shang, Peng
2009-07-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has been widely applied in many fields. In this study, a special designed superconducting magnet, which can produce three apparent gravity levels (0, 1, and 2 g), namely high magneto-gravitational environment (HMGE), was used to simulate space gravity environment. The effects of HMGE on osteoblast gene expression profile were investigated by microarray. Genes sensitive to diamagnetic levitation environment (0 g), gravity changes, and high magnetic field changes were sorted on the basis of typical cell functions. Cytoskeleton, as an intracellular load-bearing structure, plays an important role in gravity perception. Therefore, 13 cytoskeleton-related genes were chosen according to the results of microarray analysis, and the expressions of these genes were found to be altered under HMGE by real-time PCR. Based on the PCR results, the expressions of WASF2 (WAS protein family, member 2), WIPF1 (WAS/WASL interacting protein family, member 1), paxillin, and talin 1 were further identified by western blot assay. Results indicated that WASF2 and WIPF1 were more sensitive to altered gravity levels, and talin 1 and paxillin were sensitive to both magnetic field and gravity changes. Our findings demonstrated that HMGE can affect osteoblast gene expression profile and cytoskeleton-related genes expression. The identification of mechanosensitive genes may enhance our understandings to the mechanism of bone loss induced by microgravity and may provide some potential targets for preventing and treating bone loss or osteoporosis.
Cicchetti, Dante; Rogosch, Fred A.; Thibodeau, Eric
2013-01-01
Gene-environment interaction effects in predicting antisocial behavior in late childhood were investigated among maltreated and nonmaltreated low-income children (N = 627, M age = 11.27). Variants in three genes, TPH1, 5-HTTLPR, and MAOA uVNTR, were examined. In addition to child maltreatment status, we also considered the impact of maltreatment subtypes, developmental timing of maltreatment, and chronicity. Indicators of antisocial behavior were obtained from self-, peer-, and adult counselor-reports. In a series of ANCOVAs, child maltreatment and its parameters demonstrated strong main effects on early antisocial behavior as assessed by all forms of report. Genetic effects operated primarily in the context of gene-environment interactions, moderating the impact of child maltreatment on outcomes. Across the three genes, among nonmaltreated children no differences in antisocial behavior were found based on genetic variation. In contrast, among maltreated children specific polymorphisms of TPH1, 5-HTTLPR, and MAOA were each related to heightened self-report of antisocial behavior; the interaction of 5-HTTLPR and developmental timing of maltreatment also indicated more severe antisocial outcomes for children with early onset and recurrent maltreatment based on genotype. TPH1 and 5-HTTLPR interacted with maltreatment subtype to predict peer-report of antisocial behavior; genetic variation contributed to larger differences in antisocial behavior among abused children. TPH1 and 5-HTTLPR polymorphisms also moderated the effects of maltreatment subtype on adult report of antisocial behavior; again genetic effects were strongest for children who were abused. Additionally, TPH1 moderated the effect of developmental timing of maltreatment and chronicity on adult report of antisocial behavior. The findings elucidate how genetic variation contributes to identifying which maltreated children are most vulnerable to antisocial development. PMID:22781862
Evidence for Gender-Dependent Genotype by Environment Interaction in Adult Depression.
Molenaar, Dylan; Middeldorp, Christel M; Willemsen, Gonneke; Ligthart, Lannie; Nivard, Michel G; Boomsma, Dorret I
2015-10-14
Depression in adults is heritable with about 40 % of the phenotypic variance due to additive genetic effects and the remaining phenotypic variance due to unique (unshared) environmental effects. Common environmental effects shared by family members are rarely found in adults. One possible explanation for this finding is that there is an interaction between genes and the environment which may mask effects of the common environment. To test this hypothesis, we investigated genotype by environment interaction in a large sample of female and male adult twins aged 18-70 years. The anxious depression subscale of the Adult Self Report from the Achenbach System of Empirically Based Assessment (Achenbach and Rescorla in Manual for the ASEBA adult: forms and profiles, 2003) was completed by 13,022 twins who participate in longitudinal studies of the Netherlands Twin Register. In a single group analysis, we found genotype by unique environment interaction, but no genotype by common environment interaction. However, when conditioning on gender, we observed genotype by common environment interaction in men, with larger common environmental variance in men who are genetically less at risk to develop depression. Although the effect size of the interaction is characterized by large uncertainty, the results show that there is at least some variance due to the common environment in adult depression in men.
Gene-Environment Interactions in Cancer Epidemiology: A National Cancer Institute Think Tank Report
Hutter, Carolyn M.; Mechanic, Leah E.; Chatterjee, Nilanjan; Kraft, Peter; Gillander, Elizabeth M.
2014-01-01
Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF]>0.05) and less common (0.01
Reed, Jessica L; D'Ambrosio, Enrico; Marenco, Stefano; Ursini, Gianluca; Zheutlin, Amanda B; Blasi, Giuseppe; Spencer, Barbara E; Romano, Raffaella; Hochheiser, Jesse; Reifman, Ann; Sturm, Justin; Berman, Karen F; Bertolino, Alessandro; Weinberger, Daniel R; Callicott, Joseph H
2018-01-01
Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.
Barnes, J C; Jacobs, Bruce A
2013-01-01
Despite mounds of evidence to suggest that neighborhood structural factors predict violent behavior, almost no attention has been given to how these influences work synergistically (i.e., interact) with an individual's genetic propensity toward violent behavior. Indeed, two streams of research have, heretofore, flowed independently of one another. On one hand, criminologists have underscored the importance of neighborhood context in the etiology of violence. On the other hand, behavioral geneticists have argued that individual-level genetic propensities are important for understanding violence. The current study seeks to integrate these two compatible frameworks by exploring gene-environment interactions (GxE). Two GxEs were examined and supported by the data (i.e., the National Longitudinal Study of Adolescent Health). Using a scale of genetic risk based on three dopamine genes, the analysis revealed that genetic risk had a greater influence on violent behavior when the individual was also exposed to neighborhood disadvantage or when the individual was exposed to higher violent crime rates. The relevance of these findings for criminological theorizing was considered.
Molecular epidemiology, and possible real-world applications in breast cancer.
Ito, Hidemi; Matsuo, Keitaro
2016-01-01
Gene-environment interaction, a key idea in molecular epidemiology, has enabled the development of personalized medicine. This concept includes personalized prevention. While genome-wide association studies have identified a number of genetic susceptibility loci in breast cancer risk, however, the application of this knowledge to practical prevention is still underway. Here, we briefly review the history of molecular epidemiology and its progress in breast cancer epidemiology. We then introduce our experience with the trial combination of GWAS-identified loci and well-established lifestyle and reproductive risk factors in the risk prediction of breast cancer. Finally, we report our exploration of the cumulative risk of breast cancer based on this risk prediction model as a potential tool for individual risk communication, including genetic risk factors and gene-environment interaction with obesity.
Karlsson, Torgny; Ek, Weronica E.
2017-01-01
Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10−29, p = 3.83*10−26, p = 4.66*10−11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors. PMID:28873402
Dalle Molle, Roberta; Fatemi, Hajar; Dagher, Alain; Levitan, Robert D.; Silveira, Patricia P.; Dubé, Laurette
2017-01-01
The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental “layers” relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, “for better and for worse”. While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk. PMID:28024828
Gene-environment interaction on neural mechanisms of orthographic processing in Chinese children
Su, Mengmeng; Wang, Jiuju; Maurer, Urs; Zhang, Yuping; Li, Jun; McBride-Chang, Catherine; Tardif, Twila; Liu, Youyi; Shu, Hua
2015-01-01
The ability to process and identify visual words requires efficient orthographic processing of print, consisting of letters in alphabetic languages or characters in Chinese. The N170 is a robust neural marker for orthographic processes. Both genetic and environmental factors, such as home literacy, have been shown to influence orthographic processing at the behavioral level, but their relative contributions and interactions are not well understood. The present study aimed to reveal possible gene-by-environment interactions on orthographic processing at the behavioral and neural level in a normal children sample. Sixty 12 year old Chinese children from a 10-year longitudinal sample underwent an implicit visual-word color decision task on real words and stroke combinations. The ERP analysis focused on the increase of the occipito-temporal N170 to words compared to stroke combinations. The genetic analysis focused on two SNPs (rs1419228, rs1091047) in the gene DCDC2 based on previous findings linking these 2 SNPs to orthographic coding. Home literacy was measured previously as the number of children's books at home, when the children were at the age of 3. Relative to stroke combinations, real words evoked greater N170 in bilateral posterior brain regions. A significant interaction between rs1091047 and home literacy was observed on the changes of N170 comparing real words to stroke combinations in the left hemisphere. Particularly, children carrying the major allele “G” showed a similar N170 effect irrespective of their environment, while children carrying the minor allele “C” showed a smaller N170 effect in low home-literacy environment than those in good environment. PMID:26294811
Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz
2009-08-25
Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.
Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz
2009-01-01
Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156
Genetic and environmental factors affecting cryptic variations in gene regulatory networks
2013-01-01
Background Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity. PMID:23622056
Genetic and environmental factors affecting cryptic variations in gene regulatory networks.
Iwasaki, Watal M; Tsuda, Masaki E; Kawata, Masakado
2013-04-26
Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.
van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H. J.; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C. M. E.
2013-01-01
Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately. PMID:24223720
van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H J; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C M E
2013-01-01
Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately.
Li, Fengmei; Xie, Jianyin; Zhu, Xiaoyang; Wang, Xueqiang; Zhao, Yan; Ma, Xiaoqian; Zhang, Zhanying; Rashid, Muhammad A R; Zhang, Zhifang; Zhi, Linran; Zhang, Shuyang; Li, Jinjie; Li, Zichao; Zhang, Hongliang
2018-01-01
Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r 2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.
Wade, Mark; Hoffmann, Thomas J; Jenkins, Jennifer M
2015-12-01
Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behavior--two widely studied factors in ToM development-interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers' cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children's ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene-environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.
Guo, Guang; Li, Yi; Wang, Hongyu; Cai, Tianji; Duncan, Greg J
2015-11-01
The authors draw data from the College Roommate Study (ROOM) and the National Longitudinal Study of Adolescent Health to investigate gene-environment interaction effects on youth binge drinking. In ROOM, the environmental influence was measured by the precollege drinking behavior of randomly assigned roommates. Random assignment safeguards against friend selection and removes the threat of gene-environment correlation that makes gene-environment interaction effects difficult to interpret. On average, being randomly assigned a drinking peer as opposed to a nondrinking peer increased college binge drinking by 0.5-1.0 episodes per month, or 20%-40% the average amount of binge drinking. However, this peer influence was found only among youths with a medium level of genetic propensity for alcohol use; those with either a low or high genetic propensity were not influenced by peer drinking. A replication of the findings is provided in data drawn from Add Health. The study shows that gene-environment interaction analysis can uncover social-contextual effects likely to be missed by traditional sociological approaches.
Goldstein, Alisa M; Dondon, Marie-Gabrielle; Andrieu, Nadine
2006-08-01
A design combining both related and unrelated controls, named the case-combined-control design, was recently proposed to increase the power for detecting gene-environment (GxE) interaction. Under a conditional analytic approach, the case-combined-control design appeared to be more efficient and feasible than a classical case-control study for detecting interaction involving rare events. We now propose an unconditional analytic strategy to further increase the power for detecting gene-environment (GxE) interactions. This strategy allows the estimation of GxE interaction and exposure (E) main effects under certain assumptions (e.g. no correlation in E between siblings and the same exposure frequency in both control groups). Only the genetic (G) main effect cannot be estimated because it is biased. Using simulations, we show that unconditional logistic regression analysis is often more efficient than conditional analysis for detecting GxE interaction, particularly for a rare gene and strong effects. The unconditional analysis is also at least as efficient as the conditional analysis when the gene is common and the main and joint effects of E and G are small. Under the required assumptions, the unconditional analysis retains more information than does the conditional analysis for which only discordant case-control pairs are informative leading to more precise estimates of the odds ratios.
The GP problem: quantifying gene-to-phenotype relationships.
Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L
2002-01-01
In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.
ERIC Educational Resources Information Center
Rosenberg, Jenni; Pennington, Bruce F.; Willcutt, Erik G.; Olson, Richard K.
2012-01-01
Background: Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G x E) interactions. Methods: This study used behavioral genetic…
Nagaie, Satoshi; Ogishima, Soichi; Nakaya, Jun; Tanaka, Hiroshi
2015-01-01
Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.
ERIC Educational Resources Information Center
Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.
2013-01-01
Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…
Genetic Interactions with Prenatal Social Environment: Effects on Academic and Behavioral Outcomes
ERIC Educational Resources Information Center
Conley, Dalton; Rauscher, Emily
2013-01-01
Numerous studies report gene-environment interactions, suggesting that specific alleles have different effects on social outcomes depending on environment. In all these studies, however, environmental conditions are potentially endogenous to unmeasured genetic characteristics. That is, it could be that the observed interaction effects actually…
Of Pesticides and Men: A California Story of Genes and Environment in Parkinson’s Disease
Ritz, BR; Paul, KC; Bronstein, JM
2018-01-01
At the start of the post-genomics era, most Parkinson’s disease (PD) etiology cannot be explained by our knowledge of genetic or environmental factors alone. For more than a decade, we have explored gene-environment (GxE) interactions possibly responsible for the heterogeneity of genetic as well as environmental results across populations. We developed three pesticide exposure measures (ambient due to agricultural applications, home and garden use, occupational use) in a large population-based case-control study of incident PD in central California. Specifically, we assessed interactions with genes responsible for pesticide metabolism (PON1); transport across the blood brain barrier (ABCB1); pesticides interfering with or depending on dopamine transporter activity (DAT) and dopamine metabolism (ALDH2); impacting mitochondrial function via oxidative/nitrosative stress (NOS1) or proteasome inhibition (SKP1); and contributing to immune dysregulation (HLA-DR). These studies established some specificity for pesticides’ neurodegenerative actions, contributed biologic plausibility to epidemiologic findings, and identified genetically susceptible populations. PMID:26857251
[The role of genotype in the intergenerational transmission of experiences of childhood adversity].
Reichl, Corinna; Kaess, Michael; Resch, Franz; Brunner, Romuald
2014-09-01
The prevalence of childhood abuse and maltreatment is estimated to lie at about 15% in the overall German population. Previous research suggested that about one third of all individuals who had experienced childhood adversity subsequently maltreated their own children or responded insensitively to their children's needs. Empirical studies imply that interindividual differences in the responsiveness to childhood adversity can partially be explained by gene-environment interactions. This article discusses the potential interplay of genes and environment in the context of transmitting maltreating behavior and (in)sensitive parenting against the background of current challenges in genetic research. Selected studies on gene × environment interactions are presented and relevant gene polymorphisms are identified. Overall, previous studies reported interactions between polymorphisms of the serotonergic, dopaminergic, oxytocin-related, and arginine vasopressin-related systems and childhood experiences of care and abuse in the prediction of social behaviors during mother-child interactions. The results indicate a differential susceptibility toward both negative and positive environments which is dependent on genetic characteristics. Future research should thus investigate the effects of children's presumed risk gene variants toward negative as well as positive parenting. This could contribute to a deeper understanding of the underlying mechanisms of the intergenerational transmission of abusive and beneficial parenting behavior and help to avoid false stigmatizations.
Keers, Robert; Pluess, Michael
2017-12-01
While environmental adversity has been shown to increase risk for psychopathology, individuals differ in their sensitivity to these effects. Both genes and childhood experiences are thought to influence sensitivity to the environment, and these factors may operate synergistically such that the effects of childhood experiences on later sensitivity are greater in individuals who are more genetically sensitive. In line with this hypothesis, several recent studies have reported a significant three-way interaction (Gene × Environment × Environment) between two candidate genes and childhood and adult environment on adult psychopathology. We aimed to replicate and extend these findings in a large, prospective multiwave longitudinal study using a polygenic score of environmental sensitivity and objectively measured childhood and adult material environmental quality. We found evidence for both Environment × Environment and Gene × Environment × Environment effects on psychological distress. Children with a poor-quality material environment were more sensitive to the negative effects of a poor environment as adults, reporting significantly higher psychological distress scores. These effects were further moderated by a polygenic score of environmental sensitivity. Genetically sensitive children were more vulnerable to adversity as adults, if they had experienced a poor childhood environment but were significantly less vulnerable if their childhood environment was positive. These findings are in line with the differential susceptibility hypothesis and suggest that a life course approach is necessary to elucidate the role of Gene × Environment in the development of mental illnesses.
Commentary: Gene-Environment Interplay in the Context of Genetics, Epigenetics, and Gene Expression.
ERIC Educational Resources Information Center
Kramer, Douglas A.
2005-01-01
Objective: To comment on the article in this issue of the Journal by Professor Michael Rutter, "Environmentally Mediated Risks for Psychopathology: Research Strategies and Findings," in the context of current research findings on gene-environment interaction, epigenetics, and gene expression. Method: Animal and human studies are reviewed that…
Vogel, Ulla; Sørensen, Mette; Hansen, Rikke Dalgaard; Tjønneland, Anne; Overvad, Kim; Wallin, Håkan; Nexø, Bjørn A; Raaschou-Nielsen, Ole
2007-03-08
Homozygous carriers of a haplotype consisting of ERCC1 Asn118Asn(A), ASE-1 G-21A(G), RAI IVS1 A4364G(A) are at increased risk of lung cancer especially among women. Here, we analyse for gene-environment interactions with the predefined haplotype in a case cohort study including 428 lung cancer cases and a comparison group of 800 persons, all from the prospective Diet, Cancer and Health cohort of 57,000 Danes. At high smoking intensity (>20g tobacco/day), there was only additional risk of smoking intensity among women who were homozygous carriers of the haplotype (IRR=2.03; 95% CI: 1.10-3.73 per 5 additional g tobacco/day).
Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming
2018-06-13
Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.
Sam, Soya Sisy; Thomas, Vinod; Reddy, K S; Surianarayanan, Gopalakrishnan; Chandrasekaran, Adithan
2010-06-01
Genetic risk to tobacco related cancers are associated with polymorphisms in CYP1A1 and GST, which are involved in the metabolic activation and detoxification of carcinogens. The genetic variations in these drug-metabolizing enzymes may alter the susceptibility to UADT cancers triggered by environmental exposures. The hospital-based case-control study evaluated the impact of combined CYP1A1 MspI and GST (M1 & T1) polymorphisms among the individuals exposed to environmental risk factors as modulators in the risk of UADT cancers in Tamilians, a population of south India. The unrelated histopathologically confirmed 408 cases and 220 population-based controls matched by age and gender were genotyped for CYP1A1 MspI, GSTM1 and GSTT1 polymorphisms using PCR based methods. To investigate the potential gene-environment interactions, analyses were carried out stratifying by smoking and tobacco chewing status using SPSS software. The combination of genes and environment interactions by stratified analyses revealed significant interactions among the habitual tobacco smokers (CYP1A1 MspI & GSTM1 null: OR 14.06; 95% CI 3.90-50.68, CYP1A1 MspI & GSTT1 null: OR 33.28; 95% CI 4.24-261.19) and tobacco chewers (CYP1A1 MspI & GSTM1 null: OR 20.51; 95% CI 6.77-62.13, CYP1A1 MspI & GSTT1 null: OR 79.35; 95% CI 10.40-605.55) on the multiplicative scale. Our findings have indicated that the individuals polymorphic for CYP1A1 MspI either with GSTM1 null or with GSTT1 null genotypes revealed an increased risk for UADT cancers than that ascribed to a single susceptible gene among the tobacco users in the population [single gene risk among smokers and chewers, respectively, for CYP1A1 MspI (OR 6.43; 95% CI 3.69-11.21); (OR 10.24; 95% CI 5.95-17.60), GSTM1*0 (OR 3.77; 95% CI 1.94-7.37); (OR 7.97 95% CI 4.10-15.76) and GSTT1*0 (OR 6.95 95% CI 2.88-16.77); (OR 25.83 95% CI 7.78-85.76).
Exploring the Genetic Etiology of Trust in Adolescents: Combined Twin and DNA Analyses.
Wootton, Robyn E; Davis, Oliver S P; Mottershaw, Abigail L; Wang, R Adele H; Haworth, Claire M A
2016-12-01
Behavioral traits generally show moderate to strong genetic influence, with heritability estimates of around 50%. Some recent research has suggested that trust may be an exception because it is more strongly influenced by social interactions. In a sample of over 7,000 adolescent twins from the United Kingdom's Twins Early Development Study, we found broad sense heritability estimates of 57% for generalized trust and 51% for trust in friends. Genomic-relatedness-matrix restricted maximum likelihood (GREML) estimates in the same sample indicate that 21% of the narrow sense genetic variance can be explained by common single nucleotide polymorphisms for generalized trust and 43% for trust in friends. As expected, this implies a large amount of unexplained heritability, although power is low for estimating DNA-based heritability. The missing heritability may be accounted for by interactions between DNA and the social environment during development or via gene-environment correlations with rare variants. How these genes and environments correlate seem especially important for the development of trust.
ERIC Educational Resources Information Center
Kieling, Christian; Hutz, Mara H.; Genro, Julia P.; Polanczyk, Guilherme V.; Anselmi, Luciana; Camey, Suzi; Hallal, Pedro C.; Barros, Fernando C.; Victora, Cesar G.; Menezes, Ana M. B.; Rohde, Luis Augusto
2013-01-01
Background: The study of gene-environment interactions (G by E) is one of the most promising strategies to uncover the origins of mental disorders. Replication of initial findings, however, is essential because there is a strong possibility of publication bias in the literature. In addition, there is a scarcity of research on the topic originated…
How Gene-Environment Interaction Affects Children's Anxious and Fearful Behavior. Science Briefs
ERIC Educational Resources Information Center
National Scientific Council on the Developing Child, 2007
2007-01-01
"Science Briefs" summarize the findings and implications of a recent study in basic science or clinical research. This brief reports on the study "Evidence for a Gene-Environment Interaction in Predicting Behavioral Inhibition in Middle Childhood" (N. A. Fox, K E. Nichols, H. A. Henderson, K. Rubin, L. Schmidt, D. Hamer, M. Ernst, and D. S.…
ERIC Educational Resources Information Center
Dunn, Erin C.; Uddin, Monica; Subramanian, S. V.; Smoller, Jordan W.; Galea, Sandro; Koenen, Karestan C.
2011-01-01
Background: Depression is a major public health problem among youth, currently estimated to affect as many as 9% of US children and adolescents. The recognition that both genes (nature) and environments (nurture) are important for understanding the etiology of depression has led to a rapid growth in research exploring gene-environment interactions…
Vrshek-Schallhorn, Suzanne; Mineka, Susan; Zinbarg, Richard E; Craske, Michelle G; Griffith, James W; Sutton, Jonathan; Redei, Eva E; Wolitzky-Taylor, Kate; Hammen, Constance; Adam, Emma K
2014-05-01
Meta-analytic evidence supports a gene-environment (G×E) interaction between life stress and the serotonin transporter polymorphism (5-HTTLPR) on depression, but few studies have examined factors that influence detection of this effect, despite years of inconsistent results. We propose that the "candidate environment" (akin to a candidate gene) is key. Theory and evidence implicate major stressful life events (SLEs)-particularly major interpersonal SLEs-as well as chronic family stress. Participants ( N = 400) from the Youth Emotion Project (which began with 627 high school juniors oversampled for high neuroticism) completed up to five annual diagnostic and life stress interviews and provided DNA samples. A significant G×E effect for major SLEs and S -carrier genotype was accounted for significantly by major interpersonal SLEs but not significantly by major non-interpersonal SLEs. S -carrier genotype and chronic family stress also significantly interacted. Identifying such candidate environments may facilitate future G×E research in depression and psychopathology more broadly.
ISAAC - InterSpecies Analysing Application using Containers.
Baier, Herbert; Schultz, Jörg
2014-01-15
Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories. To fill this niche, we have developed ISAAC, the InterSpecies Analysing Application using Containers. The central idea of this web based tool is to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. Furthermore, one can easily switch back to previous states and perform new analyses. Currently, sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. As todays research usually is performed in larger teams and consortia, ISAAC provides group based functionalities. Here, sets as well as results of analyses can be exchanged between members of groups. ISAAC fills the gap between primary databases and tools for the analysis of large gene lists. With its highly modular, JavaEE based design, the implementation of new modules is straight forward. Furthermore, ISAAC comes with an extensive web-based administration interface including tools for the integration of third party data. Thus, a local installation is easily feasible. In summary, ISAAC is tailor made for highly explorative interactive analyses of gene, transcript and protein sets in a collaborative environment.
Tao, Yebin; Sánchez, Brisa N; Mukherjee, Bhramar
2015-03-30
Many existing cohort studies designed to investigate health effects of environmental exposures also collect data on genetic markers. The Early Life Exposures in Mexico to Environmental Toxicants project, for instance, has been genotyping single nucleotide polymorphisms on candidate genes involved in mental and nutrient metabolism and also in potentially shared metabolic pathways with the environmental exposures. Given the longitudinal nature of these cohort studies, rich exposure and outcome data are available to address novel questions regarding gene-environment interaction (G × E). Latent variable (LV) models have been effectively used for dimension reduction, helping with multiple testing and multicollinearity issues in the presence of correlated multivariate exposures and outcomes. In this paper, we first propose a modeling strategy, based on LV models, to examine the association between repeated outcome measures (e.g., child weight) and a set of correlated exposure biomarkers (e.g., prenatal lead exposure). We then construct novel tests for G × E effects within the LV framework to examine effect modification of outcome-exposure association by genetic factors (e.g., the hemochromatosis gene). We consider two scenarios: one allowing dependence of the LV models on genes and the other assuming independence between the LV models and genes. We combine the two sets of estimates by shrinkage estimation to trade off bias and efficiency in a data-adaptive way. Using simulations, we evaluate the properties of the shrinkage estimates, and in particular, we demonstrate the need for this data-adaptive shrinkage given repeated outcome measures, exposure measures possibly repeated and time-varying gene-environment association. Copyright © 2014 John Wiley & Sons, Ltd.
Smith-Paine, Julia; Wade, Shari L; Treble-Barna, Amery; Zhang, Nanhua; Zang, Huaiyu; Martin, Lisa J; Yeates, Keith Owen; Taylor, H Gerry; Kurowski, Brad G
2018-05-02
This study examined whether the ankyrin repeat and kinase domain containing 1 gene (ANKK1) C/T single-nucleotide polymorphism (SNP) rs1800497 moderated the association of family environment with long-term executive function (EF) following traumatic injury in early childhood. Caregivers of children with traumatic brain injury (TBI) and children with orthopedic injury (OI) completed the Behavior Rating Inventory of Executive Function (BRIEF) at post injury visits. DNA was collected to identify the rs1800497 genotype in the ANKK1 gene. General linear models examined gene-environment interactions as moderators of the effects of TBI on EF at two times post injury (12 months and 7 years). At 12 months post injury, analyses revealed a significant 3-way interaction of genotype with level of permissive parenting and injury type. Post-hoc analyses showed genetic effects were more pronounced for children with TBI from more positive family environments, such that children with TBI who were carriers of the risk allele (T-allele) had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. At 7 years post injury, analyses revealed a significant 2-way interaction of genotype with level of authoritarian parenting. Post-hoc analyses found that carriers of the risk allele had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. These results suggest a gene-environment interaction involving the ANKK1 gene as a predictor of EF in a pediatric injury population. The findings highlight the importance of considering environmental influences in future genetic studies on recovery following TBI and other traumatic injuries in childhood.
Social defeat interacts with Disc1 mutations in the mouse to affect behavior.
Haque, F Nipa; Lipina, Tatiana V; Roder, John C; Wong, Albert H C
2012-08-01
DISC1 (Disrupted-in-schizophrenia 1) is a strong candidate susceptibility gene for psychiatric disease that was originally discovered in a family with a chromosomal translocation severing this gene. Although the family members with the translocation had an identical genetic mutation, their clinical diagnosis and presentation varied significantly. Gene-environment interactions have been proposed as a mechanism underlying the complex heritability and variable phenotype of psychiatric disorders such as major depressive disorder and schizophrenia. We hypothesized that gene-environment interactions would affect behavior in a mutant Disc1 mouse model. We examined the effect of chronic social defeat (CSD) as an environmental stressor in two lines of mice carrying different Disc1 point mutations, on behaviors relevant to psychiatric illness: locomotion in a novel open field (OF), pre-pulse inhibition (PPI) of the acoustic startle response, latent inhibition (LI), elevated plus maze (EPM), forced swim test (FST), sucrose consumption (SC), and the social interaction task for sociability and social novelty (SSN). We found that Disc1-L100P +/- and wild-type mice have similar anxiety responses to CSD, while Q31L +/- mice had a very different response. We also found evidence of significant gene-environment interactions in the OF, EPM and SSN. Copyright © 2012 Elsevier B.V. All rights reserved.
Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin
2016-01-15
As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.
From genomics to chemical genomics: new developments in KEGG
Kanehisa, Minoru; Goto, Susumu; Hattori, Masahiro; Aoki-Kinoshita, Kiyoko F.; Itoh, Masumi; Kawashima, Shuichi; Katayama, Toshiaki; Araki, Michihiro; Hirakawa, Mika
2006-01-01
The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource () provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES) and the chemical space (KEGG LIGAND), and wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY). A fourth component, KEGG BRITE, has been formally added to the KEGG suite of databases. This reflects our attempt to computerize functional interpretations as part of the pathway reconstruction process based on the hierarchically structured knowledge about the genomic, chemical and network spaces. In accordance with the new chemical genomics initiatives, the scope of KEGG LIGAND has been significantly expanded to cover both endogenous and exogenous molecules. Specifically, RPAIR contains curated chemical structure transformation patterns extracted from known enzymatic reactions, which would enable analysis of genome-environment interactions, such as the prediction of new reactions and new enzyme genes that would degrade new environmental compounds. Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps. PMID:16381885
Aubin-Horth, N.; Letcher, B.H.; Hofmann, H.A.
2005-01-01
Organisms that share the same genotype can develop into divergent phenotypes, depending on environmental conditions. In Atlantic salmon, young males of the same age can be found either as sneakers or immature males that are future anadromous fish. Just as the organism-level phenotype varies between divergent male developmental trajectories, brain gene expression is expected to vary as well. We hypothesized that rearing environment can also have an important effect on gene expression in the brain and possibly interact with the reproductive tactic adopted. We tested this hypothesis by comparing brain gene expression profiles of the two male tactics in fish from the same population that were reared in either a natural stream or under laboratory conditions. We found that expression of certain genes was affected by rearing environment only, while others varied between male reproductive tactics independent of rearing environment. Finally, more than half of all genes that showed variable expression varied between the two male tactics only in one environment. Thus, in these fish, very different molecular pathways can give rise to similar macro-phenotypes depending on rearing environment. This result gives important insights into the molecular underpinnings of developmental plasticity in relationship to the environment. ?? 2005 The American Genetic Association.
Modeling Gene-Environment Interactions With Quasi-Natural Experiments.
Schmitz, Lauren; Conley, Dalton
2017-02-01
This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.
Mazul, Angela L; Siega-Riz, Anna Maria; Weinberg, Clarice R; Engel, Stephanie M.; Zou, Fei; Carrier, Kathryn S.; Basta, Patricia V; Vaksman, Zalman; Maris, John M; Diskin, Sharon J; Maxen, Charlene; Naranjo, Arlene; Olshan, Andrew F
2016-01-01
Purpose Neuroblastoma is a childhood cancer of the sympathetic nervous system with embryonic origins. Previous epidemiologic studies suggest maternal vitamin supplementation during pregnancy reduces the risk of neuroblastoma. We hypothesized offspring and maternal genetic variants in folate-related and choline-related genes are associated with neuroblastoma and modify the effects of maternal intake of folate, choline and folic acid. Methods The Neuroblastoma Epidemiology in North America (NENA) study recruited 563 affected children and their parents through the Children’s Oncology Group’s Childhood Cancer Research Network. We used questionnaires to ascertain pre-pregnancy supplementation and estimate usual maternal dietary intake of folate, choline and folic acid. We genotyped 955 genetic variants related to folate or choline using DNA extracted from saliva samples and used a log-linear model to estimate both child and maternal risk ratios and stratum-specific risk ratios for gene-environment interactions. Results Overall, no maternal or offspring genotypic results met criteria for a false discovery rate (FDR) Q-value <0.2. Associations were also null for gene-environment interaction with pre-pregnancy vitamin supplementation, dietary folic acid and folate. FDR significant gene-choline interactions were found for offspring SNPs rs10489810 and rs9966612 located in MTHFD1L and TYMS, respectively, with maternal choline dietary intake dichotomized at the first quartile. Conclusion These results suggest that variants related to one-carbon metabolism are not strongly associated with neuroblastoma. Choline-related variants may play a role; however, the functional consequences of the interacting variants are unknown and require independent replication. PMID:27541142
Genetics of Addiction: Future Focus on Gene × Environment Interaction?
Vink, Jacqueline M
2016-09-01
The heritability of substance use is moderate to high. Successful efforts to find genetic variants associated with substance use (smoking, alcohol, cannabis) have been undertaken by large consortia. However, the proportion of phenotypic variance explained by the identified genetic variants is small. Interestingly, there is overlap between the genetic variants that influence different substances. Moreover, there are sets of "substance-specific" genes and sets of genes contributing to a "vulnerability for addictive behavior" in general. It is important to recognize that genes alone do not determine addiction phenotypes: Environmental factors such as parental monitoring, peer pressure, or socioeconomic status also play an important role. Despite a rich epidemiologic literature focused on the social determinants of substance use, few studies have examined the moderation of genetic influences like gene-environment (G × E) interactions. Understanding this balance may hold the key to understanding the individual differences in substance use, abuse, and addictive behavior. Recommendations for future research are described in this commentary and include increasing the power of G × E studies by using state-of-the-art methods such as polygenic risk scores instead of single genetic variants and taking genetic overlap between substances into account. Future genetic studies should also investigate environmental risk factors for addictive behavior more extensively to unravel the interaction between nature and nurture. Focusing on G × E interactions not only will give insight into the underlying biological mechanism but will also characterize subgroups (based on environmental factors) at high risk for addictive behaviors. With this information, we could bridge the gap between fundamental research and applications for society.
Mazul, Angela L; Siega-Riz, Anna Maria; Weinberg, Clarice R; Engel, Stephanie M; Zou, Fei; Carrier, Kathryn S; Basta, Patricia V; Vaksman, Zalman; Maris, John M; Diskin, Sharon J; Maxen, Charlene; Naranjo, Arlene; Olshan, Andrew F
2016-10-01
Neuroblastoma is a childhood cancer of the sympathetic nervous system with embryonic origins. Previous epidemiologic studies suggest maternal vitamin supplementation during pregnancy reduces the risk of neuroblastoma. We hypothesized offspring and maternal genetic variants in folate-related and choline-related genes are associated with neuroblastoma and modify the effects of maternal intake of folate, choline, and folic acid. The Neuroblastoma Epidemiology in North America (NENA) study recruited 563 affected children and their parents through the Children's Oncology Group's Childhood Cancer Research Network. We used questionnaires to ascertain pre-pregnancy supplementation and estimate usual maternal dietary intake of folate, choline, and folic acid. We genotyped 955 genetic variants related to folate or choline using DNA extracted from saliva samples and used a log-linear model to estimate both child and maternal risk ratios and stratum-specific risk ratios for gene-environment interactions. Overall, no maternal or offspring genotypic results met criteria for a false discovery rate (FDR) Q-value <0.2. Associations were also null for gene-environment interaction with pre-pregnancy vitamin supplementation, dietary folic acid, and folate. FDR-significant gene-choline interactions were found for offspring SNPs rs10489810 and rs9966612 located in MTHFD1L and TYMS, respectively, with maternal choline dietary intake dichotomized at the first quartile. These results suggest that variants related to one-carbon metabolism are not strongly associated with neuroblastoma. Choline-related variants may play a role; however, the functional consequences of the interacting variants are unknown and require independent replication.
Sawano, Erika; Doi, Hirokazu; Nagai, Tomoko; Ikeda, Satoko; Shinohara, Kauyuki
2017-05-15
Maternal positive attitude towards one's own infant is the cornerstone of effective parenting. Previous research has revealed an influence of both genetic and environmental factors on maternal parenting behavior, but little is known of the potential gene-environment interaction in shaping a mother's affective attitude. To address this gap, we investigated the effect of a mother's childhood rearing environment and a serotonin transporter gene polymorphism (5-HTTLPR) on affective attitude towards her infant. Our analyses found an interactive effect between rearing environment and 5-HTTLPR genotype on maternal attitude. Specifically, a poor rearing environment (characterized by low maternal care and high paternal overprotection) decreased positive attitude towards one's own infant in mothers with homozygous short allele genotype. In contrast, this detrimental effect was almost eliminated in long allele carriers. Altogether, our results indicate that the 5-HTTLPR gene moderates the influence of experienced rearing environment on maternal parental behavior in a manner consistent with the notion that the short 5-HTTLPR allele amplifies environmental influence. Copyright © 2016 Elsevier B.V. All rights reserved.
Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander
2015-01-01
Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411
ERIC Educational Resources Information Center
Guimond, Fanny-Alexandra; Brendgen, Mara; Vitaro, Frank; Forget-Dubois, Nadine; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel
2014-01-01
This study used a genetically informed design to assess the effects of friends' and nonfriends' reticent and dominant behaviors on children's observed social reticence in a competitive situation. Potential gene-environment correlations (rGE) and gene-environment interactions (GxE) in the link between (a) friends' and…
Caetano-Anollés, Kelsey; Rhodes, Justin S; Garland, Theodore; Perez, Sam D; Hernandez, Alvaro G; Southey, Bruce R; Rodriguez-Zas, Sandra L
2016-01-01
The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors.
Caetano-Anollés, Kelsey; Rhodes, Justin S.; Garland, Theodore; Perez, Sam D.; Hernandez, Alvaro G.; Southey, Bruce R.; Rodriguez-Zas, Sandra L.
2016-01-01
The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors. PMID:27893846
Gene–environment interaction in tobacco-related cancers
Taioli, Emanuela
2008-01-01
This review summarizes the carcinogenic effects of tobacco smoke and the basis for interaction between tobacco smoke and genetic factors. Examples of published papers on gene–tobacco interaction and cancer risk are presented. The assessment of gene–environment interaction in tobacco-related cancers has been more complex than originally expected for several reasons, including the multiplicity of genes involved in tobacco metabolism, the numerous substrates metabolized by the relevant genes and the interaction of smoking with other metabolic pathways. Future studies on gene–environment interaction and cancer risk should include biomarkers of smoking dose, along with markers of quantitative historical exposure to tobacco. Epigenetic studies should be added to classic genetic analyses, in order to better understand gene–environmental interaction and individual susceptibility. Other metabolic pathways in competition with tobacco genetic metabolism/repair should be incorporated in epidemiological studies to generate a more complete picture of individual cancer risk associated with environmental exposure to carcinogens. PMID:18550573
Genetics and Peer Relations: A Review
ERIC Educational Resources Information Center
Brendgen, Mara
2012-01-01
Researchers have become increasingly interested in uncovering how genetic factors work together with the peer environment in influencing development. This article offers an overview of the state of knowledge. It first describes the different types of gene-environment correlations (rGE) and gene-environment interactions (GxE) that are of relevance…
Gao, Min; Li, Hang; Lv, Xiaoting; Zhou, Baosen; Yin, Zhihua
2018-06-07
Long noncoding RNAs (lncRNAs) play important roles in the development of human cancers. This is the first case-control study of the association between specific polymorphisms in lncRNA genes and the risk of lung cancer, as well as the gene-environment interaction between the polymorphisms and cooking oil fume exposure in Chinese never-smoking females. A hospital-based case-control study was carried out in Shenyang, Liaoning province. The study included 395 cases and 556 controls. The polymorphisms of rs4785367, rs3803662, rs10750417, and rs1814343 in lncRNA genes were analyzed. The gene-environment interactions were explored on both additive and multiplicative scale. In addition, the results were listed as follows: for rs3803662, compared with the individuals carrying homozygous TT genotype, those with homozygous CC genotype had the decreased risk of lung cancer (adjusted odds ratio [OR] = 0.61, 95% confidence interval [CI] = 0.40-0.92, p = 0.018). As for rs4785367, compared with homozygous TT, homozygous CC could lessen the risk of lung cancer (adjusted OR = 0.54, 95% CI = 0.33-0.89, p = 0.016). The recessive models of rs3803662 and rs4785367 showed significant association (adjusted OR = 0.65, 95% CIs = 0.44-0.97, p = 0.033; adjusted OR = 0.54, 95% CIs = 0.33-0.88, p = 0.014). The C allele of rs3803662 was suggested to be protective allele of lung cancer (adjusted OR = 0.80, 95% CI = 0.66-0.97, p = 0.023). However, rs10750417 and rs1814343 polymorphisms were not significantly associated with lung cancer risks. The measures of additive interaction and logistic models suggested that the gene-environment interactions were not statistically significant on both additive and multiplicative scales.
Kerwin, Rachel E; Feusier, Julie; Muok, Alise; Lin, Catherine; Larson, Brandon; Copeland, Daniel; Corwin, Jason A; Rubin, Matthew J; Francisco, Marta; Li, Baohua; Joseph, Bindu; Weinig, Cynthia; Kliebenstein, Daniel J
2017-08-01
Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Malhotra, Jyoti; Sartori, Samantha; Brennan, Paul; Zaridze, David; Szeszenia-Dabrowska, Neonila; Świątkowska, Beata; Rudnai, Peter; Lissowska, Jolanta; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Gaborieau, Valerie; Stücker, Isabelle; Foretova, Lenka; Janout, Vladimir; Boffetta, Paolo
2015-03-01
Occupational exposures are known risk factors for lung cancer. Role of genetically determined host factors in occupational exposure-related lung cancer is unclear. We used genome-wide association (GWA) data from a case-control study conducted in 6 European countries from 1998 to 2002 to identify gene-occupation interactions and related pathways for lung cancer risk. GWA analysis was performed for each exposure using logistic regression and interaction term for genotypes, and exposure was included in this model. Both SNP-based and gene-based interaction P values were calculated. Pathway analysis was performed using three complementary methods, and analyses were adjusted for multiple comparisons. We analyzed 312,605 SNPs and occupational exposure to 70 agents from 1,802 lung cancer cases and 1,725 cancer-free controls. Mean age of study participants was 60.1 ± 9.1 years and 75% were male. Largest number of significant associations (P ≤ 1 × 10(-5)) at SNP level was demonstrated for nickel, brick dust, concrete dust, and cement dust, and for brick dust and cement dust at the gene-level (P ≤ 1 × 10(-4)). Approximately 14 occupational exposures showed significant gene-occupation interactions with pathways related to response to environmental information processing via signal transduction (P < 0.001 and FDR < 0.05). Other pathways that showed significant enrichment were related to immune processes and xenobiotic metabolism. Our findings suggest that pathways related to signal transduction, immune process, and xenobiotic metabolism may be involved in occupational exposure-related lung carcinogenesis. Our study exemplifies an integrative approach using pathway-based analysis to demonstrate the role of genetic variants in occupational exposure-related lung cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 24(3); 570-9. ©2015 AACR. ©2015 American Association for Cancer Research.
Border, Richard; Keller, Matthew C
2017-03-01
Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.
Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Bailey, Jennifer; McGue, Matt; Iacono, William G.
