Incorporating gene-environment interaction in testing for association with rare genetic variants.

PubMed

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.

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

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.

Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease.

PubMed

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?

PubMed

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.

Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.

PubMed

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.

Environmental confounding in gene-environment interaction studies.

PubMed

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.

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

PubMed

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.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

PubMed

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.

Gene-environment interactions in mental disorders

PubMed Central

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 Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

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.

MAOA, childhood maltreatment and antisocial behavior: Meta-analysis of a gene-environment interaction

PubMed Central

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

MAOA, childhood maltreatment, and antisocial behavior: meta-analysis of a gene-environment interaction.

PubMed

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 developmental origins of externalizing behavioral problems: parental disengagement and the role of gene-environment interplay.

PubMed

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.

A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.

PubMed

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.

Interaction between Calpain 5, Peroxisome proliferator-activated receptor-gamma and Peroxisome proliferator-activated receptor-delta genes: a polygenic approach to obesity

PubMed Central

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

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

PubMed Central

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

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

PubMed

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.

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

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

PubMed Central

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

Explaining human uniqueness: genome interactions with environment, behaviour and culture.

PubMed

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.

Gene Polymorphism Association with Type 2 Diabetes and Related Gene-Gene and Gene-Environment Interactions in a Uyghur Population

PubMed Central

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

Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.

PubMed

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.

BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction.

PubMed

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.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children.

PubMed

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.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

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.

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

PubMed

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.

Gene-environment interaction and suicidal behavior.

PubMed

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.

System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

PubMed Central

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

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

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.

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…

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...

Tightly Regulated Expression of Autographa californica Multicapsid Nucleopolyhedrovirus Immediate Early Genes Emerges from Their Interactions and Possible Collective Behaviors

PubMed Central

Taka, Hitomi; Asano, Shin-ichiro; Matsuura, Yoshiharu; Bando, Hisanori

2015-01-01

To infect their hosts, DNA viruses must successfully initiate the expression of viral genes that control subsequent viral gene expression and manipulate the host environment. Viral genes that are immediately expressed upon infection play critical roles in the early infection process. In this study, we investigated the expression and regulation of five canonical regulatory immediate-early (IE) genes of Autographa californica multicapsid nucleopolyhedrovirus: ie0, ie1, ie2, me53, and pe38. A systematic transient gene-expression analysis revealed that these IE genes are generally transactivators, suggesting the existence of a highly interactive regulatory network. A genetic analysis using gene knockout viruses demonstrated that the expression of these IE genes was tolerant to the single deletions of activator IE genes in the early stage of infection. A network graph analysis on the regulatory relationships observed in the transient expression analysis suggested that the robustness of IE gene expression is due to the organization of the IE gene regulatory network and how each IE gene is activated. However, some regulatory relationships detected by the genetic analysis were contradictory to those observed in the transient expression analysis, especially for IE0-mediated regulation. Statistical modeling, combined with genetic analysis using knockout alleles for ie0 and ie1, showed that the repressor function of ie0 was due to the interaction between ie0 and ie1, not ie0 itself. Taken together, these systematic approaches provided insight into the topology and nature of the IE gene regulatory network. PMID:25816136

Rigorous tests of gene-environment interactions in a lab study of the oxytocin receptor gene (OXTR), alcohol exposure, and aggression.

PubMed

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.

Folate and Breast Cancer: Role of Intake, Blood Levels, and Metabolic Gene Polymorphisms

DTIC Science & Technology

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

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

PubMed

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.

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors

PubMed Central

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 Interactions in Schizophrenia: Review of Epidemiological Findings and Future Directions

PubMed Central

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

Chapter 20: geographic variability in growth of forest trees

Treesearch

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...

International Cancer of the Head and Neck, Genetics and Environment (InterCHANGE) Study

ClinicalTrials.gov

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

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.…

Modification of the association between early adversity and obsessive-compulsive disorder by polymorphisms in the MAOA, MAOB and COMT genes.

PubMed

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

PubMed Central

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

Explaining human uniqueness: genome interactions with environment, behaviour and culture

PubMed Central

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

Interaction between nonsynonymous polymorphisms in PLA2G7 gene and smoking on the risk of coronary heart disease in a Chinese population.

PubMed

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.

Antisocial Peer Affiliation and Externalizing Disorders: Evidence for Gene × Environment × Development Interaction

PubMed Central

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

Antisocial peer affiliation and externalizing disorders: Evidence for Gene × Environment × Development interaction.

PubMed

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.

Gene-environment interaction on neural mechanisms of orthographic processing in Chinese children

PubMed Central

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

The Interacting Effect of the BDNF Val66Met Polymorphism and Stressful Life Events on Adolescent Depression Is Not an Artifact of Gene-Environment Correlation: Evidence from a Longitudinal Twin Study

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

PubMed Central

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

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

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.

Nature versus nurture: death of a dogma, and the road ahead.

PubMed

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.

3D Reconstruction of Frozen Plant Tissue: a unique histological analysis to image post-freeze responses

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...

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.

PubMed

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.

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

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.

The Impact of Gene-Environment Dependence and Misclassification in Genetic Association Studies Incorporating Gene-Environment Interactions

PubMed Central

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

The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

PubMed

Li, Shi; Mukherjee, Bhramar; Taylor, Jeremy M G; Rice, Kenneth M; Wen, Xiaoquan; Rice, John D; Stringham, Heather M; Boehnke, Michael

2014-07-01

With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes. © 2014 WILEY PERIODICALS, INC.

Analysis of Behavioral and Emotional Problems in Children Highlights the Role of Genotype × Environment Interaction.

PubMed

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.

Meta-analysis of gene-environment-wide association scans accounting for education level identifies additional loci for refractive error.

PubMed

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.

Genetics of borderline personality disorder: systematic review and proposal of an integrative model.

PubMed

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.

Genomic Analysis of Genotype-by-Social Environment Interaction for Drosophila melanogaster Aggressive Behavior.

PubMed

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.

Interaction between early-life stress and FKBP5 gene variants in major depressive disorder and post-traumatic stress disorder: A systematic review and meta-analysis.

PubMed

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.

[Association between MAOA-u VNTR polymorphism and its interaction with stressful life events and major depressive disorder in adolescents].

PubMed

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.

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

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.

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

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.

A Twin and Adoption Study of Reading Achievement: Exploration of Shared-Environmental and Gene-Environment-Interaction Effects

ERIC Educational Resources Information Center

Kirkpatrick, Robert M.; Legrand, Lisa N.; Iacono, William G.; McGue, Matt

2011-01-01

Existing behavior-genetic research implicates substantial influence of heredity and modest influence of shared environment on reading achievement and reading disability. Applying DeFries-Fulker analysis to a combined sample of twins and adoptees (N = 4886, including 266 reading-disabled probands), the present study replicates prior findings of…

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…

Genome-wide assessment of gene-by-smoking interactions in COPD.

PubMed

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.

Endothelial pro-atherosclerotic response to extracellular diabetic-like environment: possible role of thioredoxin-interacting protein.

PubMed

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.

The Tangled Tale of Genes and Environment: Moore's The Dependent Gene: The Fallacy of “nature VS. Nurture”

PubMed Central

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.

Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

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…

Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

PubMed Central

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

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status.

PubMed

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.

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status

PubMed Central

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

Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

PubMed

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.

Integration of statistical and physiological analyses of adaptation of near-isogenic barley lines.

PubMed

Romagosa, I; Fox, P N; García Del Moral, L F; Ramos, J M; García Del Moral, B; Roca de Togores, F; Molina-Cano, J L

1993-08-01

Seven near-isogenic barley lines, differing for three independent mutant genes, were grown in 15 environments in Spain. Genotype x environment interaction (G x E) for grain yield was examined with the Additive Main Effects and Multiplicative interaction (AMMI) model. The results of this statistical analysis of multilocation yield-data were compared with a morpho-physiological characterization of the lines at two sites (Molina-Cano et al. 1990). The first two principal component axes from the AMMI analysis were strongly associated with the morpho-physiological characters. The independent but parallel discrimination among genotypes reflects genetic differences and highlights the power of the AMMI analysis as a tool to investigate G x E. Characters which appear to be positively associated with yield in the germplasm under study could be identified for some environments.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

PubMed Central

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

Supportive Family Environments, Genes That Confer Sensitivity, and Allostatic Load Among Rural African American Emerging Adults: A Prospective Analysis

PubMed Central

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

Three Approaches to Modeling Gene-Environment Interactions in Longitudinal Family Data: Gene-Smoking Interactions in Blood Pressure.

PubMed

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.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children

PubMed Central

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

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting.

PubMed

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).

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

PubMed Central

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

Childhood Temperament: Passive Gene-Environment Correlation, Gene-Environment Interaction, and the Hidden Importance of the Family Environment

PubMed Central

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

Transcriptomic analysis of skin pigmentation variation in the Virginia opossum (Didelphis virginiana).

PubMed

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.

Enhancing the gene-environment interaction framework through a quasi-experimental research design: evidence from differential responses to September 11.

PubMed

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.

Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model—Recommendations From an NIH Workshop

PubMed Central

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

Effects of the Family Environment: Gene-Environment Interaction and Passive Gene-Environment Correlation

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…

A database of gene-environment interactions pertaining to blood lipid traits, cardiovascular disease and type 2 diabetes

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...

A combination test for detection of gene-environment interaction in cohort studies.

PubMed

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.

Evidence for Gender-Dependent Genotype by Environment Interaction in Adult Depression.

PubMed

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.

Genetic risk for violent behavior and environmental exposure to disadvantage and violent crime: the case for gene-environment interaction.

PubMed

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.

RNA-seq Analysis of Host and Viral Gene Expression Highlights Interaction between Varicella Zoster Virus and Keratinocyte Differentiation

PubMed Central

Singh, Manuraj; Kanda, Ravinder K.; Yee, Michael B.; Kellam, Paul; Hollinshead, Michael; Kinchington, Paul R.; O'Toole, Edel A.; Breuer, Judith

2014-01-01

Varicella zoster virus (VZV) is the etiological agent of chickenpox and shingles, diseases characterized by epidermal skin blistering. Using a calcium-induced keratinocyte differentiation model we investigated the interaction between epidermal differentiation and VZV infection. RNA-seq analysis showed that VZV infection has a profound effect on differentiating keratinocytes, altering the normal process of epidermal gene expression to generate a signature that resembles patterns of gene expression seen in both heritable and acquired skin-blistering disorders. Further investigation by real-time PCR, protein analysis and electron microscopy revealed that VZV specifically reduced expression of specific suprabasal cytokeratins and desmosomal proteins, leading to disruption of epidermal structure and function. These changes were accompanied by an upregulation of kallikreins and serine proteases. Taken together VZV infection promotes blistering and desquamation of the epidermis, both of which are necessary to the viral spread and pathogenesis. At the same time, analysis of the viral transcriptome provided evidence that VZV gene expression was significantly increased following calcium treatment of keratinocytes. Using reporter viruses and immunohistochemistry we confirmed that VZV gene and protein expression in skin is linked with cellular differentiation. These studies highlight the intimate host-pathogen interaction following VZV infection of skin and provide insight into the mechanisms by which VZV remodels the epidermal environment to promote its own replication and spread. PMID:24497829

Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment.

PubMed

Wang, Zhaoxi; Claus Henn, Birgit; Wang, Chaolong; Wei, Yongyue; Su, Li; Sun, Ryan; Chen, Han; Wagner, Peter J; Lu, Quan; Lin, Xihong; Wright, Robert; Bellinger, David; Kile, Molly; Mazumdar, Maitreyi; Tellez-Rojo, Martha Maria; Schnaas, Lourdes; Christiani, David C

2017-07-28

Neurodevelopment is a complex process involving both genetic and environmental factors. Prenatal exposure to lead (Pb) has been associated with lower performance on neurodevelopmental tests. Adverse neurodevelopmental outcomes are more frequent and/or more severe when toxic exposures interact with genetic susceptibility. To explore possible loci associated with increased susceptibility to prenatal Pb exposure, we performed a genome-wide gene-environment interaction study (GWIS) in young children from Mexico (n = 390) and Bangladesh (n = 497). Prenatal Pb exposure was estimated by cord blood Pb concentration. Neurodevelopment was assessed using the Bayley Scales of Infant Development. We identified a locus on chromosome 8, containing UNC5D, and demonstrated evidence of its genome-wide significance with mental composite scores (rs9642758, p meta  = 4.35 × 10 -6 ). Within this locus, the joint effects of two independent single nucleotide polymorphisms (SNPs, rs9642758 and rs10503970) had a p-value of 4.38 × 10 -9 for mental composite scores. Correlating GWIS results with in vitro transcriptomic profiles identified one common gene, SLC1A5, which is involved in synaptic function, neuronal development, and excitotoxicity. Further analysis revealed interconnected interactions that formed a large network of 52 genes enriched with oxidative stress genes and neurodevelopmental genes. Our findings suggest that certain genetic polymorphisms within/near genes relevant to neurodevelopment might modify the toxic effects of Pb exposure via oxidative stress.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface.

PubMed

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.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

PubMed Central

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

Gene by Social-Context Interactions for Number of Sexual Partners Among White Male Youths: Genetics-informed Sociology

PubMed Central

Guo, Guang; Tong, Yuying; Cai, Tianji

2010-01-01

In this study, we set out to investigate whether introducing molecular genetic measures into an analysis of sexual partner variety will yield novel sociological insights. The data source is the white male DNA sample in the National Longitudinal Study of Adolescent Health. Our empirical analysis has produced a robust protective effect of the 9R/9R genotype relative to the Any10R genotype in the dopamine transporter gene (DAT1). The gene-environment interaction analysis demonstrates that the protective effect of 9R/9R tends to be lost in schools in which higher proportions of students start having sex early or among those with relatively low levels of cognitive ability. Our genetics-informed sociological analysis suggests that the “one size” of a single social theory may not fit all. Explaining a human trait or behavior may require a theory that accommodates the complex interplay between social contextual and individual influences and genetic predispositions. PMID:19569400

Life events and borderline personality features: the influence of gene-environment interaction and gene-environment correlation.

PubMed

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.

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

Behavioral science and the study of gene-nutrition and gene-physical activity interactions in obesity research.

PubMed

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.

The case-only test for gene-environment interaction is not uniformly powerful: an empirical example

PubMed Central

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

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

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

On the use of sibling recurrence risks to select environmental factors liable to interact with genetic risk factors.

PubMed

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.

Gene-Environment Interactions across Development: Exploring DRD2 Genotype and Prenatal Smoking Effects on Self-Regulation

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…

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…

Genes and environment in neonatal intraventricular hemorrhage.

PubMed

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.

PubMed

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.

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

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/.

Effect of occupational exposures on lung cancer susceptibility: a study of gene-environment interaction analysis.

PubMed

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.

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

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

Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

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.

Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy.

PubMed

O'Reilly, Paul; Ortutay, Csaba; Gernon, Grainne; O'Connell, Enda; Seoighe, Cathal; Boyce, Susan; Serrano, Luis; Szegezdi, Eva

2014-12-19

Identification of differentially expressed genes from transcriptomic studies is one of the most common mechanisms to identify tumor biomarkers. This approach however is not well suited to identify interaction between genes whose protein products potentially influence each other, which limits its power to identify molecular wiring of tumour cells dictating response to a drug. Due to the fact that signal transduction pathways are not linear and highly interlinked, the biological response they drive may be better described by the relative amount of their components and their functional relationships than by their individual, absolute expression. Gene expression microarray data for 109 tumor cell lines with known sensitivity to the death ligand cytokine tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) was used to identify genes with potential functional relationships determining responsiveness to TRAIL-induced apoptosis. The machine learning technique Random Forest in the statistical environment "R" with backward elimination was used to identify the key predictors of TRAIL sensitivity and differentially expressed genes were identified using the software GeneSpring. Gene co-regulation and statistical interaction was assessed with q-order partial correlation analysis and non-rejection rate. Biological (functional) interactions amongst the co-acting genes were studied with Ingenuity network analysis. Prediction accuracy was assessed by calculating the area under the receiver operator curve using an independent dataset. We show that the gene panel identified could predict TRAIL-sensitivity with a very high degree of sensitivity and specificity (AUC=0·84). The genes in the panel are co-regulated and at least 40% of them functionally interact in signal transduction pathways that regulate cell death and cell survival, cellular differentiation and morphogenesis. Importantly, only 12% of the TRAIL-predictor genes were differentially expressed highlighting the importance of functional interactions in predicting the biological response. The advantage of co-acting gene clusters is that this analysis does not depend on differential expression and is able to incorporate direct- and indirect gene interactions as well as tissue- and cell-specific characteristics. This approach (1) identified a descriptor of TRAIL sensitivity which performs significantly better as a predictor of TRAIL sensitivity than any previously reported gene signatures, (2) identified potential novel regulators of TRAIL-responsiveness and (3) provided a systematic view highlighting fundamental differences between the molecular wiring of sensitive and resistant cell types.

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

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.

Exposure enriched outcome dependent designs for longitudinal studies of gene-environment interaction.

PubMed

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.

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

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.

Interaction of childhood urbanicity and variation in dopamine genes alters adult prefrontal function as measured by functional magnetic resonance imaging (fMRI).

PubMed

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.

Environmental stress alters genetic regulation of novelty seeking in vervet monkeys.

PubMed

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.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

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

Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status

PubMed Central

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

Gene and environment interaction: is the differential susceptibility hypothesis relevant for obesity?

PubMed Central

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

The Oxytocin Receptor Gene (OXTR) in Relation to State Levels of Loneliness in Adolescence: Evidence for Micro-Level Gene-Environment Interactions

PubMed Central

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

The oxytocin receptor gene (OXTR) in relation to state levels of loneliness in adolescence: evidence for micro-level gene-environment interactions.

PubMed

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.

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

PubMed Central

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

ISAAC - InterSpecies Analysing Application using Containers.

PubMed

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.

Genome Sequencing and Comparative Transcriptomics of the Model Entomopathogenic Fungi Metarhizium anisopliae and M. acridum

PubMed Central

Shang, Yanfang; Duan, Zhibing; Hu, Xiao; Xie, Xue-Qin; Zhou, Gang; Peng, Guoxiong; Luo, Zhibing; Huang, Wei; Wang, Bing; Fang, Weiguo; Wang, Sibao; Zhong, Yi; Ma, Li-Jun; St. Leger, Raymond J.; Zhao, Guo-Ping; Pei, Yan; Feng, Ming-Guang; Xia, Yuxian; Wang, Chengshu

2011-01-01

Metarhizium spp. are being used as environmentally friendly alternatives to chemical insecticides, as model systems for studying insect-fungus interactions, and as a resource of genes for biotechnology. We present a comparative analysis of the genome sequences of the broad-spectrum insect pathogen Metarhizium anisopliae and the acridid-specific M. acridum. Whole-genome analyses indicate that the genome structures of these two species are highly syntenic and suggest that the genus Metarhizium evolved from plant endophytes or pathogens. Both M. anisopliae and M. acridum have a strikingly larger proportion of genes encoding secreted proteins than other fungi, while ∼30% of these have no functionally characterized homologs, suggesting hitherto unsuspected interactions between fungal pathogens and insects. The analysis of transposase genes provided evidence of repeat-induced point mutations occurring in M. acridum but not in M. anisopliae. With the help of pathogen-host interaction gene database, ∼16% of Metarhizium genes were identified that are similar to experimentally verified genes involved in pathogenicity in other fungi, particularly plant pathogens. However, relative to M. acridum, M. anisopliae has evolved with many expanded gene families of proteases, chitinases, cytochrome P450s, polyketide synthases, and nonribosomal peptide synthetases for cuticle-degradation, detoxification, and toxin biosynthesis that may facilitate its ability to adapt to heterogenous environments. Transcriptional analysis of both fungi during early infection processes provided further insights into the genes and pathways involved in infectivity and specificity. Of particular note, M. acridum transcribed distinct G-protein coupled receptors on cuticles from locusts (the natural hosts) and cockroaches, whereas M. anisopliae transcribed the same receptor on both hosts. This study will facilitate the identification of virulence genes and the development of improved biocontrol strains with customized properties. PMID:21253567

Gene by Environment Interactions Influencing Reading Disability and the Inattentive Symptom Dimension of Attention Deficit/Hyperactivity Disorder

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…

Gene × Smoking Interactions on Human Brain Gene Expression: Finding Common Mechanisms in Adolescents and Adults

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…

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…

[The role of genotype in the intergenerational transmission of experiences of childhood adversity].

PubMed

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.

The interactive effects of genetic polymorphisms within LFA-1/ICAM-1/GSK-3β pathway and environmental hazards on the development of Graves' opthalmopathy.

PubMed

Yang, Ge; Fu, Yang; Lu, Xiaoyan; Wang, Menghua; Dong, Hongtao; Li, Qiuming

2018-05-22

The purpose of this investigation was to explore the combined effects of single nucleotide polymorphisms (SNPs) within LFA-1/ICAM-1/GSK-3β pathway and environmental hazards on susceptibility to Graves' opthalmopathy (GO) among a Chinese Han population. Altogether 305 GO patients and 283 Graves' disease (GD) subjects were recruited. Information relevant to the participants' age, gender, body mass index (BMI), regular physical activity, smoking history, alcohol intake, stressful work environment, stress at work, family history of thyroid disease and 131 I treatment were summarized, and the participants' related SNPs of LFA-1/ICAM-1/GSK-3β were also detected. Then the gene-gene and gene-environment interactions were evaluated by logistic regression model and multi-factor dimensionality reduction (MDR) modeling. The results exhibited that age, BMI, smoking history, stressful work, stress at home, family history of thyroid disease and 131 I treatment appeared as potential indicators regulating GO risk, when either univariate or multivariate regression analysis was performed (all P < 0.05). Moreover, rs12716977 (T > C) and rs2230433 (G > C) of LFA-1, rs1799969 (G > A) and rs5498 (A > G) of ICAM-1, as well as rs6438552 (T > C) and rs334558 (T > C) of GSK-3β were significantly associated with altered susceptibility to GO under the allelic models (all P < 0.05). Also haplotype TGAATC acted as a protective factor against GO risk (P < 0.05), whereas haplotype CGAACC largely elevated risk of GO (P < 0.05). Besides, logistic regression analysis demonstrated that rs12716927, rs5498 and rs6438552 all would affect the influences exerted by age, BMI, smoking history, stressful work, stress at home, family history of thyroid disease or 131 I treatment on GO susceptibility (all P < 0.05). MDR modeling implied that the combined model of rs12716977, rs2230433 and rs1799969 was the supreme interactive model when BMI was co-assessed, and the interactive model of rs12716977, rs334558 and rs5491 was the most desirable among the smoking population. In conclusion, gene-gene and gene-environment interactions served as a crucial manner in affecting susceptibility to GO, providing solid evidences for screening effective GO-susceptible biomarkers and exploring potential GO treatment strategies. Copyright © 2018. Published by Elsevier Ltd.

Animal models of gene-environment interaction in schizophrenia: a dimensional perspective

PubMed Central

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V.

2015-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (GxE) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of GxE relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. PMID:26510407

Detecting regulatory gene-environment interactions with unmeasured environmental factors.

PubMed

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.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.

PubMed

Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PubMed Central

Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811

Sample size requirements for indirect association studies of gene-environment interactions (G x E).

PubMed

Hein, Rebecca; Beckmann, Lars; Chang-Claude, Jenny

2008-04-01

Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only.

Childhood quality influences genetic sensitivity to environmental influences across adulthood: A life-course Gene × Environment interaction study.

PubMed

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.

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...

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…

Gene-Environment Interaction in Externalizing Problems among Adolescents: Evidence from the Pelotas 1993 Birth Cohort Study

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.…

Genetic Dissection of Learning and Memory in Mice

PubMed Central

Mineur, Yann S.; Crusio, Wim E.; Sluyter, Frans

2004-01-01

In this minireview, we discuss different strategies to dissect genetically the keystones of learning and memory. First, we broadly sketch the neurogenetic analysis of complex traits in mice. We then discuss two general strategies to find genes affecting learning and memory: candidate gene studies and whole genome searches. Next, we briefly review more recently developed techniques, such as microarrays and RNA interference. In addition, we focus on gene-environment interactions and endophenotypes. All sections are illustrated with examples from the learning and memory field, including a table summarizing the latest information about genes that have been shown to have effects on learning and memory. PMID:15656270

Research Review: Gene-Environment Interaction Research in Youth Depression--A Systematic Review with Recommendations for Future Research

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…

Refining the Candidate Environment: Interpersonal Stress, the Serotonin Transporter Polymorphism, and Gene-Environment Interactions in Major Depression.

PubMed

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.

Interactions among genetic variants in apoptosis pathway genes, reflux symptoms, body mass index, and smoking indicate two distinct etiologic patterns of esophageal adenocarcinoma.

PubMed

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.

The moderating effect of ANKK1 on the association of family environment with longitudinal executive function following traumatic brain injury in early childhood: A preliminary study.

PubMed

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.

PubMed

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.

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity

PubMed Central

2014-01-01

Background Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of ‘adaptive differentiation with minimal gene flow’ in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Results Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Conclusions Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments. PMID:24674227

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity.

PubMed

Odendaal, Lizelle J; Jacobs, David S; Bishop, Jacqueline M

2014-03-27

Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of 'adaptive differentiation with minimal gene flow' in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments.

Computational gene network study on antibiotic resistance genes of Acinetobacter baumannii.

PubMed

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.

Interaction of rearing environment and reproductive tactic on gene expression profiles in Atlantic salmon

USGS Publications Warehouse

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.

PubMed

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.

A multilevel prediction of physiological response to challenge: Interactions among child maltreatment, neighborhood crime, endothelial nitric oxide synthase gene (eNOS), and GABA(A) receptor subunit alpha-6 gene (GABRA6).

PubMed

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.

The influence of urban/rural residency on depressive symptoms is moderated by the serotonin receptor 2A gene.

PubMed

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.

Gene by Environment Interaction and Resilience: Effects of Child Maltreatment and Serotonin, Corticotropin Releasing Hormone, Dopamine, and Oxytocin Genes

PubMed Central

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

A global evolutionary and metabolic analysis of human obesity gene risk variants.

PubMed

Castillo, Joseph J; Hazlett, Zachary S; Orlando, Robert A; Garver, William S

2017-09-05

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution. Copyright © 2017. Published by Elsevier B.V.

Interactive effects of 5-HTTLPR genotype and rearing environment on affective attitude towards own infant in Japanese mothers.

PubMed

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.

Genome-environment interactions and prospective technology assessment: evolution from pharmacogenomics to nutrigenomics and ecogenomics.