2014-01-01
Background Previous studies have shown that genetic risk for externalizing (EXT) disorders is greater in the context of adverse family environments during adolescence, but it is unclear whether these effects are long-lasting. The current study evaluated developmental changes in gene-environment interplay in the concurrent and prospective associations between parent-child relationship problems and EXT at ages 18 and 25. Method The sample included 1,382 twin pairs (48% male) from the Minnesota Twin Family Study, participating in assessments at ages 18 (M = 17.8 years, SD = 0.69) and 25 (M = 25.0 years, SD = 0.90). Perceptions of parent-child relationship problems were assessed using questionnaires. Structured interviews were used to assess symptoms of adult antisocial behavior and nicotine, alcohol, and illicit drug dependence. Results We detected a gene-environment interaction at age 18, such that the genetic influence on EXT was greater in the context of more parent-child relationship problems. This moderation effect was not present at age 25, nor did parent-relationship problems at age 18 moderate genetic influence on EXT at age 25. Rather, common genetic influences accounted for this longitudinal association. Conclusions Gene-environment interaction evident in the relationship between adolescent parent-child relationship problems and EXT is both proximal and developmentally limited. Common genetic influence, rather than a gene-environment interaction, accounts for the long-term association between parent-child relationship problems at age 18 and EXT at age 25. These results are consistent with a relatively pervasive importance of gene-environmental correlation in the transition from late adolescence to young adulthood. PMID:25066478
A Critical Look at Entropy-Based Gene-Gene Interaction Measures.
Lee, Woojoo; Sjölander, Arvid; Pawitan, Yudi
2016-07-01
Several entropy-based measures for detecting gene-gene interaction have been proposed recently. It has been argued that the entropy-based measures are preferred because entropy can better capture the nonlinear relationships between genotypes and traits, so they can be useful to detect gene-gene interactions for complex diseases. These suggested measures look reasonable at intuitive level, but so far there has been no detailed characterization of the interactions captured by them. Here we study analytically the properties of some entropy-based measures for detecting gene-gene interactions in detail. The relationship between interactions captured by the entropy-based measures and those of logistic regression models is clarified. In general we find that the entropy-based measures can suffer from a lack of specificity in terms of target parameters, i.e., they can detect uninteresting signals as interactions. Numerical studies are carried out to confirm theoretical findings. © 2016 WILEY PERIODICALS, INC.
Interactions between genetic background, insulin resistance and β-cell function.
Kahn, S E; Suvag, S; Wright, L A; Utzschneider, K M
2012-10-01
An interaction between genes and the environment is a critical component underlying the pathogenesis of the hyperglycaemia of type 2 diabetes. The development of more sophisticated techniques for studying gene variants and for analysing genetic data has led to the discovery of some 40 genes associated with type 2 diabetes. Most of these genes are related to changes in β-cell function, with a few associated with decreased insulin sensitivity and obesity. Interestingly, using quantitative traits based on continuous measures rather than dichotomous ones, it has become evident that not all genes associated with changes in fasting or post-prandial glucose are also associated with a diagnosis of type 2 diabetes. Identification of these gene variants has provided novel insights into the physiology and pathophysiology of the β-cell, including the identification of molecules involved in β-cell function that were not previously recognized as playing a role in this critical cell. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.
Gene-gene and gene-environment interactions defining lipid-related traits.
Ordovás, José M; Robertson, Ruairi; Cléirigh, Ellen Ní
2011-04-01
Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia. Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity. Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.
Gender specific gene-environment interactions on laboratory-assessed aggression.
Verona, Edelyn; Joiner, Thomas E; Johnson, Frank; Bender, Theodore W
2006-01-01
We examined gene-environment interactive effects on aggressive behavior among men and women genotyped (short versus long alleles) for the serotonin transporter gene. Aggressive behavior was indexed via a laboratory paradigm that measured the intensity and duration of shocks delivered to a putative "employee". Half of the participants were exposed to a physical stressor during the procedure (stress) and half were not (no-stress). Participants' physiological responses were gauged via acoustic startle eyeblink reactions (startle reactivity). Results were that men with the homozygous short (s/s) genotype showed increased aggression only under stress, whereas women and men carrying the long allele did not show differences in aggression in stress versus no-stress. However, although stress exposure produced increases in startle reactivity, there were no genotype or gender differences in physiology. These results replicate longitudinal research findings confirming the interactive effects of genes and environment on behavioral reactivity and on the development of externalizing psychopathological syndromes, at least in men.
Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S
2009-11-24
There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.
The field of human genetics has experienced a paradigm shift in that common diseases are now thought to be due to the complex interactions among numerous genetic and environmental factors. This paradigm shift has prompted the development of myriad novel methods to detect such int...
Kim, Kyoung-Nam; Lee, Mee-Ri; Lim, Youn-Hee; Hong, Yun-Chul
2017-12-01
Homocysteine has been causally associated with various adverse health outcomes. Evidence supporting the relationship between lead and homocysteine levels has been accumulating, but most prior studies have not focused on the interaction with genetic polymorphisms. From a community-based prospective cohort, we analysed 386 participants (aged 41-71 years) with information regarding blood lead and plasma homocysteine levels. Blood lead levels were measured between 2001 and 2003, and plasma homocysteine levels were measured in 2007. Interactions of lead levels with 42 genotyped single-nucleotide polymorphisms (SNPs) in five genes ( TF , HFE , CBS , BHMT and MTR ) were assessed via a 2-degree of freedom (df) joint test and a 1-df interaction test. In secondary analyses using imputation, we further assessed 58 imputed SNPs in the TF and MTHFR genes. Blood lead concentrations were positively associated with plasma homocysteine levels (p=0.0276). Six SNPs in the TF and MTR genes were screened using the 2-df joint test, and among them, three SNPs in the TF gene showed interactions with lead with respect to homocysteine levels through the 1-df interaction test (p<0.0083). Seven SNPs in the MTHFR gene were associated with homocysteine levels at an α-level of 0.05, but the associations did not persist after Bonferroni correction. These SNPs did not show interactions with lead levels. Blood lead levels were positively associated with plasma homocysteine levels measured 4-6 years later, and three SNPs in the TF gene modified the association. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Lin, Kuei -Han; Liao, Ben -Yang; Chang, Hao -Wei; ...
2015-12-03
Microbial diversity and community structures in acidic hot springs have been characterized by 16S rRNA gene-based diversity surveys. However, our understanding regarding the interactions among microbes, or between microbes and environmental factors, remains limited. In the present study, a metagenomic approach, followed by bioinformatics analyses, were used to predict interactions within the microbial ecosystem in Shi-Huang-Ping (SHP), an acidic hot spring in northern Taiwan. Characterizing environmental parameters and potential metabolic pathways highlighted the importance of carbon assimilatory pathways. Four distinct carbon assimilatory pathways were identified in five dominant genera of bacteria. Of those dominant carbon fixers, Hydrogenobaculum bacteria outcompeted othermore » carbon assimilators and dominated the SHP, presumably due to their ability to metabolize hydrogen and to withstand an anaerobic environment with fluctuating temperatures. Furthermore, most dominant microbes were capable of metabolizing inorganic sulfur-related compounds (abundant in SHP). However, Acidithiobacillus ferrooxidans was the only species among key rare microbes with the capability to fix nitrogen, suggesting a key role in nitrogen cycling. In addition to potential metabolic interactions, based on the 16S rRNAs gene sequence of Nanoarchaeum-related and its potential host Ignicoccus-related archaea, as well as sequences of viruses and CRISPR arrays, we inferred that there were complex microbe-microbe interactions. In conclusion, our study provided evidence that there were numerous microbe-microbe and microbe-environment interactions within the microbial community in an acidic hot spring. We proposed that Hydrogenobaculum bacteria were the dominant microbial genus, as they were able to metabolize hydrogen, assimilate carbon and live in an anaerobic environment with fluctuating temperatures.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, Kuei -Han; Liao, Ben -Yang; Chang, Hao -Wei
Microbial diversity and community structures in acidic hot springs have been characterized by 16S rRNA gene-based diversity surveys. However, our understanding regarding the interactions among microbes, or between microbes and environmental factors, remains limited. In the present study, a metagenomic approach, followed by bioinformatics analyses, were used to predict interactions within the microbial ecosystem in Shi-Huang-Ping (SHP), an acidic hot spring in northern Taiwan. Characterizing environmental parameters and potential metabolic pathways highlighted the importance of carbon assimilatory pathways. Four distinct carbon assimilatory pathways were identified in five dominant genera of bacteria. Of those dominant carbon fixers, Hydrogenobaculum bacteria outcompeted othermore » carbon assimilators and dominated the SHP, presumably due to their ability to metabolize hydrogen and to withstand an anaerobic environment with fluctuating temperatures. Furthermore, most dominant microbes were capable of metabolizing inorganic sulfur-related compounds (abundant in SHP). However, Acidithiobacillus ferrooxidans was the only species among key rare microbes with the capability to fix nitrogen, suggesting a key role in nitrogen cycling. In addition to potential metabolic interactions, based on the 16S rRNAs gene sequence of Nanoarchaeum-related and its potential host Ignicoccus-related archaea, as well as sequences of viruses and CRISPR arrays, we inferred that there were complex microbe-microbe interactions. In conclusion, our study provided evidence that there were numerous microbe-microbe and microbe-environment interactions within the microbial community in an acidic hot spring. We proposed that Hydrogenobaculum bacteria were the dominant microbial genus, as they were able to metabolize hydrogen, assimilate carbon and live in an anaerobic environment with fluctuating temperatures.« less
Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies
Aschard, Hugues; Lutz, Sharon; Maus, Bärbel; Duell, Eric J.; Fingerlin, Tasha; Chatterjee, Nilanjan; Kraft, Peter; Van Steen, Kristel
2012-01-01
The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes. PMID:22760307
Brezo, J; Bureau, A; Mérette, C; Jomphe, V; Barker, E D; Vitaro, F; Hébert, M; Carbonneau, R; Tremblay, R E; Turecki, G
2010-08-01
To investigate similarities and differences in the serotonergic diathesis for mood disorders and suicide attempts, we conducted a study in a cohort followed longitudinally for 22 years. A total of 1255 members of this cohort, which is representative of the French-speaking population of Quebec, were investigated. Main outcome measures included (1) mood disorders (bipolar disorder and major depression) and suicide attempts by early adulthood; (2) odds ratios and probabilities associated with 143 single nucleotide polymorphisms in 11 serotonergic genes, acting directly or as moderators in gene-environment interactions with childhood sexual or childhood physical abuse (CPA), and in gene-gene interactions; (3) regression coefficients for putative endophenotypes for mood disorders (childhood anxiousness) and suicide attempts (childhood disruptiveness). Five genes showed significant adjusted effects (HTR2A, TPH1, HTR5A, SLC6A4 and HTR1A). Of these, HTR2A variation influenced both suicide attempts and mood disorders, although through different mechanisms. In suicide attempts, HTR2A variants (rs6561333, rs7997012 and rs1885884) were involved through interactions with histories of sexual and physical abuse whereas in mood disorders through one main effect (rs9316235). In terms of phenotype-specific contributions, TPH1 variation (rs10488683) was relevant only in the diathesis for suicide attempts. Three genes contributed exclusively to mood disorders, one through a main effect (HTR5A (rs1657268)) and two through gene-environment interactions with CPA (HTR1A (rs878567) and SLC6A4 (rs3794808)). Childhood anxiousness did not mediate the effects of HTR2A and HTR5A on mood disorders, nor did childhood disruptiveness mediate the effects of TPH1 on suicide attempts. Of the serotonergic genes implicated in mood disorders and suicidal behaviors, four exhibited phenotype-specific effects, suggesting that despite their high concordance and common genetic determinants, suicide attempts and mood disorders may also have partially independent etiological pathways. To identify where these pathways diverge, we need to understand the differential, phenotype-specific gene-environment interactions such as the ones observed in the present study, using suitably powered samples.
ERIC Educational Resources Information Center
Carlson, Marie D.; Mendle, Jane; Harden, K. Paige
2014-01-01
Youth who experience adverse environments in early life initiate sexual activity at a younger age, on average, than those from more advantaged circumstances. Evolutionary theorists have posited that ecological stress precipitates earlier reproductive and sexual onset, but it is unclear how stressful environments interact with genetic influences on…
Genes, emotions and gut microbiota: The next frontier for the gastroenterologist
Panduro, Arturo; Rivera-Iñiguez, Ingrid; Sepulveda-Villegas, Maricruz; Roman, Sonia
2017-01-01
Most medical specialties including the field of gastroenterology are mainly aimed at treating diseases rather than preventing them. Genomic medicine studies the health/disease process based on the interaction of the human genes with the environment. The gastrointestinal (GI) system is an ideal model to analyze the interaction between our genes, emotions and the gut microbiota. Based on the current knowledge, this mini-review aims to provide an integrated synopsis of this interaction to achieve a better understanding of the GI disorders related to bad eating habits and stress-related disease. Since human beings are the result of an evolutionary process, many biological processes such as instincts, emotions and behavior are interconnected to guarantee survival. Nourishment is a physiological need triggered by the instinct of survival to satisfy the body’s energy demands. The brain-gut axis comprises a tightly connected neural-neuroendocrine circuitry between the hunger-satiety center, the dopaminergic reward system involved in the pleasure of eating and the gut microbiota that regulates which food we eat and emotions. However, genetic variations and the consumption of high-sugar and high-fat diets have overridden this energy/pleasure neurocircuitry to the point of addiction of several foodstuffs. Consequently, a gut dysbiosis generates inflammation and a negative emotional state may lead to chronic diseases. Balancing this altered processes to regain health may involve personalized-medicine and genome-based strategies. Thus, an integrated approach based on the understanding of the gene-emotions-gut microbiota interaction is the next frontier that awaits the gastroenterologist to prevent and treat GI disorders associated with obesity and negative emotions. PMID:28533660
Genes, emotions and gut microbiota: The next frontier for the gastroenterologist.
Panduro, Arturo; Rivera-Iñiguez, Ingrid; Sepulveda-Villegas, Maricruz; Roman, Sonia
2017-05-07
Most medical specialties including the field of gastroenterology are mainly aimed at treating diseases rather than preventing them. Genomic medicine studies the health/disease process based on the interaction of the human genes with the environment. The gastrointestinal (GI) system is an ideal model to analyze the interaction between our genes, emotions and the gut microbiota. Based on the current knowledge, this mini-review aims to provide an integrated synopsis of this interaction to achieve a better understanding of the GI disorders related to bad eating habits and stress-related disease. Since human beings are the result of an evolutionary process, many biological processes such as instincts, emotions and behavior are interconnected to guarantee survival. Nourishment is a physiological need triggered by the instinct of survival to satisfy the body's energy demands. The brain-gut axis comprises a tightly connected neural-neuroendocrine circuitry between the hunger-satiety center, the dopaminergic reward system involved in the pleasure of eating and the gut microbiota that regulates which food we eat and emotions. However, genetic variations and the consumption of high-sugar and high-fat diets have overridden this energy/pleasure neurocircuitry to the point of addiction of several foodstuffs. Consequently, a gut dysbiosis generates inflammation and a negative emotional state may lead to chronic diseases. Balancing this altered processes to regain health may involve personalized-medicine and genome-based strategies. Thus, an integrated approach based on the understanding of the gene-emotions-gut microbiota interaction is the next frontier that awaits the gastroenterologist to prevent and treat GI disorders associated with obesity and negative emotions.
Bisphenol-A and Female Infertility: A Possible Role of Gene-Environment Interactions
Huo, Xiaona; Chen, Dan; He, Yonghua; Zhu, Wenting; Zhou, Wei; Zhang, Jun
2015-01-01
Background: Bisphenol-A (BPA) is widely used and ubiquitous in the environment. Animal studies indicate that BPA affects reproduction, however, the gene-environment interaction mechanism(s) involved in this association remains unclear. We performed a literature review to summarize the evidence on this topic. Methods: A comprehensive search was conducted in PubMed using as keywords BPA, gene, infertility and female reproduction. Full-text articles in both human and animals published in English prior to December 2014 were selected. Results: Evidence shows that BPA can interfere with endocrine function of hypothalamic-pituitary axis, such as by changing gonadotropin-releasing hormones (GnRH) secretion in hypothalamus and promoting pituitary proliferation. Such actions affect puberty, ovulation and may even result in infertility. Ovary, uterus and other reproductive organs are also targets of BPA. BPA exposure impairs the structure and functions of female reproductive system in different times of life cycle and may contribute to infertility. Both epidemiological and experimental evidences demonstrate that BPA affects reproduction-related gene expression and epigenetic modification that are closely associated with infertility. The detrimental effects on reproduction may be lifelong and transgenerational. Conclusions: Evidence on gene-environment interactions, especially from human studies, is still limited. Further research on this topic is warranted. PMID:26371021
LoParo, Devon; Johansson, Ada; Walum, Hasse; Westberg, Lars; Santtila, Pekka; Waldman, Irwin
2016-07-01
Naturalistic studies of gene-environment interactions (G X E) have been plagued by several limitations, including difficulty isolating specific environmental risk factors from other correlated aspects of the environment, gene-environment correlation (rGE ), and the use of a single genetic variant to represent the influence of a gene. We present results from 235 Finnish young men in two lab studies of aggression and alcohol challenge that attempt to redress these limitations of the extant G X E literature. Specifically, we use a latent variable modeling approach in an attempt to more fully account for genetic variation across the oxytocin receptor gene (OXTR) and to robustly test its main effects on aggression and its interaction with alcohol exposure. We also modeled aggression as a latent variable comprising various indices, including the average and maximum levels of aggression, the earliest trial on which aggression was expressed, and the proportion of trials on which the minimum and maximum levels of aggression were expressed. The best fitting model for the genetic variation across OXTR included six factors derived from an exploratory factor analysis, roughly corresponding to six haplotype blocks. Aggression levels were higher on trials in which participants were administered alcohol, won, or were provoked. There was a significant main effect of OXTR on aggression across studies after controlling for covariates. The interaction of OXTR and alcohol was also significant across studies, such that OXTR had stronger effects on aggression in the alcohol administration condition. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Basson, Jacob; Sung, Yun Ju; de Las Fuentes, Lisa; Schwander, Karen L; Vazquez, Ana; Rao, Dabeeru C
2016-01-01
Blood pressure (BP) has been shown to be substantially heritable, yet identified genetic variants explain only a small fraction of the heritability. Gene-smoking interactions have detected novel BP loci in cross-sectional family data. Longitudinal family data are available and have additional promise to identify BP loci. However, this type of data presents unique analysis challenges. Although several methods for analyzing longitudinal family data are available, which method is the most appropriate and under what conditions has not been fully studied. Using data from three clinic visits from the Framingham Heart Study, we performed association analysis accounting for gene-smoking interactions in BP at 31,203 markers on chromosome 22. We evaluated three different modeling frameworks: generalized estimating equations (GEE), hierarchical linear modeling, and pedigree-based mixed modeling. The three models performed somewhat comparably, with multiple overlaps in the most strongly associated loci from each model. Loci with the greatest significance were more strongly supported in the longitudinal analyses than in any of the component single-visit analyses. The pedigree-based mixed model was more conservative, with less inflation in the variant main effect and greater deflation in the gene-smoking interactions. The GEE, but not the other two models, resulted in substantial inflation in the tail of the distribution when variants with minor allele frequency <1% were included in the analysis. The choice of analysis method should depend on the model and the structure and complexity of the familial and longitudinal data. © 2015 WILEY PERIODICALS, INC.
Fox, E; Beevers, C G
2016-12-01
Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic 'reactivity' or 'sensitivity' may represent heightened sensitivity to the learning environment in a 'for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in 'both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies.
Vázquez-Rosas-Landa, Mirna; Ponce-Soto, Gabriel Yaxal; Eguiarte, Luis E; Souza, V
2017-07-31
Bacteria have numerous strategies to interact with themselves and with their environment, but genes associated with these interactions are usually cataloged as pathogenic. To understand the role that these genes have not only in pathogenesis but also in bacterial interactions, we compared the genomes of eight bacteria from human-impacted environments with those of free-living bacteria from the Cuatro Ciénegas Basin (CCB), a relatively pristine oligotrophic site. Fifty-one genomes from CCB bacteria, including Pseudomonas, Vibrio, Photobacterium and Aeromonas, were analyzed. We found that the CCB strains had several virulence-related genes, 15 of which were common to all strains and were related to flagella and chemotaxis. We also identified the presence of Type III and VI secretion systems, which leads us to propose that these systems play an important role in interactions among bacterial communities beyond pathogenesis. None of the CCB strains had pathogenicity islands, despite having genes associated with antibiotics. Integrons were rare, while CRISPR elements were common. The idea that pathogenicity-related genes in many cases form part of a wider strategy used by bacteria to interact with other organisms could help us to understand the role of pathogenicity-related elements in an ecological and evolutionary framework leading toward a more inclusive One Health concept. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
The psychiatric phenotype in triple X syndrome: New hypotheses illustrated in two cases
Otter, Maarten; Schrander-Stumpel, Constance T. R. M.; Didden, Robert; Curfs, Leopold M. G.
2012-01-01
Background: Triple X syndrome (47,XXX or trisomy X) is a relatively frequent cytogenetic condition with a large variety of physical and behavioural phenotypes. Method: Two adult patients with a triple X karyotype are described. Results: Their karyotype was unknown until some years ago. What these patients have in common is that they were diagnosed with a broader autism phenotype, they were sexually abused, they suffer from psychotic illness and they show challenging behaviour, suicidality and a decline in occupational capacity. Discussion: These gene-environment interactions are discussed. Gene-environment interactions may explain the variety of behavioural and psychiatric phenotypes in triple X syndrome. Ongoing atypical development in adults is hypothesized. Conclusions: Gene-environment interactions and ongoing atypical development in adults should be taken into account in research concerning the psychiatric phenotype of developmental disorders, especially those involving triple X syndrome. PMID:22582855
Kim, Young Shin; Leventhal, Bennett L.
2014-01-01
Understanding the pathogenesis of Neurodevelopmental Disorders (NDDs) has proven to be challenging. Using Autism Spectrum Disorder (ASD) as a paradigmatic NDD, this paper reviews the existing literature on the etiologic substrates of ASD and explores how genetic epidemiology approaches including gene-environment interactions (GxE) can play roles in identifying factors associated with ASD etiology. New genetic and bioinformatics strategies have yielded important clues to ASD genetic substrates. Next steps for understanding ASD pathogenesis require significant effort to focus on how genes and environment interact with one another in typical development and its perturbations. Along with larger sample sizes, future study designs should include sample ascertainment that is epidemiologic and population-based to capture the entire ASD spectrum with both categorical and dimensional phenotypic characterization, environmental measurement with accuracy, validity and biomarkers, statistical methods to address population stratification, multiple comparisons and GxE of rare variants, animal models to test hypotheses and, new methods to broaden the capacity to search for GxE, including genome-wide and environment-wide association studies, precise estimation of heritability using dense genetic markers and consideration of GxE both as the disease cause and a disease course modifier. While examination of GxE appears to be a daunting task, tremendous recent progress in gene discovery opens new horizons for advancing our understanding the role of GxE in the pathogenesis of, and ultimately identifying the causes, treatments and even prevention for ASD and other NDDs. PMID:25483344
Miraldi Utz, Virginia
2017-01-01
Myopia is the most common eye disorder and major cause of visual impairment worldwide. As the incidence of myopia continues to rise, the need to further understand the complex roles of molecular and environmental factors controlling variation in refractive error is of increasing importance. Tkatchenko and colleagues applied a systematic approach using a combination of gene set enrichment analysis, genome-wide association studies, and functional analysis of a murine model to identify a myopia susceptibility gene, APLP2. Differential expression of refractive error was associated with time spent reading for those with low frequency variants in this gene. This provides support for the longstanding hypothesis of gene-environment interactions in refractive error development.
Boutwell, Brian B; Beaver, Kevin M; Barnes, James C; Vaske, Jamie
2012-05-30
A line of research has revealed that the influence of genes on behavioral development is closely tied to environmental experiences. Known as gene-environment interaction, research in this area is beginning to reveal that variation in parenting behaviors may moderate genetic influences on antisocial behaviors in children. Despite growing interest in gene-environment interaction research, little evidence exists concerning the role of maternal disengagement in the conditioning of genetic influences on childhood behavioral problems. The current study is intended to address this gap in the literature by analyzing a sample of twin pairs drawn from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B). Analysis of the ECLS-B provided evidence that maternal disengagement moderates genetic influences on the development of externalizing problems. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Nigenda-Morales, Sergio F; Hu, Yibo; Beasley, James C; Ruiz-Piña, Hugo A; Valenzuela-Galván, David; Wayne, Robert K
2018-06-01
Skin pigmentation and coat pigmentation are two of the best-studied examples of traits under natural selection given their quantifiable fitness interactions with the environment (e.g., camouflage) and signalling with other organisms (e.g., warning coloration). Previous morphological studies have found that skin pigmentation variation in the Virginia opossum (Didelphis virginiana) is associated with variation in precipitation and temperatures across its distribution range following Gloger's rule (lighter pigmentation in temperate environments). To investigate the molecular mechanism associated with skin pigmentation variation, we used RNA-Seq and quantified gene expression of wild opossums from tropical and temperate populations. Using differential expression analysis and a co-expression network approach, we found that expression variation in genes with melanocytic and immune functions is significantly associated with the degree of skin pigmentation variation and may be underlying this phenotypic difference. We also found evidence suggesting that the Wnt/β-catenin signalling pathway might be regulating the depigmentation observed in temperate populations. Based on our study results, we present several alternative hypotheses that may explain Gloger's rule pattern of skin pigmentation variation in opossum, including changes in pathogen diversity supporting a pathogen-resistant hypothesis, thermal stress associated with temperate environments, and pleiotropic and epistatic interactions between melanocytic and immune genes. © 2018 John Wiley & Sons Ltd.
Culumber, Zachary W; Schumer, Molly; Monks, Scott; Tobler, Michael
2015-02-01
Theory predicts that environmental heterogeneity offers a potential solution to the maintenance of genetic variation within populations, but empirical evidence remains sparse. The live-bearing fish Xiphophorus variatus exhibits polymorphism at a single locus, with different alleles resulting in up to five distinct melanistic "tailspot" patterns within populations. We investigated the effects of heterogeneity in two ubiquitous environmental variables (temperature and food availability) on two fitness-related traits (upper thermal limits and body condition) in two different tailspot types (wild-type and upper cut crescent). We found gene-by-environment (G × E) interactions between tailspot type and food level affecting upper thermal limits (UTL), as well as between tailspot type and thermal environment affecting body condition. Exploring mechanistic bases underlying these G × E patterns, we found no differences between tailspot types in hsp70 gene expression despite significant overall increases in expression under both thermal and food stress. Similarly, there was no difference in routine metabolic rates between the tailspot types. The reversal of relative performance of the two tailspot types under different environmental conditions revealed a mechanism by which environmental heterogeneity can balance polymorphism within populations through selection on different fitness-related traits. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar
2016-03-01
Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.
A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects
Marigorta, Urko M.; Gibson, Greg
2014-01-01
The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits. PMID:25101110
Gene-Based Testing of Interactions in Association Studies of Quantitative Traits
Ma, Li; Clark, Andrew G.; Keinan, Alon
2013-01-01
Various methods have been developed for identifying gene–gene interactions in genome-wide association studies (GWAS). However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene–gene interaction (GGG) tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein–protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies. PMID:23468652
Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif
2015-05-15
Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.
Gene-Environment Correlation and Interaction in Peer Effects on Adolescent Alcohol and Tobacco Use
Harden, K. Paige; Hill, Jennifer E.; Turkheimer, Eric; Emery, Robert E.
2010-01-01
Peer relationships are commonly thought to be critical for adolescent socialization, including the development of negative health behaviors such as alcohol and tobacco use. The interplay between genetic liability and peer influences on the development of adolescent alcohol and tobacco use was examined using a nationally-representative sample of adolescent sibling pairs and their best friends. Genetic factors, some of them related to an adolescent's own substance use and some of them independent of use, were associated with increased exposure to best friends with heavy substance use—a gene-environment correlation. Moreover, adolescents who were genetically liable to substance use were more vulnerable to the adverse influences of their best friends—a gene-environment interaction. PMID:18368474
Luan, Jian'an; Mihailov, Evelin; Metspalu, Andres; Forouhi, Nita G.; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Hallmans, Göran; Chu, Audrey Y.; Justice, Anne E.; Graff, Mariaelisa; Rose, Lynda M.; Langenberg, Claudia; Cupples, L. Adrienne; Ridker, Paul M.; Ong, Ken K.; Loos, Ruth J. F.; Chasman, Daniel I.; Ingelsson, Erik; Kilpeläinen, Tuomas O.; Scott, Robert A.; Mägi, Reedik
2017-01-01
Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann–Whitney = 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10−9 and 8.52×10−7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them. PMID:28614350
Chi, Yunpeng; Shi, Conghong; Zhang, Xiaojiang; Xi, Yang
2018-05-04
To investigate the impact of PLA2G7 polymorphism, and additional their interactions with smoking and drinking on coronary heart disease (CHD) risk based on Chinese population. GMDR model was used to screen the best gene-smoking and gene-drinking interaction combinations. Logistic regression was performed to investigate association between 4 SNPs and CHD, and the interaction effect between rs1805017 and smoking. For CHD patient-control haplotype analyses, the SHEsis online haplotype analysis software ( http://analysis.bio-x.cn/myAnalysis.php ) was employed. CHD risks were higher in carriers of homozygous mutant of rs1805017 and rs1805018 than those with wild-type homozygotes, OR (95% CI) were 1.45 (1.16-1.92) and 1.51 (1.23-1.97), respectively, but the other two SNPs, rs16874954 and rs1051931 were not significant associated with CHD risks. GMDR analysis indicated that there was a significant two-locus model (p = 0.0107) involving rs1805017 and smoking, indicating a potential gene-environment interaction between rs1805017 and smoking. But we did not found any gene-drinking and gene-gene interaction combinations in GMDR models. The haplotype R-I was observed most frequently in two groups, with 47.43 and 54.38% in the case and control group of the population, respectively. The results also indicated that the haplotype containing the rs1805017-H and rs1805018-T alleles were associated with a statistically increased CHD risk, OR (95% CI) 1.43 (1.10-1.86), p = 0.0021. Polymorphisms in rs1805017 and rs1805018, additional interaction between rs1805017 and smoking, and haplotype containing the rs1805017-H and rs1805018-T alleles were associated with increased CHD risk.
Robinson, Joshua F; Port, Jesse A; Yu, Xiaozhong; Faustman, Elaine M
2010-10-01
To understand the complex etiology of developmental disorders, an understanding of both genetic and environmental risk factors is needed. Human and rodent genetic studies have identified a multitude of gene candidates for specific developmental disorders such as neural tube defects (NTDs). With the emergence of toxicogenomic-based assessments, scientists now also have the ability to compare and understand the expression of thousands of genes simultaneously across strain, time, and exposure in developmental models. Using a systems-based approach in which we are able to evaluate information from various parts and levels of the developing organism, we propose a framework for integrating genetic information with toxicogenomic-based studies to better understand gene-environmental interactions critical for developmental disorders. This approach has allowed us to characterize candidate genes in the context of variables critical for determining susceptibility such as strain, time, and exposure. Using a combination of toxicogenomic studies and complementary bioinformatic tools, we characterize NTD candidate genes during normal development by function (gene ontology), linked phenotype (disease outcome), location, and expression (temporally and strain-dependent). In addition, we show how environmental exposures (cadmium, methylmercury) can influence expression of these genes in a strain-dependent manner. Using NTDs as an example of developmental disorder, we show how simple integration of genetic information from previous studies into the standard microarray design can enhance analysis of gene-environment interactions to better define environmental exposure-disease pathways in sensitive and resistant mouse strains. © Wiley-Liss, Inc.
Bokulich, Nicholas A; Bergsveinson, Jordyn; Ziola, Barry; Mills, David A
2015-01-01
Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments. DOI: http://dx.doi.org/10.7554/eLife.04634.001 PMID:25756611
Cheon, Bobby K; Livingston, Robert W; Hong, Ying-Yi; Chiao, Joan Y
2014-09-01
Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene-environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Lazary, Judit
2017-12-01
Although genetic studies have improved a lot in recent years, without clinical relevance sometimes their significance is devalued. Reviewing the major milestones of psychogenomics it can be seen that break-through success is just a question of time. Investigations of direct effect of genetic variants on phenotypes have not yielded positive findings. However, an important step was taken by adapting the gene-environment interaction model. In this model genetic vulnerability stepped into the place of "stone craved" pathology. Further progress happened when studies of environmental factors were combined with genetic function (epigenetics). This model provided the possibility for investigation of therapeutic interventions as environmental factors and it was proven that effective treatments exert a modifying effect on gene expression. Moreover, recent developments focus on therapeutic manipulation of gene function (e.g. chemogenetics). Instead of "stone craved" genes up-to-date dynamically interacting gene function became the basis of psychogenomics in which correction of the expression is a potential therapeutic tool. Keeping in mind these trends and developments, there is no doubt that genetics will be a fundamental part of daily clinical routine in the future.
Xiao, Shan; Zeng, Xiaoyun; Fan, Yong; Su, Yinxia; Ma, Qi; Zhu, Jun; Yao, Hua
2016-01-01
Background We investigated the association between 8 single-nucleotide polymorphisms (SNPs) at 3 genetic loci (CDKAL1, CDKN2A/2B and FTO) with type 2 diabetes (T2D) in a Uyghur population. Material/Methods A case-control study of 879 Uyghur patients with T2D and 895 non-diabetic Uyghur controls was conducted at the Hospital of Xinjiang Medical University between 2010 and 2013. Eight SNPs in CDKAL1, CDKN2A/2B and FTO were analyzed using Sequenom MassARRAY®SNP genotyping. Factors associated with T2D were assessed by logistic regression analyses. Gene-gene and gene-environment interactions were analyzed by generalized multifactor dimensionality reduction. Results Genotype distributions of rs10811661 (CDKN2A/2B), rs7195539, rs8050136, and rs9939609 (FTO) and allele frequencies of rs8050136 and rs9939609 differed significantly between diabetes and control groups (all P<0.05). While rs10811661, rs8050136, and rs9939609 were eliminated after adjusting for covariates (P>0.05), rs7195539 distribution differed significantly in co-dominant and dominant models (P<0.05). In gene-gene interaction analysis, after adjusting for covariates the two-locus rs10811661-rs7195539 interaction model had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.5483 (P=0.014). In gene-environment interaction analysis, the 3-locus interaction model TG-HDL-family history of diabetes had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.7072 (P<0.001). The 4-locus interaction model, rs7195539-TG-HDL-family history of diabetes had a cross-validation consistency of 8/10 (P<0.001). Conclusions Polymorphisms in CDKN2A/2B and FTO, but not CDKAL1, may be associated with T2D, and alleles rs8050136 and rs9939609 are likely risk alleles for T2D in this population. There were potential interactions among CDKN2A/2B (rs10811661) – FTO (rs7195539) or FTO (rs7195539)-TG-HDL-family history of diabetes in the pathogenesis of T2D in a Uyghur population. PMID:26873362
Seow, Wei Jie; Pan, Wen-Chi; Kile, Molly L; Tong, Lin; Baccarelli, Andrea A; Quamruzzaman, Quazi; Rahman, Mahmuder; Mostofa, Golam; Rakibuz-Zaman, Muhammad; Kibriya, Muhammad; Ahsan, Habibul; Lin, Xihong; Christiani, David C
2015-07-01
Single-nucleotide polymorphisms (SNPs) in inflammation, one-carbon metabolism, and skin cancer genes might influence susceptibility to arsenic-induced skin lesions. A case-control study was conducted in Pabna, Bangladesh (2001-2003), and the drinking-water arsenic concentration was measured for each participant. A panel of 25 candidate SNPs was analyzed in 540 cases and 400 controls. Logistic regression was used to estimate the association between each SNP and the potential for gene-environment interactions in the skin lesion risk, with adjustments for relevant covariates. Replication testing was conducted in an independent Bangladesh population with 488 cases and 2,794 controls. In the discovery population, genetic variants in the one-carbon metabolism genes phosphatidylethanolamine N-methyltransferase (rs2278952, P for interaction = .004; rs897453, P for interaction = .05) and dihydrofolate reductase (rs1650697, P for interaction = .02), the inflammation gene interleukin 10 (rs3024496, P for interaction =.04), and the skin cancer genes inositol polyphosphate-5-phosphatase (INPP5A; rs1133400, P for interaction = .03) and xeroderma pigmentosum complementation group C (rs2228000, P for interaction = .01) significantly modified the association between arsenic and skin lesions after adjustments for multiple comparisons. The significant gene-environment interaction between a SNP in the INPP5A gene (rs1133400) and water arsenic with respect to the skin lesion risk was successfully replicated in an independent population (P for interaction = .03). Minor allele carriers of the skin cancer gene INPP5A modified the odds of arsenic-induced skin lesions in both main and replicative populations. Genetic variation in INPP5A appears to have a role in susceptibility to arsenic toxicity. © 2015 American Cancer Society.
Keller, Matthew C
2014-01-01
Candidate gene × environment (G × E) interaction research tests the hypothesis that the effects of some environmental variable (e.g., childhood maltreatment) on some outcome measure (e.g., depression) depend on a particular genetic polymorphism. Because this research is inherently nonexperimental, investigators have been rightly concerned that detected interactions could be driven by confounders (e.g., ethnicity, gender, age, socioeconomic status) rather than by the specified genetic or environmental variables per se. In an attempt to eliminate such alternative explanations for detected G × E interactions, investigators routinely enter the potential confounders as covariates in general linear models. However, this practice does not control for the effects these variables might have on the G × E interaction. Rather, to properly control for confounders, researchers need to enter the covariate × environment and the covariate × gene interaction terms in the same model that tests the G × E term. In this manuscript, I demonstrate this point analytically and show that the practice of improperly controlling for covariates is the norm in the G × E interaction literature to date. Thus, many alternative explanations for G × E findings that investigators had thought were eliminated have not been. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.
Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P
2014-12-01
Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.
Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects
Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.
2015-01-01
IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142
Grabe, H J; Lange, M; Wolff, B; Völzke, H; Lucht, M; Freyberger, H J; John, U; Cascorbi, I
2005-02-01
Previous studies have yielded conflicting results as to the putative role of the functional polymorphism of the promoter region of the serotonin transporter gene (SLC6A4) in the etiology of anxiety-related traits and depressive disorders. Recently, a significant gene-environment interaction was found between life stressors, the short allele of the SLC6A4 polymorphism and depression. The aim of the present study was to investigate if such a gene-environment interaction could be replicated within a different population with a different risk structure. A total of 1005 subjects from a general population sample (Study of Health in Pomerania) were genotyped. Mental and physical distress were assessed on 38 items of the modified complaint scale (BL-38). The interaction between the SLC6A4 genotype, social stressors and chronic diseases with regard to the BL-38 score was evaluated by ANOVA. There was no independent association of genotype with mental and physical distress. However, significant interactions between genotype, unemployment and chronic diseases (F = 6.6; df = 3, 671; P < 0.001) were found in females but not in males. The genotype explained 2% of the total variance of the BL-38 score and 9.1% of the explained variance. The results partly confirm previous findings of a significant gene-environment interaction of the short allele, indicating a higher mental vulnerability to social stressors and chronic diseases. The relevance of this finding is sustained by the fact that the sample characteristics and the risk structure were highly different from previous studies.
Horwitz, Allan V
2005-10-01
This article examines how genetic and environmental interactions associated with health inequalities are constructed and framed in the presentation of scientific research. It uses the example of a major article about depression in a longitudinal study of young adults that appeared in Science in 2003. This portrayal of findings related to health inequalities uses a genetic lens that privileges genetic influences and diminishes environmental ones. The emphasis on the genetic side of Gene x Environment interactions can serve to deflect attention away from the important impact of social inequalities on health.
Nutrigenomics and nutrigenetics in inflammatory bowel diseases.
Gruber, Lisa; Lichti, Pia; Rath, Eva; Haller, Dirk
2012-10-01
Inflammatory bowel diseases (IBD) including ulcerative colitis and Crohn's disease are chronically relapsing, immune-mediated disorders of the gastrointestinal tract. A major challenge in the treatment of IBD is the heterogenous nature of these pathologies. Both, ulcerative colitis and Crohn's disease are of multifactorial etiology and feature a complex interaction of host genetic susceptibility and environmental factors such as diet and gut microbiota. Genome-wide association studies identified disease-relevant single-nucleotide polymorphisms in approximately 100 genes, but at the same time twin studies also clearly indicated a strong environmental impact in disease development. However, attempts to link dietary factors to the risk of developing IBD, based on epidemiological observations showed controversial outcomes. Yet, emerging high-throughput technologies implying complete biological systems might allow taking nutrient-gene interactions into account for a better classification of patient subsets in the future. In this context, 2 new scientific fields, "nutrigenetics" and "nutrigenomics" have been established. "Nutrigenetics," studying the effect of genetic variations on nutrient-gene interactions and "Nutrigenomics," describing the impact of nutrition on physiology and health status on the level of gene transcription, protein expression, and metabolism. It is hoped that the integration of both research areas will promote the understanding of the complex gene-environment interaction in IBD etiology and in the long-term will lead to personalized nutrition for disease prevention and treatment. This review briefly summarizes data on the impact of nutrients on intestinal inflammation, highlights nutrient-gene interactions, and addresses the potential of applying "omic" technologies in the context of IBD.
Genetic mouse models relevant to schizophrenia: taking stock and looking forward.
Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M
2012-03-01
Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.
Lowe, Sarah R; Meyers, Jacquelyn L; Galea, Sandro; Aiello, Allison E; Uddin, Monica; Wildman, Derek E; Koenen, Karestan C
2015-01-01
Background Longitudinal studies of posttraumatic stress (PTS) have documented environmental factors as predictors of trajectories of higher, versus lower, symptoms, among them experiences of childhood physical abuse. Although it is now well-accepted that genes and environments jointly shape the risk of PTS, no published studies have investigated genes, or gene-by-environment interactions (GxEs), as predictors of PTS trajectories. The purpose of this study was to fill this gap. Methods and Materials We examined associations between variants of the retinoid-related orphan receptor alpha (RORA) gene and trajectory membership among a sample of predominantly non-Hispanic Black urban adults (N = 473). The RORA gene was selected based on its association with posttraumatic stress disorder (PTSD) in the first PTSD genome wide association study. Additionally, we explored GxEs between RORA variants and childhood physical abuse history. Results We found that the minor allele of the RORA SNP rs893290 was a significant predictor of membership in a trajectory of consistently high PTS, relatively to a trajectory of consistently low PTS. Additionally, the GxE of rs893290 with childhood physical abuse was significant. Decomposition of the interaction showed that minor allele frequency was more strongly associated with membership in consistently high or decreasing PTS trajectories, relative to a consistently low PTS trajectory, among participants with higher levels of childhood physical abuse. Conclusion The results of the study provide preliminary evidence that variation in the RORA gene is associated with membership in trajectories of higher PTS and that these associations are stronger among persons exposed to childhood physical abuse. Replication and analysis of functional data are needed to further our understanding of how RORA relates to PTS trajectories. PMID:25798337
De Leonibus, C; Chatelain, P; Knight, C; Clayton, P; Stevens, A
2016-11-01
The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene-environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene-environment interactions in children treated with r-hGH.
Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.
Hur, Junguk; Özgür, Arzucan; He, Yongqun
2017-03-14
Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of these gene interaction networks identified top ranked E. coli genes and 6 INO interaction types (e.g., regulation and gene expression). Vaccine-related E. coli gene-gene interaction network was constructed using ontology-based literature mining strategy, which identified important E. coli vaccine genes and their interactions with other genes through specific interaction types.