PubMed

Ozdemir, Vural; Motulsky, Arno G; Kolker, Eugene; Godard, Béatrice

2009-02-01

The relationships between food, nutrition science, and health outcomes have been mapped over the past century. Genomic variation among individuals and populations is a new factor that enriches and challenges our understanding of these complex relationships. Hence, the confluence of nutritional science and genomics-nutrigenomics--was the focus of the OMICS: A Journal of Integrative Biology in December 2008 (Part 1). The 2009 Special Issue (Part 2) concludes the analysis of nutrigenomics research and innovations. Together, these two issues expand the scope and depth of critical scholarship in nutrigenomics, in keeping with an integrated multidisciplinary analysis across the bioscience, omics technology, social, ethical, intellectual property and policy dimensions. Historically, the field of pharmacogenetics provided the first examples of specifically identifiable gene variants predisposing to unexpected responses to drugs since the 1950s. Brewer coined the term ecogenetics in 1971 to broaden the concept of gene-environment interactions from drugs and nutrition to include environmental agents in general. In the mid-1990s, introduction of high-throughput technologies led to the terms pharmacogenomics, nutrigenomics and ecogenomics to describe, respectively, the contribution of genomic variability to differential responses to drugs, food, and environment defined in the broadest sense. The distinctions, if any, between these newer fields (e.g., nutrigenomics) and their predecessors (e.g., nutrigenetics) remain to be delineated. For nutrigenomics, its reliance on genome-wide analyses may lead to detection of new biological mechanisms governing host response to food. Recognizing "genome-environment interactions" as the conceptual thread that connects and runs through pharmacogenomics, nutrigenomics, and ecogenomics may contribute toward anticipatory governance and prospective real-time analysis of these omics fields. Such real-time analysis of omics technologies and innovations is crucial, because it can influence and positively shape them as these approaches develop, and help avoid predictable pitfalls, and thus ensure their effective and ethical application in the laboratory, clinic, and society.

Examining Gene-Environment Interactions in Comorbid Depressive and Disruptive Behavior Disorders using a Bayesian Approach

PubMed Central

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

Gene-Environment Interplay in the Link of Friends' and Nonfriends' Behaviors with Children's Social Reticence in a Competitive Situation

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…

cDNA microarray reveals the alterations of cytoskeleton-related genes in osteoblast under high magneto-gravitational environment.

PubMed

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.

Gene–environment interaction in tobacco-related cancers

PubMed Central

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

Genomic and Epigenomic Insights into Nutrition and Brain Disorders

PubMed Central

Dauncey, Margaret Joy

2013-01-01

Considerable evidence links many neuropsychiatric, neurodevelopmental and neurodegenerative disorders with multiple complex interactions between genetics and environmental factors such as nutrition. Mental health problems, autism, eating disorders, Alzheimer’s disease, schizophrenia, Parkinson’s disease and brain tumours are related to individual variability in numerous protein-coding and non-coding regions of the genome. However, genotype does not necessarily determine neurological phenotype because the epigenome modulates gene expression in response to endogenous and exogenous regulators, throughout the life-cycle. Studies using both genome-wide analysis of multiple genes and comprehensive analysis of specific genes are providing new insights into genetic and epigenetic mechanisms underlying nutrition and neuroscience. This review provides a critical evaluation of the following related areas: (1) recent advances in genomic and epigenomic technologies, and their relevance to brain disorders; (2) the emerging role of non-coding RNAs as key regulators of transcription, epigenetic processes and gene silencing; (3) novel approaches to nutrition, epigenetics and neuroscience; (4) gene-environment interactions, especially in the serotonergic system, as a paradigm of the multiple signalling pathways affected in neuropsychiatric and neurological disorders. Current and future advances in these four areas should contribute significantly to the prevention, amelioration and treatment of multiple devastating brain disorders. PMID:23503168

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…

Is exposure to cyanobacteria an environmental risk factor for amyotrophic lateral sclerosis and other neurodegenerative diseases?

USGS Publications Warehouse

Bradley, Walter G.; Borenstein, Amy R.; Nelson, Lorene M.; Codd, Geoffrey A.; Rosen, Barry H.; Stommel, Elijah W.; Cox, Paul Alan

2013-01-01

There is a broad scientific consensus that amyotrophic lateral sclerosis (ALS) is caused by gene-environment interactions. Mutations in genes underlying familial ALS (fALS) have been discovered in only 5–10% of the total population of ALS patients. Relatively little attention has been paid to environmental and lifestyle factors that may trigger the cascade of motor neuron death leading to the syndrome of ALS, although exposure to chemicals including lead and pesticides, and to agricultural environments, smoking, certain sports, and trauma have all been identified with an increased risk of ALS. There is a need for research to quantify the relative roles of each of the identified risk factors for ALS. Recent evidence has strengthened the theory that chronic environmental exposure to the neurotoxic amino acid β-N-methylamino-L-alanine (BMAA) produced by cyanobacteria may be an environmental risk factor for ALS. Here we describe methods that may be used to assess exposure to cyanobacteria, and hence potentially to BMAA, namely an epidemiologic questionnaire and direct and indirect methods for estimating the cyanobacterial load in ecosystems. Rigorous epidemiologic studies could determine the risks associated with exposure to cyanobacteria, and if combined with genetic analysis of ALS cases and controls could reveal etiologically important gene-environment interactions in genetically vulnerable individuals.

Microsatellite polymorphisms associated with human behavioural and psychological phenotypes including a gene-environment interaction.

PubMed

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.

Effects of enamel matrix genes on dental caries are moderated by fluoride exposures

PubMed Central

Shaffer, John R.; Carlson, Jenna C.; Stanley, Brooklyn O. C.; Feingold, Eleanor; Cooper, Margaret; Vanyukov, Michael M.; Maher, Brion S.; Slayton, Rebecca L.; Willing, Marcia C.; Reis, Steven E.; McNeil, Daniel W.; Crout, Richard J.; Weyant, Robert J.; Levy, Steven M.; Vieira, Alexandre R.; Marazita, Mary L.

2014-01-01

Dental caries (tooth decay) is the most common chronic disease, worldwide, affecting most children and adults. Though dental caries is highly heritable, few caries-related genes have been discovered. We investigated whether 18 genetic variants in the group of nonamelogenin enamel matrix genes (AMBN, ENAM, TUFT1, and TFIP11) were associated with dental caries experience in 13 age- and race-stratified samples from six parent studies (N=3,600). Linear regression was used to model genetic associations and test gene-byfluoride interaction effects for two sources of fluoride: daily tooth brushing and home water fluoride concentration. Meta-analysis was used to combine results across five child and eight adult samples. We observed the statistically significant association of rs2337359 upstream of TUFT1 with dental caries experience via meta-analysis across adult samples (p<0.002) and the suggestive association for multiple variants in TFIP11 across child samples (p<0.05). Moreover, we discovered two genetic variants (rs2337359 upstream of TUFT1 and missense rs7439186 in AMBN) involved in gene-by-fluoride interactions. For each interaction, participants with the risk allele/genotype exhibited greater dental caries experience only if they were not exposed to the source of fluoride. Altogether, these results confirm that variation in enamel matrix genes contributes to individual differences in dental caries liability, and demonstrate that the effects of these genes may be moderated by protective fluoride exposures. In short, genes may exert greater influence on dental caries in unprotected environments, or equivalently, the protective effects of fluoride may obviate the effects of genetic risk alleles. PMID:25373699

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

PubMed

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.

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

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

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

PubMed Central

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression.

PubMed

Hüls, Anke; Ickstadt, Katja; Schikowski, Tamara; Krämer, Ursula

2017-06-12

For the analysis of gene-environment (GxE) interactions commonly single nucleotide polymorphisms (SNPs) are used to characterize genetic susceptibility, an approach that mostly lacks power and has poor reproducibility. One promising approach to overcome this problem might be the use of weighted genetic risk scores (GRS), which are defined as weighted sums of risk alleles of gene variants. The gold-standard is to use external weights from published meta-analyses. In this study, we used internal weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression and thereby provided a method that can be used if there are no external weights available. We conducted a simulation study for the detection of GxE interactions and compared power and type I error of single SNPs analyses with Bonferroni correction and corresponding analysis with unweighted and our weighted GRS approach in scenarios with six risk SNPs and an increasing number of highly correlated (up to 210) and noise SNPs (up to 840). Applying weighted GRS increased the power enormously in comparison to the common single SNPs approach (e.g. 94.2% vs. 35.4%, respectively, to detect a weak interaction with an OR ≈ 1.04 for six uncorrelated risk SNPs and n = 700 with a well-controlled type I error). Furthermore, weighted GRS outperformed the unweighted GRS, in particular in the presence of SNPs without any effect on the phenotype (e.g. 90.1% vs. 43.9%, respectively, when 20 noise SNPs were added to the six risk SNPs). This outperforming of the weighted GRS was confirmed in a real data application on lung inflammation in the SALIA cohort (n = 402). However, in scenarios with a high number of noise SNPs (>200 vs. 6 risk SNPs), larger sample sizes are needed to avoid an increased type I error, whereas a high number of correlated SNPs can be handled even in small samples (e.g. n = 400). In conclusion, weighted GRS with weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression were shown to be a powerful tool to detect gene-environment interactions in scenarios of high Linkage disequilibrium and noise.

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

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.

Gene-Environment Interplay between Parent-Child Relationship Problems and Externalizing Disorders in Adolescence and Young Adulthood

PubMed Central

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

Confirming genes influencing risk to cleft lip with/without cleft palate in a case-parent trio study.

PubMed

Beaty, T H; Taub, M A; Scott, A F; Murray, J C; Marazita, M L; Schwender, H; Parker, M M; Hetmanski, J B; Balakrishnan, P; Mansilla, M A; Mangold, E; Ludwig, K U; Noethen, M M; Rubini, M; Elcioglu, N; Ruczinski, I

2013-07-01

A collection of 1,108 case-parent trios ascertained through an isolated, nonsyndromic cleft lip with or without cleft palate (CL/P) was used to replicate the findings from a genome-wide association study (GWAS) conducted by Beaty et al. (Nat Genet 42:525-529, 2010), where four different genes/regions were identified as influencing risk to CL/P. Tagging SNPs for 33 different genes were genotyped (1,269 SNPs). All four of the genes originally identified as showing genome-wide significance (IRF6, ABCA4 and MAF, plus the 8q24 region) were confirmed in this independent sample of trios (who were primarily of European and Southeast Asian ancestry). In addition, eight genes classified as 'second tier' hits in the original study (PAX7, THADA, COL8A1/FILIP1L, DCAF4L2, GADD45G, NTN1, RBFOX3 and FOXE1) showed evidence of linkage and association in this replication sample. Meta-analysis between the original GWAS trios and these replication trios showed PAX7, COL8A1/FILIP1L and NTN1 achieved genome-wide significance. Tests for gene-environment interaction between these 33 genes and maternal smoking found evidence for interaction with two additional genes: GRID2 and ELAVL2 among European mothers (who had a higher rate of smoking than Asian mothers). Formal tests for gene-gene interaction (epistasis) failed to show evidence of statistical interaction in any simple fashion. This study confirms that many different genes influence risk to CL/P.

Confirming genes influencing risk to cleft lip with/without cleft palate in a case-parent trio study

PubMed Central

Beaty, TH; Taub, MA; Scott, AF; Murray, JC; Marazita, ML; Schwender, H; Parker, MM; Hetmanski, JB; Balakrishnan, P; Mansilla, MA; Mangold, E; Ludwig, KU; Noethen, MM; Rubini, M; Elcioglu, N; Ruczinski, I

2013-01-01

A collection of 1,108 case-parent trios ascertained through an isolated, non-syndromic cleft lip with or without cleft palate (CL/P) was used to replicate the findings from a genome-wide association study (GWAS) conducted by Beaty et al. (2010) where four different genes/regions were identified as influencing risk to CL/P. Tagging SNPs for 33 different genes were genotyped (1,269 SNPs). All four of the genes originally identified as showing genome-wide significance (IRF6, ABCA4 and MAF, plus the 8q24 region) were confirmed in this independent sample of trios (who were primarily of European and Southeast Asian ancestry). In addition, eight genes classified as ‘second tier’ hits in the original study (PAX7, THADA, COL8A1/FILIP1L, DCAF4L2, GADD45G, NTN1, RBFOX3 and FOXE1) showed evidence of linkage and association in this replication sample. Meta-analysis between the original GWAS trios and these replication trios showed PAX7, COL8A1/FILIP1L and NTN1 achieved genome-wide significance. Tests for gene-environment interaction between these 33 genes and maternal smoking found evidence for interaction with two additional genes: GRID2 and ELAVL2 among European mothers (who had a higher rate of smoking than Asian mothers). Formal tests for gene-gene interaction (epistasis) failed to show evidence of statistical interaction in any simple fashion. This study confirms that many different genes influence risk to CL/P. PMID:23512105

The FOXO1 Gene-Obesity Interaction Increases the Risk of Type 2 Diabetes Mellitus in a Chinese Han Population.

PubMed

Gong, Lilin; Li, Rong; Ren, Wei; Wang, Zengchan; Wang, Zhihong; Yang, Maosheng; Zhang, Suhua

2017-02-01

Here, we aimed to study the effect of the forkhead box O1-insulin receptor substrate 2 (FOXO1-IRS2) gene interaction and the FOXO1 and IRS2 genes-environment interaction for the risk of type 2 diabetes mellitus (T2DM) in a Chinese Han population. We genotyped 7 polymorphism sites of FOXO1 gene and IRS2 gene in 780 unrelated Chinese Han people (474 cases of T2DM, 306 cases of healthy control). The risk of T2DM in individuals with AA genotype for rs7986407 and CC genotype for rs4581585 in FOXO1 gene was 2.092 and 2.57 times higher than that with GG genotype (odds ratio [OR] = 2.092; 95% confidence interval [CI] = 1.178-3.731; P = 0.011) and TT genotype (OR = 2.571; 95% CI = 1.404-4.695; P = 0.002), respectively. The risk of T2DM in individuals with GG genotype for Gly1057Asp in IRS2 gene was 1.42 times higher than that with AA genotype (OR = 1.422; 95% CI = 1.037-1.949; P = 0.029). The other 4 single nucleotide polymorphisms (SNPs) had no significant association with T2DM (P > 0.05). Multifactor dimensionality reduction (MDR) analysis showed that the interaction between SNPs rs7986407 and rs4325426 in FOXO1 gene and waist was the best model confirmed by interaction analysis, closely associating with T2DM. There was an increased risk for T2DM in the case of non-obesity with genotype combined AA/CC, AA/AC or AG/AA for rs7986407 and rs4325426, and obesity with genotype AA for rs7986407 or AA for rs4325426 (OR = 3.976; 95% CI = 1.156-13.675; P value from sign test [P(sign)] = 0.025; P value from permutation test [P(perm)] = 0.000-0.001). Together, this study indicates an association of FOXO1 and IRS2 gene polymorphisms with T2DM in Chinese Han population, supporting FOXO1-obesity interaction as a key factor for the risk of T2DM.

Gene-gene and gene-environment interactions defining lipid-related traits.

PubMed

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.

Genome-Wide Interaction Analysis of Air Pollution Exposure and Childhood Asthma with Functional Follow-up.

PubMed

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.

SLC6A1 gene involvement in susceptibility to attention-deficit/hyperactivity disorder: A case-control study and gene-environment interaction.

PubMed

Yuan, Fang-Fen; Gu, Xue; Huang, Xin; Zhong, Yan; Wu, Jing

2017-07-03

Attention-deficit/hyperactivity disorder (ADHD) is an early onset childhood neurodevelopmental disorder with an estimated heritability of approximately 76%. We conducted a case-control study to explore the role of the SLC6A1 gene in ADHD. The genotypes of eight variants were determined using Sequenom MassARRAY technology. The participants in the study were 302 children with ADHD and 411 controls. ADHD symptoms were assessed using the Conners Parent Symptom Questionnaire. In our study, rs2944366 was consistently shown to be associated with the ADHD risk in the dominant model (odds ratio [OR]=0.554, 95% confidence interval [CI]=0.404-0.760), and nominally associated with Hyperactive index score (P=0.027). In addition, rs1170695 has been found to be associated with the ADHD risk in the addictive model (OR=1.457, 95%CI=1.173-1.809), while rs9990174 was associated with the Hyperactive index score (P=0.010). Intriguingly, gene-environmental interactions analysis consistently revealed the potential interactions of rs1170695 with blood lead (P mul =0.044) to modify the ADHD risk. Expression quantitative trait loci analysis suggested that these positive single nucleotide polymorphisms (SNPs) may mediate SLC6A1 gene expression. Therefore, our results suggest that selected SLC6A1 gene variants may have a significant effect on the ADHD risk. Copyright © 2017 Elsevier Inc. All rights reserved.

Gender specific gene-environment interactions on laboratory-assessed aggression.

PubMed

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.

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

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.

Epistasis-list.org: A Curated Database of Gene-Gene and Gene-Environment Interactions in Human Epidemiology

EPA Science Inventory

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...

Genes, Culture and Conservatism-A Psychometric-Genetic Approach.

PubMed

Schwabe, Inga; Jonker, Wilfried; van den Berg, Stéphanie M

2016-07-01

The Wilson-Patterson conservatism scale was psychometrically evaluated using homogeneity analysis and item response theory models. Results showed that this scale actually measures two different aspects in people: on the one hand people vary in their agreement with either conservative or liberal catch-phrases and on the other hand people vary in their use of the "?" response category of the scale. A 9-item subscale was constructed, consisting of items that seemed to measure liberalism, and this subscale was subsequently used in a biometric analysis including genotype-environment interaction, correcting for non-homogeneous measurement error. Biometric results showed significant genetic and shared environmental influences, and significant genotype-environment interaction effects, suggesting that individuals with a genetic predisposition for conservatism show more non-shared variance but less shared variance than individuals with a genetic predisposition for liberalism.

Phthalic acid chemical probes synthesized for protein-protein interaction analysis.

PubMed

Liang, Shih-Shin; Liao, Wei-Ting; Kuo, Chao-Jen; Chou, Chi-Hsien; Wu, Chin-Jen; Wang, Hui-Min

2013-06-24

Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid) is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP). According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES) was deposited on silicon dioxides (SiO2) particles and phthalate chemical probes were manufactured from phthalic acid and APTES-SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells) to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA) software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies

PubMed Central

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

Differences and similarities in the serotonergic diathesis for suicide attempts and mood disorders: a 22-year longitudinal gene-environment study.

PubMed

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.

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

PubMed

Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

2011-07-01

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

Early Adverse Environments and Genetic Influences on Age at First Sex: Evidence for Gene × Environment Interaction

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…

Bisphenol-A and Female Infertility: A Possible Role of Gene-Environment Interactions

PubMed Central

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

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder.

PubMed

Mullins, N; Power, R A; Fisher, H L; Hanscombe, K B; Euesden, J; Iniesta, R; Levinson, D F; Weissman, M M; Potash, J B; Shi, J; Uher, R; Cohen-Woods, S; Rivera, M; Jones, L; Jones, I; Craddock, N; Owen, M J; Korszun, A; Craig, I W; Farmer, A E; McGuffin, P; Breen, G; Lewis, C M

2016-03-01

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Identification, characterization and expression analysis of lineage-specific genes within sweet orange (Citrus sinensis).

PubMed

Xu, Yuantao; Wu, Guizhi; Hao, Baohai; Chen, Lingling; Deng, Xiuxin; Xu, Qiang

2015-11-23

With the availability of rapidly increasing number of genome and transcriptome sequences, lineage-specific genes (LSGs) can be identified and characterized. Like other conserved functional genes, LSGs play important roles in biological evolution and functions. Two set of citrus LSGs, 296 citrus-specific genes (CSGs) and 1039 orphan genes specific to sweet orange, were identified by comparative analysis between the sweet orange genome sequences and 41 genomes and 273 transcriptomes. With the two sets of genes, gene structure and gene expression pattern were investigated. On average, both the CSGs and orphan genes have fewer exons, shorter gene length and higher GC content when compared with those evolutionarily conserved genes (ECs). Expression profiling indicated that most of the LSGs expressed in various tissues of sweet orange and some of them exhibited distinct temporal and spatial expression patterns. Particularly, the orphan genes were preferentially expressed in callus, which is an important pluripotent tissue of citrus. Besides, part of the CSGs and orphan genes expressed responsive to abiotic stress, indicating their potential functions during interaction with environment. This study identified and characterized two sets of LSGs in citrus, dissected their sequence features and expression patterns, and provided valuable clues for future functional analysis of the LSGs in sweet orange.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing.

PubMed

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.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

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

Comparative genomics of free-living Gammaproteobacteria: pathogenesis-related genes or interaction-related genes?

PubMed

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.

Genome analysis of Daldinia eschscholtzii strains UM 1400 and UM 1020, wood-decaying fungi isolated from human hosts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chan, Chai Ling; Yew, Su Mei; Ngeow, Yun Fong

Background: Daldinia eschscholtzii is a wood-inhabiting fungus that causes wood decay under certain conditions. It has a broad host range and produces a large repertoire of potentially bioactive compounds. However, there is no extensive genome analysis on this fungal species. Results: Two fungal isolates (UM 1400 and UM 1020) from human specimens were identified as Daldinia eschscholtzii by morphological features and ITS-based phylogenetic analysis. Both genomes were similar in size with 10,822 predicted genes in UM 1400 (35.8 Mb) and 11,120 predicted genes in UM 1020 (35.5 Mb). A total of 751 gene families were shared among both UM isolates,more » including gene families associated with fungus-host interactions. In the CAZyme comparative analysis, both genomes were found to contain arrays of CAZyme related to plant cell wall degradation. Genes encoding secreted peptidases were found in the genomes, which encode for the peptidases involved in the degradation of structural proteins in plant cell wall. In addition, arrays of secondary metabolite backbone genes were identified in both genomes, indicating of their potential to produce bioactive secondary metabolites. Both genomes also contained an abundance of gene encoding signaling components, with three proposed MAPK cascades involved in cell wall integrity, osmoregulation, and mating/filamentation. Besides genomic evidence for degrading capability, both isolates also harbored an array of genes encoding stress response proteins that are potentially significant for adaptation to living in the hostile environments. In conclusion: Our genomic studies provide further information for the biological understanding of the D. eschscholtzii and suggest that these wood-decaying fungi are also equipped for adaptation to adverse environments in the human host.« less

Genome analysis of Daldinia eschscholtzii strains UM 1400 and UM 1020, wood-decaying fungi isolated from human hosts

DOE PAGES

Chan, Chai Ling; Yew, Su Mei; Ngeow, Yun Fong; ...

2015-11-18

Background: Daldinia eschscholtzii is a wood-inhabiting fungus that causes wood decay under certain conditions. It has a broad host range and produces a large repertoire of potentially bioactive compounds. However, there is no extensive genome analysis on this fungal species. Results: Two fungal isolates (UM 1400 and UM 1020) from human specimens were identified as Daldinia eschscholtzii by morphological features and ITS-based phylogenetic analysis. Both genomes were similar in size with 10,822 predicted genes in UM 1400 (35.8 Mb) and 11,120 predicted genes in UM 1020 (35.5 Mb). A total of 751 gene families were shared among both UM isolates,more » including gene families associated with fungus-host interactions. In the CAZyme comparative analysis, both genomes were found to contain arrays of CAZyme related to plant cell wall degradation. Genes encoding secreted peptidases were found in the genomes, which encode for the peptidases involved in the degradation of structural proteins in plant cell wall. In addition, arrays of secondary metabolite backbone genes were identified in both genomes, indicating of their potential to produce bioactive secondary metabolites. Both genomes also contained an abundance of gene encoding signaling components, with three proposed MAPK cascades involved in cell wall integrity, osmoregulation, and mating/filamentation. Besides genomic evidence for degrading capability, both isolates also harbored an array of genes encoding stress response proteins that are potentially significant for adaptation to living in the hostile environments. In conclusion: Our genomic studies provide further information for the biological understanding of the D. eschscholtzii and suggest that these wood-decaying fungi are also equipped for adaptation to adverse environments in the human host.« less

RORA and posttraumatic stress trajectories: main effects and interactions with childhood physical abuse history

PubMed Central

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

The psychiatric phenotype in triple X syndrome: New hypotheses illustrated in two cases

PubMed Central

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

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

PubMed Central

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

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

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

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.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations.

PubMed

Sheth, Harsh; Northwood, Emma; Ulrich, Cornelia M; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H; Forman, David; Wolf, C Roland; Smith, Gillian; Jackson, Michael S; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L; Marchand, Loic Le; Lindor, Noralane M; Thibodeau, Stephen N; Potter, John D; Burn, John; Bishop, D Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin's chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68-0.86; rs1105879 OR = 0.77 95% CI = 0.69-0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations

PubMed Central

Ulrich, Cornelia M.; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H.; Forman, David; Wolf, C. Roland; Smith, Gillian; Jackson, Michael S.; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L.; Marchand, Loic Le; Lindor, Noralane M.; Thibodeau, Stephen N.; Potter, John D.; Burn, John; Bishop, D. Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin’s chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68–0.86; rs1105879 OR = 0.77 95% CI = 0.69–0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk. PMID:29425227

Social Environmental Variation, Plasticity Genes, and Aggression: Evidence for the Differential Susceptibility Hypothesis

PubMed Central

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

Meta-analysis of gene–environment-wide association scans accounting for education level identifies additional loci for refractive error

PubMed Central

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

2016-01-01

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. PMID:27020472

Chromatin immunoprecipitation assays: application of ChIP-on-chip for defining dynamic transcriptional mechanisms in bone cells.

PubMed

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.

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

PubMed Central

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

Activation of IFN pathways and plasmacytoid dendritic cell recruitment in target organs of primary Sjögren's syndrome.

PubMed

Gottenberg, Jacques-Eric; Cagnard, Nicolas; Lucchesi, Carlo; Letourneur, Franck; Mistou, Sylvie; Lazure, Thierry; Jacques, Sebastien; Ba, Nathalie; Ittah, Marc; Lepajolec, Christine; Labetoulle, Marc; Ardizzone, Marc; Sibilia, Jean; Fournier, Catherine; Chiocchia, Gilles; Mariette, Xavier

2006-02-21

Gene expression analysis of target organs might help provide new insights into the pathogenesis of autoimmune diseases. We used global gene expression profiling of minor salivary glands to identify patterns of gene expression in patients with primary Sjögren's syndrome (pSS), a common and prototypic systemic autoimmune disease. Gene expression analysis allowed for differentiating most patients with pSS from controls. The expression of 23 genes in the IFN pathways, including two Toll-like receptors (TLR8 and TLR9), was significantly different between patients and controls. Furthermore, the increased expression of IFN-inducible genes, BAFF and IFN-induced transmembrane protein 1, was also demonstrated in ocular epithelial cells by quantitative RT-PCR. In vitro activation showed that these genes were effectively modulated by IFNs in salivary gland epithelial cells, the target cells of autoimmunity in pSS. The activation of IFN pathways led us to investigate whether plasmacytoid dendritic cells were recruited in salivary glands. These IFN-producing cells were detected by immunohistochemistry in all patients with pSS, whereas none was observed in controls. In conclusion, our results support the pathogenic interaction between the innate and adaptive immune system in pSS. The persistence of the IFN signature might be related to a vicious circle, in which the environment interacts with genetic factors to drive the stimulation of salivary TLRs.