Wang, Qingzhong; Shelton, Richard C; Dwivedi, Yogesh
2018-01-01
Gene-environment interaction contributes to the risks of psychiatric disorders. Interactions between FKBP5 gene variants and early-life stress may enhance the risk not only for mood disorder, but also for a number of other behavioral phenotypes. The aim of the present study was to review and conduct a meta-analysis on the results from published studies examining interaction between FKBP5 gene variants and early-life stress and their associations with stress-related disorders such as major depression and PTSD. A literature search was conducted using PsychINFO and PubMed databases until May 2017. A total of 14 studies with a pooled total of 15109 participants met the inclusion criteria, the results of which were combined and a meta-analysis was performed using the differences in correlations as the effect measure. Based on literature, rs1360780, rs3800373, and rs9470080 SNPs were selected within the FKBP5 gene and systematic review was conducted. Based on the Comprehensive Meta-Analysis software, no publication bias was detected. Sensitivity analysis and credibility of meta-analysis results also indicated that the analyses were stable. The meta-analysis showed that individuals who carry T allele of rs1360780, C-allele of rs3800373 or T-allele of rs9470080 exposed to early-life trauma had higher risks for depression or PTSD. The effects of ethnicity, age, sex, and different stress measures were not examined due to limited sample size. These results provide strong evidence of interactions between FKBP5 genotypes and early-life stress, which could pose a significant risk factor for stress-associated disorders such as major depression and PTSD. Copyright © 2017 Elsevier B.V. All rights reserved.
GeneXplorer: an interactive web application for microarray data visualization and analysis.
Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin
2004-10-01
When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.
Burt, Alexandra
2009-04-01
Previous work has suggested that the serotonergic system plays a key role in "popularity" or likeability. A polymorphism within the 5HT-sub(2A) serotonin receptor gene (-G1438A) has also been associated with popularity, suggesting that genes may predispose individuals to particular social experiences. However, because genes cannot code directly for others' reactions, any legitimate association should be mediated via the individual's behavior (i.e., genes-->behaviors-->social consequences), a phenomenon referred to as an evocative gene-environment correlation (rGE). The current study aimed to identify one such mediating behavior. The author focused on rule breaking given its prior links to both the serotonergic system and to increased popularity during adolescence. Two samples of previously unacquainted late-adolescent boys completed a peer-based interaction paradigm designed to assess their popularity. Analyses revealed that rule breaking partially mediated the genetic effect on popularity, thereby furthering our understanding of the biological mechanisms that underlie popularity. Moreover, the present results represent the first meaningfully explicated evidence that genes predispose individuals not only to particular behaviors but also to the social consequences of those behaviors. (c) 2009 APA, all rights reserved.
Fletcher, Jason M; Conley, Dalton
2013-10-01
The integration of genetics and the social sciences will lead to a more complex understanding of the articulation between social and biological processes, although the empirical difficulties inherent in this integration are large. One key challenge is the implications of moving "outside the lab" and away from the experimental tools available for research with model organisms. Social science research methods used to examine human behavior in nonexperimental, real-world settings to date have not been fully taken advantage of during this disciplinary integration, especially in the form of gene-environment interaction research. This article outlines and provides examples of several prominent research designs that should be used in gene-environment research and highlights a key benefit to geneticists of working with social scientists.
Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis. PMID:25635858
Wang, Yang; Chen, Zhi-Hao; Yin, Chun; Ma, Jian-Hua; Li, Di-Jie; Zhao, Fan; Sun, Yu-Long; Hu, Li-Fang; Shang, Peng; Qian, Ai-Rong
2015-01-01
The diamagnetic levitation as a novel ground-based model for simulating a reduced gravity environment has recently been applied in life science research. In this study a specially designed superconducting magnet with a large gradient high magnetic field (LG-HMF), which can provide three apparent gravity levels (μ-g, 1-g, and 2-g), was used to simulate a space-like gravity environment. Osteocyte, as the most important mechanosensor in bone, takes a pivotal position in mediating the mechano-induced bone remodeling. In this study, the effects of LG-HMF on gene expression profiling of osteocyte-like cell line MLO-Y4 were investigated by Affymetrix DNA microarray. LG-HMF affected osteocyte gene expression profiling. Differentially expressed genes (DEGs) and data mining were further analyzed by using bioinfomatic tools, such as DAVID, iReport. 12 energy metabolism related genes (PFKL, AK4, ALDOC, COX7A1, STC1, ADM, CA9, CA12, P4HA1, APLN, GPR35 and GPR84) were further confirmed by real-time PCR. An integrated gene interaction network of 12 DEGs was constructed. Bio-data mining showed that genes involved in glucose metabolic process and apoptosis changed notablly. Our results demostrated that LG-HMF affected the expression of energy metabolism related genes in osteocyte. The identification of sensitive genes to special environments may provide some potential targets for preventing and treating bone loss or osteoporosis.
Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui
2014-01-01
Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.
Chen, Yu-Chih; Zhang, Zhixiong; Fouladdel, Shamileh; Deol, Yadwinder; Ingram, Patrick N; McDermott, Sean P; Azizi, Ebrahim; Wicha, Max S; Yoon, Euisik
2016-08-07
Considerable evidence suggests that cancer stem-like cells (CSCs) are critical in tumor pathogenesis, but their rarity and transience has led to much controversy about their exact nature. Although CSCs can be functionally identified using dish-based tumorsphere assays, it is difficult to handle and monitor single cells in dish-based approaches; single cell-based microfluidic approaches offer better control and reliable single cell derived sphere formation. However, like normal stem cells, CSCs are heavily regulated by their microenvironment, requiring tumor-stromal interactions for tumorigenic and proliferative behaviors. To enable single cell derived tumorsphere formation within a stromal microenvironment, we present a dual adherent/suspension co-culture device, which combines a suspension environment for single-cell tumorsphere assays and an adherent environment for co-culturing stromal cells in close proximity by selectively patterning polyHEMA in indented microwells. By minimizing dead volume and improving cell capture efficiency, the presented platform allows for the use of small numbers of cells (<100 cells). As a proof of concept, we co-cultured single T47D (breast cancer) cells and primary cancer associated fibroblasts (CAF) on-chip for 14 days to monitor sphere formation and growth. Compared to mono-culture, co-cultured T47D have higher tumorigenic potential (sphere formation rate) and proliferation rates (larger sphere size). Furthermore, 96-multiplexed single-cell transcriptome analyses were performed to compare the gene expression of co-cultured and mono-cultured T47D cells. Phenotypic changes observed in co-culture correlated with expression changes in genes associated with proliferation, apoptotic suppression, tumorigenicity and even epithelial-to-mesechymal transition. Combining the presented platform with single cell transcriptome analysis, we successfully identified functional CSCs and investigated the phenotypic and transcriptome effects induced by tumor-stromal interactions.
Fox, E; Beevers, C G
2016-01-01
Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic ‘reactivity' or ‘sensitivity' may represent heightened sensitivity to the learning environment in a ‘for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in ‘both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies. PMID:27431291
ORCHIDS: an observational randomized controlled trial on childhood differential susceptibility.
Chhangur, Rabia R; Weeland, Joyce; Overbeek, Geertjan; Matthys, Walterchj; Orobio de Castro, Bram
2012-10-29
A central tenet in developmental psychopathology is that childhood rearing experiences have a major impact on children's development. Recently, candidate genes have been identified that may cause children to be differentially susceptible to these experiences (i.e., susceptibility genes). However, our understanding of the differential impact of parenting is limited at best. Specifically, more experimental research is needed. The ORCHIDS study will investigate gene-(gene-)environment interactions to obtain more insight into a) moderating effects of polymorphisms on the link between parenting and child behavior, and b) behavioral mechanisms that underlie these gene-(gene-)environment interactions in an experimental design. The ORCHIDS study is a randomized controlled trial, in which the environment will be manipulated with an intervention (i.e., Incredible Years parent training). In a screening, families with children aged 4-8 who show mild to (sub)clinical behavior problems will be targeted through community records via two Dutch regional healthcare organizations. Assessments in both the intervention and control condition will be conducted at baseline (i.e., pretest), after 6 months (i.e., posttest), and after 10 months (i.e., follow-up). This study protocol describes the design of a randomized controlled trial that investigates gene-(gene-)environment interactions in the development of child behavior. Two hypotheses will be tested. First, we expect that children in the intervention condition who carry one or more susceptibility genes will show significantly lower levels of problem behavior and higher levels of prosocial behavior after their parent(s) received the Incredible Years training, compared to children without these genes, or children in the control group. Second, we expect that children carrying one or more susceptibility genes will show a heightened sensitivity to changes in parenting behaviors, and will manifest higher emotional synchronization in dyadic interchanges with their parents. This may lead to either more prosocial behavior or antisocial behavior depending on their parents' behavior. Dutch Trial Register (NTR3594).
Zhang, Leilei; Li, Zhi; Chen, Jie; Li, Xinying; Zhang, Jianxin; Belsky, Jay
2016-03-01
Although depressive symptoms are common during adolescence, little research has examined gene-environment interaction on youth depression. This study chose the brain-derived neurotrophic factor (BDNF) gene, tested the interaction between a functional polymorphism resulting amino acid substitution of valine (Val) to methionine (Met) in the proBDNF protein at codon 66 (Val66Met), and maternal parenting on youth depressive symptoms in a sample of 780 community adolescents of Chinese Han ethnicity (aged 11-17, M = 13.6, 51.3 % females). Participants reported their depressive symptoms and perceived maternal parenting. Results indicated the BDNF Val66Met polymorphism significantly moderated the influence of maternal warmth-reasoning, but not harshness-hostility, on youth depressive symptoms. Confirmatory model evaluation indicated that the interaction effect involving warmth-reasoning conformed to the differential-susceptibility rather than diathesis-stress model of person-X-environment interaction. Thus, Val carriers experienced less depressive symptoms than Met homozygotes when mothering was more positive but more symptoms when mothering was less positive. The findings provided evidence in support of the differential susceptibility hypothesis of youth depressive symptoms and shed light on the importance of examining the gene-environment interaction from a developmental perspective.
Genetic Contributions of Inflammation to Depression
Barnes, Jacob; Mondelli, Valeria; Pariante, Carmine M
2017-01-01
This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case–control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further ‘omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression. PMID:27555379
Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.
2007-01-01
QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937
Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H
2007-08-01
QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.
Breast and Prostate Cancer and Hormone-Related Gene Variant Study
The Breast and Prostate Cancer and Hormone-Related Gene Variant Study allows large-scale analyses of breast and prostate cancer risk in relation to genetic polymorphisms and gene-environment interactions that affect hormone metabolism.
Combining research approaches to advance our understanding of drug addiction.
van den Bree, Marianne B M
2005-04-01
Drug addiction is a complex behavior, likely to be influenced by various genes, environmental factors, and gene-gene and gene-environment interactions. Various aspects of addiction are studied by different disciplines. Animal studies are increasing insight into brain regions and genes associated with addiction. Epidemiologic studies are establishing the factors increasing risk for initiation and continuation of substance use. Twin and adoption studies are increasing our understanding of the complex mechanisms involved in substance use, including comorbidity and gene environment interaction. Finally, molecular genetic studies in humans are starting to yield some converging findings. It is argued and illustrated with examples that greater awareness of progress in other disciplines can speed up our understanding of the complex processes involved in addiction. This should help our ability to identify who is at increased risk of becoming addicted and the development of prevention and intervention strategies targeted at an individual's specific needs.
Explaining human uniqueness: genome interactions with environment, behaviour and culture.
Varki, Ajit; Geschwind, Daniel H; Eichler, Evan E
2008-10-01
What makes us human? Specialists in each discipline respond through the lens of their own expertise. In fact, 'anthropogeny' (explaining the origin of humans) requires a transdisciplinary approach that eschews such barriers. Here we take a genomic and genetic perspective towards molecular variation, explore systems analysis of gene expression and discuss an organ-systems approach. Rejecting any 'genes versus environment' dichotomy, we then consider genome interactions with environment, behaviour and culture, finally speculating that aspects of human uniqueness arose because of a primate evolutionary trend towards increasing and irreversible dependence on learned behaviours and culture - perhaps relaxing allowable thresholds for large-scale genomic diversity.
[Progress in transgenic fish techniques and application].
Ye, Xing; Tian, Yuan-Yuan; Gao, Feng-Ying
2011-05-01
Transgenic technique provides a new way for fish breeding. Stable lines of growth hormone gene transfer carps, salmon and tilapia, as well as fluorescence protein gene transfer zebra fish and white cloud mountain minnow have been produced. The fast growth characteristic of GH gene transgenic fish will be of great importance to promote aquaculture production and economic efficiency. This paper summarized the progress in transgenic fish research and ecological assessments. Microinjection is still the most common used method, but often resulted in multi-site and multi-copies integration. Co-injection of transposon or meganuclease will greatly improve the efficiency of gene transfer and integration. "All fish" gene or "auto gene" should be considered to produce transgenic fish in order to eliminate misgiving on food safety and to benefit expression of the transferred gene. Environmental risk is the biggest obstacle for transgenic fish to be commercially applied. Data indicates that transgenic fish have inferior fitness compared with the traditional domestic fish. However, be-cause of the genotype-by-environment effects, it is difficult to extrapolate simple phenotypes to the complex ecological interactions that occur in nature based on the ecological consequences of the transgenic fish determined in the laboratory. It is critical to establish highly naturalized environments for acquiring reliable data that can be used to evaluate the environ-mental risk. Efficacious physical and biological containment strategies remain to be crucial approaches to ensure the safe application of transgenic fish technology.
Livingston, Robert W.; Hong, Ying-Yi; Chiao, Joan Y.
2014-01-01
Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene–environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. PMID:23887814
Gemini surfactants mediate efficient mitochondrial gene delivery and expression.
Cardoso, Ana M; Morais, Catarina M; Cruz, A Rita; Cardoso, Ana L; Silva, Sandra G; do Vale, M Luísa; Marques, Eduardo F; Pedroso de Lima, Maria C; Jurado, Amália S
2015-03-02
Gene delivery targeting mitochondria has the potential to transform the therapeutic landscape of mitochondrial genetic diseases. Taking advantage of the nonuniversal genetic code used by mitochondria, a plasmid DNA construct able to be specifically expressed in these organelles was designed by including a codon, which codes for an amino acid only if read by the mitochondrial ribosomes. In the present work, gemini surfactants were shown to successfully deliver plasmid DNA to mitochondria. Gemini surfactant-based DNA complexes were taken up by cells through a variety of routes, including endocytic pathways, and showed propensity for inducing membrane destabilization under acidic conditions, thus facilitating cytoplasmic release of DNA. Furthermore, the complexes interacted extensively with lipid membrane models mimicking the composition of the mitochondrial membrane, which predicts a favored interaction of the complexes with mitochondria in the intracellular environment. This work unravels new possibilities for gene therapy toward mitochondrial diseases.
Sleep Duration and Body Mass Index in Twins: A Gene-Environment Interaction
Watson, Nathaniel F.; Harden, Kathryn Paige; Buchwald, Dedra; Vitiello, Michael V.; Pack, Allan I.; Weigle, David S.; Goldberg, Jack
2012-01-01
Study Objectives: To examine whether sleep duration modifies genetic and environmental influences on body mass index (BMI). Design: Genotype-environment interaction twin study. Setting: University of Washington Twin Registry. Patients or Participants: A population-based sample of US twins (1,088 pairs, 604 monozygotic, 484 dizygotic; 66% female; mean age = 36.6 yr, standard deviation (SD) = 15.9 yr). Interventions: N/A. Measurements and Results: Participants self-reported information on height, weight, and sleep. Mean BMI was calculated as 25.3 kg/m2 (SD = 5.4) and mean habitual sleep duration was 7.2 hr/night (SD = 1.2). Data were analyzed using biometric genetic interaction models. Overall the heritability of sleep duration was 34%. Longer sleep duration was associated with decreased BMI (P < 0.05). The heritability of BMI when sleep duration was < 7 hr (h2 = 70%) was more than twice as large as the heritability of BMI when sleep duration was ≥ 9 hr (h2 = 32%); this interaction was significant (P < 0.05). Conclusions: Shorter sleep duration is associated with increased BMI and increased genetic influences on BMI, suggesting that shorter sleep duration increases expression of genetic risks for high body weight. At the same time, longer sleep duration may suppress genetic influences on body weight. Future research aiming to identify specific genotypes for BMI may benefit by considering the moderating role of sleep duration. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Weigle DS; Goldberg J. Sleep duration and body mass index in twins: a gene-environment interaction. SLEEP 2012;35(5):597-603. PMID:22547885
ERIC Educational Resources Information Center
DiLalla, Lisabeth Fisher; Bersted, Kyle; John, Sufna Gheyara
2015-01-01
The development of prosocial behaviors during the preschool years is essential for children's positive interactions with peers in school and other social situations. Although there is some evidence of genetic influences on prosocial behaviors, very little is known about how genes and environment, independently and in concert, affect prosocial…
ERIC Educational Resources Information Center
Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.
2010-01-01
Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…
Linking Gene, Brain, and Behavior
Schmidt, Louis A.; Fox, Nathan A.; Perez-Edgar, Koraly; Hamer, Dean H.
2009-01-01
Gene-environment interactions involving exogenous environmental factors are known to shape behavior and personality development. Although gene-environment interactions involving endogenous environmental factors are hypothesized to play an equally important role, this conceptual approach has not been empirically applied in the study of early-developing temperament in humans. Here we report evidence for a gene-endoenvironment (i.e., resting frontal brain electroencephalogram, EEG, asymmetry) interaction in predicting child temperament. The DRD4 gene (long allele vs. short allele) moderated the relation between resting frontal EEG asymmetry (left vs. right) at 9 months and temperament at 48 months. Children who exhibited left frontal EEG asymmetry at 9 months and who possessed the DRD4 long allele were significantly more soothable at 48 months than other children. Among children with right frontal EEG asymmetry at 9 months, those with the DRD4 long allele had significantly more difficulties focusing and sustaining attention at 48 months than those with the DRD4 short allele. Resting frontal EEG asymmetry did not influence temperament in the absence of the DRD4 long allele. We discuss how the interaction of genetic and endoenvironment factors may confer risk and protection for different behavioral styles in children. PMID:19493320
Clock genes × stress × reward interactions in alcohol and substance use disorders.
Perreau-Lenz, Stéphanie; Spanagel, Rainer
2015-06-01
Adverse life events and highly stressful environments have deleterious consequences for mental health. Those environmental factors can potentiate alcohol and drug abuse in vulnerable individuals carrying specific genetic risk factors, hence producing the final risk for alcohol- and substance-use disorders development. The nature of these genes remains to be fully determined, but studies indicate their direct or indirect relation to the stress hypothalamo-pituitary-adrenal (HPA) axis and/or reward systems. Over the past decade, clock genes have been revealed to be key-players in influencing acute and chronic alcohol/drug effects. In parallel, the influence of chronic stress and stressful life events in promoting alcohol and substance use and abuse has been demonstrated. Furthermore, the reciprocal interaction of clock genes with various HPA-axis components, as well as the evidence for an implication of clock genes in stress-induced alcohol abuse, have led to the idea that clock genes, and Period genes in particular, may represent key genetic factors to consider when examining gene × environment interaction in the etiology of addiction. The aim of the present review is to summarize findings linking clock genes, stress, and alcohol and substance abuse, and to propose potential underlying neurobiological mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.
Zhang, Wenxin; Cao, Cong; Wang, Meiping; Ji, Linqin; Cao, Yanmiao
2016-04-01
To date, whether and how gene-environment (G × E) interactions operate differently across distinct subtypes of aggression remains untested. More recently, in contrast with the diathesis-stress hypothesis, an alternative hypothesis of differential susceptibility proposes that individuals could be differentially susceptible to environments depending on their genotypes in a "for better and for worse" manner. The current study examined interactions between monoamine oxidase A (MAOA) T941G and catechol-O-methyltransferase (COMT) Val158Met polymorphisms with maternal parenting on two types of aggression: reactive and proactive. Moreover, whether these potential G × E interactions would be consistent with the diathesis-stress versus the differential susceptibility hypothesis was tested. Within the sample of 1399 Chinese Han adolescents (47.2 % girls, M age = 12.32 years, SD = 0.50), MAOA and COMT genes both interacted with positive parenting in their associations with reactive but not proactive aggression. Adolescents with T alleles/TT homozygotes of MAOA gene or Met alleles of COMT gene exhibited more reactive aggression when exposed to low positive parenting, but less reactive aggression when exposed to high positive parenting. These findings provide the first evidence for distinct G × E interaction effects on reactive versus proactive aggression and lend further support for the differential susceptibility hypothesis.
Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun
2015-01-01
Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these interaction types and their associated gene-gene pairs uncovered many scientific insights. INO provides a novel approach for defining hierarchical interaction types and related keywords for literature mining. The ontology-based literature mining, in combination with an INO-based statistical interaction enrichment test, provides a new platform for efficient mining and analysis of topic-specific gene interaction networks.
Genetic and environmental influences on the development of alcoholism: resilience vs. risk.
Enoch, Mary-Anne
2006-12-01
The physiological changes of adolescence may promote risk-taking behaviors, including binge drinking. Approximately 40% of alcoholics were already drinking heavily in late adolescence. Most cases of alcoholism are established by the age of 30 years with the peak prevalence at 18-23 years of age. Therefore the key time frame for the development, and prevention, of alcoholism lies in adolescence and young adulthood. Severe childhood stressors have been associated with increased vulnerability to addiction, however, not all stress-exposed children go on to develop alcoholism. Origins of resilience can be both genetic (variation in alcohol-metabolizing genes, increased susceptibility to alcohol's sedative effects) and environmental (lack of alcohol availability, positive peer and parental support). Genetic vulnerability is likely to be conferred by multiple genes of small to modest effects, possibly only apparent in gene-environment interactions. For example, it has been shown that childhood maltreatment interacts with a monoamine oxidase A (MAOA) gene variant to predict antisocial behavior that is often associated with alcoholism, and an interaction between early life stress and a serotonin transporter promoter variant predicts alcohol abuse in nonhuman primates and depression in humans. In addition, a common Met158 variant in the catechol-O-methyltransferase (COMT) gene can confer both risk and resilience to alcoholism in different drinking environments. It is likely that a complex mix of gene(s)-environment(s) interactions underlie addiction vulnerability and development. Risk-resilience factors can best be determined in longitudinal studies, preferably starting during pregnancy. This kind of research is important for planning future measures to prevent harmful drinking in adolescence.
ERIC Educational Resources Information Center
Tucker-Drob, Elliot M.; Harden, K. Paige
2012-01-01
There is accumulating evidence that genetic influences on achievement are more pronounced among children living in higher socioeconomic status homes, and that these gene-by-environment interactions occur prior to children's entry into formal schooling. We hypothesized that one pathway through which socioeconomic status promotes genetic influences…
ERIC Educational Resources Information Center
Tucker-Drob, Elliot M.; Harden, K. Paige
2012-01-01
Recent studies have demonstrated that genetic influences on cognitive ability and academic achievement are larger for children raised in higher socioeconomic status (SES) homes. However, little work has been done to document the psychosocial processes that underlie this Gene x Environment interaction. One process may involve the conversion of…
Gene environment interaction studies in depression and suicidal behavior: An update.
Mandelli, Laura; Serretti, Alessandro
2013-12-01
Increasing evidence supports the involvement of both heritable and environmental risk factors in major depression (MD) and suicidal behavior (SB). Studies investigating gene-environment interaction (G × E) may be useful for elucidating the role of biological mechanisms in the risk for mental disorders. In the present paper, we review the literature regarding the interaction between genes modulating brain functions and stressful life events in the etiology of MD and SB and discuss their potential added benefit compared to genetic studies only. Within the context of G × E investigation, thus far, only a few reliable results have been obtained, although some genes have consistently shown interactive effects with environmental risk in MD and, to a lesser extent, in SB. Further investigation is required to disentangle the direct and mediated effects that are common or specific to MD and SB. Since traditional G × E studies overall suffer from important methodological limitations, further effort is required to develop novel methodological strategies with an interdisciplinary approach. Copyright © 2013 Elsevier Ltd. All rights reserved.
Genetic determinants of prepubertal and pubertal growth and development.
Thomis, Martine A; Towne, Bradford
2006-12-01
This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.
Wade, Mark; Hoffmann, Thomas J.; Jenkins, Jennifer M.
2015-01-01
Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behaviour—two widely studied factors in ToM development—interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers’ cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children’s ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene–environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. PMID:25977357
Sadee, Wolfgang
2013-09-01
Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.
Rosenberg, Jenni; Pennington, Bruce F; Willcutt, Erik G; Olson, Richard K
2012-03-01
Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G × E) interactions. This study used behavioral genetic methods to replicate these opposite G × E interactions in a sample of same-sex monozygotic and dizygotic twin pairs from the Colorado Learning Disabilities Research Center (CLDRC; DeFries et al., 1997) and to test a genetic hypothesis for why these opposite interactions occur. We replicated opposite G × E interactions for RD (bioecological) and ADHD-I (diathesis-stress) with parental education in the same sample of participants. The genetic hypothesis for this opposite pattern of interactions is that only genes specific to each disorder enter into these opposite interactions, not the shared genes underlying their comorbidity. To test this hypothesis, we used single models with an exploratory three-way interaction, in which the G × E interactions for each disorder were moderated by comorbidity. Neither three-way interaction was significant. The heritability of RD did not vary as a function of parental education and ADHD-I. Similarly, the heritability of ADHD-I did not vary as a function of parental education and RD. We documented opposite G × E interactions in RD and ADHD-I in the same overall twin sample, but the explanation for this apparent paradox remains unclear. Examining specific genes and more specific environmental factors may help resolve the paradox. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.
The heritable basis of gene-environment interactions in cardiometabolic traits.
Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W
2017-03-01
Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.
Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.
Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M
2013-11-01
Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.
Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong
2012-01-01
Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845
Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.
Stogner, John M; Gibson, Chris L
2016-07-01
Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.
Epistasis and Its Implications for Personal Genetics
Moore, Jason H.; Williams, Scott M.
2009-01-01
The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity. PMID:19733727
Epistasis and its implications for personal genetics.
Moore, Jason H; Williams, Scott M
2009-09-01
The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.
Hayden, Elizabeth P.; Hanna, Brigitte; Sheikh, Haroon I.; Laptook, Rebecca S.; Kim, Jiyon; Singh, Shiva M.; Klein, Daniel N.
2017-01-01
The dopamine transporter (DAT1) gene is implicated in psychopathology risk. While the processes by which this gene exerts its effects on risk are poorly understood, a small body of research suggests that DAT1 influences early emerging negative emotionality (NE), a marker of children’s psychopathology risk. As child NE evokes negative parenting practices, the DAT1 may also play a role in gene-environment correlations. To test this model, children (N = 365) were genotyped for DAT1 and participated in standardized parent-child interaction tasks with their primary caregiver. The DAT1 9-repeat variant was associated with child negative affect expressed toward the parent during parent-child interactions, and parents of children with a 9-repeat allele exhibited more hostility and lower guidance/engagement than parents of children without a 9-repeat allele. These gene-environment associations were partially mediated by child negative affect toward the parent. Findings implicate a specific polymorphism in eliciting negative parenting, suggesting that evocative associations play a role in elevating children’s risk for emotional trajectories toward psychopathology risk. PMID:23398760
Galvan, Antonella; Ioannidis, John P.A.; Dragani, Tommaso A.
2010-01-01
Genome-wide association studies (GWAS) using population-based designs have identified many genetic loci associated with risk of a range of complex diseases including cancer; however, each locus exerts a very small effect and most heritability remains unexplained. Family-based pedigree studies have also suggested tentative loci linked to increased cancer risk, often characterized by pedigree-specificity. However, a comparison between the results of population-and those of family-based studies shows little concordance. Explanations for this unidentified genetic ‘dark matter’ of cancer include phenotype ascertainment issues, limited power, gene-gene and gene-environment interactions, population heterogeneity, parent-of-origin-specific effects, rare and unexplored variants. Many of these reasons converge towards the concept of genetic heterogeneity that might implicate hundreds of genetic variants in regulating cancer risk. Dissecting the dark matter is a challenging task. Further insights can be gained from both population association and pedigree studies. PMID:20106545
Social environment influences the relationship between genotype and gene expression in wild baboons
Runcie, Daniel E.; Wiedmann, Ralph T.; Archie, Elizabeth A.; Altmann, Jeanne; Wray, Gregory A.; Alberts, Susan C.; Tung, Jenny
2013-01-01
Variation in the social environment can have profound effects on survival and reproduction in wild social mammals. However, we know little about the degree to which these effects are influenced by genetic differences among individuals, and conversely, the degree to which social environmental variation mediates genetic reaction norms. To better understand these relationships, we investigated the potential for dominance rank, social connectedness and group size to modify the effects of genetic variation on gene expression in the wild baboons of the Amboseli basin. We found evidence for a number of gene–environment interactions (GEIs) associated with variation in the social environment, encompassing social environments experienced in adulthood as well as persistent effects of early life social environment. Social connectedness, maternal dominance rank and group size all interacted with genotype to influence gene expression in at least one sex, and either in early life or in adulthood. These results suggest that social and behavioural variation, akin to other factors such as age and sex, can impact the genotype–phenotype relationship. We conclude that GEIs mediated by the social environment are important in the evolution and maintenance of individual differences in wild social mammals, including individual differences in responses to social stressors. PMID:23569293
Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.
Doust, Andrew N; Lukens, Lewis; Olsen, Kenneth M; Mauro-Herrera, Margarita; Meyer, Ann; Rogers, Kimberly
2014-04-29
Domestication is a multifaceted evolutionary process, involving changes in individual genes, genetic interactions, and emergent phenotypes. There has been extensive discussion of the phenotypic characteristics of plant domestication, and recent research has started to identify the specific genes and mutational mechanisms that control domestication traits. However, there is an apparent disconnect between the simple genetic architecture described for many crop domestication traits, which should facilitate rapid phenotypic change under selection, and the slow rate of change reported from the archeobotanical record. A possible explanation involves the middle ground between individual genetic changes and their expression during development, where gene-by-gene (epistatic) and gene-by-environment interactions can modify the expression of phenotypes and opportunities for selection. These aspects of genetic architecture have the potential to significantly slow the speed of phenotypic evolution during crop domestication and improvement. Here we examine whether epistatic and gene-by-environment interactions have shaped how domestication traits have evolved. We review available evidence from the literature, and we analyze two domestication-related traits, shattering and flowering time, in a mapping population derived from a cross between domesticated foxtail millet and its wild progenitor. We find that compared with wild progenitor alleles, those favored during domestication often have large phenotypic effects and are relatively insensitive to genetic background and environmental effects. Consistent selection should thus be able to rapidly change traits during domestication. We conclude that if phenotypic evolution was slow during crop domestication, this is more likely due to cultural or historical factors than epistatic or environmental constraints.
Wei, Wen-Hua; Massey, Jonathan; Worthington, Jane; Barton, Anne; Warren, Richard B
2018-03-01
Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.
Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar
2012-06-01
Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.
Gene-environment interactions linking air pollution and inflammation in Parkinson's disease.
Lee, Pei-Chen; Raaschou-Nielsen, Ole; Lill, Christina M; Bertram, Lars; Sinsheimer, Janet S; Hansen, Johnni; Ritz, Beate
2016-11-01
Both air pollution exposure and systemic inflammation have been linked to Parkinson's disease (PD). In the PASIDA study, 408 incident cases of PD diagnosed in 2006-2009 and their 495 population controls were interviewed and provided DNA samples. Markers of long term traffic related air pollution measures were derived from geographic information systems (GIS)-based modeling. Furthermore, we genotyped functional polymorphisms in genes encoding proinflammatory cytokines, namely rs1800629 in TNFα (tumor necrosis factor alpha) and rs16944 in IL1B (interleukin-1β). In logistic regression models, long-term exposure to NO 2 increased PD risk overall (odds ratio (OR)=1.06 per 2.94μg/m 3 increase, 95% CI=1.00-1.13). The OR for PD in individuals with high NO 2 exposure (≧75th percentile) and the AA genotype of IL1B rs16944 was 3.10 (95% CI=1.14-8.38) compared with individuals with lower NO 2 exposure (<75th percentile) and the GG genotype. The interaction term was nominally significant on the multiplicative scale (p=0.01). We did not find significant gene-environment interactions with TNF rs1800629. Our finds may provide suggestive evidence that a combination of traffic-related air pollution and genetic variation in the proinflammatory cytokine gene IL1B contribute to risk of developing PD. However, as statistical evidence was only modest in this large sample we cannot rule out that these results represent a chance finding, and additional replication efforts are warranted. Copyright © 2016 Elsevier Inc. All rights reserved.
Meyer, Andrew C.; Bardo, Michael T.
2015-01-01
Rationale Previous research suggests both genetic and environmental influences on substance abuse vulnerability. Objectives The current work sought to investigate the interaction of genes and environment on the acquisition of amphetamine self-administration, as well as amphetamine-stimulated dopamine (DA) release in nucleus accumbens shell using in vivo microdialysis. Methods Inbred Lewis (LEW) and Fischer (F344) rat strains were raised in either an enriched condition (EC), social condition (SC), or isolated condition (IC). Acquisition of amphetamine self-administration (0.1 mg/kg/infusion) was determined across an incrementing daily fixed ratio (FR) schedule. In a separate cohort of rats, extracellular DA and the metabolite dihydroxyphenylacetic acid (DOPAC) were measured in the nucleus accumbens shell following an acute amphetamine injection (1 mg/kg). Results “Addiction-prone” LEW had greater acquisition of amphetamine self-administration on a FR1 schedule compared to “addiction-resistant” F344 when raised in the SC environment. These genetic differences were negated in both the EC and IC environments, with enrichment buffering against self-administration and isolation enhancing self-administration in both strains. On a FR5 schedule, the isolation-induced increase in amphetamine self-administration was greater in F344 than LEW. While no group differences were obtained in extracellular DA, gene x environment differences were obtained in extracellular levels of the metabolite DOPAC. In IC rats only, LEW showed an attenuation in the amphetamine-induced decrease in DOPAC compared to F344. IC LEW rats also had an attenuated DOPAC response to amphetamine compared to EC LEW. Conclusions The current results demonstrate gene x environment interactions in amphetamine self-administration and amphetamine-induced changes in extracellular DOPAC in NAc shell. However, the behavioral and neurochemical differences were not related directly, indicating that mechanisms independent of DA metabolism in NAc shell likely mediate the gene x environment effects in amphetamine self-administration. PMID:25566972
ERIC Educational Resources Information Center
Beaver, Kevin M.; DeLisi, Matt; Wright, John Paul; Vaughn, Michael G.
2009-01-01
Behavioral genetic research has revealed that biogenic factors play a role in the development of antisocial behaviors. Much of this research has also explicated the way in which the environment and genes may combine to create different phenotypes. The authors draw heavily from this literature and use data from the National Longitudinal Study of…
Van Hulle, Carol A; Rathouz, Paul J
2015-02-01
Accurately identifying interactions between genetic vulnerabilities and environmental factors is of critical importance for genetic research on health and behavior. In the previous work of Van Hulle et al. (Behavior Genetics, Vol. 43, 2013, pp. 71-84), we explored the operating characteristics for a set of biometric (e.g., twin) models of Rathouz et al. (Behavior Genetics, Vol. 38, 2008, pp. 301-315), for testing gene-by-measured environment interaction (GxM) in the presence of gene-by-measured environment correlation (rGM) where data followed the assumed distributional structure. Here we explore the effects that violating distributional assumptions have on the operating characteristics of these same models even when structural model assumptions are correct. We simulated N = 2,000 replicates of n = 1,000 twin pairs under a number of conditions. Non-normality was imposed on either the putative moderator or on the ultimate outcome by ordinalizing or censoring the data. We examined the empirical Type I error rates and compared Bayesian information criterion (BIC) values. In general, non-normality in the putative moderator had little impact on the Type I error rates or BIC comparisons. In contrast, non-normality in the outcome was often mistaken for or masked GxM, especially when the outcome data were censored.
Gene function prediction with gene interaction networks: a context graph kernel approach.
Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu
2010-01-01
Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.
Lian, Yulong; Xiao, Jing; Wang, Qian; Ning, Li; Guan, Suzhen; Ge, Hua; Li, Fuye; Liu, Jiwen
2014-08-12
It is debatable whether or not glucocorticoid receptor (GR) polymorphisms moderate susceptibility to PTSD. Our objective was to examine the effects of stressful life events, social support, GR genotypes, and gene-environment interactions on the etiology of PTSD. Three tag single nucleotide polymorphisms, trauma events, stressful life events, and social support were assessed in 460 patients with PTSD and 1158 control subjects from a Chinese Han population. Gene-environment interactions were analyzed by generalized multifactor dimensionality reduction (GMDR). Variation in GR at rs41423247 and rs258747, stressful life events, social support, and the number of traumatic events were each separately associated with the risk for PTSD. A gene-environment interaction among the polymorphisms, rs41423247 and rs258747, the number of traumatic events, stressful life events, and social support resulted in an increased risk for PTSD. High-risk individuals (a large number of traumatic events, G allele of rs258747 and rs41423247, high level stressful life events, and low social support) had a 3.26-fold increased risk of developing PTSD compared to low-risk individuals. The association was statistically significant in the sub-groups with and without childhood trauma. Our data support the notion that stressful life events, the number of trauma events, and social support may play a contributing role in the risk for PTSD by interacting with GR gene polymorphisms.
Gene-Diet Interaction and Precision Nutrition in Obesity
Heianza, Yoriko; Qi, Lu
2017-01-01
The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition. PMID:28387720
Zheng, Bangyou; Biddulph, Ben; Li, Dora; Kuchel, Haydn; Chapman, Scott
2013-01-01
Heading time is a major determinant of the adaptation of wheat to different environments, and is critical in minimizing risks of frost, heat, and drought on reproductive development. Given that major developmental genes are known in wheat, a process-based model, APSIM, was modified to incorporate gene effects into estimation of heading time, while minimizing degradation in the predictive capability of the model. Model parameters describing environment responses were replaced with functions of the number of winter and photoperiod (PPD)-sensitive alleles at the three VRN1 loci and the Ppd-D1 locus, respectively. Two years of vernalization and PPD trials of 210 lines (spring wheats) at a single location were used to estimate the effects of the VRN1 and Ppd-D1 alleles, with validation against 190 trials (~4400 observations) across the Australian wheatbelt. Compared with spring genotypes, winter genotypes for Vrn-A1 (i.e. with two winter alleles) had a delay of 76.8 degree days (°Cd) in time to heading, which was double the effect of the Vrn-B1 or Vrn-D1 winter genotypes. Of the three VRN1 loci, winter alleles at Vrn-B1 had the strongest interaction with PPD, delaying heading time by 99.0 °Cd under long days. The gene-based model had root mean square error of 3.2 and 4.3 d for calibration and validation datasets, respectively. Virtual genotypes were created to examine heading time in comparison with frost and heat events and showed that new longer-season varieties could be heading later (with potential increased yield) when sown early in season. This gene-based model allows breeders to consider how to target gene combinations to current and future production environments using parameters determined from a small set of phenotyping treatments. PMID:23873997
Zheng, Bangyou; Biddulph, Ben; Li, Dora; Kuchel, Haydn; Chapman, Scott
2013-09-01
Heading time is a major determinant of the adaptation of wheat to different environments, and is critical in minimizing risks of frost, heat, and drought on reproductive development. Given that major developmental genes are known in wheat, a process-based model, APSIM, was modified to incorporate gene effects into estimation of heading time, while minimizing degradation in the predictive capability of the model. Model parameters describing environment responses were replaced with functions of the number of winter and photoperiod (PPD)-sensitive alleles at the three VRN1 loci and the Ppd-D1 locus, respectively. Two years of vernalization and PPD trials of 210 lines (spring wheats) at a single location were used to estimate the effects of the VRN1 and Ppd-D1 alleles, with validation against 190 trials (~4400 observations) across the Australian wheatbelt. Compared with spring genotypes, winter genotypes for Vrn-A1 (i.e. with two winter alleles) had a delay of 76.8 degree days (°Cd) in time to heading, which was double the effect of the Vrn-B1 or Vrn-D1 winter genotypes. Of the three VRN1 loci, winter alleles at Vrn-B1 had the strongest interaction with PPD, delaying heading time by 99.0 °Cd under long days. The gene-based model had root mean square error of 3.2 and 4.3 d for calibration and validation datasets, respectively. Virtual genotypes were created to examine heading time in comparison with frost and heat events and showed that new longer-season varieties could be heading later (with potential increased yield) when sown early in season. This gene-based model allows breeders to consider how to target gene combinations to current and future production environments using parameters determined from a small set of phenotyping treatments.
ERIC Educational Resources Information Center
Iarocci, Grace; Yager, Jodi; Elfers, Theo
2007-01-01
Social competence is a complex human behaviour that is likely to involve a system of genes that interacts with a myriad of environmental risk and protective factors. The search for its genetic and environmental origins and influences is equally complex and will require a multidimensional conceptualization and multiple methods and levels of…
Wu, Cen; Jiang, Yu; Ren, Jie; Cui, Yuehua; Ma, Shuangge
2018-02-10
Identification of gene-environment (G × E) interactions associated with disease phenotypes has posed a great challenge in high-throughput cancer studies. The existing marginal identification methods have suffered from not being able to accommodate the joint effects of a large number of genetic variants, while some of the joint-effect methods have been limited by failing to respect the "main effects, interactions" hierarchy, by ignoring data contamination, and by using inefficient selection techniques under complex structural sparsity. In this article, we develop an effective penalization approach to identify important G × E interactions and main effects, which can account for the hierarchical structures of the 2 types of effects. Possible data contamination is accommodated by adopting the least absolute deviation loss function. The advantage of the proposed approach over the alternatives is convincingly demonstrated in both simulation and a case study on lung cancer prognosis with gene expression measurements and clinical covariates under the accelerated failure time model. Copyright © 2017 John Wiley & Sons, Ltd.
The Breast and Prostate Cancer and Hormone-Related Gene Variant Study allows large-scale analyses of breast and prostate cancer risk in relation to genetic polymorphisms and gene-environment interactions that affect hormone metabolism.
Gallardo-Pujol, D; Andrés-Pueyo, A; Maydeu-Olivares, A
2013-02-01
In 2002, Caspi and colleagues provided the first epidemiological evidence that genotype may moderate individuals' responses to environmental determinants. However, in a correlational study great care must be taken to ensure the proper estimation of the causal relationship. Here, a randomized experiment was performed to test the hypothesis that the MAOA gene promoter polymorphism (MAOA-LPR) interacts with environmental adversity in determining aggressive behavior using laboratory analogs of real-life conditions. A sample of 57 Caucasian male students of Catalan and Spanish origin was recruited at the University of Barcelona. Ostracism, or social exclusion, was induced as environmental adversity using the Cyberball software. Laboratory aggression was assessed with the Point Subtraction Aggression Paradigm (PSAP), which was used as an analog of antisocial behavior. We also measured aggressiveness by means of the reduced version of the Aggression Questionnaire. The MAOA-LPR polymorphism showed a significant effect on the number of aggressive responses in the PSAP (F(1,53) = 4.63, P = 0.03, partial η(2) = 0.08), as well as social exclusion (F(1,53) = 8.03, P = 0.01, partial η(2) = 0.13). Most notably, however, we found that the MAOA-LPR polymorphism interacts significantly with social exclusion in order to provoke aggressive behavior (F(1,53) = 4.42, P = 0.04, partial η(2) = 0.08), remarkably, the low-activity allele of the MAOA-LPR polymorphism carriers in the ostracized group show significantly higher aggression scores than the rest. Our results support the notion that gene-environment interactions can be successfully reproduced within a laboratory using analogs and an appropriate design. We provide guidelines to test gene-environment interactions hypotheses under controlled, experimental settings. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.
Byrd, Amy L.; Manuck, Stephen B.