Activation of IFN pathways and plasmacytoid dendritic cell recruitment in target organs of primary Sjögren’s syndrome

PubMed Central

Gottenberg, Jacques-Eric; Cagnard, Nicolas; Lucchesi, Carlo; Letourneur, Franck; Mistou, Sylvie; Lazure, Thierry; Jacques, Sebastien; Ba, Nathalie; Ittah, Marc; Lepajolec, Christine; Labetoulle, Marc; Ardizzone, Marc; Sibilia, Jean; Fournier, Catherine; Chiocchia, Gilles; Mariette, Xavier

2006-01-01

Gene expression analysis of target organs might help provide new insights into the pathogenesis of autoimmune diseases. We used global gene expression profiling of minor salivary glands to identify patterns of gene expression in patients with primary Sjögren’s syndrome (pSS), a common and prototypic systemic autoimmune disease. Gene expression analysis allowed for differentiating most patients with pSS from controls. The expression of 23 genes in the IFN pathways, including two Toll-like receptors (TLR8 and TLR9), was significantly different between patients and controls. Furthermore, the increased expression of IFN-inducible genes, BAFF and IFN-induced transmembrane protein 1, was also demonstrated in ocular epithelial cells by quantitative RT-PCR. In vitro activation showed that these genes were effectively modulated by IFNs in salivary gland epithelial cells, the target cells of autoimmunity in pSS. The activation of IFN pathways led us to investigate whether plasmacytoid dendritic cells were recruited in salivary glands. These IFN-producing cells were detected by immunohistochemistry in all patients with pSS, whereas none was observed in controls. In conclusion, our results support the pathogenic interaction between the innate and adaptive immune system in pSS. The persistence of the IFN signature might be related to a vicious circle, in which the environment interacts with genetic factors to drive the stimulation of salivary TLRs. PMID:16477017

Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

PubMed

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.

Genome-wide association studies suggest that APOL1-environment interactions more likely trigger kidney disease in African Americans with nondiabetic nephropathy than strong APOL1-second gene interactions.

PubMed

Langefeld, Carl D; Comeau, Mary E; Ng, Maggie C Y; Guan, Meijian; Dimitrov, Latchezar; Mudgal, Poorva; Spainhour, Mitzie H; Julian, Bruce A; Edberg, Jeffrey C; Croker, Jennifer A; Divers, Jasmin; Hicks, Pamela J; Bowden, Donald W; Chan, Gary C; Ma, Lijun; Palmer, Nicholette D; Kimberly, Robert P; Freedman, Barry I

2018-06-06

African Americans carrying two apolipoprotein L1 gene (APOL1) renal risk variants have a high risk for nephropathy. However, only a minority develops end-stage renal disease (ESRD). Hence, modifying factors likely contribute to initiation of kidney disease such as endogenous (HIV infection) or exogenous (interferon treatment) environmental modifiers. In this report, genome-wide association studies and a meta-analysis were performed to identify novel loci for nondiabetic ESRD in African Americans and to detect genetic modifiers in APOL1-associated nephropathy. Two African American cohorts were analyzed, 1749 nondiabetic ESRD cases and 1136 controls from Wake Forest and 901 lupus nephritis (LN)-ESRD cases and 520 controls with systemic lupus erythematosus but lacking nephropathy from the LN-ESRD Consortium. Association analyses adjusting for APOL1 G1/G2 renal-risk variants were completed and stratified by APOL1 risk genotype status. Individual genome-wide association studies and meta-analysis results of all 2650 ESRD cases and 1656 controls did not detect significant genome-wide associations with ESRD beyond APOL1. Similarly, no single nucleotide polymorphism showed significant genome-wide evidence of an interaction with APOL1 risk variants. Thus, although variants with small individual effects cannot be ruled out and are likely to exist, our results suggest that APOL1-environment interactions may be of greater clinical importance in triggering nephropathy in African Americans than APOL1 interactions with other single nucleotide polymorphisms. Copyright © 2018 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Gene-Environment Correlation and Interaction in Peer Effects on Adolescent Alcohol and Tobacco Use

PubMed Central

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

Changes in the striatal proteome of YAC128Q mice exhibit gene-environment interactions between mutant huntingtin and manganese.

PubMed

Wegrzynowicz, Michal; Holt, Hunter K; Friedman, David B; Bowman, Aaron B

2012-02-03

Huntington's disease (HD) is a neurodegenerative disorder caused by expansion of a CAG repeat within the Huntingtin (HTT) gene, though the clinical presentation of disease and age-of-onset are strongly influenced by ill-defined environmental factors. We recently reported a gene-environment interaction wherein expression of mutant HTT is associated with neuroprotection against manganese (Mn) toxicity. Here, we are testing the hypothesis that this interaction may be manifested by altered protein expression patterns in striatum, a primary target of both neurodegeneration in HD and neurotoxicity of Mn. To this end, we compared striatal proteomes of wild-type and HD (YAC128Q) mice exposed to vehicle or Mn. Principal component analysis of proteomic data revealed that Mn exposure disrupted a segregation of WT versus mutant proteomes by the major principal component observed in vehicle-exposed mice. Identification of altered proteins revealed novel markers of Mn toxicity, particularly proteins involved in glycolysis, excitotoxicity, and cytoskeletal dynamics. In addition, YAC128Q-dependent changes suggest that axonal pathology may be an early feature in HD pathogenesis. Finally, for several proteins, genotype-specific responses to Mn were observed. These differences include increased sensitivity to exposure in YAC128Q mice (UBQLN1) and amelioration of some mutant HTT-induced alterations (SAE1, ENO1). We conclude that the interaction of Mn and mutant HTT may suppress proteomic phenotypes of YAC128Q mice, which could reveal potential targets in novel treatment strategies for HD.

Analysis of the Pseudoalteromonas tunicata genome reveals properties of a surface-associated life style in the marine environment.

PubMed

Thomas, Torsten; Evans, Flavia F; Schleheck, David; Mai-Prochnow, Anne; Burke, Catherine; Penesyan, Anahit; Dalisay, Doralyn S; Stelzer-Braid, Sacha; Saunders, Neil; Johnson, Justin; Ferriera, Steve; Kjelleberg, Staffan; Egan, Suhelen

2008-09-24

Colonisation of sessile eukaryotic host surfaces (e.g. invertebrates and seaweeds) by bacteria is common in the marine environment and is expected to create significant inter-species competition and other interactions. The bacterium Pseudoalteromonas tunicata is a successful competitor on marine surfaces owing primarily to its ability to produce a number of inhibitory molecules. As such P. tunicata has become a model organism for the studies into processes of surface colonisation and eukaryotic host-bacteria interactions. To gain a broader understanding into the adaptation to a surface-associated life-style, we have sequenced and analysed the genome of P. tunicata and compared it to the genomes of closely related strains. We found that the P. tunicata genome contains several genes and gene clusters that are involved in the production of inhibitory compounds against surface competitors and secondary colonisers. Features of P. tunicata's oxidative stress response, iron scavenging and nutrient acquisition show that the organism is well adapted to high-density communities on surfaces. Variation of the P. tunicata genome is suggested by several landmarks of genetic rearrangements and mobile genetic elements (e.g. transposons, CRISPRs, phage). Surface attachment is likely to be mediated by curli, novel pili, a number of extracellular polymers and potentially other unexpected cell surface proteins. The P. tunicata genome also shows a utilisation pattern of extracellular polymers that would avoid a degradation of its recognised hosts, while potentially causing detrimental effects on other host types. In addition, the prevalence of recognised virulence genes suggests that P. tunicata has the potential for pathogenic interactions. The genome analysis has revealed several physiological features that would provide P. tunciata with competitive advantage against other members of the surface-associated community. We have also identified properties that could mediate interactions with surfaces other than its currently recognised hosts. This together with the detection of known virulence genes leads to the hypothesis that P. tunicata maintains a carefully regulated balance between beneficial and detrimental interactions with a range of host surfaces.

Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance

PubMed Central

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

Gene regulatory networks in lactation: identification of global principles using bioinformatics.

PubMed

Lemay, Danielle G; Neville, Margaret C; Rudolph, Michael C; Pollard, Katherine S; German, J Bruce

2007-11-27

The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Mammary gland microarray data, cellular localization data, protein-protein interactions, and literature-mined genes were integrated and analyzed using statistics, principal component analysis, gene ontology analysis, pathway analysis, and network analysis to identify global biological principles that govern molecular events during pregnancy, lactation, and involution. Several key principles were derived: (1) nearly a third of the transcriptome fluctuates to build, run, and disassemble the lactation apparatus; (2) genes encoding the secretory machinery are transcribed prior to lactation; (3) the diversity of the endogenous portion of the milk proteome is derived from fewer than 100 transcripts; (4) while some genes are differentially transcribed near the onset of lactation, the lactation switch is primarily post-transcriptionally mediated; (5) the secretion of materials during lactation occurs not by up-regulation of novel genomic functions, but by widespread transcriptional suppression of functions such as protein degradation and cell-environment communication; (6) the involution switch is primarily transcriptionally mediated; and (7) during early involution, the transcriptional state is partially reverted to the pre-lactation state. A new hypothesis for secretory diminution is suggested - milk production gradually declines because the secretory machinery is not transcriptionally replenished. A comprehensive network of protein interactions during lactation is assembled and new regulatory gene targets are identified. Less than one fifth of the transcriptionally regulated nodes in this lactation network have been previously explored in the context of lactation. Implications for future research in mammary and cancer biology are discussed.

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat.

PubMed

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.

Transcriptomic analysis of inbreeding depression in cold-sensitive Drosophila melanogaster shows upregulation of the immune response.

PubMed

Vermeulen, C J; Sørensen, P; Kirilova Gagalova, K; Loeschcke, V

2013-09-01

In sexually reproducing species, increased homozygosity often causes a decline in fitness, called inbreeding depression. Recently, researchers started describing the functional genomic changes that occur during inbreeding, both in benign conditions and under environmental stress. To further this aim, we have performed a genome-wide gene expression study of inbreeding depression, manifesting as cold sensitivity and conditional lethality. Our focus was to describe general patterns of gene expression during inbreeding depression and to identify specific processes affected in our line. There was a clear difference in gene expression between the stressful restrictive environment and the benign permissive environment in both the affected inbred line and the inbred control line. We noted a strong inbreeding-by-environment interaction, whereby virtually all transcriptional differences between lines were found in the restrictive environment. Functional annotation showed enrichment of transcripts coding for serine proteases and their inhibitors (serpins and BPTI/Kunitz family), which indicates activation of the innate immune response. These genes have previously been shown to respond transcriptionally to cold stress, suggesting the conditional lethal effect is associated with an exaggerated cold stress response. The set of differentially expressed genes significantly overlapped with those found in three other studies of inbreeding depression, demonstrating that it is possible to detect a common signature across different genetic backgrounds. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit Neighborhood Health Study.

PubMed

Meyers, J L; Cerdá, M; Galea, S; Keyes, K M; Aiello, A E; Uddin, M; Wildman, D E; Koenen, K C

2013-08-13

Cigarette smoking is influenced both by genetic and environmental factors. Until this year, all large-scale gene identification studies on smoking were conducted in populations of European ancestry. Consequently, the genetic architecture of smoking is not well described in other populations. Further, despite a rich epidemiologic literature focused on the social determinants of smoking, few studies have examined the moderation of genetic influences (for example, gene-environment interactions) on smoking in African Americans. In the Detroit Neighborhood Health Study (DNHS), a sample of randomly selected majority African American residents of Detroit, we constructed a genetic risk score (GRS), in which we combined top (P-value <5 × 10(-7)) genetic variants from a recent meta-analysis conducted in a large sample of African Americans. Using regression (effective n=399), we first tested for association between the GRS and cigarettes per day, attempting to replicate the findings from the meta-analysis. Second, we examined interactions with three social contexts that may moderate the genetic association with smoking: traumatic events, neighborhood social cohesion and neighborhood physical disorder. Among individuals who had ever smoked cigarettes, the GRS significantly predicted the number of cigarettes smoked per day and accounted for ~3% of the overall variance in the trait. Significant interactions were observed between the GRS and number of traumatic events experienced, as well as between the GRS and average neighborhood social cohesion; the association between genetic risk and smoking was greater among individuals who had experienced an increased number of traumatic events in their lifetimes, and diminished among individuals who lived in a neighborhood characterized by greater social cohesion. This study provides support for the utility of the GRS as an alternative approach to replication of common polygenic variation, and in gene-environment interaction, for smoking behaviors. In addition, this study indicates that environmental determinants have the potential to both exacerbate (traumatic events) and diminish (neighborhood social cohesion) genetic influences on smoking behaviors.

[From stone-craved genes to Michelangelo: significance and different aspects of gene-environment interaction].

PubMed

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.

A distinct and replicable variant of the squamous cell carcinoma gene inositol polyphosphate-5-phosphatase modifies the susceptibility of arsenic-associated skin lesions in Bangladesh.

PubMed

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.

Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution.

PubMed

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.

The interaction of early life experiences with COMT val158met affects anxiety sensitivity.

PubMed

Baumann, C; Klauke, B; Weber, H; Domschke, K; Zwanzger, P; Pauli, P; Deckert, J; Reif, A

2013-11-01

The pathogenesis of anxiety disorders is considered to be multifactorial with a complex interaction of genetic factors and individual environmental factors. Therefore, the aim of this study was to examine gene-by-environment interactions of the genes coding for catechol-O-methyltransferase (COMT) and monoamine oxidase A (MAOA) with life events on measures related to anxiety. A sample of healthy subjects (N = 782; thereof 531 women; mean age M = 24.79, SD = 6.02) was genotyped for COMT rs4680 and MAOA-uVNTR (upstream variable number of tandem repeats), and was assessed for childhood adversities [Childhood Trauma Questionnaire (CTQ)], anxiety sensitivity [Anxiety Sensitivity Index (ASI)] and anxious apprehension [Penn State Worry Questionnaire (PSWQ)]. Main and interaction effects of genotype, environment and gender on measures related to anxiety were assessed by means of regression analyses. Association analysis showed no main gene effect on either questionnaire score. A significant interactive effect of childhood adversities and COMT genotype was observed: Homozygosity for the low-active met allele and high CTQ scores was associated with a significant increment of explained ASI variance [R(2) = 0.040, false discovery rate (FDR) corrected P = 0.04]. A borderline interactive effect with respect to MAOA-uVNTR was restricted to the male subgroup. Carriers of the low-active MAOA allele who reported more aversive experiences in childhood exhibited a trend for enhanced anxious apprehension (R(2) = 0.077, FDR corrected P = 0.10). Early aversive life experiences therefore might increase the vulnerability to anxiety disorders in the presence of homozygosity for the COMT 158met allele or low-active MAOA-uVNTR alleles. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Mental and physical distress is modulated by a polymorphism in the 5-HT transporter gene interacting with social stressors and chronic disease burden.

PubMed

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.

From Viruses to Russian Roulette to Dance: A Rhetorical Critique and Creation of Genetic Metaphors

PubMed Central

Gronnvoll, Marita; Landau, Jamie

2010-01-01

This essay critiques and creates metaphoric genetic rhetoric by examining metaphors for genes used by representatives of the lay American public. We assess these metaphors with a new rhetorical orientation that we developed by building onto work by Robert Ivie and social scientific qualitative studies of audiences. Specifically, our analysis reveals three themes of genetic metaphors, with the first two appearing most frequently: 1) genes as a disease or problem 2) genes as fire or bomb, and 3) genes as gambling. We not only discuss the problems and untapped potential of these metaphors, but also we suggest metaphorically understanding genes interacting with the environment as a dance or a band. This essay has implications for rhetorical criticism, science studies, and public health. PMID:20625448

Media portrayals and health inequalities: a case study of characterizations of Gene x Environment interactions.

PubMed

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.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution

PubMed Central

Braberg, Hannes; Moehle, Erica A.; Shales, Michael; Guthrie, Christine; Krogan, Nevan J.

2014-01-01

We have achieved a residue-level resolution of genetic interaction mapping – a technique that measures how the function of one gene is affected by the alteration of a second gene – by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. PMID:24842270

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

Physical activity attenuates genetic effects on BMI: Results from a study of Chinese adult twins.

PubMed

Wang, Biqi; Gao, Wenjing; Lv, Jun; Yu, Canqing; Wang, Shengfeng; Pang, Zengchang; Cong, Liming; Dong, Zhong; Wu, Fan; Wang, Hua; Wu, Xianping; Jiang, Guohong; Wang, Xiaojie; Wang, Binyou; Cao, Weihua; Li, Liming

2016-03-01

This study aimed to examine the gene-environment interaction of physical activity and body mass index (BMI) using the Chinese National Twin Registry (CNTR). A total of 19,308 same-sex adult twins from CNTR were included in the analysis. Twin zygosity was determined by self-reported questionnaire. Height and weight were measured using self-reported questionnaire. The vigorous physical activity was defined as greater or equal to five times a week of at least 30 min moderate- or high-intensity physical activity. A twin structural equation model was used to analyze the gene-environment interaction of vigorous exercise with BMI among 13,506 monozygotic twins and 5,802 dizygotic twins. A structural equation model adjusting for age and sex found vigorous exercise significantly moderated the additive genetic effects (P < 0.001) and shared environmental effects (P < 0.001) on BMI. The genetic contributions to BMI were significantly lower for people who adopted a physically active lifestyle [h(2) = 40%, 95% confidence interval (CI): 35%-46%] than those who were relative sedentary (h(2) = 59%, 95% CI: 52%-66%). The observed gene-physical activity interaction was more pronounced in men than women. Our results suggested that adopting a physically active lifestyle may help to reduce the genetic influence on BMI among the Chinese population. © 2016 The Obesity Society.

Synergistic Association of Genetic Variants with Environmental Risk Factors in Susceptibility to Essential Hypertension.

PubMed

Sousa, Ana Célia; Mendonça, Maria I; Pereira, Andreia; Gouveia, Sara; Freitas, Ana I; Guerra, Graça; Rodrigues, Mariana; Henriques, Eva; Freitas, Sónia; Borges, Sofia; Pereira, Décio; Brehm, António; Palma Dos Reis, Roberto

2017-10-01

Essential hypertension (EH) is a disease in which both environment and genes have an important role. This study was designed to identify the interaction model between genetic variants and environmental risk factors that most highly potentiates EH development. We performed a case-control study with 1641 participants (mean age 50.6 ± 8.1 years), specifically 848 patients with EH and 793 controls, adjusted for gender and age. Traditional risk factors, biochemical and genetic parameters, including the genotypic discrimination of 14 genetic variants previously associated with EH, were investigated. Multifactorial dimensionality reduction (MDR) software was used to analyze gene-environment interactions. Validation was performed using logistic regression analysis with environmental risk factors, significant genetic variants, and the best MDR model. The best model indicates that the interactions among the ADD1 rs4961 640T allele, diabetes, and obesity (body mass index ≥30) increase approximately four-fold the risk of EH (odds ratio = 3.725; 95% confidence interval: 2.945-4.711; p < 0.0001). This work showed that the interaction between the ADD1 rs4961 variant, obesity, and the presence of diabetes increased the susceptibility to EH four-fold. In these circumstances, lifestyle adjustment and diabetes control should be intensified in patients who carry the ADD1 variant.

Genome-Wide Association Study (GWAS) and Genome-Wide Environment Interaction Study (GWEIS) of Depressive Symptoms in African American and Hispanic/Latina Women

PubMed Central

Dunn, Erin C.; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M.; Gogarten, Stephanie M.; Sofer, Tamar; Faul, Jessica D.; Kardia, Sharon L.R.; Smith, Jennifer A.; Weir, David R.; Zhao, Wei; Soare, Thomas W.; Mirza, Saira S.; Hek, Karin; Tiemeier, Henning W.; Goveas, Joseph S.; Sarto, Gloria E.; Snively, Beverly M.; Cornelis, Marilyn; Koenen, Karestan C.; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J.; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W.

2016-01-01

Background Genome-wide association studies (GWAS) have been unable to identify variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (G×E) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide environment interaction study (GWEIS) of depressive symptoms. Methods Using data from the SHARe cohort of the Women’s Health Initiative, comprising African Americans (n=7179) and Hispanics/Latinas (n=3138), we examined genetic main effects and G×E with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. Results No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20kb from GPR139, p=5.75×10−8) and rs75407252 (intronic to CACNA2D3, p=6.99×10−7). In Hispanics/Latinas, the top signals were rs2532087 (located 27kb from CD38, p=2.44×10−7) and rs4542757 (intronic to DCC, p=7.31×10−7). In the GWEIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; p=4.10×10−10; located 14kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG=0.95), suggesting that common variation underlying depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Conclusions Our results underscore the need for larger samples, more GWEIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. PMID:27038408

GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN.

PubMed

Dunn, Erin C; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M; Gogarten, Stephanie M; Sofer, Tamar; Faul, Jessica D; Kardia, Sharon L R; Smith, Jennifer A; Weir, David R; Zhao, Wei; Soare, Thomas W; Mirza, Saira S; Hek, Karin; Tiemeier, Henning; Goveas, Joseph S; Sarto, Gloria E; Snively, Beverly M; Cornelis, Marilyn; Koenen, Karestan C; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W

2016-04-01

Genome-wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide by environment interaction study (GWEIS) of depressive symptoms. Using data from the SHARe cohort of the Women's Health Initiative, comprising African Americans (n = 7,179) and Hispanics/Latinas (n = 3,138), we examined genetic main effects and GxE with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20 kb from GPR139, P = 5.75 × 10(-8) ) and rs75407252 (intronic to CACNA2D3, P = 6.99 × 10(-7) ). In Hispanics/Latinas, the top signals were rs2532087 (located 27 kb from CD38, P = 2.44 × 10(-7) ) and rs4542757 (intronic to DCC, P = 7.31 × 10(-7) ). In the GEWIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; P = 4.10 × 10(-10) ; located 14 kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG = 0.95), suggesting that common variation underlying self-reported depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Our results underscore the need for larger samples, more GEWIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. © 2016 Wiley Periodicals, Inc.

From genomics to chemical genomics: new developments in KEGG

PubMed Central

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

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress.

PubMed

Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun

2014-06-01

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.

Does parental expressed emotion moderate genetic effects in ADHD? An exploration using a genome wide association scan.

PubMed

Sonuga-Barke, Edmund J S; Lasky-Su, Jessica; Neale, Benjamin M; Oades, Robert; Chen, Wai; Franke, Barbara; Buitelaar, Jan; Banaschewski, Tobias; Ebstein, Richard; Gill, Michael; Anney, Richard; Miranda, Ana; Mulas, Fernando; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Steinhausen, Hans Christoph; Thompson, Margaret; Asherson, Philip; Faraone, Stephen V

2008-12-05

Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid conduct disorder are moderated by high maternal expressed emotion (EE). SNPs (600,000) were genotyped in 958 ADHD proband-parent trios. After applying data cleaning procedures we examined 429,981 autosomal SNPs in 909 family trios. ADHD symptom severity and comorbid conduct disorder was measured using the Parental Account of Childhood Symptoms interview. Maternal criticism and warmth (i.e., EE) were coded by independent observers on comments made during the interview. No G x E interactions reached genome-wide significance. Nominal effects were found both with and without genetic main effects. For those with genetic main effects 36 uncorrected interaction P-values were <10(-5) implicating both novel genes as well as some previously supported candidates. These were found equally often for all of the interactions being investigated. The observed interactions in SLC1A1 and NRG3 SNPs represent reasonable candidate genes for further investigation given their previous association with several psychiatric illnesses. We find evidence for the role of EE in moderating the effects of genes on ADHD severity and comorbid conduct disorder, implicating both novel and established candidates. These findings need replicating in larger independent samples. Copyright 2008 Wiley-Liss, Inc.

Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

PubMed

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.

The challenge of causal inference in gene-environment interaction research: leveraging research designs from the social sciences.

PubMed

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.

Modification of the interleukin-6 response to air pollution by interleukin-6 and fibrinogen polymorphisms.

PubMed

Ljungman, Petter; Bellander, Tom; Schneider, Alexandra; Breitner, Susanne; Forastiere, Francesco; Hampel, Regina; Illig, Thomas; Jacquemin, Bénédicte; Katsouyanni, Klea; von Klot, Stephanie; Koenig, Wolfgang; Lanki, Timo; Nyberg, Fredrik; Pekkanen, Juha; Pistelli, Riccardo; Pitsavos, Christos; Rosenqvist, Mårten; Sunyer, Jordi; Peters, Annette

2009-09-01

Evidence suggests that cardiovascular effects of air pollution are mediated by inflammation and that air pollution can induce genetic expression of the interleukin-6 gene (IL6). We investigated whether IL6 and fibrinogen gene variants can affect plasma IL-6 responses to air pollution in patients with cardiovascular disease. We repeatedly determined plasma IL-6 in 955 myocardial infarction survivors from six European cities (n = 5,539). We conducted city-specific analyses using additive mixed models adjusting for patient characteristics, time trend, and weather to assess the impact of air pollutants on plasma IL-6. We pooled city-specific estimates using meta-analysis methodology. We selected three IL6 single-nucleotide polymorphisms (SNPs) and one SNP each from the fibrinogen alpha-chain gene (FGA) and beta-chain gene (FGB) for gene-environment analyses. We found the most consistent modifications for variants in IL6 rs2069832 and FBG rs1800790 after exposure to carbon monoxide (CO; 24-hr average; p-values for interaction, 0.034 and 0.019, respectively). Nitrogen dioxide effects were consistently modified, but p-values for interaction were larger (0.09 and 0.19, respectively). The strongest effects were seen 6-11 hr after exposure, when, for example, the overall effect of a 2.2% increase in IL-6 per 0.64 mg/m(3) CO was modified to a 10% (95% confidence interval, 4.6-16%) increase in IL-6 (p-value for interaction = 0.002) for minor homozygotes of FGB rs1800790. The effect of gaseous traffic-related air pollution on inflammation may be stronger in genetic subpopulations with ischemic heart disease. This information could offer an opportunity to identify postinfarction patients who would benefit more than others from a cleaner environment and antiinflammatory treatment.

Many Saccharomyces cerevisiae Cell Wall Protein Encoding Genes Are Coregulated by Mss11, but Cellular Adhesion Phenotypes Appear Only Flo Protein Dependent.