2013-01-01
Background In a seminal study of gene-environment interaction, childhood maltreatment predicted antisocial behavior more strongly in males carrying an MAOA promoter variant of lesser, compared to higher, transcriptional efficiency. Many further investigations have been reported, including studies of other early environmental exposures and females. Here we report a meta-analysis of studies testing the interaction of MAOA genotype and childhood adversities on antisocial outcomes in predominantly non-clinical samples. Method Included were 27 peer-reviewed, English-language studies published through August, 2012, that contained indicators of maltreatment or “other” family (e.g., parenting, sociodemographic) hardships; MAOA genotype; indices of aggressive and antisocial behavior; and statistical test of genotype-environment interaction. Studies of forensic and exclusively clinical samples, clinical cohorts lacking proportionally matched controls, or outcomes non-specific for antisocial behavior were excluded. The Liptak-Stouffer weighted Z-test for meta-analysis was implemented to maximize study inclusion and calculated separately for male and female cohorts. Results Across 20 male cohorts, early adversity presaged antisocial outcomes more strongly for low, relative to high, activity MAOA genotype (P=.0044). Stratified analyses showed the interaction specific to maltreatment (P=.0000008) and robust to several sensitivity analyses. Across 11 female cohorts, MAOA did not interact with combined early life adversities, whereas maltreatment alone predicted antisocial behaviors preferentially, but weakly, in females of high activity MAOA genotype (P=.02). Conclusions We found common regulatory variation in MAOA to moderate effects of childhood maltreatment on male antisocial behaviors, confirming a sentinel finding in research on gene-environment interaction. An analogous, but less consistent, finding in females warrants further investigation. PMID:23786983
Byrd, Amy L; Manuck, Stephen B
2014-01-01
In a seminal study of gene-environment interaction, childhood maltreatment predicted antisocial behavior more strongly in male subjects carrying an MAOA promoter variant of lesser, compared with higher, transcriptional efficiency. Many further investigations have been reported, including studies of other early environmental exposures and female subjects. Here, we report a meta-analysis of studies testing the interaction of MAOA genotype and childhood adversities on antisocial outcomes in predominantly nonclinical samples. Included were 27 peer-reviewed, English-language studies published through August, 2012, that contained indicators of maltreatment or other family (e.g., parenting, sociodemographic) hardships; MAOA genotype; indices of aggressive and antisocial behavior; and statistical test of genotype-environment interaction. Studies of forensic and exclusively clinical samples, clinical cohorts lacking proportionally matched control subjects, or outcomes nonspecific for antisocial behavior were excluded. The Liptak-Stouffer weighted Z-test for meta-analysis was implemented to maximize study inclusion and calculated separately for male and female cohorts. Across 20 male cohorts, early adversity presaged antisocial outcomes more strongly for low-activity, relative to high- activity, MAOA genotype (p = .0044). Stratified analyses showed the interaction specific to maltreatment (p = .00000082) and robust to several sensitivity analyses. Across 11 female cohorts, MAOA did not interact with combined early life adversities, whereas maltreatment alone predicted antisocial behaviors preferentially, but weakly, in female subjects of high-activity MAOA genotype (p = .02). We found common regulatory variation in MAOA to moderate effects of childhood maltreatment on male antisocial behaviors, confirming a sentinel finding in research on gene-environment interaction. An analogous, but less consistent, finding in female subjects warrants further investigation. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
The genetics of music accomplishment: evidence for gene-environment correlation and interaction.
Hambrick, David Z; Tucker-Drob, Elliot M
2015-02-01
Theories of skilled performance that emphasize training history, such as K. Anders Ericsson and colleagues' deliberate-practice theory, have received a great deal of recent attention in both the scientific literature and the popular press. Twin studies, however, have demonstrated evidence for moderate-to-strong genetic influences on skilled performance. Focusing on musical accomplishment in a sample of over 800 pairs of twins, we found evidence for gene-environment correlation, in the form of a genetic effect on music practice. However, only about one quarter of the genetic effect on music accomplishment was explained by this genetic effect on music practice, suggesting that genetically influenced factors other than practice contribute to individual differences in music accomplishment. We also found evidence for gene-environment interaction, such that genetic effects on music accomplishment were most pronounced among those engaging in music practice, suggesting that genetic potentials for skilled performance are most fully expressed and fostered by practice.
How Genes and the Social Environment Moderate Each Other
Leve, Leslie D.; Neiderhiser, Jenae M.
2013-01-01
Recent research has suggested that the social environment can moderate the expression of genetic influences on health and that genetic influences can shape an individual’s sensitivity to the social environment. Evidence supports 4 major mechanisms: genes can influence an individual’s response to environmental stress, genes may enhance an individual’s sensitivity to both favorable and adverse environments, inherited characteristics may better fit with some environments than with others, and inherited capabilities may only become manifest in challenging or responsive environments. Further progress depends on better recognition of patterns of gene–environment interaction, improved methods of assessing the environment and its impact on genetic mechanisms, the use of appropriately designed laboratory studies, identification of heritable differences in an individual before environmental moderation occurs, and clarification of the timing of the impact of social and genetic moderation. PMID:23927504
Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M
2014-04-10
Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.
Pathotype profile of Xanthomonas oryzae pv. oryzae isolates from North Sumatera
NASA Astrophysics Data System (ADS)
Noer, Z.; Hasanuddin; Lisnawita; Suryanto, D.
2018-02-01
The Bacterial blight disease caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most important diseases and has caused crop failure in rice crops. This pathogen infects the leaves in all plant growth phases. The purpose of this study is to investigation 10 Xoo isolates pathotype obtained from North Sumatra based on their interactions with 10 near-isogenic rice lines (NIL) of IRRI. The results showed that there are 6 pathotypes of virulence in North Sumatra, they are; pathotype I with incompatible interaction to all Xa genes, pathotype II with compatible interaction to Xa1 and Xa3 genes, while it has incompatible interaction to other genes, pathotype III with compatible interaction to Xa1, Xa5, Xa7, Xa8, Xa10 and Xa11 genes, but it has incompatible interaction to other genes, pathotype IV with compatible interaction to all Xa genes, pathotype V with compatible interaction to Xa1 gene and incompatible interaction to other genes, and pathotype VI with compatible interaction to Xa3 gene and incompatible interaction to other genes. Based on the resistant genes in each individual Xa2, Xa4, and Xa21 genes are the combination of Xa genes which are most suitable for use in the development of rice cultivars in North Sumatra.
Prevention of asthma: where are we in the 21st century?
Propp, Phaedra; Becker, Allan
2013-12-01
Asthma is the most common chronic disease of childhood and, in the latter part of the 20th century, reached epidemic proportions. Asthma is generally believed to result from gene-environment interactions. There is consensus that a 'window of opportunity' exists during pregnancy and early in life when environmental factors may influence its development. We review multiple environmental, biologic and sociologic factors that may be important in the development of asthma. Meta-analyses of studies have demonstrated that multifaceted interventions are required in order to develop asthma prevention. Multifaceted allergen reduction studies have shown clinical benefits. Asthma represents a dysfunctional interaction with our genes and the environment to which they are exposed, especially in fetal and early infant life. The increasing prevalence of asthma also may be an indication of increased population risk for the development of other chronic non-communicable autoimmune diseases. This review will focus on the factors which may be important in the primary prevention of asthma. Better understanding of the complex gene-environment interactions involved in the development of asthma will provide insight into personalized interventions for asthma prevention.
2011-01-01
Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118
Yang, Chunxia; Sun, Ning; Liu, Zhifen; Li, Xinrong; Xu, Yong; Zhang, Kerang
2016-03-30
Major depressive disorder (MDD) is a mental disorder that results from complex interplay between multiple and partially overlapping sets of susceptibility genes and environmental factors. The brain derived neurotrophic factor (BDNF) and Protein kinase C gamma type (PRKCG) are logical candidate genes in MDD. Among diverse environmental factors, negative life events have been suggested to exert a crucial impact on brain development. In the present study, we hypothesized that interactions between genetic variants in BDNF and PRKCG and negative life events may play an important role in the development of MDD. We recruited a total of 406 patients with MDD and 391 age- and gender-matched control subjects. Gene-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Under a dominant model, we observed a significant three-way interaction among BDNF rs6265, PRKCG rs3745406, and negative life events. The gene-environment combination of PRKCG rs3745406 C allele, BDNF rs6265 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 5.97; 95% CI, 2.71-13.15). To our knowledge, this is the first report of evidence that the BDNF-PRKCG interaction may modify the relationship between negative life events and MDD in the Chinese population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Genetics of borderline personality disorder: systematic review and proposal of an integrative model.
Amad, Ali; Ramoz, Nicolas; Thomas, Pierre; Jardri, Renaud; Gorwood, Philip
2014-03-01
Borderline personality disorder (BPD) is one of the most common mental disorders and is characterized by a pervasive pattern of emotional lability, impulsivity, interpersonal difficulties, identity disturbances, and disturbed cognition. Here, we performed a systematic review of the literature concerning the genetics of BPD, including familial and twin studies, association studies, and gene-environment interaction studies. Moreover, meta-analyses were performed when at least two case-control studies testing the same polymorphism were available. For each gene variant, a pooled odds ratio (OR) was calculated using fixed or random effects models. Familial and twin studies largely support the potential role of a genetic vulnerability at the root of BPD, with an estimated heritability of approximately 40%. Moreover, there is evidence for both gene-environment interactions and correlations. However, association studies for BPD are sparse, making it difficult to draw clear conclusions. According to our meta-analysis, no significant associations were found for the serotonin transporter gene, the tryptophan hydroxylase 1 gene, or the serotonin 1B receptor gene. We hypothesize that such a discrepancy (negative association studies but high heritability of the disorder) could be understandable through a paradigm shift, in which "plasticity" genes (rather than "vulnerability" genes) would be involved. Such a framework postulates a balance between positive and negative events, which interact with plasticity genes in the genesis of BPD. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gene-Diet Interactions in Childhood Obesity
Garver, William S
2011-01-01
Childhood overweight and obesity have reached epidemic proportions worldwide, and the increase in weight-associated co-morbidities including premature type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease will soon become major healthcare and economic problems. A number of studies now indicate that the childhood obesity epidemic which has emerged during the past 30 years is a complex multi-factorial disease resulting from interaction of susceptibility genes with an obesogenic environment. This review will focus on gene-diet interactions suspected of having a prominent role in promoting childhood obesity. In particular, the specific genes that will be presented (FTO, MC4R, and NPC1) have recently been associated with childhood obesity through a genome-wide association study (GWAS) and were shown to interact with nutritional components to increase weight gain. Although a fourth gene (APOA2) has not yet been associated with childhood obesity, this review will also present information on what now represents the best characterized gene-diet interaction in promoting weight gain. PMID:22043166
Advances in asthma and allergy genetics in 2007.
Vercelli, Donata
2008-08-01
This review discusses the main advances in the genetics of asthma and allergy published in the Journal in 2007. The association studies discussed herein addressed 3 main topics: the effect of the environment and gene-environment interactions on asthma/allergy susceptibility, the contribution of T(H)2 immunity gene variants to allergic inflammation, and the role of filaggrin mutations in atopic dermatitis and associated phenotypes. Other articles revealed novel, potentially important candidate genes or confirmed known ones. Collectively, the works published in 2007 reiterate that allergy and asthma are typical complex diseases; that is, they are disorders in which intricate interactions among environmental and genetic factors modify disease susceptibility by altering the fundamental structural and functional properties of target organs at critical developmental windows.
NASA Astrophysics Data System (ADS)
Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.
2010-06-01
Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.
Interactions between genetic variation and cellular environment in skeletal muscle gene expression.
Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S
2018-01-01
From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.
Finding gene-environment interactions for phobias.
Gregory, Alice M; Lau, Jennifer Y F; Eley, Thalia C
2008-03-01
Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G x E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G x Es for phobias. In addition to the careful conceptualisation of new studies, it is suggested that data already collected should be re-analysed in light of increased understanding of processes influencing phobias.
Richards, Jennifer S; Arias Vásquez, Alejandro; van Rooij, Daan; van der Meer, Dennis; Franke, Barbara; Hoekstra, Pieter J; Heslenfeld, Dirk J; Oosterlaan, Jaap; Faraone, Stephen V; Hartman, Catharina A; Buitelaar, Jan K
2017-06-01
Impaired inhibitory control is a key feature of attention-deficit/hyperactivity disorder (ADHD). We investigated gene-environment interaction (GxE) as a possible contributing factor to response inhibition variation in context of the differential susceptibility theory. This states individuals carrying plasticity gene variants will be more disadvantaged in negative, but more advantaged in positive environments. Behavioural and neural measures of response inhibition were assessed during a Stop-signal task in participants with (N = 197) and without (N = 295) ADHD, from N = 278 families (age M = 17.18, SD =3.65). We examined GxE between candidate plasticity genes (DAT1, 5-HTT, DRD4) and social environments (maternal expressed emotion, peer affiliation). A DRD4 × Positive peer affiliation interaction was found on the right fusiform gyrus (rFG) activation during successful inhibition. Further, 5-HTT short allele carriers showed increased rFG activation during failed inhibitions. Maternal warmth and positive peer affiliation were positively associated with right inferior frontal cortex activation during successful inhibition. Deviant peer affiliation was positively related to the error rate. While a pattern of differential genetic susceptibility was found, more clarity on the role of the FG during response inhibition is warranted before firm conclusions can be made. Positive and negative social environments were related to inhibitory control. This extends previous research emphasizing adverse environments.
A mathematical model of in vivo bovine blastocyst developmental to gestational Day 15.
Shorten, P R; Donnison, M; McDonald, R M; Meier, S; Ledgard, A M; Berg, D
2018-06-20
Bovine embryo growth involves a complex interaction between the developing embryo and the growth-promoting potential of the uterine environment. We have previously established links between embryonic factors (embryo stage, embryo gene expression), maternal factors (progesterone, body condition score), and embryonic growth to 8 d after bulk transfer of Day 7 in vitro-produced blastocysts. In this study we recovered blastocysts on Days 7 and 15 after artificial insemination to test the hypothesis that in vivo and in vitro embryos follow a similar growth program. We conducted our study using 4 commercial farms and repeated our study over 2 yr (2014, 2015), with data available from 2 of the 4 farms in the second year. Morphological and gene expression measurements (196 candidate genes) of the Day 7 embryos were measured and the progesterone concentration of the cows were measured throughout the reproductive cycle as a reflection of the state of the uterine environment. These data were also used to assess the interaction between the uterine environment and the developing embryo and to examine how well Day 7 embryo stage can be predicted from the Day 7 gene expression profile. Progesterone was not a strong predictor of in vivo embryo growth to Day 15. This contrasts with a range of Day 7 embryo transfer studies which demonstrated that progesterone is a very good predictor of embryo growth to Day 15. Our analysis demonstrates that in vivo embryos are 3 times less sensitive to progesterone than in vitro-transferred embryos (up to Day 15). This highlights that caution must be applied when extrapolating the results of in vitro embryo transfer studies to the in vivo situation. The similar variance in measured and predicted (based on Day 15 length) Day 7 embryo stage indicate low stochastic perturbations for in vivo embryo growth (large stochastic growth effects would generate a significantly larger standard deviation in measured embryo length on Day 15). We also identified that Day 7 embryo stage could be predicted based on the Day 7 gene expression profile (58% overall success rate for classification of 5 embryo stages). Our analysis also associated genes with each developmental stage and demonstrates the high level of temporal regulation of genes that occurs during early embryonic development. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Lück, Anja; Klimmasch, Lukas; Großmann, Peter; Germerodt, Sebastian; Kaleta, Christoph
2018-01-10
Organisms need to adapt to changing environments and they do so by using a broad spectrum of strategies. These strategies include finding the right balance between expressing genes before or when they are needed, and adjusting the degree of noise inherent in gene expression. We investigated the interplay between different nutritional environments and the inhabiting organisms' metabolic and genetic adaptations by applying an evolutionary algorithm to an agent-based model of a concise bacterial metabolism. Our results show that constant environments and rapidly fluctuating environments produce similar adaptations in the organisms, making the predictability of the environment a major factor in determining optimal adaptation. We show that exploitation of expression noise occurs only in some types of fluctuating environment and is strongly dependent on the quality and availability of nutrients: stochasticity is generally detrimental in fluctuating environments and beneficial only at equal periods of nutrient availability and above a threshold environmental richness. Moreover, depending on the availability and nutritional value of nutrients, nutrient-dependent and stochastic expression are both strategies used to deal with environmental changes. Overall, we comprehensively characterize the interplay between the quality and periodicity of an environment and the resulting optimal deterministic and stochastic regulation strategies of nutrient-catabolizing pathways.
Bultman, Scott J.
2013-01-01
Gene-environment interactions are so numerous and biologically complicated that it can be challenging to understand their role in cancer. However, dietary fiber and colorectal cancer prevention may represent a tractable model system. Fiber is fermented by colonic bacteria into short-chain fatty acids such as butyrate. One molecular pathway that has emerged involves butyrate having differential effects depending on its concentration and the metabolic state of the cell. Low-moderate concentrations, which are present near the base of colonic crypts, are readily metabolized in the mitochondria to stimulate cell proliferation via energetics. Higher concentrations, which are present near the lumen, exceed the metabolic capacity of the colonocyte. Unmetabolized butyrate enters the nucleus and functions as a histone deacetylase (HDAC) inhibitor that epigenetically regulates gene expression to inhibit cell proliferation and induce apoptosis as the colonocytes exfoliate into the lumen. Butyrate may therefore play a role in normal homeostasis by promoting turnover of the colonic epithelium. Because cancerous colonocytes undergo the Warburg effect, their preferred energy source is glucose instead of butyrate. Consequently, even moderate concentrations of butyrate accumulate in cancerous colonocytes and function as HDAC inhibitors to inhibit cell proliferation and induce apoptosis. These findings implicate a bacterial metabolite with metaboloepigenetic properties in tumor suppression. PMID:24270685
Gene-environment interactions in the aetiology of systemic lupus erythematosus.
Jönsen, Andreas; Bengtsson, Anders A; Nived, Ola; Truedsson, Lennart; Sturfelt, Gunnar
2007-12-01
Systemic lupus erythematosus (SLE) is a disease that displays a multitude of symptoms and a vast array of autoantibodies. The disease course may vary substantially between patients. The current understanding of SLE aetiology includes environmental factors acting on a genetically prone individual during an undetermined time period resulting in autoimmunity and finally surpassing that individual's disease threshold. Genetic differences and environmental factors may interact specifically in the pathogenetic processes and may influence disease development and modify the disease course. Identification of these factors and their interactions in the pathogenesis of SLE is vital in understanding the disease and may contribute to identify new treatment targets and perhaps also aid in disease prevention. However, there are several problems that need to be overcome, such as the protracted time frame of environmental influence, time dependent epigenetic alterations and the possibility that different pathogenetic pathways may result in a similar disease phenotype. This is mirrored by the relatively few studies that suggest specific gene-environment interactions. These include an association between SLE diagnosis and glutation S-transferase gene variants combined with occupational sun exposure as well as variants of the N-acetyl transferase gene in combination with either aromatic amine exposure or hydralazine. With increased knowledge on SLE pathogenesis, the role of environmental factors and their genetic interactions may be further elucidated.
Acosta-Pech, Rocío; Crossa, José; de Los Campos, Gustavo; Teyssèdre, Simon; Claustres, Bruno; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino
2017-07-01
A new genomic model that incorporates genotype × environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype × environment interaction (G × E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G × E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G × E in the prediction of untested maize hybrids increases the accuracy of genomic models.
Zhai, Rihong; Chen, Feng; Liu, Geoffrey; Su, Li; Kulke, Matthew H; Asomaning, Kofi; Lin, Xihong; Heist, Rebecca S; Nishioka, Norman S; Sheu, Chau-Chyun; Wain, John C; Christiani, David C
2010-05-10
Apoptosis pathway, gastroesophageal reflux symptoms (reflux), higher body mass index (BMI), and tobacco smoking have been individually associated with esophageal adenocarcinoma (EA) development. However, how multiple factors jointly affect EA risk remains unclear. In total, 305 patients with EA and 339 age- and sex-matched controls were studied. High-order interactions among reflux, BMI, smoking, and functional polymorphisms in five apoptotic genes (FAS, FASL, IL1B, TP53BP, and BAT3) were investigated by entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional logistic regression (LR) models. In LR analysis, reflux, BMI, and smoking were significantly associated with EA risk, with reflux as the strongest individual factor. No individual single nucleotide polymorphism was associated with EA susceptibility. However, there was a two-way interaction between IL1B + 3954C>T and reflux (P = .008). In both CART and MDR analyses, reflux was also the strongest individual factor for EA risk. In individuals with reflux symptoms, CART analysis indicated that strongest interaction was among variant genotypes of IL1B + 3954C>T and BAT3S625P, higher BMI, and smoking (odds ratio [OR], 5.76; 95% CI, 2.48 to 13.38), a finding independently found using MDR analysis. In contrast, for participants without reflux symptoms, the strongest interaction was found between higher BMI and smoking (OR, 3.27; 95% CI, 1.88 to 5.68), also echoed by entropy-based MDR analysis. Although a history of reflux is an important risk for EA, multifactor interactions also play important roles in EA risk. Gene-environment interaction patterns differ between patients with and without reflux symptoms.
Gene-environment interactions of circadian-related genes for cardiometabolic traits
USDA-ARS?s Scientific Manuscript database
Objective: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153,...
Gene-Environment Studies and Borderline Personality Disorder: A Review
Carpenter, Ryan W.; Tomko, Rachel L.; Boomsma, Dorret I.
2014-01-01
We review recent gene-environment studies relevant to borderline personality disorder, including those focusing on impulsivity, emotion sensitivity, suicidal behavior, aggression and anger, and the borderline personality phenotype itself. Almost all the studies reviewed suffered from a number of methodological and statistical problems, limiting the conclusions that currently can be drawn. The best evidence to date supports a gene-environment correlation (rGE) model for borderline personality traits and a range of adverse life events, indicating that those at risk for BPD are also at increased risk for exposure to environments that may trigger BPD. We provide suggestions regarding future research on GxE interaction and rGE effects in borderline personality. PMID:23250817
Dalton, Elizabeth D; Hammen, Constance L; Najman, Jake M; Brennan, Patricia A
2014-12-01
Functional genetic polymorphisms associated with Brain-Derived Neurotrophic Factor (BDNF) and serotonin (5-HTTLPR) have demonstrated associations with depression in interaction with environmental stressors. In light of evidence for biological connections between BDNF and serotonin, it is prudent to consider genetic epistasis between variants in these genes in the development of depressive symptoms. The current study examined the effects of val66met, 5-HTTLPR, and family environment quality on youth depressive symptoms in adolescence and young adulthood in a longitudinal sample oversampled for maternal depression history. A differential susceptibility model was tested, comparing the effects of family environment on depression scores across different levels of a cumulative plasticity genotype, defined as presence of both, either, or neither plasticity alleles (defined here as val66met Met and 5-HTTLPR 'S'). Cumulative plasticity genotype interacted with family environment quality to predict depression among males and females at age 15. After age 15, however, the interaction of cumulative plasticity genotype and early family environment quality was only predictive of depression among females. Results supported a differential susceptibility model at age 15, such that plasticity allele presence was associated with more or less depressive symptoms depending on valence of the family environment, and a diathesis-stress model of gene-environment interaction after age 15. These findings, although preliminary because of the small sample size, support prior results indicating interactive effects of 5-HTTLPR, val66met, and environmental stress, and suggest that family environment may have a stronger influence on genetically susceptible women than men.
Sáez, María E; Grilo, Antonio; Morón, Francisco J; Manzano, Luis; Martínez-Larrad, María T; González-Pérez, Antonio; Serrano-Hernando, Javier; Ruiz, Agustín; Ramírez-Lorca, Reposo; Serrano-Ríos, Manuel
2008-01-01
Context Obesity is a multifactorial disorder, that is, a disease determined by the combined effect of genes and environment. In this context, polygenic approaches are needed. Objective To investigate the possibility of the existence of a crosstalk between the CALPAIN 10 homologue CALPAIN 5 and nuclear receptors of the peroxisome proliferator-activated receptors family. Design Cross-sectional, genetic association study and gene-gene interaction analysis. Subjects The study sample comprise 1953 individuals, 725 obese (defined as body mass index ≥ 30) and 1228 non obese subjects. Results In the monogenic analysis, only the peroxisome proliferator-activated receptor delta (PPARD) gene was associated with obesity (OR = 1.43 [1.04–1.97], p = 0.027). In addition, we have found a significant interaction between CAPN5 and PPARD genes (p = 0.038) that reduces the risk for obesity in a 55%. Conclusion Our results suggest that CAPN5 and PPARD gene products may also interact in vivo. PMID:18657264
2012-01-01
Background Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses. Results Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since multiple TLRs were found in the generic fever network, it is reasonable to hypothesize that vaccine-TLR interactions may play an important role in inducing fever response, which deserves a further investigation. Conclusions This study demonstrated that ontology-based literature mining is a powerful method for analyzing gene interaction networks and generating new scientific hypotheses. PMID:23256563
Thanki, Anil S; Soranzo, Nicola; Haerty, Wilfried; Davey, Robert P
2018-03-01
Gene duplication is a major factor contributing to evolutionary novelty, and the contraction or expansion of gene families has often been associated with morphological, physiological, and environmental adaptations. The study of homologous genes helps us to understand the evolution of gene families. It plays a vital role in finding ancestral gene duplication events as well as identifying genes that have diverged from a common ancestor under positive selection. There are various tools available, such as MSOAR, OrthoMCL, and HomoloGene, to identify gene families and visualize syntenic information between species, providing an overview of syntenic regions evolution at the family level. Unfortunately, none of them provide information about structural changes within genes, such as the conservation of ancestral exon boundaries among multiple genomes. The Ensembl GeneTrees computational pipeline generates gene trees based on coding sequences, provides details about exon conservation, and is used in the Ensembl Compara project to discover gene families. A certain amount of expertise is required to configure and run the Ensembl Compara GeneTrees pipeline via command line. Therefore, we converted this pipeline into a Galaxy workflow, called GeneSeqToFamily, and provided additional functionality. This workflow uses existing tools from the Galaxy ToolShed, as well as providing additional wrappers and tools that are required to run the workflow. GeneSeqToFamily represents the Ensembl GeneTrees pipeline as a set of interconnected Galaxy tools, so they can be run interactively within the Galaxy's user-friendly workflow environment while still providing the flexibility to tailor the analysis by changing configurations and tools if necessary. Additional tools allow users to subsequently visualize the gene families produced by the workflow, using the Aequatus.js interactive tool, which has been developed as part of the Aequatus software project.
Sun, Zhichao; Mukherjee, Bhramar; Estes, Jason P; Vokonas, Pantel S; Park, Sung Kyun
2017-08-15
Joint effects of genetic and environmental factors have been increasingly recognized in the development of many complex human diseases. Despite the popularity of case-control and case-only designs, longitudinal cohort studies that can capture time-varying outcome and exposure information have long been recommended for gene-environment (G × E) interactions. To date, literature on sampling designs for longitudinal studies of G × E interaction is quite limited. We therefore consider designs that can prioritize a subsample of the existing cohort for retrospective genotyping on the basis of currently available outcome, exposure, and covariate data. In this work, we propose stratified sampling based on summaries of individual exposures and outcome trajectories and develop a full conditional likelihood approach for estimation that adjusts for the biased sample. We compare the performance of our proposed design and analysis with combinations of different sampling designs and estimation approaches via simulation. We observe that the full conditional likelihood provides improved estimates for the G × E interaction and joint exposure effects over uncorrected complete-case analysis, and the exposure enriched outcome trajectory dependent design outperforms other designs in terms of estimation efficiency and power for detection of the G × E interaction. We also illustrate our design and analysis using data from the Normative Aging Study, an ongoing longitudinal cohort study initiated by the Veterans Administration in 1963. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Pei, Lijun; Zhu, Huiping; Ye, Rongwei; Wu, Jilei; Liu, Jianmeng; Ren, Aiguo; Li, Zhiwen; Zheng, Xiaoying
2015-01-01
Many studies have indicated that the reduced folate carrier gene (SLC19A1) is associated with an increased risk of neural tube defects (NTDs). However, the interaction between the SLC19A1 gene variant and maternal fever exposure and NTD risk remains unknown. The aim of this study was to investigate whether the risk for NTDs was influenced by the interactions between the SLC19A1 (rs1051266) variant and maternal first trimester fever. We investigated the potential interaction between maternal first trimester fever and maternal or offspring SLC19A1 polymorphism through a population-based case-control study. One hundred and four nuclear families with NTDs and 100 control families with nonmal newborns were included in the study. SLC19A1 polymorphism was determined using polymerase chain reaction-restricted fragment length polymorphism. Mothers who had the GG/GA genotype and first trimester fever had an elevated risk of NTDs (adjusted odds ratio, 11.73; 95% confidence interval, 3.02-45.58) as compared to absence of maternal first trimester fever and AA genotype after adjusting for maternal education, paternal education, and age, and had a significant interactive coefficient (γ = 3.17) between maternal GG/GA genotype and first trimester fever. However, there was no interaction between offspring's GG/GA genotype and maternal first trimester fever (the interactive coefficient γ = 0.97) after adjusting for confounding factors. Our findings suggested that the risk of NTDs was potentially influenced by a gene-environment interaction between maternal SLC19A1 rs1051266 GG/GA genotype and first trimester fever. Maternal GG/GA genotype may strengthen the effect of maternal fever exposure on NTD risk in this Chinese population. © 2014 Wiley Periodicals, Inc.
Chapman, Robert W; Mancia, Annalaura; Beal, Marion; Veloso, Artur; Rathburn, Charles; Blair, Anne; Holland, A F; Warr, G W; Didinato, Guy; Sokolova, Inna M; Wirth, Edward F; Duffy, Edward; Sanger, Denise
2011-04-01
Understanding the mechanisms by which organisms adapt to environmental conditions is a fundamental question for ecology and evolution. In this study, we evaluate changes in gene expression of a marine mollusc, the eastern oyster Crassostrea virginica, associated with the physico-chemical conditions and the levels of metals and other contaminants in their environment. The results indicate that transcript signatures can effectively disentangle the complex interactive gene expression responses to the environment and are also capable of disentangling the complex dynamic effects of environmental factors on gene expression. In this context, the mapping of environment to gene and gene to environment is reciprocal and mutually reinforcing. In general, the response of transcripts to the environment is driven by major factors known to affect oyster physiology such as temperature, pH, salinity, and dissolved oxygen, with pollutant levels playing a relatively small role, at least within the range of concentrations found in the studied oyster habitats. Further, the two environmental factors that dominate these effects (temperature and pH) interact in a dynamic and nonlinear fashion to impact gene expression. Transcriptomic data obtained in our study provide insights into the mechanisms of physiological responses to temperature and pH in oysters that are consistent with the known effects of these factors on physiological functions of ectotherms and indicate important linkages between transcriptomics and physiological outcomes. Should these linkages hold in further studies and in other organisms, they may provide a novel integrated approach for assessing the impacts of climate change, ocean acidification and anthropogenic contaminants on aquatic organisms via relatively inexpensive microarray platforms. © 2011 Blackwell Publishing Ltd.
O’Connor, Shannon M.; Klump, Kelly L.; VanHuysse, Jessica L.; McGue, Matt; Iacono, William
2015-01-01
Objective Previous research suggests that parental divorce moderates genetic influences on body dissatisfaction. Specifically, the heritability of body dissatisfaction is higher in children of divorced versus intact families, suggesting possible gene-environment interaction effects. However, prior research is limited to a single, self-report measure of body dissatisfaction. The primary aim of the present study was to examine whether these findings extend to a different dimension of body dissatisfaction, body image perceptions. Method Participants were 1,534 female twins from the Minnesota Twin Family Study, ages 16–20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Results Although BRS scores were heritable in twins from divorced and intact families, the heritability estimates in the divorced group were not significantly greater than estimates in the intact group. However, there were differences in nonshared environmental effects, where the magnitude of these environmental influences was larger in the divorced as compared to the intact families. Discussion Different dimensions of body dissatisfaction (i.e., negative self-evaluation versus body image perceptions) may interact with environmental risk, such as parental divorce, in discrete ways. Future research should examine this possibility and explore differential gene x environment interactions using diverse measures. PMID:26314278
O'Connor, Shannon M; Klump, Kelly L; VanHuysse, Jessica L; McGue, Matt; Iacono, William
2016-02-01
Previous research suggests that parental divorce moderates genetic influences on body dissatisfaction. Specifically, the heritability of body dissatisfaction is higher in children of divorced versus intact families, suggesting possible gene-environment interaction effects. However, prior research is limited to a single, self-reported measure of body dissatisfaction. The primary aim of this study was to examine whether these findings extend to a different dimension of body dissatisfaction: body image perceptions. Participants were 1,534 female twins from the Minnesota Twin Family Study, aged 16-20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Although BRS scores were heritable in twins from divorced and intact families, the heritability estimates in the divorced group were not significantly greater than estimates in the intact group. However, there were differences in nonshared environmental effects, where the magnitude of these environmental influences was larger in the divorced as compared with the intact families. Different dimensions of body dissatisfaction (i.e., negative self-evaluation versus body image perceptions) may interact with environmental risk, such as parental divorce, in discrete ways. Future research should examine this possibility and explore differential gene-environment interactions using diverse measures. © 2015 Wiley Periodicals, Inc.
Gene-environment interaction involving recently identified colorectal cancer susceptibility loci
Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily
2014-01-01
BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789
Singh, Ravi; Pantarotto, Davide; McCarthy, David; Chaloin, Olivier; Hoebeke, Johan; Partidos, Charalambos D; Briand, Jean-Paul; Prato, Maurizio; Bianco, Alberto; Kostarelos, Kostas
2005-03-30
Carbon nanotubes (CNTs) constitute a class of nanomaterials that possess characteristics suitable for a variety of possible applications. Their compatibility with aqueous environments has been made possible by the chemical functionalization of their surface, allowing for exploration of their interactions with biological components including mammalian cells. Functionalized CNTs (f-CNTs) are being intensively explored in advanced biotechnological applications ranging from molecular biosensors to cellular growth substrates. We have been exploring the potential of f-CNTs as delivery vehicles of biologically active molecules in view of possible biomedical applications, including vaccination and gene delivery. Recently we reported the capability of ammonium-functionalized single-walled CNTs to penetrate human and murine cells and facilitate the delivery of plasmid DNA leading to expression of marker genes. To optimize f-CNTs as gene delivery vehicles, it is essential to characterize their interactions with DNA. In the present report, we study the interactions of three types of f-CNTs, ammonium-functionalized single-walled and multiwalled carbon nanotubes (SWNT-NH3+; MWNT-NH3+), and lysine-functionalized single-walled carbon nanotubes (SWNT-Lys-NH3+), with plasmid DNA. Nanotube-DNA complexes were analyzed by scanning electron microscopy, surface plasmon resonance, PicoGreen dye exclusion, and agarose gel shift assay. The results indicate that all three types of cationic carbon nanotubes are able to condense DNA to varying degrees, indicating that both nanotube surface area and charge density are critical parameters that determine the interaction and electrostatic complex formation between f-CNTs with DNA. All three different f-CNT types in this study exhibited upregulation of marker gene expression over naked DNA using a mammalian (human) cell line. Differences in the levels of gene expression were correlated with the structural and biophysical data obtained for the f-CNT:DNA complexes to suggest that large surface area leading to very efficient DNA condensation is not necessary for effective gene transfer. However, it will require further investigation to determine whether the degree of binding and tight association between DNA and nanotubes is a desirable trait to increase gene expression efficiency in vitro or in vivo. This study constitutes the first thorough investigation into the physicochemical interactions between cationic functionalized carbon nanotubes and DNA toward construction of carbon nanotube-based gene transfer vector systems.
Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Therefore, in addressing questions concerning the etiology of complex health outcomes, it is essential that the systemic nature of biology be ta...
Gene-environment interactions of circadian-related genes for cardiometabolic traits
USDA-ARS?s Scientific Manuscript database
Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs1...
Singh, Rama S
2015-01-01
Genes and environment make the organism. Darwin stood firm in his denial of any direct role of environment in the modification of heredity. His theory of evolution heralded two debates: one about the importance and adequacy of natural selection as the main mechanism of evolution, and the other about the role of genes versus environment in the modification of phenotype and evolution. Here, I provide an overview of the second debate and show that the reasons for the gene versus environment battle were twofold: first, there was confusion about the role of environment in modifying the inheritance of a trait versus the evolution of that trait, and second, there was misunderstanding about the meaning of environment and its interaction with genes in the production of phenotypes. It took nearly a century to see that environment does not directly affect the inheritance of a phenotype (i.e., its heredity), but it is nevertheless the primary mover of phenotypic evolution. Effects of genes and environment are not separate but interdependent. One cannot separate the effect of genes from that of environment, or nature from nurture. To answer the question posed in the title, it is partly because the 20th century has been a century of unending progress in genetics. But also because unlike physics, biology is not colorblind; progress in biology has often been delayed beyond the Kuhnian paradigm change due to built-in interest in negating the influence of environment. Those who are against evolution, of course, cannot be expected to understand the role of environment in evolution. Those for it, many biologists included, believing in the supremacy of genes empowers them by giving adaptation a solely gene-directed (self-driven) "teleological" interpretation.
Leigh, Hoyle
2009-01-01
To review recent genetic and neuroscientific research on psychiatric syndromes based on the current diagnostic scheme, and develop a better-fitting multiaxial patient-oriented diagnostic model. DSM I, published in 1952, considered psychiatric illnesses as reactions or extremes of adaptations of the patient's personality to stressful environmental demands. Personality itself was determined by constitution and psychodynamic development. In 1980, this continuum model gave way to an atheoretical categorical diagnostic scheme (DSM III), based on research diagnostic criteria for obtaining 'pure cultures' of patients for biological research. Subsequent research using the 'pure cultures' suggests that psychiatric syndromes represent a phenotypic continuum determined by genes, childhood traumas, and recent stress, mitigated by childhood nurturance, education, and current social support. Specific gene x childhood abuse x recent stress interactions have been discovered, which may serve as a model of how interacting vulnerability genes may or may not result in a psychiatric syndrome, depending on the individual's developmental history and current stress. A continuum model is proposed, with genes interacting with early experiences of stress or nurturance resulting in brain states that may evince minor but persistent symptoms (neurosis) or maladaptive patterns of behavior (personality disorder). The addition of recent or current stress may precipitate a major psychiatric syndrome. While a severe genetic predisposition, such as a mutation, may be sufficient to cause a major syndrome, major psychiatric syndromes are best conceptualized as dysregulation of evolutionarily adaptive brain functions, such as anxiety and vigilance. A new multiaxial model of psychiatric diagnosis is proposed based on this model: axis I for phenomenological diagnoses that include major psychiatric syndromes (e.g. depressive syndrome, psychosis), neuroses, personality disorders, and isolated symptoms; axis II for geno-neuroscience diagnoses, some of which may represent biological conditions associated with axis I, i.e. genes, specific brain morphology, and the functional state of specific brain areas based on laboratory and imaging studies; axis III for medical diseases and conditions; axis IV for stress (childhood, recent, and current); axis V for psychosocial assets (intelligence, education, school/work, social support, and global assessment of functioning) over past 5 years and current. (c) 2008 S. Karger AG, Basel.
Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che
2014-01-16
To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.
2014-01-01
Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926
SNP by SNP by environment interaction network of alcoholism.
Zollanvari, Amin; Alterovitz, Gil
2017-03-14
Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.
Lahey, Benjamin B.; Rathouz, Paul J.; Lee, Steve S.; Chronis-Tuscano, Andrea; Pelham, William E.; Waldman, Irwin D.; Cook, Edwin H.
2010-01-01
Mounting evidence suggests that genetic risks for mental disorders often interact with the social environment, but most studies still ignore environmental moderation of genetic influences. We tested interactions between maternal parenting and the variable number tandem repeat (VNTR) polymorphism in the 3′ untranslated region (UTR) of the dopamine transporter gene in the child to increase understanding of gene-environment interactions involving early parenting. Participants were part of a 9-year longitudinal study of 4–6-year-old children who met criteria for attention-deficit/hyperactivity disorder (ADHD) and demographically matched controls. Maternal parenting was observed during standard mother-child interactions in wave 1. The child’s conduct disorder (CD) symptoms 5–8 years later were measured using separate structured diagnostic interviews of the mother and youth. Controlling for ADHD symptoms and child disruptive behavior during the mother-child interaction, there was a significant inverse relation between levels of both positive and negative parenting at 4–6 years and the number of later CD symptoms, but primarily among children with two copies of the 9-repeat allele of the VNTR. The significant interaction with negative parenting was replicated in parent and youth reports of CD symptoms separately. PMID:21171728
Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.
2011-01-01
Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306
ERIC Educational Resources Information Center
van Roekel, Eeske; Goossens, Luc; Scholte, Ron H. J.; Engels, Rutger C. M. E.; Verhagen, Maaike
2011-01-01
Background: Loneliness is a common problem in adolescence. Earlier research focused on genes within the serotonin and oxytocin systems, but no studies have examined the role of dopamine-related genes in loneliness. In the present study, we focused on the dopamine D2 receptor gene (DRD2). Methods: Associations among the DRD2, sex, parental support,…
Nutrient-gene interactions in early pregnancy: a vascular hypothesis.
Steegers-Theunissen, R P M; Steegers, E A P
2003-02-10
It is hypothesized that the following periconceptional and early pregnancy nutrient-gene interactions link vascular-related reproductive complications and cardiovascular diseases in adulthood: (1) Maternal and paternal genetically controlled nutrient status affects the quality of gametes and fertilization capacity; (2) The embryonic genetic constitution, derived from both parents, and the maternal genetically controlled nutrient environment determine embryogenesis and fetal growth; (3) Trophoblast invasion of decidua and spiral arteries is driven by genes derived from both parents as well as by maternal nutritional factors; (4) Angiogenesis, vasculogenesis and vascular function are dependent on the genetic constitution of the embryo, derived from both parents, and the maternal genetically controlled nutritional environment.Early intra-uterine programming of vessels may concern the same (in)dependent determinants of vascular-related complications during pregnancy and cardiovascular diseases in later life.
Identifying the genes of unconventional high temperature superconductors.
Hu, Jiangping
We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d -orbitals of cations that participate in strong in-plane couplings to the p -orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.
Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction
Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai
2014-01-01
Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923
Dokter, Elisabeth M J; van Rooij, Iris A L M; Wijers, Charlotte H W; Groothuismink, Johanne M; van der Biezen, Jan Jaap; Feitz, Wout F J; Roeleveld, Nel; van der Zanden, Loes F M
2016-04-01
Hypospadias is a congenital malformation with both environmental factors and genetic predisposition involved in the pathogenesis. The role of maternal periconceptional folic acid supplement use in the development of hypospadias is unclear. As folate levels may also be influenced by the C677T polymorphism in the methylenetetrahydrofolate reductase (MTHFR) gene, we hypothesize that a gene-environment interaction between this polymorphism and folic acid use is involved in the etiology of hypospadias. We conducted a case-control study among 855 hypospadias cases and 713 population-based controls from the AGORA data- and biobank. Folic acid supplement use was derived from maternal questionnaires and infant and maternal DNA was used to determine the MTHFR C677T polymorphism using Taqman assays. We performed separate analyses for different hypospadias phenotypes (anterior/middle/posterior). Hypospadias was neither associated with folic acid use or the MTHFR C677T polymorphism, nor with their interaction. However, we did find an association with middle hypospadias when no supplements were used (odds ratio = 1.6; 95% confidence interval, 1.1-2.4), especially in infants carrying the CT/TT genotype (odds ratio = 2.5; 95% confidence interval, 1.4-4.7). In addition, more infants with these genotypes seemed to have posterior hypospadias, regardless of folic acid use. Our study does not suggest a major role for folic acid supplements or the MTHFR C677T polymorphism in the etiology of hypospadias in general, but not using folic acid and/or carrying the MTHFR C677T polymorphism may be associated with middle and posterior hypospadias. Therefore, we stress the importance of studying gene-environment interactions preferably in stratified analyses for different hypospadias phenotypes. © 2016 Wiley Periodicals, Inc.