PubMed

Bester, Michael C; Jacobson, Dan; Bauer, Florian F

2012-01-01

The outer cell wall of the yeast Saccharomyces cerevisiae serves as the interface with the surrounding environment and directly affects cell-cell and cell-surface interactions. Many of these interactions are facilitated by specific adhesins that belong to the Flo protein family. Flo mannoproteins have been implicated in phenotypes such as flocculation, substrate adhesion, biofilm formation, and pseudohyphal growth. Genetic data strongly suggest that individual Flo proteins are responsible for many specific cellular adhesion phenotypes. However, it remains unclear whether such phenotypes are determined solely by the nature of the expressed FLO genes or rather as the result of a combination of FLO gene expression and other cell wall properties and cell wall proteins. Mss11 has been shown to be a central element of FLO1 and FLO11 gene regulation and acts together with the cAMP-PKA-dependent transcription factor Flo8. Here we use genome-wide transcription analysis to identify genes that are directly or indirectly regulated by Mss11. Interestingly, many of these genes encode cell wall mannoproteins, in particular, members of the TIR and DAN families. To examine whether these genes play a role in the adhesion properties associated with Mss11 expression, we assessed deletion mutants of these genes in wild-type and flo11Δ genetic backgrounds. This analysis shows that only FLO genes, in particular FLO1/10/11, appear to significantly impact on such phenotypes. Thus adhesion-related phenotypes are primarily dependent on the balance of FLO gene expression.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing

PubMed Central

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.

PubMed

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).

The BDNF Val66Met Polymorphism Interacts with Maternal Parenting Influencing Adolescent Depressive Symptoms: Evidence of Differential Susceptibility Model.

PubMed

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.

Expression Quantitative Trait Locus Mapping across Water Availability Environments Reveals Contrasting Associations with Genomic Features in Arabidopsis[C][W][OPEN

PubMed Central

Lowry, David B.; Logan, Tierney L.; Santuari, Luca; Hardtke, Christian S.; Richards, James H.; DeRose-Wilson, Leah J.; McKay, John K.; Sen, Saunak; Juenger, Thomas E.

2013-01-01

The regulation of gene expression is crucial for an organism’s development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression. PMID:24045022

AURKA Phe31Ile polymorphism interacted with use of alcohol, betel quid, and cigarettes at multiplicative risk of oral cancer occurrence.

PubMed

Lee, Chi-Pin; Chiang, Shang-Lun; Lee, Chien-Hung; Tsai, Yi-Shan; Wang, Zhi-Hong; Hua, Chun-Hung; Chen, Yuan-Chien; Tsai, Eing-Mei; Ko, Ying-Chin

2015-11-01

The expression levels of two DNA repair genes (CHAF1A and CHAF1B) and a chromosome segregation gene (AURKA) were susceptible to arecoline exposure, a major alkaloid of areca nut. We hypothesize that genetic variants of these genes might also be implicated in the risk of oral cancer and could be modified by substance use of betel quid or alcohol and cigarettes. A case-control study, which included 507 patients with oral cancer and 717 matched controls, was performed in order to evaluate the cancer susceptibility by the tagging single-nucleotide polymorphisms (tagSNPs) in AURKA, CHAF1A, and CHAF1B using a genotyping assay and gene-environment interaction analysis. The Phe31Ile polymorphism (rs2273535, T91A) of AURKA was significantly associated with an increased risk of oral cancer (odds ratio (OR) = 2.1, 95% confidence interval (CI) 1.2-3.5). The gene dosage of the 91A allele also showed a significant trend in risk of oral cancer (P = 0.008). Furthermore, we found the AURKA 91AA homozygote was modifiable by substance use of alcohol, betel quid, and cigarettes (ABC), leading to increased risk of oral cancer in an additive or a multiplicative model (combined effect indexes = 1.2-4.0 and 1.5-2.2, respectively). However, no association was observed between the genetic variants of CHAF1A or CHAF1B and oral cancer risk in the study. These findings reveal the functional Phe31Ile polymorphism tagSNP of AURKA may be a strong susceptibility gene in ABC-related oral cancer occurrence. The results of this betel-related oral cancer study provide the evidence of environment-gene interaction for early prediction and molecular diagnosis.

Breast and Prostate Cancer and Hormone-Related Gene Variant Study

Cancer.gov

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.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork.

PubMed

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William T B; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-11-18

A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.

Combining research approaches to advance our understanding of drug addiction.

PubMed

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.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

PubMed

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.

Gene-environment interaction between adiponectin gene polymorphisms and environmental factors on the risk of diabetic retinopathy.

PubMed

Li, Yuan; Wu, Qun Hong; Jiao, Ming Li; Fan, Xiao Hong; Hu, Quan; Hao, Yan Hua; Liu, Ruo Hong; Zhang, Wei; Cui, Yu; Han, Li Yuan

2015-01-01

To evaluate whether the adiponectin gene is associated with diabetic retinopathy (DR) risk and interaction with environmental factors modifies the DR risk, and to investigate the relationship between serum adiponectin levels and DR. Four adiponectin polymorphisms were evaluated in 372 DR cases and 145 controls. Differences in environmental factors between cases and controls were evaluated by unconditional logistic regression analysis. The model-free multifactor dimensionality reduction method and traditional multiple regression models were applied to explore interactions between the polymorphisms and environmental factors. Using the Bonferroni method, we found no significant associations between four adiponectin polymorphisms and DR susceptibility. Multivariate logistic regression found that physical activity played a protective role in the progress of DR, whereas family history of diabetes (odds ratio 1.75) and insulin therapy (odds ratio 1.78) were associated with an increased risk for DR. The interaction between the C-11377 G (rs266729) polymorphism and insulin therapy might be associated with DR risk. Family history of diabetes combined with insulin therapy also increased the risk of DR. No adiponectin gene polymorphisms influenced the serum adiponectin levels. Serum adiponectin levels did not differ between the DR group and non-DR group. No significant association was identified between four adiponectin polymorphisms and DR susceptibility after stringent Bonferroni correction. The interaction between C-11377G (rs266729) polymorphism and insulin therapy, as well as the interaction between family history of diabetes and insulin therapy, might be associated with DR susceptibility.

Genome Wide Gene by Environment Interaction Analysis Identifies Common SNPs at 17q21.2 that Are Associated with Increased Body Mass Index Only among Asthmatics

DTIC Science & Technology

2015-12-16

polymorphisms (SNPs), a candidate gene association study was conducted to identify shared genetic variants between childhood asthma and obesity , but no SNP was...10):969– 76. doi: 10.1093/aje/kwh303 PMID: 15522853. 33. von Kries R, Hermann M, Grunert VP, von Mutius E. Is obesity a risk factor for childhood ...88PA, Case # 2014-4685, 7 Oct 2014. PLoS One. 2015; 10(12):e0144114. 14. ABSTRACT Asthmatics have an increased risk of being overweight/ obese

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat

PubMed Central

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

Influence of apolipoprotein E genotype on the transmission of Alzheimer disease in a community-based sample

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarvik, G.P.; Larson, E.B.; Goddard, K.

1996-01-01

The {epsilon}4 allele of the apolipoprotein E locus (APOE) has been found to be an important predictor of Alzheimer disease (AD). However, linkage analysis has not clarified the role of APOE in the transmission of AD. The results of the current study provide evidence that the pattern of transmission of memory disorders differs in nuclear families in which the AD-affected proband did carry an {epsilon}4 allele versus those families in which the AD-affected proband did not carry an {epsilon}4 allele. Further, risk of AD due to APOE genotype in the probands is modified by family history of memory disorders, suggestingmore » gene-by-gene interactions. Family history remained a significant predictor of AD for affected probands with some, but not all, APOE genotypes in a logistic regression analysis. Though nonadditive in the prediction of AD, APOE genotype and family history acted additively in the prediction of age at AD onset. The results of complex segregation analysis were inconsistent with Mendelian segregation of memory disorders both in families of affected probands who did or did not carry an {epsilon}4 allele, yet these two groups had significantly different parameter estimates for their transmission models. These results are consistent with gene-by-gene interactions, but also could result from common elements in the familial environment. 41 refs., 1 fig., 7 tabs.« less

Gene Expression Profiling Reveals Potential Players of Left-Right Asymmetry in Female Chicken Gonads.

PubMed

Wan, Zhiyi; Lu, Yanan; Rui, Lei; Yu, Xiaoxue; Yang, Fang; Tu, Chengfang; Li, Zandong

2017-06-20

Most female birds develop only a left ovary, whereas males develop bilateral testes. The mechanism underlying this process is still not completely understood. Here, we provide a comprehensive transcriptional analysis of female chicken gonads and identify novel candidate side-biased genes. RNA-Seq analysis was carried out on total RNA harvested from the left and right gonads on embryonic day 6 (E6), E12, and post-hatching day 1 (D1). By comparing the gene expression profiles between the left and right gonads, 347 differentially expressed genes (DEGs) were obtained on E6, 3730 were obtained on E12, and 2787 were obtained on D1. Side-specific genes were primarily derived from the autosome rather than the sex chromosome. Gene ontology and pathway analysis showed that the DEGs were most enriched in the Piwi-interactiing RNA (piRNA) metabolic process, germ plasm, chromatoid body, P granule, neuroactive ligand-receptor interaction, microbial metabolism in diverse environments, and methane metabolism. A total of 111 DEGs, five gene ontology (GO) terms, and three pathways were significantly different between the left and right gonads among all the development stages. We also present the gene number and the percentage within eight development-dependent expression patterns of DEGs in the left and right gonads of female chicken.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

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.

HFE gene C282Y variant is associated with colorectal cancer in Caucasians: a meta-analysis.

PubMed

Chen, Weidong; Zhao, Hua; Li, Tiegang; Yao, Hongliang

2013-08-01

The HFE gene has been suggested to play an important role in the pathogenesis of colorectal cancer. However, the results have been conflicting. In this study, we performed a meta-analysis to clarify the association of HFE gene C282Y variant with colorectal cancer. PubMed and Embase were retrieved to identify the potential literature. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. A total of eight papers including nine studies (7,588 colorectal cancer cases and 81,571 controls) for HFE gene C282Y variant were included in the meta-analysis. The result indicated that HFE gene C282Y variant was significantly associated with colorectal cancer under recessive model (OR = 2.00, 95 % CI = 1.32-3.04), with no evidence of between-study heterogeneity (I (2) = 0.2 %, p = 0.432). Further subgroup analysis by number of cases suggested the effect was significant in studies with more than 500 cases (OR = 2.51, 95 % CI = 1.58-3.98, I (2) = 0.0 %, p = 0.921), but not in studies with less than 500 cases (OR = 0.75, 95 % CI = 0.28-1.97, I (2) = 0.0 %, p = 0.622). The current meta-analysis supported the positive association of HFE gene C282Y variant with colorectal cancer. Further large-scale studies with the consideration for gene-gene/gene-environment interactions should be conducted to investigate the association.

Nutrigenomics of high fat diet induced obesity in mice suggests relationships between susceptibility to fatty liver disease and the proteasome.

PubMed

Waller-Evans, Helen; Hue, Christophe; Fearnside, Jane; Rothwell, Alice R; Lockstone, Helen E; Caldérari, Sophie; Wilder, Steven P; Cazier, Jean-Baptiste; Scott, James; Gauguier, Dominique

2013-01-01

Nutritional factors play important roles in the etiology of obesity, type 2 diabetes mellitus and their complications through genotype x environment interactions. We have characterised molecular adaptation to high fat diet (HFD) feeding in inbred mouse strains widely used in genetic and physiological studies. We carried out physiological tests, plasma lipid assays, obesity measures, liver histology, hepatic lipid measurements and liver genome-wide gene transcription profiling in C57BL/6J and BALB/c mice fed either a control or a high fat diet. The two strains showed marked susceptibility (C57BL/6J) and relative resistance (BALB/c) to HFD-induced insulin resistance and non alcoholic fatty liver disease (NAFLD). Global gene set enrichment analysis (GSEA) of transcriptome data identified consistent patterns of expression of key genes (Srebf1, Stard4, Pnpla2, Ccnd1) and molecular pathways in the two strains, which may underlie homeostatic adaptations to dietary fat. Differential regulation of pathways, including the proteasome, the ubiquitin mediated proteolysis and PPAR signalling in fat fed C57BL/6J and BALB/c suggests that altered expression of underlying diet-responsive genes may be involved in contrasting nutrigenomic predisposition and resistance to insulin resistance and NAFLD in these models. Collectively, these data, which further demonstrate the impact of gene x environment interactions on gene expression regulations, contribute to improved knowledge of natural and pathogenic adaptive genomic regulations and molecular mechanisms associated with genetically determined susceptibility and resistance to metabolic diseases.

Evidence of Reactive Gene-Environment Correlation in Preschoolers' Prosocial Play with Unfamiliar Peers

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…

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

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

PubMed Central

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

No Association Between Variant N-acetyltransferase Genes, Cigarette Smoking and Prostate Cancer Susceptibility Among Men of African Descent

PubMed Central

Kidd, La Creis Renee; VanCleave, Tiva T.; Doll, Mark A.; Srivastava, Daya S.; Thacker, Brandon; Komolafe, Oyeyemi; Pihur, Vasyl; Brock, Guy N.; Hein, David W.