Further Evidence That Cannabis Moderates Familial Correlation of Psychosis-Related Experiences
van Winkel, Ruud
2015-01-01
Background Familial correlations underlie heritability estimates of psychosis. If gene-environment interactions are important, familial correlation will vary as a function of environmental exposure. Methods Associations between sibling and parental schizotypy (n = 669 pairs, n = 1222 observations), and between sibling schizotypy and patient CAPE psychosis (n = 978 pairs, n = 1723 observations) were examined as a function of sibling cannabis use. This design is based on the prediction that in unaffected siblings who are not exposed, vulnerability for psychosis will remain latent, whereas in case of exposure, latent psychosis vulnerability may become expressed, at the level of schizotypal symptoms, causing the phenotypic correlation between relatives to become “visible” under the influence of cannabis. Results Siblings exposed to recent cannabis use resembled their patient-relative more closely in terms of positive schizotypy (urinalysis(+):B = 0.30, P<.001; urinalysis(-):B = 0.10, p<0.001; p-interaction = 0.0135). Similarly, the familial correlation in positive schizotypy between parent and sibling was significantly greater in siblings recently exposed to cannabis (urinalysis(+):B = 0.78, P<.001; urinalysis(-):B = 0.43, p<0.001; p interaction = 0.0017). Results were comparable when using lifetime cannabis frequency of use as exposure instead of recent use. Parental schizotypy did not predict cannabis use in the healthy sibling, nor in the patient. Similarly, parental cannabis use was not associated with level of schizotypy in the sibling, nor with psychotic symptoms in the patient, making gene-environment correlation unlikely. Conclusion Familial correlation of psychosis-related experiences varies considerably as a function of exposure to cannabis, confirming the importance of gene-cannabis interaction in shifts of expression of psychosis-related experiences. PMID:26384217
Hyndman, Iain Joseph
2016-04-01
Cancer is a leading cause of mortality worldwide. Cancer arises due to a series of somatic mutations that accumulate within the nucleus of a cell which enable the cell to proliferate in an unregulated manner. These mutations arise as a result of both endogenous and exogenous factors. Genes that are commonly mutated in cancer cells are involved in cell cycle regulation, growth and proliferation. It is known that both nature and nurture play important roles in cancer development through complex gene-environment interactions; however, the exact mechanism of these interactions in carcinogenesis is presently unclear. Key environmental factors that play a role in carcinogenesis include smoking, UV light and oncoviruses. Angiogenesis, inflammation and altered cell metabolism are important factors in carcinogenesis and are influenced by both genetic and environmental factors. Although the exact mechanism of nature-nurture interactions in solid tumour formation are not yet fully understood, it is evident that neither nature nor nurture can be considered in isolation. By understanding more about gene-environment interactions, it is possible that cancer mortality could be reduced.
Genetic approaches to addiction: genes and alcohol
Ducci, Francesca; Goldman, David
2008-01-01
Aims Alcoholism is a chronic relapsing disorder with an enormous societal impact. Understanding the genetic basis of alcoholism is crucial to characterize individuals' risk and to develop efficacious prevention and treatment strategies. Methods We examined the available scientific literature to provide an overview of different approaches that are being integrated increasingly to advance our knowledge of the genetic bases of alcoholism. Examples of genes that have been shown to influence vulnerability to alcoholism and related phenotypes are also discussed. Results Genetic factors account for more than 50% of the variance in alcoholism liability. Susceptibility loci for alcoholism include both alcohol-specific genes acting either at the pharmacokinetic or pharmacodynamic levels, as well as loci moderating neuronal pathways such as reward, behavioral control and stress resiliency, that are involved in several psychiatric diseases. In recent years, major progress in gene identification has occurred using intermediate phenotypes such as task-related brain activation that confer the advantage of increased power and the opportunity of exploring the neuronal mechanisms through which genetic variation is translated into behavior. Fundamental to the detection of gene effects is also the understanding of the interplay between genes as well as genes/environment interactions. Whole Genome Association studies represent a unique opportunity to identify alcohol-related loci in hypothesis-free fashion. Finally, genome-wide analyses of transcripts and chromatin remodeling promise an increase in our understanding of the genome function and of the mechanisms through which gene and environment cause diseases. Conclusions Although the genetic bases of alcoholism remain largely unknown, there are reasons to think that more genes will be discovered in the future. Multiple and complementary approaches will be required to piece together the mosaic of causation. PMID:18422824
Roux, F; Bergelson, J
2016-01-01
In the context of global change, predicting the responses of plant communities in an ever-changing biotic environment calls for a multipronged approach at the interface of evolutionary genetics and community ecology. However, our understanding of the genetic basis of natural variation involved in mediating biotic interactions, and associated adaptive dynamics of focal plants in their natural communities, is still in its infancy. Here, we review the genetic and molecular bases of natural variation in the response to biotic interactions (viruses, bacteria, fungi, oomycetes, herbivores, and plants) in the model plant Arabidopsis thaliana as well as the adaptive value of these bases. Among the 60 identified genes are a number that encode nucleotide-binding site leucine-rich repeat (NBS-LRR)-type proteins, consistent with early examples of plant defense genes. However, recent studies have revealed an extensive diversity in the molecular mechanisms of defense. Many types of genetic variants associate with phenotypic variation in biotic interactions, even among the genes of large effect that tend to be identified. In general, we found that (i) balancing selection rather than directional selection explains the observed patterns of genetic diversity within A. thaliana and (ii) the cost/benefit tradeoffs of adaptive alleles can be strongly dependent on both genomic and environmental contexts. Finally, because A. thaliana rarely interacts with only one biotic partner in nature, we highlight the benefit of exploring diffuse biotic interactions rather than tightly associated host-enemy pairs. This challenge would help to improve our understanding of coevolutionary quantitative genetics within the context of realistic community complexity. © 2016 Elsevier Inc. All rights reserved.
Peng, Jiajie; Zhang, Xuanshuo; Hui, Weiwei; Lu, Junya; Li, Qianqian; Liu, Shuhui; Shang, Xuequn
2018-03-19
Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, most existing semantic similarity approaches rely only on GO annotations and structure, or incorporate only local interactions in the co-functional network. This may lead to inaccurate GO-based similarity resulting from the incomplete GO topology structure and gene annotations. We present NETSIM2, a new network-based method that allows researchers to measure GO-based gene functional similarities by considering the global structure of the co-functional network with a random walk with restart (RWR)-based method, and by selecting the significant term pairs to decrease the noise information. Based on the EC number (Enzyme Commission)-based groups of yeast and Arabidopsis, evaluation test shows that NETSIM2 can enhance the accuracy of Gene Ontology-based gene functional similarity. Using NETSIM2 as an example, we found that the accuracy of semantic similarities can be significantly improved after effectively incorporating the global gene-to-gene interactions in the co-functional network, especially on the species that gene annotations in GO are far from complete.
Aslund, C; Nordquist, N; Comasco, E; Leppert, J; Oreland, L; Nilsson, K W
2011-03-01
The present study investigated a possible interaction between a functional polymorphism in the MAOA gene promoter (MAOA-VNTR) and childhood maltreatment in the prediction of adolescent male and female delinquency. A cohort of 1,825 high school students, 17-18 years old, completed an anonymous questionnaire during class hours which included questions on childhood maltreatment, sexual abuse, and delinquency. Saliva samples were collected for DNA isolation, and analyzed for the MAOA-VNTR polymorphism. Self-reported maltreatment was a strong risk factor for adolescent delinquent behavior. The MAOA genotype also showed a significant main effect when controlled for maltreatment. Boys with a short variant and girls with one or two long variants of the polymorphism showed a higher risk for delinquency when exposed to maltreatment. Our results confirm previous findings of an interaction between the MAOA-VNTR polymorphism and self-reported maltreatment. Results for boys and girls differ according to MAOA-VNTR genotype and direction of phenotypic expression.
NASA Astrophysics Data System (ADS)
Pérez-de-Mora, Alfredo; Schulz, Stephan; Schloter, Michael
Hydrocarbons are major contaminants of soil ecosystems as a result of uncontrolled oil spills and wastes disposal into the environment. Ecological risk assessment and remediation of affected sites is often constrained due to lack of suitable prognostic and diagnostic tools that provide information of abiotic-biotic interactions occurring between contaminants and biological targets. Therefore, the identification and quantification of genes involved in the degradation of hydrocarbons may play a crucial role for evaluating the natural attenuation potential of contaminated sites and the development of successful bioremediation strategies. Besides other gene clusters, the alk operon has been identified as a major player for alkane degradation in different soils. An oxygenase gene (alkB) codes for the initial step of the degradation of aliphatic alkanes under aerobic conditions. In this work, we present an MPN- and a real-time PCR method for the quantification of the bacterial gene alkB (coding for rubredoxin-dependent alkane monooxygenase) in environmental samples. Both approaches enable a rapid culture-independent screening of the alkB gene in the environment, which can be used to assess the intrinsic natural attenuation potential of a site or to follow up the on-going progress of bioremediation assays.
Tang, Deliang
2014-01-01
Polycyclic aromatic hydrocarbons (PAH) are a class of chemicals common in the environment. Certain PAH are carcinogenic, although the degree to which genetic variation influences susceptibility to carcinogenic PAH remains unclear. Also unknown is the influence of genetic variation on the procarcinogenic effect of in utero exposures to PAH. Benzo[a]pyrene (B[a]P) is a well-studied PAH that is classified as a probable human carcinogen. Within our New York City-based cohort, we explored interactions between maternal exposure to airborne PAH during pregnancy and maternal and newborn haplotypes (and in one case, a single-nucleotide polymorphism) in key B[a]P metabolism genes on B[a]P-DNA adducts in paired cord blood samples. The study subjects included non-smoking African-American (n = 132) and Dominican (n = 235) women with available data on maternal PAH exposure, paired cord adducts and genetic data who resided in the Washington Heights, Central Harlem and South Bronx neighborhoods of New York City. We selected seven maternal and newborn genes related to B[a]P metabolism, detoxification and repair for our analyses: CYP1A1, CYP1A2, CYP1B1, GSTM3, GSTT2, NQO1 and XRCC1. We found significant interactions between maternal PAH exposure and haplotype on cord B[a]P-DNA adducts in the following genes: maternal CYP1B1, XRCC1 and GSTM3, and newborn CYP1A2 and XRCC1 in African-Americans; and maternal XRCC1 and newborn NQO1 in Dominicans. These novel findings highlight differences in maternal and newborn genetic contributions to B[a]P-DNA adduct formation, as well as ethnic differences in gene–environment interactions, and have the potential to identify at-risk subpopulations who are susceptible to the carcinogenic potential of B[a]P. PMID:24177223
The free-energy cost of interaction between DNA loops.
Huang, Lifang; Liu, Peijiang; Yuan, Zhanjiang; Zhou, Tianshou; Yu, Jianshe
2017-10-03
From the viewpoint of thermodynamics, the formation of DNA loops and the interaction between them, which are all non-equilibrium processes, result in the change of free energy, affecting gene expression and further cell-to-cell variability as observed experimentally. However, how these processes dissipate free energy remains largely unclear. Here, by analyzing a mechanic model that maps three fundamental topologies of two interacting DNA loops into a 4-state model of gene transcription, we first show that a longer DNA loop needs more mean free energy consumption. Then, independent of the type of interacting two DNA loops (nested, side-by-side or alternating), the promotion between them always consumes less mean free energy whereas the suppression dissipates more mean free energy. More interestingly, we find that in contrast to the mechanism of direct looping between promoter and enhancer, the facilitated-tracking mechanism dissipates less mean free energy but enhances the mean mRNA expression, justifying the facilitated-tracking hypothesis, a long-standing debate in biology. Based on minimal energy principle, we thus speculate that organisms would utilize the mechanisms of loop-loop promotion and facilitated tracking to survive in complex environments. Our studies provide insights into the understanding of gene expression regulation mechanism from the view of energy consumption.
Explaining human uniqueness: genome interactions with environment, behaviour and culture
Varki, Ajit; Geschwind, Daniel H.; Eichler, Evan E.
2009-01-01
What makes us human? Specialists in each discipline respond through the lens of their own expertise. In fact, ‘anthropogeny’ (explaining the origin of humans) requires a transdisciplinary approach that eschews such barriers. Here we take a genomic and genetic perspective towards molecular variation, explore systems analysis of gene expression and discuss an organ-systems approach. Rejecting any ‘genes versus environment’ dichotomy, we then consider genome interactions with environment, behaviour and culture, finally speculating that aspects of human uniqueness arose because of a primate evolutionary trend towards increasing and irreversible dependence on learned behaviours and culture — perhaps relaxing allowable thresholds for large-scale genomic diversity. PMID:18802414
Biomarkers of susceptibility to chemical carcinogens: the example of non-Hodgkin lymphomas.
Kelly, Rachel S; Vineis, Paolo
2014-09-01
Genetic susceptibly to suspected chemical and environmental carcinogens may modify the response to exposure. The aim of this review was to explore the issues involved in the study of gene-environment interactions, and to consider the use of susceptibility biomarkers in cancer epidemiology, using non-Hodgkin lymphoma (NHL) as an example. PubMed, EMBASE and Web of Science were searched for peer-reviewed articles considering biomarkers of susceptibility to chemical, agricultural and industrial carcinogens in the aetiology of NHL. The results suggest a modifying role for genetic susceptibility to a number of occupational and environmental exposures including organochlorines, chlorinated solvents, chlordanes and benzene in the aetiology of NHL. The potential importance of these gene-environment interactions in NHL may help to explain the lack of definitive carcinogens identified to date for this malignancy. Although a large number of genetic variants and gene-environment interactions have been explored for NHL, to date replication is lacking and therefore the findings remain to be validated. These findings highlight the need for novel standardized methodologies in the study of genetic susceptibility to chemical carcinogens. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Individualized weight management: what can be learned from nutrigenomics and nutrigenetics?
Rudkowska, Iwona; Pérusse, Louis
2012-01-01
The rise in the prevalence of obesity observed over the past decades is taken by many as an indication of the predominance of environmental factors (the so-called obesogenic environment) over genetic factors in explaining why obesity has reached epidemic proportions. While a changing environment favoring increased food intake and decreased physical activity levels has clearly contributed to shifting the distribution of body mass index (BMI) at the population level, not everyone is becoming overweight or obese. This suggests that there are genetic factors interacting with environmental factors to predispose some individuals to obesity. This gene-environment interaction is not only important in determining an individual's susceptibility to obesity but can also influence the outcome of weight-loss programs and weight-management strategies in overweight and obese subjects. This chapter reviews the role of gene-nutrient interactions in the context of weight management. The first section reviews the application of transcriptomics in human nutrition intervention studies on the molecular impact of caloric restriction and macronutrient composition. The second section reviews the effects of various obesity candidate gene polymorphisms on the response of body weight or weight-related phenotypes to weight-loss programs which include nutritional interventions. Copyright © 2012 Elsevier Inc. All rights reserved.
Relations between three dopaminergic system genes, school attachment, and adolescent delinquency.
Fine, Adam; Mahler, Alissa; Simmons, Cortney; Chen, Chuansheng; Moyzis, Robert; Cauffman, Elizabeth
2016-11-01
Both environmental factors and genetic variation, particularly in genes responsible for the dopaminergic system such as DRD4, DRD2, and DAT1 (SLC6A3), affect adolescent delinquency. The school context, despite its developmental importance, has been overlooked in gene-environment research. Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (NICHD ECCYD), this study examined key interactions between school attachment and (a) each of the DRD4, DRD2, and DAT1 (SLC6A3) genotypes; and (b) a polygenic score. Results indicate that there is a main effect of school attachment, unlike genetic variation, on delinquency. Interestingly, there are important interactive effects of school attachment and dopaminergic genotypes on delinquency. Carriers of the DRD2-A1 allele were differentially affected by both positive and negative school environments, whereas DAT1-10R carriers fared the same as 9R homozygotes in poorer and moderate school environments, but fared disproportionately better in more positive environments. Contrary to expectations, youth without the DRD4-7R allele were particularly affected by the school environment. These findings contribute to the literature considering the roles of both context and genes in delinquency research, and inform our understanding of the individual-level traits that influence sensitivity to particular contexts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V
2013-09-01
Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.
Molenaar, Dylan; Middeldorp, Christel; van Beijsterveldt, Toos; Boomsma, Dorret I
2015-01-01
This study tested for Genotype × Environment (G × E) interaction on behavioral and emotional problems in children using new methods that do not require identification of candidate genes or environments, can distinguish between interaction with shared and unique environment, and are insensitive to scale effects. Parental ratings of problem behavior from 14,755 twin pairs (5.3 years, SD = 0.22) indicated G × E interaction on emotional liability, social isolation, aggression, attention problems, dependency, anxiety, and physical coordination. Environmental influences increased in children who were genetically more predisposed to problem behavior, with ~20% of the variance due to G × E interaction (8% for anxiety to 37% for attention problems). Ignoring G × E interaction does not greatly bias heritability estimates, but it does offer a comprehensive model of the etiology for childhood problems. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.
Genetic Expression Outside the Skin: Clues to Mechanisms of Genotype × Environment Interaction
Reiss, David; Leve, Leslie D.
2007-01-01
The rapidly moving study of Gene × Environment interaction needs interim conceptual tools to track progress, integrate findings, and apply this knowledge to preventive intervention. We define two closely related concepts: the social mediation of the expression of genetic influences and the interaction between the entire genotype and the social environment (Genotype × Environment interaction; G×E). G×E interaction, the primary focus of this report, assesses individual differences in the full genotype using twin, sibling, and adoption designs and, for the most part, employs fine-grained analyses of relational processes in the social environment. In comparison, studies of Allele × Environment interaction (A×E) assess the influence on development of one or more measured polymorphisms as modified by environmental factors. G×E studies build on work showing how the social environment responds to genetic influences and how genetic influences shape the social environment. Recent G×E research has yielded new insight into variations in the sensitivity of the social environment to genotypic influences and provides clues to the specificity and timing of these environmental responses that can be leveraged to inform preventive interventions aimed at reducing genetic risk for problem behavior. PMID:17931431
Folate and Breast Cancer: Role of Intake, Blood Levels, and Metabolic Gene Polymorphisms
2006-06-01
polymorphisms . The specific aims are 1) methodological training in the analysis of gene - gene and gene -environment interactions by studying folate...evaluation of folate intake, plasma folate, and metabolic gene polymorphisms in relation to breast cancer risk: Months 1-19. b. Prepare blood samples...isolated for the folate and gene polymorphism assays among the 184 cases and matched controls. The folate assays are on-going at this time and over
Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T
2014-12-01
Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).
Brevik, Asgeir; Joshi, Amit D; Corral, Román; Onland-Moret, N Charlotte; Siegmund, Kimberly D; Le Marchand, Loïc; Baron, John A; Martinez, Maria Elena; Haile, Robert W; Ahnen, Dennis J; Sandler, Robert S; Lance, Peter; Stern, Mariana C
2010-12-01
A diet high in red meat is an established colorectal cancer (CRC) risk factor. Carcinogens generated during meat cooking have been implicated as causal agents and can induce oxidative DNA damage, which elicits repair by the base excision repair (BER) pathway. Using a family-based study, we investigated the role of polymorphisms in 4 BER genes (APEX1 Gln51His, Asp148Glu; OGG1 Ser236Cys; PARP Val742Ala; and XRCC1 Arg194Trp, Arg280His, Arg399Gln) as potential CRC risk factors and modifiers of the association between diets high in red meat or poultry and CRC risk. We tested for gene-environment interactions using case-only analyses (n = 577) and compared statistically significant results with those obtained using case-unaffected sibling comparisons (n = 307 sibships). Carriers of the APEX1 codon 51 Gln/His genotype had a reduced CRC risk compared with carriers of the Gln/Gln genotype (odds ratio (OR) = 0.15, 95% CI = 0.03-0.69, P = 0.015). The association between higher red meat intake (>3 servings per week) and CRC was modified by the PARP Val762Ala single-nucleotide polymorphisms (SNP; case-only interaction P = 0.026). This SNP also modified the association between higher intake of high-temperature cooked red meat (case-only interaction P = 0.0009). We report evidence that the BER pathway PARP gene modifies the association of diets high in red meat cooked at high temperatures with risk of CRC. Our findings suggest a contribution to colorectal carcinogenesis of free radical damage as one of the possible harmful effects of a diet high in red meat. ©2010 AACR.
Brevik, Asgeir; Joshi, Amit D.; Corral, Román; Onland-Moret, N. Charlotte; Siegmund, Kimberly D.; Le Marchand, Loïc; Baron, John A.; Martinez, Maria Elena; Haile, Robert W.; Ahnen, Dennis J.; Sandler, Robert S.; Lance, Peter; Stern, Mariana C.
2010-01-01
Background A diet high in red meat is an established colorectal cancer (CRC) risk factor. Carcinogens generated during meat cooking have been implicated as causal agents, and can induce oxidative DNA damage, which elicits repair by the base excision repair (BER) pathway. Methods Using a family-based study we investigated the role of polymorphisms in four BER genes (APEX1 Gln51His, Asp148Glu; OGG1 Ser236Cys; PARP Val742Ala; XRCC1 Arg194Trp, Arg280His, Arg399Gln) as potential CRC risk factors and modifiers of the association between high-red meat or poultry diets and CRC risk. We tested for gene-environment interactions using case-only analyses (N = 577) and compared statistically significant results to those obtained using case-unaffected sibling comparisons (N = 307 sibships). Results Carriers of the APEX1 codon 51 Gln/His genotype had a reduced CRC risk compared to carriers of the Gln/Gln genotype (OR 0.15, 95% CI 0.03-0.69, p = 0.015). The association between higher red meat intake (>3 servings/week) and CRC was modified by the PARP Val762Ala SNP (case-only interaction p = 0.026). This SNP also modified the association between higher intake of high-temperature cooked red meat (case-only interaction p = 0.0009). Conclusions We report evidence that the BER pathway PARP gene modifies the association of diets high in red meat cooked at high temperatures with risk of CRC. Impact Our findings suggest a contribution to colorectal carcinogenesis of free radical damage as one of the possible harmful effects of a high-red meat diet. PMID:21037106
Tchetgen Tchetgen, Eric
2011-03-01
This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.
Mullineaux, Paula Y; DiLalla, Lisabeth Fisher
2015-07-01
Nearly all aspects of human development are influenced by genetic and environmental factors, which conjointly shape development through several gene-environment interplay mechanisms. More recently, researchers have begun to examine the influence of genetic factors on peer and family relationships across the pre-adolescent and adolescent time periods. This article introduces the special issue by providing a critical overview of behavior genetic methodology and existing research demonstrating gene-environment processes operating on the link between peer and family relationships and adolescent adjustment. The overview is followed by a summary of new research studies, which use genetically informed samples to examine how peer and family environment work together with genetic factors to influence behavioral outcomes across adolescence. The studies in this special issue provide further evidence of gene-environment interplay through innovative behavior genetic methodological approaches across international samples. Results from the quantitative models indicate environmental moderation of genetic risk for coercive adolescent-parent relationships and deviant peer affiliation. The molecular genetics studies provide support for a gene-environment interaction differential susceptibility model for dopamine regulation genes across positive and negative peer and family environments. Overall, the findings from the studies in this special issue demonstrate the importance of considering how genes and environments work in concert to shape developmental outcomes during adolescence.
Gene-environment interaction in the etiology of mathematical ability using SNP sets.
Docherty, Sophia J; Kovas, Yulia; Plomin, Robert
2011-01-01
Mathematics ability and disability is as heritable as other cognitive abilities and disabilities, however its genetic etiology has received relatively little attention. In our recent genome-wide association study of mathematical ability in 10-year-old children, 10 SNP associations were nominated from scans of pooled DNA and validated in an individually genotyped sample. In this paper, we use a 'SNP set' composite of these 10 SNPs to investigate gene-environment (GE) interaction, examining whether the association between the 10-SNP set and mathematical ability differs as a function of ten environmental measures in the home and school in a sample of 1888 children with complete data. We found two significant GE interactions for environmental measures in the home and the school both in the direction of the diathesis-stress type of GE interaction: The 10-SNP set was more strongly associated with mathematical ability in chaotic homes and when parents are negative.
Ohneck, Emily J.; Arivett, Brock A.; Fiester, Steven E.; Wood, Cecily R.; Metz, Maeva L.; Simeone, Gabriella M.
2018-01-01
The capacity of Acinetobacter baumannii to persist and cause infections depends on its interaction with abiotic and biotic surfaces, including those found on medical devices and host mucosal surfaces. However, the extracellular stimuli affecting these interactions are poorly understood. Based on our previous observations, we hypothesized that mucin, a glycoprotein secreted by lung epithelial cells, particularly during respiratory infections, significantly alters A. baumannii’s physiology and its interaction with the surrounding environment. Biofilm, virulence and growth assays showed that mucin enhances the interaction of A. baumannii ATCC 19606T with abiotic and biotic surfaces and its cytolytic activity against epithelial cells while serving as a nutrient source. The global effect of mucin on the physiology and virulence of this pathogen is supported by RNA-Seq data showing that its presence in a low nutrient medium results in the differential transcription of 427 predicted protein-coding genes. The reduced expression of ion acquisition genes and the increased transcription of genes coding for energy production together with the detection of mucin degradation indicate that this host glycoprotein is a nutrient source. The increased expression of genes coding for adherence and biofilm biogenesis on abiotic and biotic surfaces, the degradation of phenylacetic acid and the production of an active type VI secretion system further supports the role mucin plays in virulence. Taken together, our observations indicate that A. baumannii recognizes mucin as an environmental signal, which triggers a response cascade that allows this pathogen to acquire critical nutrients and promotes host-pathogen interactions that play a role in the pathogenesis of bacterial infections. PMID:29309434
Bockholt, Susanne M.; West, J. Paige; Bollenbacher, Walter E.
2003-01-01
Multimedia has the potential of providing bioscience education novel learning environments and pedagogy applications to foster student interest, involve students in the research process, advance critical thinking/problem-solving skills, and develop conceptual understanding of biological topics. Cancer Cell Biology, an interactive, multimedia, problem-based module, focuses on how mutations in protooncogenes and tumor suppressor genes can lead to uncontrolled cell proliferation by engaging students as research scientists/physicians with the task of diagnosing the molecular basis of tumor growth for a group of patients. The process of constructing the module, which was guided by scientist and student feedback/responses, is described. The completed module and insights gained from its development are presented as a potential “multimedia pedagogy” for the development of other multimedia science learning environments. PMID:12822037
Hayden, Elizabeth P.; Klein, Daniel N.; Dougherty, Lea R.; Olino, Thomas M.; Laptook, Rebecca S.; Dyson, Margaret W.; Bufferd, Sara J.; Durbin, C. Emily; Sheikh, Haroon I.; Singh, Shiva M.
2012-01-01
Objectives Research implicates the A1 allele of the dopamine D2 receptor gene (DRD2) Taq1A polymorphism in the development of depression and anxiety. Furthermore, recent papers suggest that children with A1 allele of this gene may receive less positive parenting, and that the effects of this gene on child symptoms may be moderated by parenting. We sought to replicate and extend these findings using behavioral measures in a nonclinical sample of young children. Methods In a sample of 473 preschool-aged children and their mothers, structured clinical interview measures and maternal reports of child symptoms were collected, and standardized observations of parent–child interactions were conducted. Results An association was detected between the DRD2 A1 allele and symptoms of depression and anxiety indexed using interview and parent report methods. As found in previous reports, children with the DRD2 A1 allele received less supportive parenting and displayed higher levels of negative emotionality during parent–child interactions. Tests of mediation and moderation were conducted. Conclusion We found associations between the DRD2 A1 allele and early-emerging anxious and depressive symptoms in a community sample of preschool-aged children, and evidence of a gene–environment correlation and moderation of the main effect of child genotype on child symptoms by parenting. PMID:20526230
Gene-environment interaction in major depression: focus on experience-dependent biological systems.
Lopizzo, Nicola; Bocchio Chiavetto, Luisella; Cattane, Nadia; Plazzotta, Giona; Tarazi, Frank I; Pariante, Carmine M; Riva, Marco A; Cattaneo, Annamaria
2015-01-01
Major depressive disorder (MDD) is a multifactorial and polygenic disorder, where multiple and partially overlapping sets of susceptibility genes interact each other and with the environment, predisposing individuals to the development of the illness. Thus, MDD results from a complex interplay of vulnerability genes and environmental factors that act cumulatively throughout individual's lifetime. Among these environmental factors, stressful life experiences, especially those occurring early in life, have been suggested to exert a crucial impact on brain development, leading to permanent functional changes that may contribute to lifelong risk for mental health outcomes. In this review, we will discuss how genetic variants (polymorphisms, SNPs) within genes operating in neurobiological systems that mediate stress response and synaptic plasticity, can impact, by themselves, the vulnerability risk for MDD; we will also consider how this MDD risk can be further modulated when gene × environment interaction is taken into account. Finally, we will discuss the role of epigenetic mechanisms, and in particular of DNA methylation and miRNAs expression changes, in mediating the effect of the stress on the vulnerability risk to develop MDD. Taken together, we aim to underlie the role of genetic and epigenetic processes involved in stress- and neuroplasticity-related biological systems on the development of MDD after exposure to early life stress, thereby building the basis for future research and clinical interventions.
Lucas-Thompson, Rachel G; Holman, E Alison
2013-04-01
We examined whether the oxytocin receptor gene (OXTR) single nucleotide polymorphism (SNP) rs53576 genotype buffers the combined impact of negative social environments (e.g., interpersonal conflict/constraint) and economic stress on post-traumatic stress (PTS) symptoms and impaired daily functioning following collective stress (September 11th terrorist attacks). Saliva was collected by mail and used to genotype 704 respondents. Participants completed Web-based assessments of pre-9/11 mental health, acute stress 9-23 days after 9/11, the quality of social environments 1 year post-9/11, economic stress 18 months post-9/11, and PTS symptoms and impaired functioning 2 and 3 years post-9/11. Interactions between negative social environments and economic stress were examined separately based on OXTR rs53576 genotype (GG vs. any A allele). For individuals with an A allele, a negative social environment significantly increased PTS symptoms without regard to the level of economic stress experienced. However, for respondents with a GG genotype, negative social environments predicted elevated PTS symptoms only for those also experiencing high economic stress. Gender moderated associations between negative social environments, economic stress, and impaired functioning. The functioning of females was most affected by negative social environments regardless of genotype and economic stress, whereas the functioning of males was differentially susceptible to economic stress depending on OXTR genotype and negative social environments. These findings suggest that it is important to consider the combined impact of gender and ongoing stress in different domains as moderators of genetic vulnerability following collective stress. Copyright © 2013 Elsevier Inc. All rights reserved.
Attachment style and oxytocin receptor gene variation interact in influencing social anxiety.
Notzon, S; Domschke, K; Holitschke, K; Ziegler, C; Arolt, V; Pauli, P; Reif, A; Deckert, J; Zwanzger, P
2016-01-01
Social anxiety has been suggested to be promoted by an insecure attachment style. Oxytocin is discussed as a mediator of trust and social bonding as well as a modulator of social anxiety. Applying a gene-environment (G × E) interaction approach, in the present pilot study the main and interactive effects of attachment styles and oxytocin receptor (OXTR) gene variation were probed in a combined risk factor model of social anxiety in healthy probands. Participants (N = 388; 219 females, 169 males; age 24.7 ± 4.7 years) were assessed for anxiety in social situations (Social Phobia and Anxiety Inventory) depending on attachment style (Adult Attachment Scale, AAS) and OXTR rs53576 A/G genotype. A less secure attachment style was significantly associated with higher social anxiety. This association was partly modulated by OXTR genotype, with a stronger negative influence of a less secure attachment style on social anxiety in A allele carriers as compared to GG homozygotes. The present pilot data point to a strong association of less secure attachment and social anxiety as well as to a gene-environment interaction effect of OXTR rs53576 genotype and attachment style on social anxiety possibly constituting a targetable combined risk marker of social anxiety disorder.
Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Lin-Xing; Mendez-Garcia, Celia; Dombrowski, Nina
Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. For this study, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitatmore » distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchae ota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.« less
Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota.
Chen, Lin-Xing; Méndez-García, Celia; Dombrowski, Nina; Servín-Garcidueñas, Luis E; Eloe-Fadrosh, Emiley A; Fang, Bao-Zhu; Luo, Zhen-Hao; Tan, Sha; Zhi, Xiao-Yang; Hua, Zheng-Shuang; Martinez-Romero, Esperanza; Woyke, Tanja; Huang, Li-Nan; Sánchez, Jesús; Peláez, Ana Isabel; Ferrer, Manuel; Baker, Brett J; Shu, Wen-Sheng
2018-03-01
Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. Here, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitat distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchaeota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.
Metabolic versatility of small archaea Micrarchaeota and Parvarchaeota
Chen, Lin-Xing; Mendez-Garcia, Celia; Dombrowski, Nina; ...
2017-12-08
Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. For this study, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitatmore » distribution for this phylum. Despite their small genomes (0.64-1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchae ota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.« less
Zhao, Mingzhe; Chen, Lu; Yang, Jiarun; Han, Dong; Fang, Deyu; Qiu, Xiaohui; Yang, Xiuxian; Qiao, Zhengxue; Ma, Jingsong; Wang, Lin; Jiang, Shixiang; Song, Xuejia; Zhou, Jiawei; Zhang, Jian; Chen, Mingqi; Qi, Dong; Yang, Yanjie; Pan, Hui
2018-02-01
Depression is thought to be multifactorial in etiology, including genetic and environmental components. While a number of gene-environment interaction studies have been carried out, meta-analyses are scarce. The present meta-analysis aimed to quantify evidence on the interaction between brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and stress in depression. Included were 31 peer-reviewed with a pooled total of 21060 participants published before October 2016 and literature searches were conducted using PubMed, Wolters Kluwer, Web of Science, EBSCO, Elsevier Science Direct and Baidu Scholar databases. The results indicated that the Met allele of BDNF Val66Met polymorphism significantly moderated the relationship between stress and depression (Z=2.666, p = 0.003). The results of subgroup analysis concluded that stressful life events and childhood adversity separately interacted with the Met allele of BDNF Val66Met polymorphism in depression (Z = 2.552, p = 0.005; Z = 1.775, p = 0.03). The results could be affected by errors or bias in primary studies which had small sample sizes with relatively lower statistic power. We could not estimate how strong the interaction effect between gene and environment was. We found evidence that supported the hypothesis that BDNF Val66Met polymorphism moderated the relationship between stress and depression, despite the fact that many included individual studies did not show this effect. Copyright © 2017 Elsevier B.V. All rights reserved.
Knafo, Ariel; Israel, Salomon; Ebstein, Richard P
2011-02-01
Theoretical considerations and new empirical evidence suggest that children's development cannot simply be explained by either genes or environment but that their interaction is important to understanding child behavior. In particular, a genetic polymorphism, the exon III repeat region of the dopamine receptor D4, has been the focus of interest regarding differential susceptibility to parental influence. To study environmental and genetic influences on children's prosocial behavior, 168 twin pairs (mean age = 44 months) participated in an experiment that assessed prosocial behavior via three measures: compliant prosocial behavior elicited in response to social requests, self-initiated prosocial behavior enacted voluntarily, and mothers' rating of children's behavior. Genetic effects accounted for 34% to 53% of the variance in prosocial behavior. The rest of the variance was accounted for by nonshared environment and error. Parenting measures of maternal positivity, negativity, and unexplained punishment did not correlate significantly with children's prosocial behavior. However, when parenting was stratified by presence or absence of the child's dopamine receptor D4 7-repeat allele in an overlapping sample of 167 children to model differential susceptibility to parental influence, a richer picture emerged. Positive parenting related meaningfully to mother-rated prosocial behavior, and unexplained punishment related positively to self-initiated prosocial behavior, but only among children carrying the 7-repeat allele. The findings demonstrate that a molecular genetic strategy, based on genotyping of common polymorphisms and combined with a classic twin approach, provides a richer description of how genes and environment interact to shape children's behavior, and allows for the identification of differential sensitivity to parental influence.
Kazma, Rémi; Bonaïti-Pellié, Catherine; Norris, Jill M; Génin, Emmanuelle
2010-01-01
Gene-environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene-environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene-environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype.
Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.
Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi
2007-10-04
In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.
Mandy, William; Lai, Meng-Chuan
2016-03-01
Although autism spectrum condition (ASC) is strongly genetic in origin, accumulating evidence points to the critical roles of various environmental influences on its emergence and subsequent developmental course. A developmental psychopathology framework was used to synthesise literature on environmental factors associated with the onset and course of ASC (based on a systematic search of the literature using PubMed, PsychInfo and Google Scholar databases). Particular emphasis was placed on gene-environment interplay, including gene-environment interaction (G × E) and gene-environment correlation (rGE). Before conception, advanced paternal and maternal ages may independently enhance offspring risk for ASC. Exogenous prenatal risks are evident (e.g. valproate and toxic chemicals) or possible (e.g. selective serotonin reuptake inhibitors), and processes endogenous to the materno-foeto-placental unit (e.g. maternal diabetes, enhanced steroidogenic activities and maternal immune activation) likely heighten offspring vulnerability to ASC. Folate intake is a prenatal protective factor, with a particular window of action around 4 weeks preconception and during the first trimester. These prenatal risks and protective mechanisms appear to involve G × E and potentially rGE. A variety of perinatal risks are related to offspring ASC risk, possibly reflecting rGE. Postnatal social factors (e.g. caregiver-infant interaction, severe early deprivation) during the first years of life may operate through rGE to influence the likelihood of manifesting a full ASC phenotype from a 'prodromal' phase (a proposal distinct to the discredited and harmful 'refrigerator mother hypothesis'); and later postnatal risks, after the full manifestation of ASC, shape life span development through transactions mediated by rGE. There is no evidence that vaccination is a postnatal risk for ASC. Future investigations should consider the specificity of risks for ASC versus other atypical neurodevelopmental trajectories, timing of risk and protective mechanisms, animal model systems to study mechanisms underlying gene-environment interplay, large-sample genome-envirome designs to address G × E and longitudinal studies to elucidate how rGE plays out over time. Clinical and public health implications are discussed. © 2016 Association for Child and Adolescent Mental Health.
Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong
2016-01-01
Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162
Exploring the Genetic Etiology of Trust in Adolescents: Combined Twin and DNA Analyses
Wootton, Robyn E.; Davis, Oliver S. P.; Mottershaw, Abigail L.; Wang, R. Adele H.; Haworth, Claire M. A.
2017-01-01
Behavioral traits generally show moderate to strong genetic influence, with heritability estimates of around 50%. Some recent research has suggested that trust may be an exception because it is more strongly influenced by social interactions. In a sample of over 7,000 adolescent twins from the United Kingdom’s Twins Early Development Study, we found broad sense heritability estimates of 57% for generalized trust and 51% for trust in friends. Genomic-relatedness-matrix restricted maximum likelihood (GREML) estimates in the same sample indicate that 21% of the narrow sense genetic variance can be explained by common single nucleotide polymorphisms for generalized trust and 43% for trust in friends. As expected, this implies a large amount of unexplained heritability, although power is low for estimating DNA-based heritability. The missing heritability may be accounted for by interactions between DNA and the social environment during development or via gene–environment correlations with rare variants. How these genes and environments correlate seem especially important for the development of trust. PMID:27852354
Association of Polyaminergic Loci With Anxiety, Mood Disorders, and Attempted Suicide
Fiori, Laura M.; Wanner, Brigitte; Jomphe, Valérie; Croteau, Jordie; Vitaro, Frank
2010-01-01
Background The polyamine system has been implicated in a number of psychiatric conditions, which display both alterations in polyamine levels and altered expression of genes related to polyamine metabolism. Studies have identified associations between genetic variants in spermidine/spermine N1-acetyltransferase (SAT1) and both anxiety and suicide, and several polymorphisms appear to play important roles in determining gene expression. Methodology/Principal Findings We genotyped 63 polymorphisms, spread across four polyaminergic genes (SAT1, spermine synthase (SMS), spermine oxidase (SMOX), and ornithine aminotransferase like-1 (OATL1)), in 1255 French-Canadian individuals who have been followed longitudinally for 22 years. We assessed univariate associations with anxiety, mood disorders, and attempted suicide, as assessed during early adulthood. We also investigated the involvement of gene-environment interactions in terms of childhood abuse, and assessed internalizing and externalizing symptoms as endophenotypes mediating these interactions. Overall, each gene was associated with at least one main outcome: anxiety (SAT1, SMS), mood disorders (SAT1, SMOX), and suicide attempts (SAT1, OATL1). Several SAT1 polymorphisms displayed disease-specific risk alleles, and polymorphisms in this gene were involved in gene-gene interactions with SMS to confer risk for anxiety disorders, as well as gene-environment interactions between childhood physical abuse and mood disorders. Externalizing behaviors demonstrated significant mediation with regards to the association between OATL1 and attempted suicide, however there was no evidence that externalizing or internalizing behaviors were appropriate endophenotypes to explain the associations with mood or anxiety disorders. Finally, childhood sexual abuse did not demonstrate mediating influences on any of our outcomes. Conclusions/Significance These results demonstrate that genetic variants in polyaminergic genes are associated with psychiatric conditions, each of which involves a set of separate and distinct risk alleles. As several of these polymorphisms are associated with gene expression, these findings may provide mechanisms to explain the alterations in polyamine metabolism which have been observed in psychiatric disorders. PMID:21152090
Association of polyaminergic loci with anxiety, mood disorders, and attempted suicide.
Fiori, Laura M; Wanner, Brigitte; Jomphe, Valérie; Croteau, Jordie; Vitaro, Frank; Tremblay, Richard E; Bureau, Alexandre; Turecki, Gustavo
2010-11-30
The polyamine system has been implicated in a number of psychiatric conditions, which display both alterations in polyamine levels and altered expression of genes related to polyamine metabolism. Studies have identified associations between genetic variants in spermidine/spermine N1-acetyltransferase (SAT1) and both anxiety and suicide, and several polymorphisms appear to play important roles in determining gene expression. We genotyped 63 polymorphisms, spread across four polyaminergic genes (SAT1, spermine synthase (SMS), spermine oxidase (SMOX), and ornithine aminotransferase like-1 (OATL1)), in 1255 French-Canadian individuals who have been followed longitudinally for 22 years. We assessed univariate associations with anxiety, mood disorders, and attempted suicide, as assessed during early adulthood. We also investigated the involvement of gene-environment interactions in terms of childhood abuse, and assessed internalizing and externalizing symptoms as endophenotypes mediating these interactions. Overall, each gene was associated with at least one main outcome: anxiety (SAT1, SMS), mood disorders (SAT1, SMOX), and suicide attempts (SAT1, OATL1). Several SAT1 polymorphisms displayed disease-specific risk alleles, and polymorphisms in this gene were involved in gene-gene interactions with SMS to confer risk for anxiety disorders, as well as gene-environment interactions between childhood physical abuse and mood disorders. Externalizing behaviors demonstrated significant mediation with regards to the association between OATL1 and attempted suicide, however there was no evidence that externalizing or internalizing behaviors were appropriate endophenotypes to explain the associations with mood or anxiety disorders. Finally, childhood sexual abuse did not demonstrate mediating influences on any of our outcomes. These results demonstrate that genetic variants in polyaminergic genes are associated with psychiatric conditions, each of which involves a set of separate and distinct risk alleles. As several of these polymorphisms are associated with gene expression, these findings may provide mechanisms to explain the alterations in polyamine metabolism which have been observed in psychiatric disorders.
Autism risk factors: genes, environment, and gene-environment interactions
Chaste, Pauline; Leboyer, Marion
2012-01-01
The aim of this review is to summarize the key findings from genetic and epidemiological research, which show that autism is a complex disorder resulting from the combination of genetic and environmental factors. Remarkable advances in the knowledge of genetic causes of autism have resulted from the great efforts made in the field of genetics. The identification of specific alleles contributing to the autism spectrum has supplied important pieces for the autism puzzle. However, many questions remain unanswered, and new questions are raised by recent results. Moreover, given the amount of evidence supporting a significant contribution of environmental factors to autism risk, it is now clear that the search for environmental factors should be reinforced. One aspect of this search that has been neglected so far is the study of interactions between genes and environmental factors. PMID:23226953
Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G
2017-08-01
Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.
GENE-ENVIRONMENT INTERACTIONS: A REVIEW OF EFFECTS ON REPRODUCTION AND DEVELOPMENT
Polymorphisms in genes can lead to differences in the level of susceptibility of individuals to potentially adverse effects of environmental influences, such as chemical exposure, on prenatal development or male or female reproductive function. We have reviewed the literature in ...
Seminar: Developmental Dyslexia
Peterson, Robin L.; Pennington, Bruce F.
2012-01-01
Summary Dyslexia is a neurodevelopmental disorder that is characterized by slow and inaccurate word recognition. Dyslexia has been found in every culture studied, and mounting evidence underscores cross-linguistic similarity in its neurobiological and neurocognitive bases. There has been considerable progress across levels of analysis in the last five years. At a neuropsychological level, the phonological theory remains the most compelling, though it is increasingly clear that phonological problems interact with other cognitive risk factors. At a neurobiological level, recent research confirms that dyslexia is characterized by dysfunction of the normal left hemisphere language network and also implicates abnormal white matter development. Studies accounting for reading experience demonstrate that many observed neural differences reflect causes rather than effects of dyslexia. At an etiologic risk level, six candidate genes have been identified, and there is evidence for gene by environment interaction. This review includes a focus on these and other recent developments. PMID:22513218
Côté, Guillaume; Perry, Guy; Blier, Pierre; Bernatchez, Louis
2007-01-01
Background Quantitative reaction norm theory proposes that genotype-by-environment interaction (GxE) results from inter-individual differences of expression in adaptive suites of genes in distinct environments. However, environmental norms for actual gene suites are poorly documented. In this study, we investigated the effects of GxE interactions on levels of gene transcription and growth by documenting the impact of rearing environment (freshwater vs. saltwater), sex and genotypic (low vs. high estimated breeding value EBV) effects on the transcription level of insulin-like growth factor (IGF-1) and growth hormone receptor (GHR) in brook charr (Salvelinus fontinalis). Results Males grew faster than females (μ♀ = 1.20 ± 0.07 g·d-1, μ♂ = 1.46 ± 0.06 g·d-1) and high-EBV fish faster than low-EBV fish (μLOW = 0.97 ± 0.05 g·d-1, μHIGH = 1.58 ± 0.07 g·d-1; p < 0.05). However, growth was markedly lower in saltwater-reared fish than freshwater sibs (μFW = 1.52 ± 0.07 g·d-1, μSW = 1.15 ± 0.06 g·d-1), yet GHR mRNA transcription level was significantly higher in saltwater than in freshwater (μSW = 0.85 ± 0.05, μFW = 0.61 ± 0.05). The ratio of actual growth to units in assayed mRNA ('individual transcript efficiency', iTE; g·d-1·u-1) also differed among EBV groups (μLOW = 2.0 ± 0.24 g·d-1·u-1; μHIGH = 3.7 ± 0.24 g·d-1·u-1) and environments (μSW = 2.0 ± 0.25 g·d-1·u-1; μFW = 3.7 ± 0.25 g·d-1·u-1) for GHR. Males had a lower iTE for GHR than females (μ♂ = 2.4 ± 0.29 g·d-1·u-1; μ♀ = 3.1 ± 0.23 g·d-1·u-1). There was no difference in IGF-1 transcription level between environments (p > 0.7) or EBV groups (p > 0.15) but the level of IGF-1 was four times higher in males than females (μ♂ = 2.4 ± 0.11, μ♀ = 0.58 ± 0.09; p < 0.0001). We detected significant sexual differences in iTE (μ♂ = 1.3 ± 0.59 g·d-1·u-1; μ♀ = 3.9 ± 0.47 g·d-1·u-1), salinities (μSW = 2.3 ± 0.52 g·d-1·u-1; μFW = 3.7 ± 0.53 g·d-1·u-1) and EBV-groups (μLOW = 2.4 ± 0.49 g·d-1·u-1; μHIGH = 3.8 ± 0.49 g·d-1·u-1). Interaction between EBV-group and environment was detected for both GHR (p = 0.027) and IGF-1 (p = 0.019), and for iTE in the two genes (p < 0.0001; p < 0.05, respectively), where increased divergence in levels of GHR and IGF-1 transcription occurred among EBV-groups in the saltwater environment. Conclusion Our results show that both environment and sex have major impacts on the expression of mRNA for two key genes involved in the physiological pathway for growth. We also demonstrate for the first time, at least in fish, genotype-by-environment interaction at the level of individual gene transcription. This work contributes significantly to ongoing efforts towards documenting environmentally and sexually induced variance of gene activity and understanding the resulting phenotypes. PMID:18154679
Leveraging Gene-Environment Interactions and Endotypes for Asthma Gene Discovery
Bønnelykke, Klaus; Ober, Carole
2016-01-01
Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs and the advantages of studying responses to asthma-associated exposures in clinical birth cohorts, as well as in cell models of GEIs, to dissect the context-specific nature of genotypic risks, to prioritize variants in genome-wide association studies, and to identify pathways involved in pathogenesis in subgroups of patients. We propose that such approaches, in spite of their many challenges, present great opportunities for better understanding of asthma pathogenesis and heterogeneity and, ultimately, for improving prevention and treatment of disease. PMID:26947980
Cicchetti, Dante; Rogosch, Fred A; Hecht, Kathryn F; Crick, Nicki R; Hetzel, Susan
2014-08-01
In this investigation, gene-environment-gender interaction effects in predicting child borderline personality disorder symptomatology among maltreated and nonmaltreated low-income children (N = 1,051) were examined. In the context of a summer research camp, adult-, peer-, and self-report assessments of borderline precursor indicators were obtained, as well as child self-report on the Borderline Personality Features Scale for Children. Genetic variants of the oxytocin receptor genotype and the FK506 binding protein 5 gene CATT haplotype were investigated. Children who self-reported high levels of borderline personality symptomatology were differentiated by adults, peers, and additional self-report on indicators of emotional instability, conflictual relationships with peers and adults, preoccupied attachment, and indicators of self-harm and suicidal ideation. Maltreated children also were more likely to evince many of these difficulties relative to nonmaltreated children. A series of analyses of covariance, controlling for age and ancestrally informative markers, indicated significant Maltreatment × Gene × Gender three-way interactions. Consideration of the maltreatment parameters of subtype, onset, and recency expanded understanding of variation among maltreated children. The three-way interaction effects demonstrated differential patterns among girls and boys. Among girls, the gene-environment interaction was more consistent with a diathesis-stress model, whereas among boys a differential-sensitivity interaction effect was indicated. Moreover, the genetic variants associated with greater risk for higher borderline symptomatology, dependent on maltreatment experiences, were opposite in girls compared to boys. The findings have important implications for understanding variability in early predictors of borderline personality pathology.
Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2.
Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina F; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S; Ritz, Beate
2016-01-01
Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine; thus, gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. In a population-based case-control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and gender-matched controls), we assessed interactions between lifetime coffee consumption and 3 polymorphisms in ADORA2A and CYP1A2 for all subjects, and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction = 0.66 [95% CI 0.46-0.94], p = 0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enroll prevalent PD cases. © 2017 S. Karger AG, Basel.
Population genetic approaches to neurological disease: Parkinson's disease as an example
Gandhi, S; Abou-Sleiman, P.M; Healy, D.G; Weale, M; Gilks, W; Ahmadi, K; Goldstein, D.B; Wood, N.W
2005-01-01
Parkinson's disease (PD) is a common, progressive, incurable disabling condition. The cause is unknown but over the past few years tremendous progress in our understanding of the genetic bases of this condition has been made. To date, this has almost exclusively come from the study of relatively rare Mendelian forms of the disease and there are no currently, widely accepted common variants known to increase susceptibility. The role that the ‘Mendelian’ genes play in common sporadic forms of PD is unknown. Moreover, most studies in PD can really be described as candidate polymorphism studies rather than true and complete assessments of the genes themselves. We provide a model of how one might tackle some of these issues using Parkinson's disease as an illustration. One of the emerging hypotheses of gene environment interaction in Parkinson's disease is based on drug metabolizing (or xenobiotic) enzymes and their interaction with putative environmental toxins. This motivated us to describe a tagging approach for an extensive but not exhaustive list of 55 drug metabolizing enzyme genes. We use these data to illustrate the power, and some of the limitations of a haplotype tagging approach. We show that haplotype tagging is extremely efficient and works well with only a modest increase in effort through different populations. The tagging approach works much less well if the minor allele frequency is below 5%. However, it will now be possible using these tags to evaluate these genes comprehensively in PD and other neurodegenerative conditions. PMID:16096106
Population genetic approaches to neurological disease: Parkinson's disease as an example.
Gandhi, S; Abou-Sleiman, P M; Healy, D G; Weale, M; Gilks, W; Ahmadi, K; Goldstein, D B; Wood, N W
2005-08-29
Parkinson's disease (PD) is a common, progressive, incurable disabling condition. The cause is unknown but over the past few years tremendous progress in our understanding of the genetic bases of this condition has been made. To date, this has almost exclusively come from the study of relatively rare Mendelian forms of the disease and there are no currently, widely accepted common variants known to increase susceptibility. The role that the "Mendelian" genes play in common sporadic forms of PD is unknown. Moreover, most studies in PD can really be described as candidate polymorphism studies rather than true and complete assessments of the genes themselves. We provide a model of how one might tackle some of these issues using Parkinson's disease as an illustration. One of the emerging hypotheses of gene environment interaction in Parkinson's disease is based on drug metabolizing (or xenobiotic) enzymes and their interaction with putative environmental toxins. This motivated us to describe a tagging approach for an extensive but not exhaustive list of 55 drug metabolizing enzyme genes. We use these data to illustrate the power, and some of the limitations of a haplotype tagging approach. We show that haplotype tagging is extremely efficient and works well with only a modest increase in effort through different populations. The tagging approach works much less well if the minor allele frequency is below 5%. However, it will now be possible using these tags to evaluate these genes comprehensively in PD and other neurodegenerative conditions.
Gene-environment interactions in geriatric depression.
Lotrich, Francis E
2011-06-01
In older adults, several environmental challenges can potentially trigger the onset of an episode of major depression. Vulnerability to these challenges can be influenced by genetics. There is accumulating evidence for an interaction between stress and a serotonin transporter polymorphism, though there is also heterogeneity among studies. Other relevant genes include those encoding for the neuroendocrine stress axis, growth factors, and other monoaminergic systems. Each of these may interact with either predisposing traumas in early childhood or precipitating events later in life. Copyright © 2011 Elsevier Inc. All rights reserved.
Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George
2017-01-01
Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.
Comasco, Erika; Hodgins, Sheilagh; Oreland, Lars; Åslund, Cecilia
2015-01-01
Background: Previous evidence of gene-by-environment interactions associated with emotional and behavioral disorders is contradictory. Differences in findings may result from variation in valence and dose of the environmental factor, and/or failure to take account of gene-by-gene interactions. The present study investigated interactions between the brain-derived neurotrophic factor gene (BDNF Val66Met), the serotonin transporter gene-linked polymorphic region (5-HTTLPR), the monoamine oxidase A (MAOA-uVNTR) polymorphisms, family conflict, sexual abuse, the quality of the child-parent relationship, and teenage delinquency. Methods: In 2006, as part of the Survey of Adolescent Life in Västmanland, Sweden, 1 337 high-school students, aged 17–18 years, anonymously completed questionnaires and provided saliva samples for DNA analyses. Results: Teenage delinquency was associated with two-, three-, and four-way interactions of each of the genotypes and the three environmental factors. Significant four-way interactions were found for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × family conflicts and for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × sexual abuse. Further, the two genotype combinations that differed the most in expression levels (BDNF Val66Met Val, 5-HTTLPR LL, MAOA-uVNTR LL [girls] and L [boys] vs BDNF Val66Met Val/Met, 5-HTTLPR S/LS, MAOA-uVNTR S/SS/LS) in interaction with family conflict and sexual abuse were associated with the highest delinquency scores. The genetic variants previously shown to confer vulnerability for delinquency (BDNF Val66Met Val/Met × 5-HTTLPR S × MAOA-uVNTR S) were associated with the lowest delinquency scores in interaction with a positive child-parent relationship. Conclusions: Functional variants of the MAOA-uVNTR, 5-HTTLPR, and BDNF Val66Met, either alone or in interaction with each other, may be best conceptualized as modifying sensitivity to environmental factors that confer either risk or protection for teenage delinquency. PMID:25522433
Brody, Gene H.; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M.; Evans, Gary W.; Windle, Michael; Gerrard, Meg; Gibbons, Frederick X.; Simons, Ronald L.; Philibert, Robert A.
2012-01-01
The purpose of this study was to investigate interactions between exposure to supportive family environments and genetic characteristics, which were hypothesized to forecast variations in allostatic load (AL) in a representative sample of 315 rural African American youths. Data on family environments were gathered when youths were 11–13, and genetic data were collected when they were 16, years of age. Data on AL were obtained at the beginning of emerging adulthood, age 19 years. The data analyses revealed that, as predicted, emerging adults exposed to less supportive family environments across preadolescence manifested higher levels of AL when they carried the short (s) allele at the 5-HTTLPR and an allele of DRD4 with 7 or more repeats. This is an E(family environment) × G(5-HTTLPR status) × G(DRD4 status) interaction. These data suggest that African American youths carrying genes that confer sensitivity who are exposed to less supportive family environments may be at greater risk for adverse physical health consequences that AL presages. PMID:22468688
Gene-environment interplay in the etiology of psychosis.
Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf
2018-01-15
Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.
Guilarte, Tomás R.; Opler, Mark; Pletnikov, Mikhail
2013-01-01
Schizophrenia is a devastating neuropsychiatric disorder of unknown etiology. There is general agreement in the scientific community that schizophrenia is a disorder of neurodevelopmental origin in which both genes and environmental factors come together to produce a schizophrenia phenotype later in life. The challenging questions have been which genes and what environmental factors? Although there is evidence that different chromosome loci and several genes impart susceptibility for schizophrenia; and epidemiological studies point to broad aspects of the environment, only recently there has been an interest in studying gene × environment interactions. Recent evidence of a potential association between prenatal lead (Pb2+) exposure and schizophrenia precipitated the search for plausible neurobiological connections. The most promising connection is that in schizophrenia and in developmental Pb2+ exposure there is strong evidence for hypoactivity of the N-methyl-d-aspartate (NMDA) subtype of excitatory amino acid receptors as an underlying neurobiological mechanism in both conditions. A hypofunction of the NMDA receptor (NMDAR) complex during critical periods of development may alter neurobiological processes that are essential for brain growth and wiring, synaptic plasticity and cognitive and behavioral outcomes associated with schizophrenia. We also describe on-going proof of concept gene-environment interaction studies of early life Pb2+ exposure in mice expressing the human mutant form of the disrupted in schizophrenia 1 (DISC-1) gene, a gene that is strongly associated with schizophrenia and allied mental disorders. PMID:22178136
Koneva, L A; Vyas, A K; McEachin, R C; Puttabyatappa, M; Wang, H-S; Sartor, M A; Padmanabhan, V
2017-01-01
Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85-141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. Environ. Mol. Mutagen. 58:4-18, 2017. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Environmental and gene-environment interactions and risk of rheumatoid arthritis
Karlson, Elizabeth W.; Deane, Kevin
2012-01-01
Multiple environmental factors including hormones, dietary factors, infections and exposure to tobacco smoke as well as gene-environment interactions have been associated with increased risk for rheumatoid arthritis (RA). Importantly, the growing understanding of the prolonged period prior to the first onset of symptoms of RA suggests that these environmental and genetic factors are likely acting to drive the development of RA-related autoimmunity long before the appearance of the first joint symptoms and clinical findings that are characteristic of RA. Herein we will review these factors and interactions, especially those that have been investigated in a prospective fashion prior to the symptomatic onset of RA. We will also discuss how these factors may be explored in future study to further the understanding of the pathogenesis of RA, and ultimately perhaps develop preventive measures for this disease. PMID:22819092
Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong
2013-01-01
For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809
Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong
2013-01-01
For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.
P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.
Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D
2017-11-01
P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.
Darling, Katherine Weatherford; Ackerman, Sara L; Hiatt, Robert H; Lee, Sandra Soo-Jin; Shim, Janet K
2016-04-01
Despite a proclaimed shift from 'nature versus nurture' to 'genes and environment' paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does 'the environment' mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers' expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to 'go into the body' and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. Copyright © 2016 Elsevier Ltd. All rights reserved.
Genomic features of bacterial adaptation to plants
Levy, Asaf; Gonzalez, Isai Salas; Mittelviefhaus, Maximilian; Clingenpeel, Scott; Paredes, Sur Herrera; Miao, Jiamin; Wang, Kunru; Devescovi, Giulia; Stillman, Kyra; Monteiro, Freddy; Alvarez, Bryan Rangel; Lundberg, Derek S.; Lu, Tse-Yuan; Lebeis, Sarah; Jin, Zhao; McDonald, Meredith; Klein, Andrew P.; Feltcher, Meghan E.; del Rio, Tijana Glavina; Grant, Sarah R.; Doty, Sharon L.; Ley, Ruth E.; Zhao, Bingyu; Venturi, Vittorio; Pelletier, Dale A.; Vorholt, Julia A.; Tringe, Susannah G.; Woyke, Tanja; Dangl, Jeffery L.
2017-01-01
Plants intimately associate with diverse bacteria. Plant-associated (PA) bacteria have ostensibly evolved genes enabling adaptation to the plant environment. However, the identities of such genes are mostly unknown and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3837 bacterial genomes to identify thousands of PA gene clusters. Genomes of PA bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant associated genomes. We experimentally validated candidates from two sets of PA genes, one involved in plant colonization, the other serving in microbe-microbe competition between PA bacteria. We also identified 64 PA protein domains that potentially mimic plant domains; some are shared with PA fungi and oomycetes. This work expands the genome-based understanding of plant-microbe interactions and provides leads for efficient and sustainable agriculture through microbiome engineering. PMID:29255260
Epigenetic switch from repressive to permissive chromatin in response to cold stress.
Park, Junghoon; Lim, Chae Jin; Shen, Mingzhe; Park, Hee Jin; Cha, Joon-Yung; Iniesto, Elisa; Rubio, Vicente; Mengiste, Tesfaye; Zhu, Jian-Kang; Bressan, Ray A; Lee, Sang Yeol; Lee, Byeong-Ha; Jin, Jing Bo; Pardo, Jose M; Kim, Woe-Yeon; Yun, Dae-Jin
2018-06-05
Switching from repressed to active status in chromatin regulation is part of the critical responses that plants deploy to survive in an ever-changing environment. We previously reported that HOS15, a WD40-repeat protein, is involved in histone deacetylation and cold tolerance in Arabidopsis However, it remained unknown how HOS15 regulates cold responsive genes to affect cold tolerance. Here, we show that HOS15 interacts with histone deacetylase 2C (HD2C) and both proteins together associate with the promoters of cold-responsive COR genes, COR15A and COR47 Cold induced HD2C degradation is mediated by the CULLIN4 (CUL4)-based E3 ubiquitin ligase complex in which HOS15 acts as a substrate receptor. Interference with the association of HD2C and the COR gene promoters by HOS15 correlates with increased acetylation levels of histone H3. HOS15 also interacts with CBF transcription factors to modulate cold-induced binding to the COR gene promoters. Our results here demonstrate that cold induces HOS15-mediated chromatin modifications by degrading HD2C. This switches the chromatin structure status and facilitates recruitment of CBFs to the COR gene promoters. This is an apparent requirement to acquire cold tolerance. Copyright © 2018 the Author(s). Published by PNAS.
Epigenetic switch from repressive to permissive chromatin in response to cold stress
Park, Junghoon; Lim, Chae Jin; Shen, Mingzhe; Park, Hee Jin; Cha, Joon-Yung; Iniesto, Elisa; Rubio, Vicente; Mengiste, Tesfaye; Bressan, Ray A.; Lee, Sang Yeol; Lee, Byeong-ha; Kim, Woe-Yeon; Yun, Dae-Jin
2018-01-01
Switching from repressed to active status in chromatin regulation is part of the critical responses that plants deploy to survive in an ever-changing environment. We previously reported that HOS15, a WD40-repeat protein, is involved in histone deacetylation and cold tolerance in Arabidopsis. However, it remained unknown how HOS15 regulates cold responsive genes to affect cold tolerance. Here, we show that HOS15 interacts with histone deacetylase 2C (HD2C) and both proteins together associate with the promoters of cold-responsive COR genes, COR15A and COR47. Cold induced HD2C degradation is mediated by the CULLIN4 (CUL4)-based E3 ubiquitin ligase complex in which HOS15 acts as a substrate receptor. Interference with the association of HD2C and the COR gene promoters by HOS15 correlates with increased acetylation levels of histone H3. HOS15 also interacts with CBF transcription factors to modulate cold-induced binding to the COR gene promoters. Our results here demonstrate that cold induces HOS15-mediated chromatin modifications by degrading HD2C. This switches the chromatin structure status and facilitates recruitment of CBFs to the COR gene promoters. This is an apparent requirement to acquire cold tolerance. PMID:29784800
“Real time” genetic manipulation: a new tool for ecological field studies
Schäfer, Martin; Brütting, Christoph; Gase, Klaus; Reichelt, Michael; Baldwin, Ian; Meldau, Stefan
2014-01-01
Summary Field experiments with transgenic plants often reveal the functional significance of genetic traits important for plant performance in their natural environments. Until now, only constitutive overexpression, ectopic expression and gene silencing methods have been used to analyze gene-related phenotypes in natural habitats. These methods do not allow sufficient control over gene expression to study ecological interactions in real-time, genetic traits playing essential roles in development, or dose-dependent effects. We applied the sensitive dexamethasone (DEX)-inducible pOp6/LhGR expression system to the ecological model plant Nicotiana attenuata and established a lanolin-based DEX application method to facilitate ectopic gene expression and RNAi mediated gene silencing in the field and under challenging conditions (e.g. high temperature, wind and UV radiation). Fully established field-grown plants were used to silence phytoene desaturase and thereby cause photobleaching only in specific plant sectors, and to activate expression of the cytokinin (CK) biosynthesis gene isopentenyl transferase (ipt). We used ipt expression to analyze the role of CK’s in both the glasshouse and field to understand resistance to the native herbivore Tupiocoris notatus, which attack plants at small spatial scales. By spatially restricting ipt expression and elevating CK levels in single leaves, T. notatus damage increased, demonstrating CK’s role in this plant-herbivore interaction at a small scale. As the arena of most ecological interactions is highly constrained in time and space, these tools will advance the genetic analysis of dynamic traits that matter for plant performance in nature. PMID:23906159
Matosin, Natalie; Halldorsdottir, Thorhildur; Binder, Elisabeth B
2018-05-15
Epidemiologic and genetic studies suggest common environmental and genetic risk factors for a number of psychiatric disorders, including depression, bipolar disorder, and schizophrenia. Genetic and environmental factors, especially adverse life events, not only have main effects on disease development but also may interact to shape risk and resilience. Such gene by adversity interactions have been described for FKBP5, an endogenous regulator of the stress-neuroendocrine system, conferring risk for a number of psychiatric disorders. In this review, we present a molecular and cellular model of the consequences of FKBP5 by early adversity interactions. We illustrate how altered genetic and epigenetic regulation of FKBP5 may contribute to disease risk by covering evidence from clinical and preclinical studies of FKBP5 dysregulation, known cell-type and tissue-type expression patterns of FKBP5 in humans and animals, and the role of FKBP5 as a stress-responsive molecular hub modulating many cellular pathways. FKBP5 presents the possibility to better understand the molecular and cellular factors contributing to a disease-relevant gene by environment interaction, with implications for the development of biomarkers and interventions for psychiatric disorders. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Lu, Yuan; Klimovich, Charlotte M; Robeson, Kalen Z; Boswell, William; Ríos-Cardenas, Oscar; Walter, Ronald B; Morris, Molly R
2017-01-01
Nutritional programming takes place in early development. Variation in the quality and/or quantity of nutrients in early development can influence long-term health and viability. However, little is known about the mechanisms of nutritional programming. The live-bearing fish Xiphophorus multilineatus has the potential to be a new model for understanding these mechanisms, given prior evidence of nutritional programming influencing behavior and juvenile growth rate. We tested the hypotheses that nutritional programming would influence behaviors involved in energy homeostasis as well gene expression in X. multilineatus. We first examined the influence of both juvenile environment (varied in nutrition and density) and adult environment (varied in nutrition) on behaviors involved in energy acquisition and energy expenditure in adult male X. multilineatus . We also compared the behavioral responses across the genetically influenced size classes of males. Males stop growing at sexual maturity, and the size classes of can be identified based on phenotypes (adult size and pigment patterns). To study the molecular signatures of nutritional programming, we assembled a de novo transcriptome for X. multilineatus using RNA from brain, liver, skin, testis and gonad tissues, and used RNA-Seq to profile gene expression in the brains of males reared in low quality (reduced food, increased density) and high quality (increased food, decreased density) juvenile environments. We found that both the juvenile and adult environments influenced the energy intake behavior, while only the adult environment influenced energy expenditure. In addition, there were significant interactions between the genetically influenced size classes and the environments that influenced energy intake and energy expenditure, with males from one of the four size classes (Y-II) responding in the opposite direction as compared to the other males examined. When we compared the brains of males of the Y-II size class reared in a low quality juvenile environment to males from the same size class reared in high quality juvenile environment, 131 genes were differentially expressed, including metabolism and appetite master regulator agrp gene. Our study provides evidence for nutritional programming in X. multilineatus , with variation across size classes of males in how juvenile environment and adult diet influences behaviors involved in energy homeostasis. In addition, we provide the first transcriptome of X. multilineatus , and identify a group of candidate genes involved in nutritional programming.
Computational identification of gene–social environment interaction at the human IL6 locus
Cole, Steven W.; Arevalo, Jesusa M. G.; Takahashi, Rie; Sloan, Erica K.; Lutgendorf, Susan K.; Sood, Anil K.; Sheridan, John F.; Seeman, Teresa E.
2010-01-01
To identify genetic factors that interact with social environments to impact human health, we used a bioinformatic strategy that couples expression array–based detection of environmentally responsive transcription factors with in silico discovery of regulatory polymorphisms to predict genetic loci that modulate transcriptional responses to stressful environments. Tests of one predicted interaction locus in the human IL6 promoter (SNP rs1800795) verified that it modulates transcriptional response to β-adrenergic activation of the GATA1 transcription factor in vitro. In vivo validation studies confirmed links between adverse social conditions and increased transcription of GATA1 target genes in primary neural, immune, and cancer cells. Epidemiologic analyses verified the health significance of those molecular interactions by documenting increased 10-year mortality risk associated with late-life depressive symptoms that occurred solely for homozygous carriers of the GATA1-sensitive G allele of rs1800795. Gating of depression-related mortality risk by IL6 genotype pertained only to inflammation-related causes of death and was associated with increased chronic inflammation as indexed by plasma C-reactive protein. Computational modeling of molecular interactions, in vitro biochemical analyses, in vivo animal modeling, and human molecular epidemiologic analyses thus converge in identifying β-adrenergic activation of GATA1 as a molecular pathway by which social adversity can alter human health risk selectively depending on individual genetic status at the IL6 locus. PMID:20176930
Harden, K. Paige; Mendle, Jane
2014-01-01
Early pubertal timing places girls at elevated risk for a breadth of negative outcomes, including involvement in delinquent behavior. While previous developmental research has emphasized the unique social challenges faced by early maturing girls, this relation is complicated by genetic influences for both delinquent behavior and pubertal timing, which are seldom controlled for in existing research. The current study uses genetically informed data on 924 female-female twin and sibling pairs drawn from the National Longitudinal Study of Adolescent Health to (1) disentangle biological versus environmental mechanisms for the effects of early pubertal timing and (2) test for gene-environment interactions. Results indicate that early pubertal timing influences girls’ delinquency through a complex interplay between biological risk and environmental experiences. Genes related to earlier age at menarche and higher perceived development significantly predict increased involvement in both non-violent and violent delinquency. Moreover, after accounting for this genetic association between pubertal timing and delinquency, the impact of non-shared environmental influences on delinquency are significantly moderated by pubertal timing, such that the non-shared environment is most important among early maturing girls. This interaction effect is particularly evident for non-violent delinquency. Overall, results suggest early maturing girls are vulnerable to an interaction between genetic and environmental risks for delinquent behavior. PMID:21668078
Grazioplene, Rachael G; Deyoung, Colin G; Rogosch, Fred A; Cicchetti, Dante
2013-08-01
The differential susceptibility hypothesis states that some genetic variants that confer risk in adverse environments are beneficial in normal or nurturing environments. The cholinergic system is promising as a source of susceptibility genes because of its involvement in learning and neural plasticity. The cholinergic receptor gene CHRNA4 has been linked to characteristics related to the personality traits Neuroticism and Openness/Intellect. The effects of interaction between CHRNA4 genotype and maltreatment status on child personality were examined in a well matched sample of 339 maltreated and 275 non-maltreated children (aged 8-13 years). Variation in CHRNA4 interacted with childhood maltreatment to predict personality in a manner indicating differential susceptibility. The interaction of CHRNA4 and maltreatment status predicted Neuroticism and Openness/Intellect. Maltreated children with the rs1044396 T/T genotype scored highest on Neuroticism and showed no effect of genotype on Openness/Intellect. Non-maltreated children with this genotype scored lowest on Neuroticism and highest on Openness/Intellect. Variation in CHRNA4 appears to contribute to personality by affecting degree of developmental sensitivity to both normal and adverse environments. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.
Spires, Tara L; Hannan, Anthony J
2005-05-01
Neurodegenerative disorders, such as Huntington's, Alzheimer's, and Parkinson's diseases, affect millions of people worldwide and currently there are few effective treatments and no cures for these diseases. Transgenic mice expressing human transgenes for huntingtin, amyloid precursor protein, and other genes associated with familial forms of neurodegenerative disease in humans provide remarkable tools for studying neurodegeneration because they mimic many of the pathological and behavioural features of the human conditions. One of the recurring themes revealed by these various transgenic models is that different diseases may share similar molecular and cellular mechanisms of pathogenesis. Cellular mechanisms known to be disrupted at early stages in multiple neurodegenerative disorders include gene expression, protein interactions (manifesting as pathological protein aggregation and disrupted signaling), synaptic function and plasticity. Recent work in mouse models of Huntington's disease has shown that enriching the environment of transgenic animals delays the onset and slows the progression of Huntington's disease-associated motor and cognitive symptoms. Environmental enrichment is known to induce various molecular and cellular changes in specific brain regions of wild-type animals, including altered gene expression profiles, enhanced neurogenesis and synaptic plasticity. The promising effects of environmental stimulation, demonstrated recently in models of neurodegenerative disease, suggest that therapy based on the principles of environmental enrichment might benefit disease sufferers and provide insight into possible mechanisms of neurodegeneration and subsequent identification of novel therapeutic targets. Here, we review the studies of environmental enrichment relevant to some major neurodegenerative diseases and discuss their research and clinical implications.
Reynolds, Chandra A; Gatz, Margaret; Christensen, Kaare; Christiansen, Lene; Dahl Aslan, Anna K; Kaprio, Jaakko; Korhonen, Tellervo; Kremen, William S; Krueger, Robert; McGue, Matt; Neiderhiser, Jenae M; Pedersen, Nancy L
2016-01-01
Despite emerging interest in gene-environment interaction (GxE) effects, there is a dearth of studies evaluating its potential relevance apart from specific hypothesized environments and biometrical variance trends. Using a monozygotic within-pair approach, we evaluated evidence of G×E for body mass index (BMI), depressive symptoms, and cognition (verbal, spatial, attention, working memory, perceptual speed) in twin studies from four countries. We also evaluated whether APOE is a 'variability gene' across these measures and whether it partly represents the 'G' in G×E effects. In all three domains, G×E effects were pervasive across country and gender, with small-to-moderate effects. Age-cohort trends were generally stable for BMI and depressive symptoms; however, they were variable-with both increasing and decreasing age-cohort trends-for different cognitive measures. Results also suggested that APOE may represent a 'variability gene' for depressive symptoms and spatial reasoning, but not for BMI or other cognitive measures. Hence, additional genes are salient beyond APOE.
Rajangam, Thanavel; An, Seong Soo A
2013-01-01
Over the past two decades, many types of natural and synthetic polymer-based micro- and nanocarriers, with exciting properties and applications, have been developed for application in various types of tissue regeneration, including bone, cartilage, nerve, blood vessels, and skin. The development of suitable polymers scaffold designs to aid the repair of specific cell types have created diverse and important potentials in tissue restoration. Fibrinogen (Fbg)- and fibrin (Fbn)-based micro- and nanostructures can provide suitable natural matrix environments. Since these primary materials are abundantly available in blood as the main coagulation proteins, they can easily interact with damaged tissues and cells through native biochemical interactions. Fbg- and Fbn-based micro and nanostructures can also be consecutively furnished/or encapsulated and specifically delivered, with multiple growth factors, proteins, and stem cells, in structures designed to aid in specific phases of the tissue regeneration process. The present review has been carried out to demonstrate the progress made with micro and nanoscaffold applications and features a number of applications of Fbg- and Fbn-based carriers in the field of biomaterials, including the delivery of drugs, active biomolecules, cells, and genes, that have been effectively used in tissue engineering and regenerative medicine. PMID:24106425
The Dopamine Receptor D4 Gene ("DRD4") Moderates Family Environmental Effects on ADHD
ERIC Educational Resources Information Center
Martel, Michelle M.; Nikolas, Molly; Jernigan, Katherine; Friderici, Karen; Waldman, Irwin; Nigg, Joel T.
2011-01-01
Attention-Deficit/Hyperactivity Disorder (ADHD) is a prime candidate for exploration of gene-by-environment interaction (i.e., G x E), particularly in relation to dopamine system genes, due to strong evidence that dopamine systems are dysregulated in the disorder. Using a G x E design, we examined whether the "DRD4" promoter 120-bp tandem repeat…
Heterogeneous computing architecture for fast detection of SNP-SNP interactions.
Sluga, Davor; Curk, Tomaz; Zupan, Blaz; Lotric, Uros
2014-06-25
The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems.
Heterogeneous computing architecture for fast detection of SNP-SNP interactions
2014-01-01
Background The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. Results We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. Conclusions General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems. PMID:24964802
Life Events, Genetic Susceptibility, and Smoking among Adolescents
Pampel, Fred C.; Boardman, Jason D.; Daw, Jonathan; Stallings, Michael C.; Smolen, Andrew; Haberstick, Brett; Widaman, Keith F.; Neppl, Tricia K.; Conger, Rand D.
2015-01-01
Although stressful life events during adolescence are associated with the adoption of unhealthy behaviors such as smoking, both social circumstances and physical traits can moderate the relationship. This study builds on the stress paradigm and gene-environment approach to social behavior by examining how a polymorphism in the serotonin transporter gene 5-HTTLPR moderates the effect of life events on adolescent smoking. Tests of interaction hypotheses use data from the Family Transitions Project, a longitudinal study of 7th graders followed for 5 years. A sibling-pair design with separate models for the gender composition of pairs (brothers, sisters, or brother/sister) controls for unmeasured family background. The results show that negative life events are significantly and positively associated with smoking. Among brother pairs but not other pairs, the results provide evidence of gene-environment interaction by showing that life events more strongly influence smoking behavior for those with more copies of the 5-HTTLPR S allele. PMID:26463545
Defining a genetic ideotype for crop improvement.
Trethowan, Richard M
2014-01-01
While plant breeders traditionally base selection on phenotype, the development of genetic ideotypes can help focus the selection process. This chapter provides a road map for the establishment of a refined genetic ideotype. The first step is an accurate definition of the target environment including the underlying constraints, their probability of occurrence, and impact on phenotype. Once the environmental constraints are established, the wealth of information on plant physiological responses to stresses, known gene information, and knowledge of genotype ×environment and gene × environment interaction help refine the target ideotype and form a basis for cross prediction.Once a genetic ideotype is defined the challenge remains to build the ideotype in a plant breeding program. A number of strategies including marker-assisted recurrent selection and genomic selection can be used that also provide valuable information for the optimization of genetic ideotype. However, the informatics required to underpin the realization of the genetic ideotype then becomes crucial. The reduced cost of genotyping and the need to combine pedigree, phenotypic, and genetic data in a structured way for analysis and interpretation often become the rate-limiting steps, thus reducing genetic gain. Systems for managing these data and an example of ideotype construction for a defined environment type are discussed.
Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A
2016-10-13
The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.
Cortico-limbic connectivity in MAOA-L carriers is vulnerable to acute tryptophan depletion.
Eisner, Patrick; Klasen, Martin; Wolf, Dhana; Zerres, Klaus; Eggermann, Thomas; Eisert, Albrecht; Zvyagintsev, Mikhail; Sarkheil, Pegah; Mathiak, Krystyna A; Zepf, Florian; Mathiak, Klaus
2017-03-01
A gene-environment interaction between expression genotypes of the monoamine oxidase A (MAOA) and adverse childhood experience increases the risk of antisocial behavior. However, the neural underpinnings of this interaction remain uninvestigated. A cortico-limbic circuit involving the prefrontal cortex (PFC) and the amygdala is central to the suppression of aggressive impulses and is modulated by serotonin (5-HT). MAOA genotypes may modulate the vulnerability of this circuit and increase the risk for emotion regulation deficits after specific life events. Acute tryptophan depletion (ATD) challenges 5-HT regulation and may identify vulnerable neuronal circuits, contributing to the gene-environment interaction. Functional magnetic resonance imaging measured the resting-state state activity in 64 healthy males in a double-blind, placebo-controlled study. Cortical maps of amygdala correlation identified the impact of ATD and its interaction with low- (MAOA-L) and high-expression variants (MAOA-H) of MAOA on cortico-limbic connectivity. Across all Regions of Interest (ROIs) exhibiting an ATD effect on cortico-limbic connectivity, MAOA-L carriers were more susceptible to ATD than MAOA-H carriers. In particular, the MAOA-L group exhibited a larger reduction of amygdala connectivity with the right prefrontal cortex and a larger increase of amygdala connectivity with the insula and dorsal PCC. MAOA-L carriers were more susceptable to a central 5-HT challenge in cortico-limbic networks. Such vulnerability of the cortical serotonergic system may contribute to the emergence of antisocial behavior after systemic challenges, observed as gene-environment interaction. Hum Brain Mapp 38:1622-1635, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice.
Senthilvel, Senapathy; Vinod, Kunnummal Kurungara; Malarvizhi, Palaniappan; Maheswaran, Marappa
2008-09-01
Agricultural environments deteriorate due to excess nitrogen application. Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input. Rice genotypes respond variably to soil available nitrogen. The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits. Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena. Three nitrogen regimes namely, native (0 kg/ha; no nitrogen applied), optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments. The parents and DH lines were significantly varying for all traits under different nitrogen regimes. All traits except plant height recorded significant genotype x environment interaction. Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake. Sixteen QTLs were detected by composite interval mapping. Eleven QTLs showed significant QTL x environment interactions. On chromosome 3, seven QTLs were detected associated with nitrogen use, plant yield and associated traits. A QTL region between markers RZ678, RZ574 and RZ284 was associated with nitrogen use and yield. This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.
Epigenetics and obesity: the devil is in the details.
Franks, Paul W; Ling, Charlotte
2010-12-21
Obesity is a complex disease with multiple well-defined risk factors. Nevertheless, susceptibility to obesity and its sequelae within obesogenic environments varies greatly from one person to the next, suggesting a role for gene × environment interactions in the etiology of the disorder. Epigenetic regulation of the human genome provides a putative mechanism by which specific environmental exposures convey risk for obesity and other human diseases and is one possible mechanism that underlies the gene × environment/treatment interactions observed in epidemiological studies and clinical trials. A study published in BMC Medicine this month by Wang et al. reports on an examination of DNA methylation in peripheral blood leukocytes of lean and obese adolescents, comparing methylation patterns between the two groups. The authors identified two genes that were differentially methylated, both of which have roles in immune function. Here we overview the findings from this study in the context of those emerging from other recent genetic and epigenetic studies, discuss the strengths and weaknesses of the study and speculate on the future of epigenetics in chronic disease research.
Environmental stress alters genetic regulation of novelty seeking in vervet monkeys.
Fairbanks, L A; Bailey, J N; Breidenthal, S E; Laudenslager, M L; Kaplan, J R; Jorgensen, M J
2011-08-01
Considerable attention has been paid to identifying genetic influences and gene-environment interactions that increase vulnerability to environmental stressors, with promising but inconsistent results. A nonhuman primate model is presented here that allows assessment of genetic influences in response to a stressful life event for a behavioural trait with relevance for psychopathology. Genetic and environmental influences on free-choice novelty seeking behaviour were assessed in a pedigreed colony of vervet monkeys before and after relocation from a low stress to a higher stress environment. Heritability of novelty seeking scores, and genetic correlations within and between environments were conducted using variance components analysis. The results showed that novelty seeking was markedly inhibited in the higher stress environment, with effects persisting across a 2-year period for adults but not for juveniles. There were significant genetic contributions to novelty seeking scores in each year (h(2) = 0.35-0.43), with high genetic correlations within each environment (rhoG > 0.80) and a lower genetic correlation (rhoG = 0.35, non-significant) between environments. There were also significant genetic contributions to individual change scores from before to after the move (h(2) = 0.48). These results indicate that genetic regulation of novelty seeking was modified by the level of environmental stress, and they support a role for gene-environment interactions in a behavioural trait with relevance for mental health. © 2011 The Authors. Genes, Brain and Behavior © 2011 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.
Music training and speech perception: a gene-environment interaction.
Schellenberg, E Glenn
2015-03-01
Claims of beneficial side effects of music training are made for many different abilities, including verbal and visuospatial abilities, executive functions, working memory, IQ, and speech perception in particular. Such claims assume that music training causes the associations even though children who take music lessons are likely to differ from other children in music aptitude, which is associated with many aspects of speech perception. Music training in childhood is also associated with cognitive, personality, and demographic variables, and it is well established that IQ and personality are determined largely by genetics. Recent evidence also indicates that the role of genetics in music aptitude and music achievement is much larger than previously thought. In short, music training is an ideal model for the study of gene-environment interactions but far less appropriate as a model for the study of plasticity. Children seek out environments, including those with music lessons, that are consistent with their predispositions; such environments exaggerate preexisting individual differences. © 2015 New York Academy of Sciences.
A Scalable Approach for Discovering Conserved Active Subnetworks across Species
Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.
2010-01-01
Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309
GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.
Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan
2011-05-01
Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.
Coulon, Sandra M.; Wilson, Dawn K.; Van Horn, M. L.; Hand, Gregory A.; Kresovich, Stephen
2016-01-01
Background African-American adults are disproportionately affected by stress-related chronic conditions like high blood pressure (BP), and both environmental stress and genetic risk may play a role in its development. Purpose This study tested whether the dual risk of low neighborhood socioeconomic status (SES) and glucocorticoid genetic sensitivity interacted to predict waking cortisol and BP. Methods Cross-sectional waking cortisol and BP were collected from 208 African-American adults who were participating in a follow-up visit as part of the Positive Action for Today’s Health trial. Three single nucleotide polymorphisms were genotyped, salivary cortisol samples were collected, and neighborhood SES was calculated using 2010 Census data. Results The sample was mostly female (65%), with weight classified as overweight or obese (MBMI=32.74, SD=8.88), and a mean age of 55.64 (SD=15.21). The gene-by-neighborhood SES interaction predicted cortisol (B=0.235, p=.001, r2=.036), but not BP. For adults with high genetic risk, waking cortisol was lower with lower SES but higher with higher SES (B=0.87). Lower neighborhood SES was also related to higher systolic BP (B=−0.794, p=.028). Conclusions Findings demonstrated an interaction whereby African-American adults with high genetic sensitivity had high levels of waking cortisol with higher neighborhood SES, and low levels with lower neighborhood SES. This moderation effect is consistent with a differential susceptibility gene-environment pattern, rather than a dual-risk pattern. These findings contribute to a growing body of evidence that demonstrates the importance of investigating complex gene-environment relations in order to better understand stress-related health disparities. PMID:26685668
ERIC Educational Resources Information Center
Marceau, Kristine; Horwitz, Briana N.; Narusyte, Jurgita; Ganiban, Jody M.; Spotts, Erica L.; Reiss, David; Neiderhiser, Jenae M.
2013-01-01
Studies of adolescent or parent-based twins suggest that gene-environment correlation (rGE) is an important mechanism underlying parent-adolescent relationships. However, information on how parents' and children's genes and environments influence correlated parent "and" child behaviors is needed to distinguish types of rGE. The present…
Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation
Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.
2016-01-01
Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038
Jokela, Markus; Keltikangas-Järvinen, Liisa; Kivimäki, Mika; Puttonen, Sampsa; Elovainio, Marko; Rontu, Riikka; Lehtimäki, Terho
2007-03-01
Gene-environment interactions are assumed to be involved in the development of depression. To determine whether the serotonin receptor 2A (HTR2A) gene moderates the association between childhood maternal nurturance and depressive symptoms in adulthood. A 21-year, prospective, longitudinal study with 2 measurements of the independent and dependent variables. A population-based sample. A subsample of 1212 participants of the Cardiovascular Risk in Young Finns study, aged 3 to 18 years at baseline. Main Outcome Measure Depressive symptoms in adulthood. Individuals carrying the T/T or T/C genotype of the T102C polymorphism of the HTR2A gene were responsive to the protective aspects of nurturing mothering, so that in the presence of high maternal nurturance, they expressed low levels of depressive symptoms, while this was not true with the carriers of the C/C genotype. The HTR2A gene may be involved in the development of depression by influencing the ability of individuals to use environmental support.
Association between NINJ2 gene polymorphisms and ischemic stroke: a family-based case-control study.
Zhu, Yanping; Liu, Kuo; Tang, Xun; Wang, Jinwei; Yu, Zhiping; Wu, Yiqun; Chen, Dafang; Wang, Xueyin; Fang, Kai; Li, Na; Huang, Shaoping; Hu, Yonghua
2014-11-01
Novel susceptibility genes related to ischemic stroke (IS) are proposed in recent literatures. Population-based replicate studies would cause false positive results due to population stratification. 229 recruit IS patients and their 229 non-IS siblings were used in this study to avoid population stratification. The family-based study was conducted in Beijing from June 2005 to June 2012. Association between SNPs and IS was found in the sibship discordant tests, and the conditional logistic regression was performed to identify effect size and explore gene-environment interactions. Significant allelic association was identified between NINJ2 gene rs11833579 (P = 0.008), protein kinase C η gene rs2230501 (P = 0.039) and IS. The AA genotype of rs11833579 increased 1.51-fold risk (95% CI 1.04-3.46; P = 0.043) of IS, and it conferred susceptibility to IS only in a dominant model (OR 2.69; 95% CI 1.06-6.78; P = 0.036]. Risk of IS was higher (HR 3.58; 95% CI 1.54-8.31; P = 0.003) especially when the carriers of rs11833579 AA genotype were smokers. The present study suggests A allele of rs11833579 may play a role in mediating susceptibility to IS and it may increase the risk of IS together with smoking.
Plasticity of genetic interactions in metabolic networks of yeast.
Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela
2007-02-13
Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.
Gene-Environment Interaction in the Etiology of Mathematical Ability Using SNP Sets
Kovas, Yulia; Plomin, Robert
2010-01-01
Mathematics ability and disability is as heritable as other cognitive abilities and disabilities, however its genetic etiology has received relatively little attention. In our recent genome-wide association study of mathematical ability in 10-year-old children, 10 SNP associations were nominated from scans of pooled DNA and validated in an individually genotyped sample. In this paper, we use a ‘SNP set’ composite of these 10 SNPs to investigate gene-environment (GE) interaction, examining whether the association between the 10-SNP set and mathematical ability differs as a function of ten environmental measures in the home and school in a sample of 1888 children with complete data. We found two significant GE interactions for environmental measures in the home and the school both in the direction of the diathesis-stress type of GE interaction: The 10-SNP set was more strongly associated with mathematical ability in chaotic homes and when parents are negative. PMID:20978832
Cataldo, Ilaria; Azhari, Atiqah; Lepri, Bruno; Esposito, Gianluca
2017-10-21
Oxytocin plays an important role in the modulation of social behavior in both typical and atypical contexts. Also, the quality of early parental care sets the foundation for long-term psychosocial development. Here, we review studies that investigated how oxytocin receptor (OXTR) interacts with early parental care experiences to influence the development of psychiatric disorders. Using Pubmed, Scopus and PsycInfo databases, we utilized the keyword "OXTR" before subsequently searching for specific OXTR single nucleotide polymorphisms (SNPs), generating a list of 598 studies in total. The papers were catalogued in a database and filtered for gene-environment interaction, psychiatric disorders and involvement of parental care. In particular, rs53576 and rs2254298 were found to be significantly involved in gene-environment interactions that modulated risk for psychopathology and the following psychiatric disorders: disruptive behavior, depression, anxiety, eating disorder and borderline personality disorder. These results illustrate the importance of OXTR in mediating the impact of parental care on the emergence of psychopathology. Copyright © 2017 Elsevier Ltd. All rights reserved.
Moderating Effects of Autism on Parent Views of Genetic Screening for Aggression
ERIC Educational Resources Information Center
May, Michael E.; Brandt, Rachel C.; Bohannan, Joseph K.
2012-01-01
Advances in gene-environment interaction research have revealed genes that are associated with aggression. However, little is known about parent perceptions of genetic screening for behavioral symptoms like aggression as opposed to diagnosing disabilities. These perceptions may influence future research endeavors involving genetic linkage studies…
International Cancer of the Head and Neck, Genetics and Environment (InterCHANGE) Study
2013-10-29
Evaluate the Association Between Certain Environmental Exposures (e.g. Cigarette Smoking, Alcohol Drinking, Betel Nut Chewing…) and Head and Neck Cancers; Assess the Effect of Genetic Factors, Including Both SNP and Copy Number Variation (CNV) Through Analysis of Both Main Effect and Gene-gene Interaction
Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.
Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K
2017-11-01
Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Li, James J.; Lee, Steve S.
2012-01-01
Relatively little is known about the potential interplay between genetic and environmental influences on attention-deficit/hyperactivity disorder (ADHD), including gene-environment interaction (GxE). There is evidence that parenting behavior interacts with offspring genotype in the development of externalizing problems, but studies have largely…
Seyedsayamdost, Mohammad R; Traxler, Matthew F; Clardy, Jon; Kolter, Roberto
2012-01-01
Actinomycetes, a group of filamentous, Gram-positive bacteria, have long been a remarkable source of useful therapeutics. Recent genome sequencing and transcriptomic studies have shown that these bacteria, responsible for half of the clinically used antibiotics, also harbor a large reservoir of gene clusters, which have the potential to produce novel secreted small molecules. Yet, many of these clusters are not expressed under common culture conditions. One reason why these clusters have not been linked to a secreted small molecule lies in the way that actinomycetes have typically been studied: as pure cultures in nutrient-rich media that do not mimic the complex environments in which these bacteria evolved. New methods based on multispecies culture conditions provide an alternative approach to investigating the products of these gene clusters. We have recently implemented binary interspecies interaction assays to mine for new secondary metabolites and to study the underlying biology of interactinomycete interactions. Here, we describe the detailed biological and chemical methods comprising these studies. Copyright © 2012 Elsevier Inc. All rights reserved.
Chen, Dana; Orenstein, Yaron; Golodnitsky, Rada; Pellach, Michal; Avrahami, Dorit; Wachtel, Chaim; Ovadia-Shochat, Avital; Shir-Shapira, Hila; Kedmi, Adi; Juven-Gershon, Tamar; Shamir, Ron; Gerber, Doron
2016-01-01
Transcription factors (TFs) alter gene expression in response to changes in the environment through sequence-specific interactions with the DNA. These interactions are best portrayed as a landscape of TF binding affinities. Current methods to study sequence-specific binding preferences suffer from limited dynamic range, sequence bias, lack of specificity and limited throughput. We have developed a microfluidic-based device for SELEX Affinity Landscape MAPping (SELMAP) of TF binding, which allows high-throughput measurement of 16 proteins in parallel. We used it to measure the relative affinities of Pho4, AtERF2 and Btd full-length proteins to millions of different DNA binding sites, and detected both high and low-affinity interactions in equilibrium conditions, generating a comprehensive landscape of the relative TF affinities to all possible DNA 6-mers, and even DNA10-mers with increased sequencing depth. Low quantities of both the TFs and DNA oligomers were sufficient for obtaining high-quality results, significantly reducing experimental costs. SELMAP allows in-depth screening of hundreds of TFs, and provides a means for better understanding of the regulatory processes that govern gene expression. PMID:27628341
De Leonibus, C; Chatelain, P; Knight, C; Clayton, P; Stevens, A
2016-01-01
The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene–environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene–environment interactions in children treated with r-hGH. PMID:26503811
Sam, Soya Sisy; Thomas, Vinod; Sivagnanam, Kumaran; Reddy, Kanipakapatanam Sathyanarayana; Surianarayanan, Gopalakrishnan; Chandrasekaran, Adithan
2007-10-01
Upper aerodigestive tract (UADT) cancers are associated with the tobacco use and alcohol consumption. Certain toxins and carcinogens causing UADT cancers are found to be substrates of polymorphic ABCB1 gene encoded P-glycoprotein efflux pump. This study investigates the association between ABCB1 gene polymorphism at exon 26 (3435C>T) and risk to UADT cancers in Tamilians, a population of south India. The study included 219 unrelated histopathologically confirmed cases and 210 population-based controls. Genomic DNA was extracted from peripheral leukocytes and genotyped for ABCB1 3435C>T polymorphism by PCR-restriction fragment length polymorphism method. The multivariate logistic regression analyses demonstrated that the homozygous ABCB1 TT genotype was significantly associated with an overall increased risk for developing UADT cancers [odds ratio (OR): 2.53; 95% confidence interval (CI): 1.28-5.02]. Further, the determination of gene-environment interaction by stratified analyses have revealed a significant interaction between the smoking and homozygous TT genotype [(OR: 7.52; CI: 1.50-37.70) and (OR: 16.89; CI: 3.87-73.79) for 11-20 and >20 pack-years, respectively]. The strongest interaction was observed among the regular tobacco chewers (OR: 45.29; CI: 8.94-130.56) homozygous for TT genotype. No suggestion, however, of an interaction between the genotypes and the alcohol consumption on the multiplicative scale was made. The ABCB1 gene polymorphism at exon 26 (3435C>T) may be one of the risk factors for susceptibility to UADT cancers. Furthermore, the significant interaction among habitual smokers and tobacco chewers, homozygous for TT genotype modulates the risk to UADT cancers in the Tamilian population of south India.
Does MAOA Increase Susceptibility to Prenatal Stress in Young Children?
Massey, Suena H.; Hatcher, Amalia E.; Clark, Caron A.C.; Burns, James L.; Pine, Daniel S.; Skol, Andrew D.; Mroczek, Daniel K.; Espy, Kimberly A.; Goldman, David; Cook, Edwin; Wakschlag, Lauren S.
2017-01-01
Background We previously demonstrated a gene-by-prenatal-environment interaction whereby the monoamine oxidase A gene (MAOA) modified the impact of prenatal tobacco exposure (PTE) on adolescent disruptive behavior (DB), with the MAOA risk genotype varying by sex. We extend this work by examining whether this mechanism is evident with another common adversity, prenatal stress exposure (PSE), and whether sex differences are present earlier in development in closer proximity to exposure. Methods Participants were 281 mothers and their 285 children derived from a prenatal cohort with in-depth prospective measures of PSE and PTE. We assessed DB at age 5 via dimensional developmentally-sensitive measurement. Analyses were stratified by sex based on prior evidence for sex differences. Results Concurrent stress exposure predicted DB in children (β=.310, p=.001), while main effects of prenatal exposures were seen only in boys. We found a three-way interaction of MAOAxPSExsex on DB (β=.813, p=.022). Boys with MAOA-H had more DB as a function of PSE, controlling for PTE (β=.774, p=.015), and as a function of PTE, controlling for PSE (β=.362, p=.037). Boys with MAOA-L did not show this susceptibility. MAOA did not interact with PSE (β=−.133, p=.561) nor PTE (β= −.144; p=.505) in predicting DB in girls. Examination of gene-environment correlation (rGE) showed a correlation between paternal MAOA-L and daughters’ concurrent stress exposure (r=−.240, p=.013). Discussion Findings underscore complex mechanisms linking genetic susceptibility and early adverse exposures. Replication in larger cohorts followed from the pregnancy through adolescence is suggested to elucidate mechanisms that appear to have varying developmental expression. PMID:28163169
The CRHR1 Gene, Trauma Exposure, and Alcoholism Risk: A Test of G × E Effects
Ray, Lara A.; Sehl, Mary; Bujarski, Spencer; Hutchison, Kent; Blaine, Sara; Enoch, Mary-Anne
2014-01-01
The corticotropin-releasing hormone type I receptor (CRHR1) gene has been implicated in the liability for neuropsychiatric disorders, particularly under conditions of stress. Based on the hypothesized effects of CRHR1 variation on stress reactivity, measures of adulthood traumatic stress exposure were analyzed for their interaction with CRHR1 haplotypes and SNPs in predicting the risk for alcoholism. Phenotypic data on 2,533 non-related Caucasian individuals (1167 alcoholics and 1366 controls) were culled from the publically available Study of Addiction: Genetics and Environment (SAGE) genome-wide association study (GWAS). Genotypes were available for 19 tag SNPs. Logistic regression models examined the interaction between CRHR1 haplotypes / SNPs and adulthood traumatic stress exposure in predicting alcoholism risk. Two haplotype blocks spanned CRHR1. Haplotype analyses identified one haplotype in the proximal block 1 (p = 0.029) and two haplotypes in the distal block 2 (p = 0.026, 0.042) that showed nominally significant (corrected p < .025) genotype × traumatic stress interactive effects on the likelihood of developing alcoholism. The block 1 haplotype effect was driven by SNPs rs110402 (p = 0.019) and rs242924 (p = 0.019). In block 2, rs17689966 (p = 0.018) showed significant, and rs173365 (p = 0.026) showed nominally significant, gene × environment (G × E) effects on alcoholism status. This study extends the literature on the interplay between CRHR1 variation and alcoholism, in the context of exposure to traumatic stress. These findings are consistent with the hypothesized role of the extra hypothalamic CRF system dysregulation in the initiation and maintenance of alcoholism. Molecular and experimental studies are needed to more fully understand the mechanisms of risk and protection conferred by genetic variation at the identified loci. PMID:23473364
Does MAOA increase susceptibility to prenatal stress in young children?
Massey, Suena H; Hatcher, Amalia E; Clark, Caron A C; Burns, James L; Pine, Daniel S; Skol, Andrew D; Mroczek, Daniel K; Espy, Kimberly A; Goldman, David; Cook, Edwin; Wakschlag, Lauren S
2017-05-01
We previously demonstrated a gene-by-prenatal-environment interaction whereby the monoamine oxidase A gene (MAOA) modified the impact of prenatal tobacco exposure (PTE) on adolescent disruptive behavior (DB), with the MAOA risk genotype varying by sex. We extend this work by examining whether this mechanism is evident with another common adversity, prenatal stress exposure (PSE), and whether sex differences are present earlier in development in closer proximity to exposure. Participants were 281 mothers and their 285 children derived from a prenatal cohort with in-depth prospective measures of PSE and PTE. We assessed DB at age 5 via dimensional developmentally-sensitive measurement. Analyses were stratified by sex based on prior evidence for sex differences. Concurrent stress exposure predicted DB in children (β=0.310, p=0.001), while main effects of prenatal exposures were seen only in boys. We found a three-way interaction of MAOA×PSE×sex on DB (β=0.813, p=0.022). Boys with MAOA-H had more DB as a function of PSE, controlling for PTE (β=0.774, p=0.015), and as a function of PTE, controlling for PSE (β=0.362, p=0.037). Boys with MAOA-L did not show this susceptibility. MAOA did not interact with PSE (β=-0.133, p=0.561) nor PTE (β=-0.144; p=0.505) in predicting DB in girls. Examination of gene-environment correlation (rGE) showed a correlation between paternal MAOA-L and daughters' concurrent stress exposure (r=-0.240, p=0.013). Findings underscore complex mechanisms linking genetic susceptibility and early adverse exposures. Replication in larger cohorts followed from the pregnancy through adolescence is suggested to elucidate mechanisms that appear to have varying developmental expression. Copyright © 2017 Elsevier Inc. All rights reserved.
Gene essentiality and the topology of protein interaction networks
Coulomb, Stéphane; Bauer, Michel; Bernard, Denis; Marsolier-Kergoat, Marie-Claude
2005-01-01
The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. PMID:16087428
[The nature of personality: a co-evolutionary perspective].
Asendorpf, J B
1996-01-01
Personality psychologists' attempts to explain human diversity have traditionally focused upon processes of person-situation interaction, and genotype-environment interaction. The great variability of genotypes and environments within cultures has remained unexplained in these efforts. Which processes may be responsible for the genetic and environmental variability within cultures? Answers to this question are sought in processes of genetic-cultural coevolution: mutation and sexual recombination of genes, innovation and synthesis of memes (units of cultural transmission), genotype-->environment and meme-->environment effects, and frequency-dependent natural and cultural selection. This twofold evolutionary explanation of personality differences within cultures suggests that a solid foundation of personality psychology requires bridging biology and cultural science.
Anorexia nervosa and bulimia nervosa: brains, bones and breeding.
Starr, Taylor B; Kreipe, Richard E
2014-05-01
Recent research has modified both the conceptualization and treatment of eating disorders. New diagnostic criteria reducing the "not otherwise specified" category should facilitate the early recognition and treatment of anorexia nervosa (AN) and bulimia nervosa (BN). Technology-based studies identify AN and BN as "brain circuit" disorders; epidemiologic studies reveal that the narrow racial, ethnic and income profile of individuals no longer holds true for AN. The major organs affected long term-the brain and skeletal system-both respond to improved nutrition, with maintenance of body weight the best predictor of recovery. Twin studies have revealed gene x environment interactions, including both the external (social) and internal (pubertal) environments of boys and of girls. Family-based treatment has the best evidence base for effectiveness for younger patients. Medication plays a limited role in AN, but a major role in BN. Across diagnoses, the most important medicine is food.
Darling, Katherine Weatherford; Ackerman, Sara L.; Hiatt, Robert H.; Lee, Sandra Soo-Jin; Shim, Janet K.
2016-01-01
Despite a proclaimed shift from ‘nature versus nurture’ to ‘genes and environment’ paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does ‘the environment’ mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers’ expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to ‘go into the body’ and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. PMID:26994357
Early Life Precursors, Epigenetics, and the Development of Food Allergy1
Hong, Xiumei; Wang, Xiaobin
2012-01-01
Food allergy (FA), a major clinical and public health concern worldwide, is caused by a complex interplay of environmental exposures, genetic variants, gene-environment interactions, and epigenetic alterations. This review summarizes recent advances surrounding these key factors, with a particular focus on the potential role of epigenetics in the development of FA. Epidemiologic studies have reported a number of non-genetic factors that may influence the risk of FA, such as timing of food introduction and feeding pattern, diet/nutrition, exposure to environmental tobacco smoking, prematurity and low birthweight, microbial exposure, and race/ethnicity. Current studies on the genetics of FA are mainly conducted using candidate gene approaches, which have linked more than 10 genes to the genetic susceptibility of FA. Studies on gene-environment interactions of FA are very limited. Epigenetic alteration has been proposed as one of the mechanisms to mediate the influence of early-life environmental exposures and gene-environment interactions on the development of diseases later in life. The role of epigenetics in the regulation of the immune system and the epigenetic effects of some FA-associated environmental exposures are discussed in this review. There is a particular lack of large-scale prospective birth cohort studies that simultaneously assess the inter-relationships of early life exposures, genetic susceptibility, epigenomic alterations and the development of FA. The identification of these key factors and their independent and joint contributions to FA will allow us to gain important insight into the biological mechanisms by which environmental exposures and genetic susceptibility affect the risk of FA, and will provide essential information to develop more effective new paradigms in the diagnosis, prevention and management of FA. PMID:22777545
Han, Dong; Qiao, Zhengxue; Chen, Lu; Qiu, Xiaohui; Fang, Deyu; Yang, Xiuxian; Ma, Jingsong; Chen, Mingqi; Yang, Jiarun; Wang, Lin; Zhu, Xiongzhao; Zhang, Congpei; Yang, Yanjie; Pan, Hui
2017-08-01
Recent studies suggest that vascular endothelial growth factor (VEGF) is involved in the development of major depressive disorder. The aim of this study is to investigate the interaction between vascular endothelial growth factor (VEGF) polymorphism (+405G/C, rs2010963) and negative life events in the pathogenesis of major depressive disorder (MDD). DNA genotyping was performed on peripheral blood leukocytes in 274 patients with MDD and 273 age-and sex-matched controls. The frequency and severity of negative life events were assessed by the Life Events Scale (LES). A logistics method was employed to assess the gene-environment interaction (G×E). Differences in rs2010963 genotype distributions were observed between MDD patients and controls. Significant G×E interactions between allelic variation of rs2010963 and negative life events were observed. Individuals carrying the C alleles were susceptible to MDD only when exposed to high-negative life events. These results indicate that interactions between the VEGF rs2010963 polymorphism and environment increases the risk of developing MDD. Copyright © 2017 Elsevier B.V. All rights reserved.
Interaction between PON1 and population density in amyotrophic lateral sclerosis.
Diekstra, Frank P; Beleza-Meireles, Ana; Leigh, Nigel P; Shaw, Christopher E; Al-Chalabi, Ammar
2009-01-28
Paraoxonase polymorphisms have been associated with amyotrophic lateral sclerosis (ALS). Paraoxonases are detoxifying enzymes involved in the metabolism of organophosphates. We tested the hypothesis that genetic variation within paraoxonase genes would interact with the environmental exposure to paraoxonase substrates. We used population density in the location of residence of ALS patients as a surrogate marker for environmental exposure. Paraoxonase genotypes at previously associated single nucleotide polymorphisms rs662, rs854560, rs6954345, and rs11981433 were studied in 98 patients from the South East England ALS population-based register. A case-only analysis was carried out and median population density was used to categorize patients into rural or urban environments. We found a significant interaction with population density for marker rs854560 (L55M) in ALS.
Bornovalova, Marina A.; Cummings, Jenna R.; Hunt, Elizabeth; Blazei, Ryan; Malone, Steve; Iacono, William G.
2013-01-01
Background: Previous work reports an association between familial risk factors stemming from parental characteristics and offspring disruptive behavior disorders (DBDs). This association may reflect a) the direct effects of familial environment, and b) a passive gene-environment correlation, wherein the parents provide both the genes and the environment. The current study examined the contributions of direct environmental influences and passive gene-environment correlations by comparing the effects of familial risk factors on child DBDs in genetically related (biological) and non-related (adoptive) families. Method: Participants were 402 adoptive and 204 biological families. Familial environment was defined as maternal and paternal maladaptive parenting and antisociality, marital conflict, and divorce; offspring DBDs included attention deficit/hyperactivity disorder, conduct disorder, and oppositional defiant disorder. Mixed-level regressions estimated the main effects of familial environment, adoption status, and the familial environment by adoption status interaction term, which tested for a presence of passive gene-environment correlations. Results: There was a main effect of maternal and paternal maladaptive parenting and marital discord on child DBDs, indicating a direct environmental effect. There was no direct environmental effect of maternal or paternal antisociality, but maternal and paternal antisociality had stronger associations with child DBDs in biological families than adoptive families, indicating the presence of a passive gene-environment correlation. Conclusions: Many familial risk factors affected children equally across genetically-related and non-related families, providing evidence for direct environmental effects. The relationship of parental antisociality and offspring DBDs was best explained by a passive gene-environment correlation, where a general vulnerability toward externalizing psychopathology is passed down by the parents to the children. PMID:23714724
Are there genetic influences on addiction: evidence from family, adoption and twin studies.
Agrawal, Arpana; Lynskey, Michael T
2008-07-01
In this exciting era of gene discovery, we review evidence from family, adoption and twin studies that examine the genetic basis for addiction. With a focus on the classical twin design that utilizes data on monozygotic and dizygotic twins, we discuss support in favor of heritable influences on alcohol, nicotine, cannabis and other illicit drug dependence. We review whether these genetic factors also influence earlier stages (e.g. experimentation) of the addictive process and whether there are genetic influences specific to each psychoactive substance. Converging evidence from these studies supports the role of moderate to high genetic influences on addiction with estimates ranging from 0.30 to 0.70. The changing role of these heritable factors as a function of gender, age and cultural characteristics is also discussed. We highlight the importance of the interplay between genes and the environment as it relates to risk for addiction and the utility of the children-of-twins design for emerging studies of gene-environment interaction is presented. Despite the advances being made by low-cost high-throughput whole genome association assays, we posit that information garnered from twin studies, especially extended twin designs with power to examine gene-environment interactions, will continue to form the foundation for genomic research.
A meta-analysis of heritability of cognitive aging: minding the "missing heritability" gap.
Reynolds, Chandra A; Finkel, Deborah
2015-03-01
The etiologies underlying variation in adult cognitive performance and cognitive aging have enjoyed much attention in the literature, but much of that attention has focused on broad factors, principally general cognitive ability. The current review provides meta-analyses of age trends in heritability of specific cognitive abilities and considers the profile of genetic and environmental factors contributing to cognitive aging to address the 'missing heritability' issue. Our findings, based upon evaluating 27 reports in the literature, indicate that verbal ability demonstrated declining heritability, after about age 60, as did spatial ability and perceptual speed more modestly. Trends for general memory, working memory, and spatial ability generally indicated stability, or small increases in heritability in mid-life. Equivocal results were found for executive function. A second meta-analysis then considered the gap between twin-based versus SNP-based heritability derived from population-based GWAS studies. Specifically, we considered twin correlation ratios to agnostically re-evaluate biometrical models across age and by cognitive domain. Results modestly suggest that nonadditive genetic variance may become increasingly important with age, especially for verbal ability. If so, this would support arguments that lower SNP-based heritability estimates result in part from uncaptured non-additive influences (e.g., dominance, gene-gene interactions), and possibly gene-environment (GE) correlations. Moreover, consistent with longitudinal twin studies of aging, as rearing environment becomes a distal factor, increasing genetic variance may result in part from nonadditive genetic influences or possible GE correlations. Sensitivity to life course dynamics is crucial to understanding etiological contributions to adult cognitive performance and cognitive aging.
Lobach, Iryna; Mallick, Bani; Carroll, Raymond J
2011-01-01
Case-control studies are widely used to detect gene-environment interactions in the etiology of complex diseases. Many variables that are of interest to biomedical researchers are difficult to measure on an individual level, e.g. nutrient intake, cigarette smoking exposure, long-term toxic exposure. Measurement error causes bias in parameter estimates, thus masking key features of data and leading to loss of power and spurious/masked associations. We develop a Bayesian methodology for analysis of case-control studies for the case when measurement error is present in an environmental covariate and the genetic variable has missing data. This approach offers several advantages. It allows prior information to enter the model to make estimation and inference more precise. The environmental covariates measured exactly are modeled completely nonparametrically. Further, information about the probability of disease can be incorporated in the estimation procedure to improve quality of parameter estimates, what cannot be done in conventional case-control studies. A unique feature of the procedure under investigation is that the analysis is based on a pseudo-likelihood function therefore conventional Bayesian techniques may not be technically correct. We propose an approach using Markov Chain Monte Carlo sampling as well as a computationally simple method based on an asymptotic posterior distribution. Simulation experiments demonstrated that our method produced parameter estimates that are nearly unbiased even for small sample sizes. An application of our method is illustrated using a population-based case-control study of the association between calcium intake with the risk of colorectal adenoma development.
Li, James J; Berk, Michele S; Lee, Steve S
2013-11-01
Although family support reliably predicts the development of adolescent depression and suicidal behaviors, relatively little is known about the interplay of family support with potential genetic factors. We tested the association of the 44 base pair polymorphism in the serotonin transporter linked promoter region gene (5-HTTLPR), family support (i.e., cohesion, communication, and warmth), and their interaction with self-reported depression symptoms and risk for suicide in 1,030 Caucasian adolescents and young adults from the National Longitudinal Study of Adolescent Health. High-quality family support predicted fewer symptoms of depression and reduced risk for suicidality. There was also a significant interaction between 5-HTTLPR and family support for boys and a marginally significant interaction for girls. Among boys with poor family support, youth with at least one short allele had more symptoms of depression and a higher risk for suicide attempts relative to boys homozygous for the long allele. However, in the presence of high family support, boys with the short allele had the fewest depression symptoms (but not suicide attempts). Results suggest that the short allele may increase reactivity to both negative and positive family influences in the development of depression. We discuss the potential role of interactive exchanges between family support and offspring genotype in the development of adolescent depression and suicidal behaviors.
DiLalla, Lisabeth Fisher; Bersted, Kyle; John, Sufna Gheyara
2015-10-01
The development of prosocial behaviors during the preschool years is essential for children's positive interactions with peers in school and other social situations. Although there is some evidence of genetic influences on prosocial behaviors, very little is known about how genes and environment, independently and in concert, affect prosocial behaviors in young children. This study of 126 twin and sibling pairs examined 5-year-old preschool children's positive behaviors (prosocial and easy-going) while playing freely with an unfamiliar, same-age, same-sex peer. Children were randomly paired, allowing us to rule out passive (parent-influenced environment) and active (child-driven peer choices) gene-environment correlations as potential influences on the results. We found evidence of reactive gene-environment correlation, demonstrating that children who are genetically more likely to act prosocially and to be temperamentally outgoing appear to evoke more prosocial and easy-going behaviors from an unfamiliar peer. We also found that both dominant genetic and nonshared environmental factors were significant influences on preschoolers' prosocial play behaviors, but that neither genetic nor shared environmental factors were significant for easy-going play behaviors. These findings shed important light on influences of prosocial behaviors in preschoolers. Via inherited tendencies, preschool children's positive behaviors evoke similar positive behaviors from their play peers. Given that prosocial behaviors are preludes to a large range of important socially appropriate behaviors, prosocial children should be encouraged to interact with their peers to potentially create a more positive atmosphere within social contexts. (c) 2015 APA, all rights reserved).
Maere, Steven; Heymans, Karel; Kuiper, Martin
2005-08-15
The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.
A kernel regression approach to gene-gene interaction detection for case-control studies.
Larson, Nicholas B; Schaid, Daniel J
2013-11-01
Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.
Mielniczuk, Jan; Teisseyre, Paweł
2018-03-01
Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chung, Chi-Jung; Department of Medical Research, China Medical University Hospital, Taichung, Taiwan; Huang, Chao-Yuan
Inter-individual variation in the metabolism of xenobiotics, caused by factors such as cigarette smoking or inorganic arsenic exposure, is hypothesized to be a susceptibility factor for urothelial carcinoma (UC). Therefore, our study aimed to evaluate the role of gene–environment interaction in the carcinogenesis of UC. A hospital-based case–control study was conducted. Urinary arsenic profiles were measured using high-performance liquid chromatography–hydride generator-atomic absorption spectrometry. Genotyping was performed using a polymerase chain reaction-restriction fragment length polymorphism technique. Information about cigarette smoking exposure was acquired from a lifestyle questionnaire. Multivariate logistic regression was applied to estimate the UC risk associated with certain riskmore » factors. We found that UC patients had higher urinary levels of total arsenic, higher percentages of inorganic arsenic (InAs%) and monomethylarsonic acid (MMA%) and lower percentages of dimethylarsinic acid (DMA%) compared to controls. Subjects carrying the GSTM1 null genotype had significantly increased UC risk. However, no association was observed between gene polymorphisms of CYP1A1, EPHX1, SULT1A1 and GSTT1 and UC risk after adjustment for age and sex. Significant gene–environment interactions among urinary arsenic profile, cigarette smoking, and GSTM1 wild/null polymorphism and UC risk were observed after adjustment for potential risk factors. Overall, gene–environment interactions simultaneously played an important role in UC carcinogenesis. In the future, large-scale studies should be conducted using tag-SNPs of xenobiotic-metabolism-related enzymes for gene determination. -- Highlights: ► Subjects with GSTM1 null genotype had significantly increased UC risk. ► UC patients had poor arsenic metabolic ability compared to controls. ► GSTM1 null genotype may modify arsenic related UC risk.« less
Lin, Eugene; Kuo, Po-Hsiu; Liu, Yu-Li; Yang, Albert C; Kao, Chung-Feng; Tsai, Shih-Jen
2017-04-11
Previous animal studies have indicated associations between circadian clock genes and cognitive impairment . In this study, we assessed whether 11 circadian clockgenes are associated with cognitive aging independently and/or through complex interactions in an old Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to evaluate cognitive function. Our data showed associations between cognitive aging and single nucleotide polymorphisms (SNPs) in 4 key circadian clock genes, CLOCK rs3749473 (p = 0.0017), NPAS2 rs17655330 (p = 0.0013), RORA rs13329238 (p = 0.0009), and RORB rs10781247 (p = 7.9 x 10-5). We also found that interactions between CLOCK rs3749473, NPAS2 rs17655330, RORA rs13329238, and RORB rs10781247 affected cognitive aging (p = 0.007). Finally, we investigated the influence of interactions between CLOCK rs3749473, RORA rs13329238, and RORB rs10781247 with environmental factors such as alcohol consumption, smoking status, physical activity, and social support on cognitive aging (p = 0.002 ~ 0.01). Our study indicates that circadian clock genes such as the CLOCK, NPAS2, RORA, and RORB genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-environment interactions.
Hartman, Sarah; Widaman, Keith F; Belsky, Jay
2015-08-01
Manuck, Craig, Flory, Halder, and Ferrell (2011) reported that a theoretically anticipated effect of family rearing on girls' menarcheal age was genetically moderated by two single nucleotide polymorphisms (SNPs) of the estrogen receptor-α gene. We sought to replicate and extend these findings, studying 210 White females followed from birth. The replication was general because a different measure of the rearing environment was used in this inquiry (i.e., maternal sensitivity) than in the prior one (i.e., family cohesion). Extensions of the work included prospective rather than retrospective measurements of the rearing environment, reports of first menstruation within a year of its occurrence rather than decades later, accounting for some heritability of menarcheal age by controlling for maternal age of menarche, and using a new model-fitting approach to competitively compare diathesis-stress versus differential-susceptibility models of Gene × Environment interaction. The replication/extension effort proved successful in the case of both estrogen receptor-α SNPs, with the Gene × Environment interactions principally reflecting diathesis-stress: lower levels of maternal sensitivity predicted earlier age of menarche for girls homozygous for the minor alleles of either SNP but not for girls carrying other genotypes. Results are discussed in light of the new analytic methods adopted.
Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation
Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; ...
2016-11-24
Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli, which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-meansmore » clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus. We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli. As a result, this analysis produces insights into improving the design of gene expression experiments.« less
Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.
Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. A multitude of technologies, abstractions, and interpretive frameworks have emerged to answer the challenges presented by genome function and regulatory network inference. Here, we propose a new approach for producing biologically meaningful clusters of coexpressed genes, called Atomic Regulons (ARs), based on expression data, gene context, and functional relationships. We demonstrate this new approach by computing ARs for Escherichia coli, which we compare with the coexpressed gene clusters predicted by two prevalent existing methods: hierarchical clustering and k-meansmore » clustering. We test the consistency of ARs predicted by all methods against expected interactions predicted by the Context Likelihood of Relatedness (CLR) mutual information based method, finding that the ARs produced by our approach show better agreement with CLR interactions. We then apply our method to compute ARs for four other genomes: Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus. We compare the AR clusters from all genomes to study the similarity of coexpression among a phylogenetically diverse set of species, identifying subsystems that show remarkable similarity over wide phylogenetic distances. We also study the sensitivity of our method for computing ARs to the expression data used in the computation, showing that our new approach requires less data than competing approaches to converge to a near final configuration of ARs. We go on to use our sensitivity analysis to identify the specific experiments that lead most rapidly to the final set of ARs for E. coli. As a result, this analysis produces insights into improving the design of gene expression experiments.« less
Zitman-Gal, Tali; Green, Janice; Pasmanik-Chor, Metsada; Oron-Karni, Varda; Bernheim, Jacques
2010-07-01
BACKGROUND. High blood and tissue concentrations of glucose and advanced glycation end-products (AGEs) are thought to play an important role in the development of vascular diabetic complications. Therefore, the impact of extracellular AGEs and different glucose concentrations was evaluated by studying the gene expressions and the underlying cellular pathways involved in the development of inflammatory pro-atherosclerotic processes observed in cultured endothelial cells. METHODS. Fresh human umbilical vein cord endothelial cells (HUVEC) were treated in the presence of elevated extracellular glucose concentrations (5.5-28 mmol/l) with and without AGE-human serum albumin (HSA). Affymetrix GeneChip(R) Human Gene 1.0 ST arrays were used for gene expression analysis (total 20 chips). Genes of interest were further validated using real-time PCR and western blot techniques. RESULTS. Microarray analysis revealed significant changes in some gene expressions in the presence of the different stimuli, suggesting that different pathways are involved. Six genes were selected for validation as follows: thioredoxin-interacting protein (TXNIP), thioredoxin (TXN), nuclear factor of kappa B (NF-kappaB), interleukin 6 (IL6), interleukin 8 (IL8) and receptor of advanced glycation end-products (RAGE). Interestingly, it was found that the association of AGEs together with the highest pathophysiological concentration of glucose (28 mmol/l) diminished the expression of these specific genes, excluding TXN. CONCLUSIONS. In the present model that mimics a diabetic environment, the relatively short-term experimental conditions used showed an unexpected blunting action of AGEs in the presence of the highest glucose concentration (28 mmol/l). The interactive cellular pathways involved in these processes should be further investigated.
Bernstein, Jonine L; Langholz, Bryan; Haile, Robert W; Bernstein, Leslie; Thomas, Duncan C; Stovall, Marilyn; Malone, Kathleen E; Lynch, Charles F; Olsen, Jørgen H; Anton-Culver, Hoda; Shore, Roy E; Boice, John D; Berkowitz, Gertrud S; Gatti, Richard A; Teitelbaum, Susan L; Smith, Susan A; Rosenstein, Barry S; Børresen-Dale, Anne-Lise; Concannon, Patrick; Thompson, W Douglas
2004-01-01
Introduction Deficiencies in cellular responses to DNA damage can predispose to cancer. Ionizing radiation can cause cluster damage and double-strand breaks (DSBs) that pose problems for cellular repair processes. Three genes (ATM, BRCA1, and BRCA2) encode products that are essential for the normal cellular response to DSBs, but predispose to breast cancer when mutated. Design To examine the joint roles of radiation exposure and genetic susceptibility in the etiology of breast cancer, we designed a case-control study nested within five population-based cancer registries. We hypothesized that a woman carrying a mutant allele in one of these genes is more susceptible to radiation-induced breast cancer than is a non-carrier. In our study, 700 women with asynchronous bilateral breast cancer were individually matched to 1400 controls with unilateral breast cancer on date and age at diagnosis of the first breast cancer, race, and registry region, and counter-matched on radiation therapy. Each triplet comprised two women who received radiation therapy and one woman who did not. Radiation absorbed dose to the contralateral breast after initial treatment was estimated with a comprehensive dose reconstruction approach that included experimental measurements in anthropomorphic and water phantoms applying patient treatment parameters. Blood samples were collected from all participants for genetic analyses. Conclusions Our study design improves the potential for detecting gene–environment interactions for diseases when both gene mutations and the environmental exposures of interest are rare in the general population. This is particularly applicable to the study of bilateral breast cancer because both radiation dose and genetic susceptibility have important etiologic roles, possibly by interactive mechanisms. By using counter-matching, we optimized the informativeness of the collected dosimetry data by increasing the variability of radiation dose within the case–control sets and enhanced our ability to detect radiation–genotype interactions. PMID:15084244
Bagshaw, Andrew T M; Horwood, L John; Fergusson, David M; Gemmell, Neil J; Kennedy, Martin A
2017-02-03
The genetic and environmental influences on human personality and behaviour are a complex matter of ongoing debate. Accumulating evidence indicates that short tandem repeats (STRs) in regulatory regions are good candidates to explain heritability not accessed by genome-wide association studies. We tested for associations between the genotypes of four selected repeats and 18 traits relating to personality, behaviour, cognitive ability and mental health in a well-studied longitudinal birth cohort (n = 458-589) using one way analysis of variance. The repeats were a highly conserved poly-AC microsatellite in the upstream promoter region of the T-box brain 1 (TBR1) gene and three previously studied STRs in the activating enhancer-binding protein 2-beta (AP2-β) and androgen receptor (AR) genes. Where significance was found we used multiple regression to assess the influence of confounding factors. Carriers of the shorter, most common, allele of the AR gene's GGN microsatellite polymorphism had fewer anxiety-related symptoms, which was consistent with previous studies, but in our study this was not significant following Bonferroni correction. No associations with two repeats in the AP2-β gene withstood this correction. A novel finding was that carriers of the minor allele of the TBR1 AC microsatellite were at higher risk of conduct problems in childhood at age 7-9 (p = 0.0007, which did pass Bonferroni correction). Including maternal smoking during pregnancy (MSDP) in models controlling for potentially confounding influences showed that an interaction between TBR1 genotype and MSDP was a significant predictor of conduct problems in childhood and adolescence (p < 0.001), and of self-reported criminal behaviour up to age 25 years (p ≤ 0.02). This interaction remained significant after controlling for possible confounders including maternal age at birth, socio-economic status and education, and offspring birth weight. The potential functional importance of the TBR1 gene's promoter microsatellite deserves further investigation. Our results suggest that it participates in a gene-environment interaction with MDSP and antisocial behaviour. However, previous evidence that mothers who smoke during pregnancy carry genes for antisocial behaviour suggests that epistasis may influence the interaction.
Cicchetti, Dante; Rogosch, Fred A.; Hecht, Kathryn F.; Crick, Nicki R; Hetzel, Susan
2014-01-01
In this investigation, gene-environment-gender interaction effects in predicting child borderline personality disorder symptomatology among maltreated and nonmaltreated low-income children (N = 1,051) were examined. In the context of a summer research camp, adult-peer-, and self-report assessments of borderline precursor indicators were obtained, as well as child self-report on the Borderline Personality Features Scale-Children. Genetic variants of the OXTR genotype and the FKPB5 CATT haplotype were investigated. Children who self-reported high levels of borderline personality symptomatology were differentiated by adults, peers, and additional self-report on indicators of emotional instability, conflictual relationships with peers and adults, preoccupied attachment, and indicators of self-harm and suicidal ideation. Maltreated children also were more likely to evince many of these difficulties relative to nonmaltreated children. In a series of ANCOVAs, controlling for age and ancestrally informative markers, indicated significant maltreatment X gene X gender three-way interactions. Consideration of the maltreatment parameters of subtype, onset, and recency expanded understanding of variation among maltreated children. The three-way interaction effects demonstrated differential patterns among girls and boys. Among girls, the gene-environment interaction was more consistent with a diathesis-stress model, whereas among boys a differential-sensitivity interaction effect was indicated. Moreover, the genetic variants associated with greater risk for higher borderline symptomatology, dependent on maltreatment experiences, were opposite in girls compared to boys. The findings have important implications for understanding variability in early predictors of borderline personality pathology. PMID:25047302
Gene network biological validity based on gene-gene interaction relevance.
Gómez-Vela, Francisco; Díaz-Díaz, Norberto
2014-01-01
In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the algorithms used are precise. Usually, this validation process can be carried out using prior biological knowledge. The metabolic pathways stored in KEGG are one of the most widely used knowledgeable sources for analyzing relationships between genes. This paper introduces a new methodology, GeneNetVal, to assess the biological validity of gene networks based on the relevance of the gene-gene interactions stored in KEGG metabolic pathways. Hence, a complete KEGG pathway conversion into a gene association network and a new matching distance based on gene-gene interaction relevance are proposed. The performance of GeneNetVal was established with three different experiments. Firstly, our proposal is tested in a comparative ROC analysis. Secondly, a randomness study is presented to show the behavior of GeneNetVal when the noise is increased in the input network. Finally, the ability of GeneNetVal to detect biological functionality of the network is shown.
Caspi, Avshalom; Moffitt, Terrie E; Cannon, Mary; McClay, Joseph; Murray, Robin; Harrington, HonaLee; Taylor, Alan; Arseneault, Louise; Williams, Ben; Braithwaite, Antony; Poulton, Richie; Craig, Ian W
2005-05-15
Recent evidence documents that cannabis use by young people is a modest statistical risk factor for psychotic symptoms in adulthood, such as hallucinations and delusions, as well as clinically significant schizophrenia. The vast majority of cannabis users do not develop psychosis, however, prompting us to hypothesize that some people are genetically vulnerable to the deleterious effects of cannabis. In a longitudinal study of a representative birth cohort followed to adulthood, we tested why cannabis use is associated with the emergence of psychosis in a minority of users, but not in others. A functional polymorphism in the catechol-O-methyltransferase (COMT) gene moderated the influence of adolescent cannabis use on developing adult psychosis. Carriers of the COMT valine158 allele were most likely to exhibit psychotic symptoms and to develop schizophreniform disorder if they used cannabis. Cannabis use had no such adverse influence on individuals with two copies of the methionine allele. These findings provide evidence of a gene x environment interaction and suggest that a role of some susceptibility genes is to influence vulnerability to environmental pathogens.
HuMiChip: Development of a Functional Gene Array for the Study of Human Microbiomes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tu, Q.; Deng, Ye; Lin, Lu
Microbiomes play very important roles in terms of nutrition, health and disease by interacting with their hosts. Based on sequence data currently available in public domains, we have developed a functional gene array to monitor both organismal and functional gene profiles of normal microbiota in human and mouse hosts, and such an array is called human and mouse microbiota array, HMM-Chip. First, seed sequences were identified from KEGG databases, and used to construct a seed database (seedDB) containing 136 gene families in 19 metabolic pathways closely related to human and mouse microbiomes. Second, a mother database (motherDB) was constructed withmore » 81 genomes of bacterial strains with 54 from gut and 27 from oral environments, and 16 metagenomes, and used for selection of genes and probe design. Gene prediction was performed by Glimmer3 for bacterial genomes, and by the Metagene program for metagenomes. In total, 228,240 and 801,599 genes were identified for bacterial genomes and metagenomes, respectively. Then the motherDB was searched against the seedDB using the HMMer program, and gene sequences in the motherDB that were highly homologous with seed sequences in the seedDB were used for probe design by the CommOligo software. Different degrees of specific probes, including gene-specific, inclusive and exclusive group-specific probes were selected. All candidate probes were checked against the motherDB and NCBI databases for specificity. Finally, 7,763 probes covering 91.2percent (12,601 out of 13,814) HMMer confirmed sequences from 75 bacterial genomes and 16 metagenomes were selected. This developed HMM-Chip is able to detect the diversity and abundance of functional genes, the gene expression of microbial communities, and potentially, the interactions of microorganisms and their hosts.« less
USDA-ARS?s Scientific Manuscript database
Winter hardiness in plants is the result of a complex interaction between genes, the tissue where those genes are expressed and the environment. The light microscope is a valuable tool to understand this complexity which will ultimately help researchers improve the tolerance of plants to freezing st...
Loneliness in Adolescence: Gene x Environment Interactions Involving the Serotonin Transporter Gene
ERIC Educational Resources Information Center
van Roekel, Eeske; Scholte, Ron H. J.; Verhagen, Maaike; Goossens, Luc; Engels, Rutger C. M. E.
2010-01-01
Background: Loneliness is assumed to peak in early adolescence and to decrease throughout middle and late adolescence, but longitudinal confirmation of this tendency is lacking. Behavioral genetic studies with twin designs have found a significant genetic component for loneliness in children and adults, but no molecular genetic studies have been…
ERIC Educational Resources Information Center
Bogdan, Ryan; Agrawal, Arpana; Gaffrey, Michael S.; Tillman, Rebecca; Luby, Joan L.
2014-01-01
Background: Scientific enthusiasm about gene × environment interactions, spurred by the 5-HTTLPR (serotonin transporter-linked polymorphic region) × SLEs (stressful life events) interaction predicting depression, have recently been tempered by sober realizations of small effects and meta-analyses reaching opposing conclusions. These mixed findings…
Shame and Guilt-Proneness in Adolescents: Gene-Environment Interactions
Szentágotai-Tătar, Aurora; Chiș, Adina; Vulturar, Romana; Dobrean, Anca; Cândea, Diana Mirela; Miu, Andrei C.
2015-01-01
Rooted in people’s preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology. PMID:26230319
Shame and Guilt-Proneness in Adolescents: Gene-Environment Interactions.
Szentágotai-Tătar, Aurora; Chiș, Adina; Vulturar, Romana; Dobrean, Anca; Cândea, Diana Mirela; Miu, Andrei C
2015-01-01
Rooted in people's preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology.
Gene-environment interaction and male reproductive function
Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L.; Rylander, Lars; Giwercman, Aleksander
2010-01-01
As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism, but the number of studies is still limited. This type of interaction studies may improve our understanding of normal physiology and help us to identify the risk factors to male reproductive malfunction. We also shortly discuss other aspects of gene-environment interaction specifically associated with the issue of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity in the offspring. PMID:20348940
Combinatory approaches prevent preterm birth profoundly exacerbated by gene-environment interactions
Cha, Jeeyeon; Bartos, Amanda; Egashira, Mahiro; Haraguchi, Hirofumi; Saito-Fujita, Tomoko; Leishman, Emma; Bradshaw, Heather; Dey, Sudhansu K.; Hirota, Yasushi
2013-01-01
There are currently more than 15 million preterm births each year. We propose that gene-environment interaction is a major contributor to preterm birth. To address this experimentally, we generated a mouse model with uterine deletion of Trp53, which exhibits approximately 50% incidence of spontaneous preterm birth due to premature decidual senescence with increased mTORC1 activity and COX2 signaling. Here we provide evidence that this predisposition provoked preterm birth in 100% of females exposed to a mild inflammatory insult with LPS, revealing the high significance of gene-environment interactions in preterm birth. More intriguingly, preterm birth was rescued in LPS-treated Trp53-deficient mice when they were treated with a combination of rapamycin (mTORC1 inhibitor) and progesterone (P4), without adverse effects on maternal or fetal health. These results provide evidence for the cooperative contributions of two sites of action (decidua and ovary) toward preterm birth. Moreover, a similar signature of decidual senescence with increased mTORC1 and COX2 signaling was observed in women undergoing preterm birth. Collectively, our findings show that superimposition of inflammation on genetic predisposition results in high incidence of preterm birth and suggest that combined treatment with low doses of rapamycin and P4 may help reduce the incidence of preterm birth in high-risk women. PMID:23979163
Humblet, Olivier; Korrick, Susan A; Williams, Paige L; Sergeyev, Oleg; Emond, Claude; Birnbaum, Linda S; Burns, Jane S; Altshul, Larisa M; Patterson, Donald G; Turner, Wayman E; Lee, Mary M; Revich, Boris; Hauser, Russ
2013-01-01
Exposure to dioxins has been associated with delayed pubertal onset in both epidemiologic and animal studies. Whether genetic polymorphisms may modify this association is currently unknown. Identifying such genes could provide insight into mechanistic pathways. This is one of the first studies to assess genetic susceptibility to dioxins. We evaluated whether common polymorphisms in genes affecting either molecular responses to dioxin exposure or pubertal onset influence the association between peripubertal serum dioxin concentration and male pubertal onset. In this prospective cohort of Russian adolescent boys (n = 392), we assessed gene-environment interactions for 337 tagging single-nucleotide polymorphisms (SNPs) from 46 candidate genes and two intergenic regions. Dioxins were measured in the boys' serum at age 8-9 years. Pubertal onset was based on testicular volume and on genitalia staging. Statistical approaches for controlling for multiple testing were used, both with and without prescreening for marginal genetic associations. After accounting for multiple testing, two tag SNPs in the glucocorticoid receptor (GR/NR3C1) gene and one in the estrogen receptor-α (ESR1) gene were significant (q < 0.2) modifiers of the association between peripubertal serum dioxin concentration and male pubertal onset defined by genitalia staging, although not by testicular volume. The results were sensitive to whether multiple comparison adjustment was applied to all gene-environment tests or only to those with marginal genetic associations. Common genetic polymorphisms in the glucocorticoid receptor and estrogen receptor-α genes may modify the association between peripubertal serum dioxin concentration and pubertal onset. Further studies are warranted to confirm these findings.
Knafo-Noam, Ariel; Vertsberger, Dana; Israel, Salomon
2018-04-01
Children's prosocial behaviors show considerable variability. Here we discuss the genetic and environmental contributions to individual differences in children's prosocial behavior. Twin research systematically shows, at least from the age of 3 years, a genetic contribution to individual differences in prosocial behavior, both questionnaire-based and observed. This finding is demonstrated across a wide variety of cultures. We discuss the possibility that different prosocial behaviors have different genetic etiologies. A re-analysis of past twin data shows that sharing and comforting are affected by overlapping genetic factors at age 3.5 years. In contrast, the association between helping and comforting is attributed to environmental factors. The few molecular genetic studies of children's prosocial behavior are reviewed, and we point out genome-wide and polygenic methods as a key future direction. Finally, we discuss the interplay of genetic and environmental factors, focusing on both gene×environment interactions and gene-environment correlations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bridging the gap between research into biological and psychosocial models of psychosis.
Murray, Robin M; Sideli, Lucia; LA Cascia, Caterina; LA Barbera, Daniele
2015-06-25
Paul Bebbington's recent Special Article provides an excellent synthesis of recent advances in psychosocial research on psychosis. However, we doubt that a model based solely on social epidemiology and cognitive theory can totally describe psychosis, and to be fair, Bebbington does not suggest that it does. A complete model must also incorporate what we have learned from non-social epidemiology, neuroscience, and genetics. Evidence indicates that both the social risk factors that interest Bebbington and biological risk factors, such as abuse of stimulants and cannabis, can provoke psychotic symptoms by dysregulating striatal dopamine. The role of neurodevelopmental deviance also needs to be considered in the etiology of schizophrenia-like psychosis. Moreover, the striking advances in our understanding of the genetic architecture of psychosis open an exciting door into studies examining gene-environment correlation and gene-environment interaction. In short, Bebbington demonstrates the value of cognitive and social researchers talking to each other, but the occasional chat with the more biologically inclined could produce a more comprehensive model.
Topology association analysis in weighted protein interaction network for gene prioritization
NASA Astrophysics Data System (ADS)
Wu, Shunyao; Shao, Fengjing; Zhang, Qi; Ji, Jun; Xu, Shaojie; Sun, Rencheng; Sun, Gengxin; Du, Xiangjun; Sui, Yi
2016-11-01
Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.
Kim, Daniel S.; Burt, Amber A.; Ranchalis, Jane E.; Jarvik, Ella R.; Rosenthal, Elisabeth A.; Hatsukami, Thomas S.; Furlong, Clement E.; Jarvik, Gail P.
2013-01-01
Cardiovascular disease (CVD) is the leading cause of death in developed countries. Plasma cholesterol level is a key risk factor in CVD pathogenesis. Genetic and dietary variation both influence plasma cholesterol; however, little is known about dietary interactions with genetic variants influencing the absorption and transport of dietary cholesterol. We sought to determine whether gut expressed variants predicting plasma cholesterol differentially affected the relationship between dietary and plasma cholesterol levels in 1,128 subjects (772/356 in the discovery/replication cohorts, respectively). Four single nucleotide polymorphisms (SNPs) within three genes (APOB, CETP, and NPC1L1) were significantly associated with plasma cholesterol in the discovery cohort. These were subsequently evaluated for gene-by-environment (GxE) interactions with dietary cholesterol for the prediction of plasma cholesterol, with significant findings tested for replication. Novel GxE interactions were identified and replicated for two variants: rs1042034, an APOB Ser4338Asn missense SNP and rs2072183 (in males only), a synonymous NPC1L1 SNP in linkage disequilibrium with SNPs 5′ of NPC1L1. This study identifies the presence of novel GxE and gender interactions implying that differential gut absorption is the basis for the variant associations with plasma cholesterol. These GxE interactions may account for part of the “missing heritability” not accounted for by genetic associations. PMID:23482652
Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.
Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S; Mefford, Joel A; Zaitlen, Noah; Weiss, Lauren A
2017-02-01
Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene-sex interaction at autosomal loci, major contribution of the X-chromosome, or gene-environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10 -9 ). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. Copyright © 2017 by the Genetics Society of America.
Nurturing nature: social experiences and the brain.
Champagne, Frances A
2009-10-01
Summary How does 'nurture' change the brain? Recent evidence suggests that maternal care may shape the infant brain by turning genes 'on' or 'off' during development. Some of the genes affected are important for maternal and social behaviour leading to long-term changes in the nurturing behaviour of offspring. These studies provide new insights into the inheritance of behaviour and the interactions between genes and the social environment across the lifespan.
Gref, Anna; Merid, Simon K; Gruzieva, Olena; Ballereau, Stéphane; Becker, Allan; Bellander, Tom; Bergström, Anna; Bossé, Yohan; Bottai, Matteo; Chan-Yeung, Moira; Fuertes, Elaine; Ierodiakonou, Despo; Jiang, Ruiwei; Joly, Stéphane; Jones, Meaghan; Kobor, Michael S; Korek, Michal; Kozyrskyj, Anita L; Kumar, Ashish; Lemonnier, Nathanaël; MacIntyre, Elaina; Ménard, Camille; Nickle, David; Obeidat, Ma'en; Pellet, Johann; Standl, Marie; Sääf, Annika; Söderhäll, Cilla; Tiesler, Carla M T; van den Berge, Maarten; Vonk, Judith M; Vora, Hita; Xu, Cheng-Jian; Antó, Josep M; Auffray, Charles; Brauer, Michael; Bousquet, Jean; Brunekreef, Bert; Gauderman, W James; Heinrich, Joachim; Kere, Juha; Koppelman, Gerard H; Postma, Dirkje; Carlsten, Christopher; Pershagen, Göran; Melén, Erik
2017-05-15
The evidence supporting an association between traffic-related air pollution exposure and incident childhood asthma is inconsistent and may depend on genetic factors. To identify gene-environment interaction effects on childhood asthma using genome-wide single-nucleotide polymorphism (SNP) data and air pollution exposure. Identified loci were further analyzed at epigenetic and transcriptomic levels. We used land use regression models to estimate individual air pollution exposure (represented by outdoor NO 2 levels) at the birth address and performed a genome-wide interaction study for doctors' diagnoses of asthma up to 8 years in three European birth cohorts (n = 1,534) with look-up for interaction in two separate North American cohorts, CHS (Children's Health Study) and CAPPS/SAGE (Canadian Asthma Primary Prevention Study/Study of Asthma, Genetics and Environment) (n = 1,602 and 186 subjects, respectively). We assessed expression quantitative trait locus effects in human lung specimens and blood, as well as associations among air pollution exposure, methylation, and transcriptomic patterns. In the European cohorts, 186 SNPs had an interaction P < 1 × 10 -4 and a look-up evaluation of these disclosed 8 SNPs in 4 loci, with an interaction P < 0.05 in the large CHS study, but not in CAPPS/SAGE. Three SNPs within adenylate cyclase 2 (ADCY2) showed the same direction of the interaction effect and were found to influence ADCY2 gene expression in peripheral blood (P = 4.50 × 10 -4 ). One other SNP with P < 0.05 for interaction in CHS, rs686237, strongly influenced UDP-Gal:betaGlcNAc β-1,4-galactosyltransferase, polypeptide 5 (B4GALT5) expression in lung tissue (P = 1.18 × 10 -17 ). Air pollution exposure was associated with differential discs, large homolog 2 (DLG2) methylation and expression. Our results indicated that gene-environment interactions are important for asthma development and provided supportive evidence for interaction with air pollution for ADCY2, B4GALT5, and DLG2.
Díaz-Mejía, J Javier; Celaj, Albi; Mellor, Joseph C; Coté, Atina; Balint, Attila; Ho, Brandon; Bansal, Pritpal; Shaeri, Fatemeh; Gebbia, Marinella; Weile, Jochen; Verby, Marta; Karkhanina, Anna; Zhang, YiFan; Wong, Cassandra; Rich, Justin; Prendergast, D'Arcy; Gupta, Gaurav; Öztürk, Sedide; Durocher, Daniel; Brown, Grant W; Roth, Frederick P
2018-05-28
Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1 , SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.
A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity
Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.
2014-01-01
Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837
van der Deen, Margaretha; Hassan, Mohammad Q; Pratap, Jitesh; Teplyuk, Nadiya M; Young, Daniel W; Javed, Amjad; Zaidi, Sayyed K; Lian, Jane B; Montecino, Martin; Stein, Janet L; Stein, Gary S; van Wijnen, Andre J
2008-01-01
Normal cell growth and differentiation of bone cells requires the sequential expression of cell type specific genes to permit lineage specification and development of cellular phenotypes. Transcriptional activation and repression of distinct sets of genes support the anabolic functions of osteoblasts and the catabolic properties of osteoclasts. Furthermore, metastasis of tumors to the bone environment is controlled by transcriptional mechanisms. Insights into the transcriptional regulation of genes in bone cells may provide a conceptual basis for improved therapeutic approaches to treat bone fractures, genetic osteopathologies, and/or cancer metastases to bone. Chromatin immunoprecipitation (ChIP) is a powerful technique to establish in vivo binding of transcription factors to the promoters of genes that are either activated or repressed in bone cells. Combining ChIP with genomic microarray analysis, colloquially referred to as "ChIP-on-chip," has become a valuable method for analysis of endogenous protein/DNA interactions. This technique permits assessment of chromosomal binding sites for transcription factors or the location of histone modifications at a genomic scale. This chapter discusses protocols for performing chromatin immunoprecipitation experiments, with a focus on ChIP-on-chip analysis. The information presented is based on the authors' experience with defining interactions of Runt-related (RUNX) transcription factors with bone-related genes within the context of the native nucleosomal organization of intact osteoblastic cells.
Yildirim, Bariş O; Derksen, Jan J L
2013-08-01
Since its theoretical inception, psychopathy has been considered by philosophers, clinicians, theorists, and empirical researchers to be substantially and critically explained by genetic factors. In this systematic review and structural analysis, new hypotheses will be introduced regarding gene-gene and gene-environment interactions in the etiology of psychopathy and sociopathy. Theory and research from neurobiological and behavioral sciences will be integrated in order to place this work in a broader conceptual framework and promote synergy across fields. First, a between groups comparison between psychopathy and sociopathy is made based on their specific dysfunctions in emotional processing, behavioral profiles, etiological pathways, HPA-axis functioning, and serotonergic profiles. Next, it is examined how various polymorphisms in serotonergic genes (e.g., TPH, 5HTT, HTR1A, HTR2A, HTR2C, and HTR3) might contribute either individually or interactively to the development of these disorders and through which specific biological and behavioral endophenotypes this effect could be mediated. A short introduction is made into mediating variables such as GABAergic functioning and testosterone which could potentially alter the decisive effect of serotonergic genotypes on behavior and physiology. Finally, critical commentary is presented on how to interpret the hypotheses put forward in this review. Copyright © 2013 Elsevier Ltd. All rights reserved.
A human functional protein interaction network and its application to cancer data analysis
2010-01-01
Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850
An integrative model of evolutionary covariance: a symposium on body shape in fishes.
Walker, Jeffrey A
2010-12-01
A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).
Orteiza, N; Linder, J E; Rice, W R
2005-09-01
The empirical foundation for sexual conflict theory is the data from many different taxa demonstrating that females are harmed while interacting with males. However, the interpretation of this keystone evidence has been challenged because females may more than counterbalance the direct costs of interacting with males by the indirect benefits of obtaining higher quality genes for their offspring. A quantification of this trade-off is critical to resolve the controversy and is presented here. A multi-generation fitness assay in the Drosophila melanogaster laboratory model system was used to quantify both the direct costs to females due to interactions with males and indirect benefits via sexy sons. We specifically focus on the interactions that occur between males and nonvirgin females. In the laboratory environment of our base population, females mate soon after eclosion and store sufficient sperm for their entire lifetime, yet males persistently court these nonvirgin females and frequently succeed in re-mating them. Females may benefit from these interactions despite direct costs to their lifetime fecundity if re-mating allows them to trade-up to mates of higher genetic quality and thereby secure indirect benefits for their offspring. We found that direct costs of interactions between males and nonvirgin females substantially exceeded indirect benefits through sexy sons. These data, in combination with past studies of the good genes route of indirect benefits, demonstrate that inter-sexual interactions drive sexually antagonistic co-evolution in this model system.
Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences
Huynen, Martijn; Snel, Berend; Lathe, Warren; Bork, Peer
2000-01-01
Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes. PMID:10958638
Bouret, Sebastien; Levin, Barry E.; Ozanne, Susan E.
2015-01-01
Obesity and type 2 diabetes mellitus (T2DM) often occur together and affect a growing number of individuals in both the developed and developing worlds. Both are associated with a number of other serious illnesses that lead to increased rates of mortality. There is likely a polygenic mode of inheritance underlying both disorders, but it has become increasingly clear that the pre- and postnatal environments play critical roles in pushing predisposed individuals over the edge into a disease state. This review focuses on the many genetic and environmental variables that interact to cause predisposed individuals to become obese and diabetic. The brain and its interactions with the external and internal environment are a major focus given the prominent role these interactions play in the regulation of energy and glucose homeostasis in health and disease. PMID:25540138
Gene-by-Socioeconomic Status Interaction on School Readiness
Rhemtulla, Mijke; Tucker-Drob, Elliot M.
2017-01-01
In previous work with a nationally representative sample of over 1,400 monozygotic and dizygotic twins born in the United States, Tucker-Drob, Rhemtulla, Harden, Turkheimer, and Fask (2011; Psychological Science, 22, 125–133) uncovered a gene × environment interaction on scores on the Bayley Short Form test of mental ability at 2 years of age—higher socioeconomic status (SES) was associated not only with higher mental ability, but also with larger genetic contributions to individual differences in mental ability. The current study examined gene × SES interactions in mathematics skill and reading skill at 4 years of age (preschool age) in the same sample of twins, and further examined whether interactions detected at 4 years could be attributed to the persistence of the interaction previously observed at 2 years. For early mathematics skill but not early reading skill, genetic influences were more pronounced at higher levels of SES. This interaction was not accounted for by the interaction observed at 2 years. These findings indicate that SES moderates the etiological influences on certain cognitive functions at multiple stages of child development. PMID:22350185
Mirkovic, Bojan; Laurent, Claudine; Podlipski, Marc-Antoine; Frebourg, Thierry; Cohen, David; Gerardin, Priscille
2016-01-01
Suicidal behaviors (SBs), which range from suicidal ideation to suicide attempts and completed suicide, represent a fatal dimension of mental ill-health. The involvement of genetic risk factors in SB is supported by family, twin, and adoption studies. The aim of this paper is to review recent genetic association studies in SBs including (i) case–control studies, (ii) family-based association studies, and (iii) genome-wide association studies (GWAS). Various studies on genetic associations have tended to suggest that a number of genes [e.g., tryptophan hydroxylase, serotonin receptors and transporters, or brain-derived neurotrophic factors (BDNFs)] are linked to SBs, but these findings are not consistently supported by the results obtained. Although the candidate–gene approach is useful, it is hampered by the present state of knowledge concerning the pathophysiology of diseases. Interpretations of GWAS results are mostly hindered by a lack of annotation describing the functions of most variation throughout the genome. Association studies have addressed a wide range of single-nucleotide polymorphisms in numerous genes. We have included 104 such studies, of which 10 are family-based association studies and 11 are GWAS. Numerous meta-analyses of case–control studies have shown significant associations of SB with variants in the serotonin transporter gene (5-HTT or SLC6A4) and the tryptophan hydroxylase 1 gene (TPH1), but others report contradictory results. The gene encoding BDNF and its receptor (NTRK2) are also promising candidates. Only two of the GWAS showed any significant associations. Several pathways are mentioned in an attempt to understand the lack of reproducibility and the disappointing results. Consequently, we review and discuss here the following aspects: (i) sample characteristics and confounding factors; (ii) statistical limits; (iii) gene–gene interactions; (iv) gene, environment, and by time interactions; and (v) technological and theoretical limits. PMID:27721799
Sasaki, Joni Y; Kim, Heejung S; Mojaverian, Taraneh; Kelley, Lauren D S; Park, In Young; Janusonis, Skirmantas
2013-02-01
Building on gene-environment interaction (G × E) research, this study examines how the dopamine D4 receptor (DRD4) gene interacts with a situational prime of religion to influence prosocial behavior. Some DRD4 variants tend to be more susceptible to environmental influences, whereas other variants are less susceptible. Thus, certain life environments may be associated with acts of prosociality for some DRD4 variants but not others. Given that religion can act as an environmental influence that increases prosocial behavior, environmental input in the form of religion priming may have G × E effects. Results showed that participants with DRD4 susceptibility variants were more prosocial when implicitly primed with religion than not primed with religion, whereas participants without DRD4 susceptibility variants were not impacted by priming. This research has implications for understanding why different people may behave prosocially for different reasons and also integrates G × E research with experimental psychology.
Genomic features of bacterial adaptation to plants
Levy, Asaf; Salas Gonzalez, Isai; Mittelviefhaus, Maximilian; ...
2017-12-18
Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. In this study, we sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and themore » other serving in microbe–microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. In conclusion, this work expands the genome-based understanding of plant–microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering.« less
Genomic features of bacterial adaptation to plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levy, Asaf; Salas Gonzalez, Isai; Mittelviefhaus, Maximilian
Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. In this study, we sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and themore » other serving in microbe–microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. In conclusion, this work expands the genome-based understanding of plant–microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering.« less
Schizophrenia, vitamin D, and brain development.
Mackay-Sim, Alan; Féron, François; Eyles, Darryl; Burne, Thomas; McGrath, John
2004-01-01
Schizophrenia research is invigorated at present by the recent discovery of several plausible candidate susceptibility genes identified from genetic linkage and gene expression studies of brains from persons with schizophrenia. It is a current challenge to reconcile this gathering evidence for specific candidate susceptibility genes with the "neurodevelopmental hypothesis," which posits that schizophrenia arises from gene-environment interactions that disrupt brain development. We make the case here that schizophrenia may result not from numerous genes of small effect, but a few genes of transcriptional regulation acting during brain development. In particular we propose that low vitamin D during brain development interacts with susceptibility genes to alter the trajectory of brain development, probably by epigenetic regulation that alters gene expression throughout adult life. Vitamin D is an attractive "environmental" candidate because it appears to explain several key epidemiological features of schizophrenia. Vitamin D is an attractive "genetic" candidate because its nuclear hormone receptor regulates gene expression and nervous system development. The polygenic quality of schizophrenia, with linkage to many genes of small effect, maybe brought together via this "vitamin D hypothesis." We also discuss the possibility of a broader set of environmental and genetic factors interacting via the nuclear hormone receptors to affect the development of the brain leading to schizophrenia.
Jiang, Yushi; Bachner-Melman, Rachel; Chew, Soo Hong; Ebstein, Richard P
2015-01-01
On a large sample of 2288 Han Chinese undergraduates, we investigated how religion and DRD4 are related to human altruistic giving behavior as measured with the Andreoni-Miller Dictator Game. This game enables us to clearly specify (non-)selfishness, efficiency, and fairness motives for sharing. Participants were further classified into religious categories (Christian, Buddhist-Tao, and No Religion) based on self-reports, and genotyped for the dopamine D4 receptor (DRD4) gene exon III VNTR. Our analysis revealed a significant interaction between religion and DRD4 correlated with giving behavior solely among males: Whereas no significant association between religion and sharing decisions was observed in the majority 4R/4R genotype group, a significant difference in giving behavior between Christian and non-Christian males was seen in the non-4R/4R group, with Christian men being overall more altruistic (less selfish and fairer) than non-Christian men. These results support the vantage sensitivity hypothesis regarding DRD4 that the non-4R/4R "susceptibility" genotype is more responsive to a positive environment provided by some religions.
Jiang, Yushi; Bachner-Melman, Rachel; Chew, Soo Hong; Ebstein, Richard P.
2015-01-01
On a large sample of 2288 Han Chinese undergraduates, we investigated how religion and DRD4 are related to human altruistic giving behavior as measured with the Andreoni-Miller Dictator Game. This game enables us to clearly specify (non-)selfishness, efficiency, and fairness motives for sharing. Participants were further classified into religious categories (Christian, Buddhist-Tao, and No Religion) based on self-reports, and genotyped for the dopamine D4 receptor (DRD4) gene exon III VNTR. Our analysis revealed a significant interaction between religion and DRD4 correlated with giving behavior solely among males: Whereas no significant association between religion and sharing decisions was observed in the majority 4R/4R genotype group, a significant difference in giving behavior between Christian and non-Christian males was seen in the non-4R/4R group, with Christian men being overall more altruistic (less selfish and fairer) than non-Christian men. These results support the vantage sensitivity hypothesis regarding DRD4 that the non-4R/4R “susceptibility” genotype is more responsive to a positive environment provided by some religions. PMID:26441510
A molecular study of microbe transfer between distant environments.
Hooper, Sean D; Raes, Jeroen; Foerstner, Konrad U; Harrington, Eoghan D; Dalevi, Daniel; Bork, Peer
2008-07-09
Environments and their organic content are generally not static and isolated, but in a constant state of exchange and interaction with each other. Through physical or biological processes, organisms, especially microbes, may be transferred between environments whose characteristics may be quite different. The transferred microbes may not survive in their new environment, but their DNA will be deposited. In this study, we compare two environmental sequencing projects to find molecular evidence of transfer of microbes over vast geographical distances. By studying synonymous nucleotide composition, oligomer frequency and orthology between predicted genes in metagenomics data from two environments, terrestrial and aquatic, and by correlating with phylogenetic mappings, we find that both environments are likely to contain trace amounts of microbes which have been far removed from their original habitat. We also suggest a bias in direction from soil to sea, which is consistent with the cycles of planetary wind and water. Our findings support the Baas-Becking hypothesis formulated in 1934, which states that due to dispersion and population sizes, microbes are likely to be found in widely disparate environments. Furthermore, the availability of genetic material from distant environments is a possible font of novel gene functions for lateral gene transfer.
A Molecular Study of Microbe Transfer between Distant Environments
Hooper, Sean D.; Raes, Jeroen; Foerstner, Konrad U.; Harrington, Eoghan D.; Dalevi, Daniel; Bork, Peer
2008-01-01
Background Environments and their organic content are generally not static and isolated, but in a constant state of exchange and interaction with each other. Through physical or biological processes, organisms, especially microbes, may be transferred between environments whose characteristics may be quite different. The transferred microbes may not survive in their new environment, but their DNA will be deposited. In this study, we compare two environmental sequencing projects to find molecular evidence of transfer of microbes over vast geographical distances. Methodology By studying synonymous nucleotide composition, oligomer frequency and orthology between predicted genes in metagenomics data from two environments, terrestrial and aquatic, and by correlating with phylogenetic mappings, we find that both environments are likely to contain trace amounts of microbes which have been far removed from their original habitat. We also suggest a bias in direction from soil to sea, which is consistent with the cycles of planetary wind and water. Conclusions Our findings support the Baas-Becking hypothesis formulated in 1934, which states that due to dispersion and population sizes, microbes are likely to be found in widely disparate environments. Furthermore, the availability of genetic material from distant environments is a possible font of novel gene functions for lateral gene transfer. PMID:18612393
Levallois, Patrick; Giguère, Yves; Nguile-Makao, Molière; Rodriguez, Manuel; Campagna, Céline; Tardif, Robert; Bureau, Alexandre
2016-01-01
Exposure to disinfection by-products (DBPs) during pregnancy was associated with reduced foetal growth. Genetic susceptibility might play a role, especially for genes encoding for the Cytochrome P450 (CYP2E1) and Glutathione S-Transferase (GST) enzymes, involved in metabolism and activation of DBPs. Few epidemiological studies evaluated these gene-environment interactions and their results were never replicated. This study aims to examine interactions between trihalomethanes (THM) or haloacetic acids (HAA) exposure and genetic polymorphisms on small for gestational age (SGA) neonates by investigating single nucleotide polymorphisms (SNPs) in CYP2E1 gene and GSTM1 and GSTT1 deletions in mothers-children pairs. A population-based case-control study of 1549 mothers and 1455 children was conducted on SGA and THM/HAA exposure. DNA was extracted from blood or saliva cells. Targeted SNPs and deletions were genotyped. Statistical interaction between SNPs/deletions and THMs or HAAs in utero exposure with regard to SGA occurrence was evaluated by unconditional logistic regression with control of potential confounders. Previously reported positive modification of the effect of THM uterine exposure by mothers or newborns CYP2E1 rs3813867 C allele or GSTM1 deletion was not replicated. However interactions with CYP2E1 rs117618383 and rs2515641 were observed but were not statistically significant after correction for multiple testing. Previous positive interactions between THMs exposure and CYP2E1 and GSTM1 were not replicated but interactions with other CYP2E1 polymorphisms are reported. Copyright © 2016 Elsevier Ltd. All rights reserved.
Levallois, Patrick; Giguère, Yves; Nguile-Makao, Molière; Rodriguez, Manuel; Campagna, Céline; Tardif, Robert; Bureau, Alexandre
2016-01-01
Background Exposure to disinfection by-products (DBPs) during pregnancy was associated with reduced fetal growth. Genetic susceptibility might play a role, especially for genes encoding for the Cytochrome P450 (CYP2E1) and Glutathione S-Transferase (GST) enzymes, involved in metabolism and activation of DBPs. Few epidemiological studies evaluated these gene-environment interactions and their results were never replicated. Objective This study aims to examine interactions between trihalomethanes (THM) or haloacetic acids (HAA) exposure and genetic polymorphisms on small for gestational age (SGA) neonates by investigating single nucleotide polymorphisms (SNPs) in CYP2E1 gene and GSTM1 and GSTT1 deletions in mothers-children pairs. Methods A population-based case-control study of 1549 mothers and 1455 children was conducted on SGA and THM/HAA exposure. DNA was extracted from blood or saliva cells. Targeted SNPs and deletions were genotyped. Statistical interaction between SNPs/deletions and THMs or HAAs in utero exposure with regard to SGA occurrence was evaluated by unconditional logistic regression with control of potential confounders. Results Previously reported positive modification of the effect of THM uterine exposure by mothers or newborns CYP2E1 rs3813867 C allele or GSTM1 deletion was not replicated. However interactions with CYP2E1 rs117618383 and rs2515641 were observed but were not statistically significant after correction for multiple testing. Conclusions Previous positive interactions between THMs exposure and CYP2E1 and GSTM1 were not replicated but interactions with other CYP2E1 polymorphisms are reported. PMID:27107227
ERIC Educational Resources Information Center
Gibb, Brandon E.; McGeary, John E.; Beevers, Christopher G.; Miller, Ivan W.
2006-01-01
There is growing evidence that a functional polymorphism in the serotonin transporter gene (5-HTTLPR) moderates the impact of negative life events (e.g., childhood abuse) on the development of depression. However, it is unclear whether the gene x environment interaction predicts suicide attempts specifically. In addition, previous studies have not…
USDA-ARS?s Scientific Manuscript database
While genome-wide association studies (GWAS) and candidate gene approach have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. The present study aimed to examine variance contribu...
Annual Research Review: Developmental Considerations of Gene by Environment Interactions
ERIC Educational Resources Information Center
Lenroot, Rhoshel K.; Giedd, Jay N.
2011-01-01
Biological development is driven by a complex dance between nurture and nature, determined not only by the specific features of the interacting genetic and environmental influences but also by the timing of their rendezvous. The initiation of large-scale longitudinal studies, ever-expanding knowledge of genetics, and increasing availability of…
The Behavioural Phenotype of Smith-Magenis Syndrome: Evidence for a Gene-Environment Interaction
ERIC Educational Resources Information Center
Taylor, L.; Oliver, C.
2008-01-01
Background: Behaviour problems and a preference for adult contact are reported to be prominent in the phenotype of Smith-Magenis syndrome. In this study we examined the relationship between social interactions and self-injurious and aggressive/disruptive behaviour in Smith-Magenis syndrome to explore potential operant reinforcement of problem…
Family Conflict Interacts with Genetic Liability in Predicting Childhood and Adolescent Depression
ERIC Educational Resources Information Center
Rice, Frances; Harold, Gordon T.; Shelton, Katherine H.; Thapar, Anita
2006-01-01
Objective: To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms…
ERIC Educational Resources Information Center
Choudhry, Zia; Sengupta, Sarojini M.; Grizenko, Natalie; Fortier, Marie-Eve; Thakur, Geeta A.; Bellingham, Johanne; Joober, Ridha
2012-01-01
Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous behavioral disorder, complex both in etiology and clinical expression. Both genetic and environmental factors have been implicated, and it has been suggested that gene-environment interactions may play a pivotal role in the disorder. Recently, a significant association…
Fan, Qiao; Verhoeven, Virginie J M; Wojciechowski, Robert; Barathi, Veluchamy A; Hysi, Pirro G; Guggenheim, Jeremy A; Höhn, René; Vitart, Veronique; Khawaja, Anthony P; Yamashiro, Kenji; Hosseini, S Mohsen; Lehtimäki, Terho; Lu, Yi; Haller, Toomas; Xie, Jing; Delcourt, Cécile; Pirastu, Mario; Wedenoja, Juho; Gharahkhani, Puya; Venturini, Cristina; Miyake, Masahiro; Hewitt, Alex W; Guo, Xiaobo; Mazur, Johanna; Huffman, Jenifer E; Williams, Katie M; Polasek, Ozren; Campbell, Harry; Rudan, Igor; Vatavuk, Zoran; Wilson, James F; Joshi, Peter K; McMahon, George; St Pourcain, Beate; Evans, David M; Simpson, Claire L; Schwantes-An, Tae-Hwi; Igo, Robert P; Mirshahi, Alireza; Cougnard-Gregoire, Audrey; Bellenguez, Céline; Blettner, Maria; Raitakari, Olli; Kähönen, Mika; Seppala, Ilkka; Zeller, Tanja; Meitinger, Thomas; Ried, Janina S; Gieger, Christian; Portas, Laura; van Leeuwen, Elisabeth M; Amin, Najaf; Uitterlinden, André G; Rivadeneira, Fernando; Hofman, Albert; Vingerling, Johannes R; Wang, Ya Xing; Wang, Xu; Tai-Hui Boh, Eileen; Ikram, M Kamran; Sabanayagam, Charumathi; Gupta, Preeti; Tan, Vincent; Zhou, Lei; Ho, Candice E H; Lim, Wan'e; Beuerman, Roger W; Siantar, Rosalynn; Tai, E-Shyong; Vithana, Eranga; Mihailov, Evelin; Khor, Chiea-Chuen; Hayward, Caroline; Luben, Robert N; Foster, Paul J; Klein, Barbara E K; Klein, Ronald; Wong, Hoi-Suen; Mitchell, Paul; Metspalu, Andres; Aung, Tin; Young, Terri L; He, Mingguang; Pärssinen, Olavi; van Duijn, Cornelia M; Jin Wang, Jie; Williams, Cathy; Jonas, Jost B; Teo, Yik-Ying; Mackey, David A; Oexle, Konrad; Yoshimura, Nagahisa; Paterson, Andrew D; Pfeiffer, Norbert; Wong, Tien-Yin; Baird, Paul N; Stambolian, Dwight; Wilson, Joan E Bailey; Cheng, Ching-Yu; Hammond, Christopher J; Klaver, Caroline C W; Saw, Seang-Mei; Rahi, Jugnoo S; Korobelnik, Jean-François; Kemp, John P; Timpson, Nicholas J; Smith, George Davey; Craig, Jamie E; Burdon, Kathryn P; Fogarty, Rhys D; Iyengar, Sudha K; Chew, Emily; Janmahasatian, Sarayut; Martin, Nicholas G; MacGregor, Stuart; Xu, Liang; Schache, Maria; Nangia, Vinay; Panda-Jonas, Songhomitra; Wright, Alan F; Fondran, Jeremy R; Lass, Jonathan H; Feng, Sheng; Zhao, Jing Hua; Khaw, Kay-Tee; Wareham, Nick J; Rantanen, Taina; Kaprio, Jaakko; Pang, Chi Pui; Chen, Li Jia; Tam, Pancy O; Jhanji, Vishal; Young, Alvin L; Döring, Angela; Raffel, Leslie J; Cotch, Mary-Frances; Li, Xiaohui; Yip, Shea Ping; Yap, Maurice K H; Biino, Ginevra; Vaccargiu, Simona; Fossarello, Maurizio; Fleck, Brian; Yazar, Seyhan; Tideman, Jan Willem L; Tedja, Milly; Deangelis, Margaret M; Morrison, Margaux; Farrer, Lindsay; Zhou, Xiangtian; Chen, Wei; Mizuki, Nobuhisa; Meguro, Akira; Mäkelä, Kari Matti
2016-03-29
Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10(-5)), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia.
Sumner, Jennifer A; McLaughlin, Katie A; Walsh, Kate; Sheridan, Margaret A; Koenen, Karestan C
2015-03-03
A theory-driven confirmatory approach comparing diathesis-stress and differential susceptibility models of Gene × Environment (G × E) interactions was applied to examine whether 5-HTTLPR genotype moderated the effect of early maternal caregiving on autonomic nervous system (ANS) stress reactivity in 113 adolescents aged 13-17 years. Findings supported a differential susceptibility, rather than diathesis-stress, framework. Carriers of one or more 5-HTTLPR short alleles (SS/SL carriers) reporting higher quality caregiving exhibited approach ANS responses to a speech task, whereas those reporting lower quality caregiving exhibited withdrawal ANS responses. Carriers of two 5-HTTLPR long alleles (LL carriers) were unaffected by caregiving. Findings suggest that 5-HTTLPR genotype and early caregiving in interaction are associated with ANS stress reactivity in adolescents in a "for better and for worse" fashion, and they demonstrate the promise of confirmatory methods for testing G × E interactions. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.