2011-01-01

Objective We evaluated the individual and combination effects of NAT1, NAT2 and tobacco smoking in a case-control study of 219 incident prostate cancer (PCa) cases and 555 disease-free men. Methods Allelic discriminations for 15 NAT1 and NAT2 loci were detected in germ-line DNA samples using Taqman polymerase chain reaction (PCR) assays. Single gene, gene-gene and gene-smoking interactions were analyzed using logistic regression models and multi-factor dimensionality reduction (MDR) adjusted for age and subpopulation stratification. MDR involves a rigorous algorithm that has ample statistical power to assess and visualize gene-gene and gene-environment interactions using relatively small samples sizes (i.e., 200 cases and 200 controls). Results Despite the relatively high prevalence of NAT1*10/*10 (40.1%), NAT2 slow (30.6%), and NAT2 very slow acetylator genotypes (10.1%) among our study participants, these putative risk factors did not individually or jointly increase PCa risk among all subjects or a subset analysis restricted to tobacco smokers. Conclusion Our data do not support the use of N-acetyltransferase genetic susceptibilities as PCa risk factors among men of African descent; however, subsequent studies in larger sample populations are needed to confirm this finding. PMID:21709725

Clock genes × stress × reward interactions in alcohol and substance use disorders.

PubMed

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.

Monoamine Oxidase A (MAOA) and Catechol-O-Methyltransferase (COMT) Gene Polymorphisms Interact with Maternal Parenting in Association with Adolescent Reactive Aggression but not Proactive Aggression: Evidence of Differential Susceptibility.

PubMed

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.

Genetic and environmental influences on the development of alcoholism: resilience vs. risk.

PubMed

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.

Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

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…

Intellectual Interest Mediates Gene x Socioeconomic Status Interaction on Adolescent Academic Achievement

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.

PubMed

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.

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.

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.

PubMed

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.

A mathematical model of in vivo bovine blastocyst developmental to gestational Day 15.

PubMed

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.

Gene-gene-environment interactions between drugs, transporters, receptors, and metabolizing enzymes: Statins, SLCO1B1, and CYP3A4 as an example.

PubMed

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.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

PubMed Central

Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet. PMID:28695067

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis.

PubMed

Costa, Raquel L; Gadelha, Luiz; Ribeiro-Alves, Marcelo; Porto, Fábio

2017-01-01

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

Cancer risk and the complexity of the interactions between environmental and host factors: HENVINET interactive diagrams as simple tools for exploring and understanding the scientific evidence.

PubMed

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.

Gene by environment interactions influencing reading disability and the inattentive symptom dimension of attention deficit/hyperactivity disorder.

PubMed

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.

Systematic review, structural analysis, and new theoretical perspectives on the role of serotonin and associated genes in the etiology of psychopathy and sociopathy.

PubMed

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.

Listening to the noise: random fluctuations reveal gene network parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Munsky, Brian; Khammash, Mustafa

2009-01-01

The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich sourcemore » of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.« less

Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.

PubMed

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.

Correlation of interactions between NOS3 polymorphisms and oxygen therapy with retinopathy of prematurity susceptibility

PubMed Central

Yu, Chunhong; Yi, Jinglin; Yin, Xiaolong; Deng, Yan; Liao, Yujun; Li, Xiaobing

2015-01-01

Aim: This study was aimed to detect the correlation of nitric oxide synthase 3 (NOS3) gene polymorphisms (T-786C and G894T) and retinopathy of prematurity (ROP) susceptibility. Interaction between NOS3 gene polymorphisms and the duration of oxygen therapy was also explored in ROP babies. Methods: Genotypes of NOS3 gene polymorphisms were genotyped by MassArray method. Hardy-Weinberg equilibrium (HWE) was used to calculate the representativeness of the cases and controls. Crossover analysis was utilized to explore the gene environment interactions. Relative risk of ROP was presented by odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs). Results: Among the subject features, oxygen therapy had obvious difference between case and control groups (P<0.05). There existed significant association between-786C allele and ROP susceptibility (P=0.049, OR=0.669, 95% CI=0.447-0.999). Genotypes of T-786C polymorphism and genotypes and alleles of G894T polymorphism did not related to the susceptibility of ROP. Interactions were existed between NOS3 gene polymorphisms and oxygen therapy duration. When the duration of oxygen therapy was less than 17 days, both -786CC genotype and 894GT genotype were correlated with ROP susceptibility (P=0.020, OR=0.115, 95% CI=0.014-0.960; P=0.011, OR=0.294, 95% CI=0.100-0.784). Conclusion: -786C allele might have a protective effect for ROP. Interactions of -786CC and 894GT genotype with oxygen therapy duration (less than 17 days) were both protection factors of ROP. PMID:26823875

Child Dopamine Transporter Genotype and Parenting: Evidence for Evocative Gene-Environment Correlations

PubMed Central

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

Social environment influences the relationship between genotype and gene expression in wild baboons

PubMed Central

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

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer

PubMed Central

2014-01-01

Background A colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response. Methods A set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software). Results Here we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue. Conclusions The systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients. PMID:24597571

Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.

PubMed

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.

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

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.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Amphetamine Self-Administration and Dopamine Function: Assessment of Gene x Environment Interactions in Lewis and Fischer 344 Rats

PubMed Central

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

Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

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.

A gene-environment interaction analysis of plasma selenium with prevalent and incident diabetes: The Hortega study.

PubMed

Galan-Chilet, Inmaculada; Grau-Perez, Maria; De Marco, Griselda; Guallar, Eliseo; Martin-Escudero, Juan Carlos; Dominguez-Lucas, Alejandro; Gonzalez-Manzano, Isabel; Lopez-Izquierdo, Raul; Briongos-Figuero, Laisa Socorro; Redon, Josep; Chaves, Felipe Javier; Tellez-Plaza, Maria

2017-08-01

Selenium and single-nucleotide-polymorphisms in selenoprotein genes have been associated to diabetes. However, the interaction of selenium with genetic variation in diabetes and oxidative stress-related genes has not been evaluated as a potential determinant of diabetes risk. We evaluated the cross-sectional and prospective associations of plasma selenium concentrations with type 2 diabetes, and the interaction of selenium concentrations with genetic variation in candidate polymorphisms, in a representative sample of 1452 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.2µg/L. 120 participants had diabetes at baseline. Among diabetes-free participants who were not lost during the follow-up (N=1234), 75 developed diabetes over time. The multivariable adjusted odds ratios (95% confidence interval) for diabetes prevalence comparing the second and third to the first tertiles of plasma selenium levels were 1.80 (1.03, 3.14) and 1.97 (1.14, 3.41), respectively. The corresponding hazard ratios (95% CI) for diabetes incidence were 1.76 (0.96, 3.22) and 1.80 (0.98, 3.31), respectively. In addition, we observed significant interactions between selenium and polymorphisms in PPARGC1A, and in genes encoding mitochondrial proteins, such as BCS1L and SDHA, and suggestive interactions of selenium with other genes related to selenoproteins and redox metabolism. Plasma selenium was positively associated with prevalent and incident diabetes. While the statistical interactions of selenium with polymorphisms involved in regulation of redox and insulin signaling pathways provide biological plausibility to the positive associations of selenium with diabetes, further research is needed to elucidate the causal pathways underlying these associations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

Gene--Environment Interplay and Delinquent Involvement: Evidence of Direct, Indirect, and Interactive Effects

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…

Operating Characteristics of Statistical Methods for Detecting Gene-by-Measured Environment Interaction in the Presence of Gene-Environment Correlation under Violations of Distributional Assumptions.

PubMed

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.

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

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

The relationship between glucocorticoid receptor polymorphisms, stressful life events, social support, and post-traumatic stress disorder.

PubMed

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.

Trends of the Major Porin Gene (ompF) Evolution: Insight from the Genus Yersinia

PubMed Central

Stenkova, Anna M.; Isaeva, Marina P.; Shubin, Felix N.; Rasskazov, Valeri A.; Rakin, Alexander V.

2011-01-01

OmpF is one of the major general porins of Enterobacteriaceae that belongs to the first line of bacterial defense and interactions with the biotic as well as abiotic environments. Porins are surface exposed and their structures strongly reflect the history of multiple interactions with the environmental challenges. Unfortunately, little is known on diversity of porin genes of Enterobacteriaceae and the genus Yersinia especially. We analyzed the sequences of the ompF gene from 73 Yersinia strains covering 14 known species. The phylogenetic analysis placed most of the Yersinia strains in the same line assigned by 16S rDNA-gyrB tree. Very high congruence in the tree topologies was observed for Y. enterocolitica, Y. kristensenii, Y. ruckeri, indicating that intragenic recombination in these species had no effect on the ompF gene. A significant level of intra- and interspecies recombination was found for Y. aleksiciae, Y. intermedia and Y. mollaretii. Our analysis shows that the ompF gene of Yersinia has evolved with nonrandom mutational rate under purifying selection. However, several surface loops in the OmpF porin contain positively selected sites, which very likely reflect adaptive diversification Yersinia to their ecological niches. To our knowledge, this is a first investigation of diversity of the porin gene covering the whole genus of the family Enterobacteriaceae. This study demonstrates that recombination and positive selection both contribute to evolution of ompF, but the relative contribution of these evolutionary forces are different among Yersinia species. PMID:21655186

The Evaluation of Methicillin Resistance in Staphylococcus aboard the International Space Station

NASA Technical Reports Server (NTRS)

Ott, C. M.; Bassinger, V. J.; Fontenot, S. L.; Castro, V. A.; Pierson, D. L.

2005-01-01

The International Space Station (ISS) represents a semi-closed environment with a high level of crewmember interaction. As community-acquired methicillin-resistant Staphylococcus aureus (MRSA) has emerged as a health concern in environments with susceptible hosts in close proximity, an evaluation of isolates of clinical and environmental Staphylococcus aureus and coagulase negative Staphylococcus was performed to determine if this trend was also present in astronauts aboard ISS or the space station itself. Rep-PCR fingerprinting analysis of archived ISS isolates confirmed our earlier studies indicating a transfer of S. aureus between crewmembers. In addition, this fingerprinting also indicated a transfer between crewmembers and their environment. While a variety of S. aureus were identified from both the crewmembers and the environment, phenotypic evaluations indicated minimal methicillin resistance. However, positive results for the Penicillin Binding Protein, indicative of the presence of the mecA gene, were detected in multiple isolates of archived Staphylococcus epidermidis and Staphylococcus haemolyticus. Phenotypic analysis of these isolates confirmed their resistance to methicillin. While MRSA has not been isolated aboard ISS, the potential exists for the transfer of the gene, mecA, from coagulase negative environmental Staphylococcus to S. aureus creating MRSA strains. This study suggests the need to expand environmental monitoring aboard long duration exploration spacecraft to include antibiotic resistance profiling.

Gene-Diet Interaction and Precision Nutrition in Obesity

PubMed Central

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

Vulnerability or Sensitivity to the Environment? Methodological Issues, Trends, and Recommendations in Gene-Environment Interactions Research in Human Behavior.

PubMed

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.

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

PubMed

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?

PubMed Central

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

Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

What Gene-Environment Interactions Can Tell Us about Social Competence in Typical and Atypical Populations

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…

Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.

PubMed

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.

Original BPC3 Research Plan

Cancer.gov

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.

MAOA genotype, social exclusion and aggression: an experimental test of a gene-environment interaction.

PubMed

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.

Understanding oral stereotypies in calves: alternative strategies, hypothalamic-pituitary-adrenal axis (re)activity and gene by environment interactions.

PubMed

Webb, L E; van Reenen, C G; Engel, B; Berends, H; Gerrits, W J J; Bokkers, E A M

2017-06-01

Stereotypies are used as indicators of poor animal welfare and it is, therefore, important to understand underlying factors mediating their development. In calves, two oral stereotypies, that is, tongue playing and object manipulation, result mostly from insufficient structure in the diet. Three hypotheses were studied: (1) oral stereotypies in calves are one of two alternative strategies, the alternative being hypo-activity; (2) stereotyping and non-stereotyping calves differ in terms of cortisol secretion; (3) oral stereotypy development in calves rests on a gene by environment interaction. Eight-week-old bull calves (n=48) were assigned to one of four solid feed allowances (0, 9, 18 or 27 g dry matter/kg metabolic weight per day) with the following composition: 50% concentrate, 25% maize silage and 25% straw on dry matter basis. The calves received milk replacer in buckets, the provision of which was adjusted to achieve equal growth rates. At 14 to 18 weeks of age, calves were exposed to a challenge, that is, tethering inside cages. Oral stereotypies and inactivity were recorded in the home pens in the 4 weeks before the challenge using instantaneous scan sampling. Salivary cortisol levels were measured at -120, +40, +80, +120 min and +48 h relative to the challenge. Individual differences in behaviour were recorded in the first 30 min after challenge implementation using focal animal sampling and continuous recording, and these elements were entered into a principal component (PC) analysis to extract PCs. Regression analyses were performed to find relationships between stereotypies and inactivity, stereotypies and cortisol, and stereotypies and PCs (individual differences, genes) and solid feed (environment). Relationships between PCs and cortisol were also investigated to help with the interpretation of PCs. Hypotheses 1 and 2 were rejected. Hypothesis 3, however, was supported: calves with a zero solid feed allowance, that is, in the most barren environment, showed links between stereotypies and two of the PCs. Calves that displayed high levels of idle and rapid locomotion and low levels of oral contact with the cage during the challenge also displayed high levels of object manipulation in the home pens. Calves that displayed low levels of stepping and turning attempts during the challenge also displayed high levels of tongue playing in the home pens. This study corroborates the gene by environment interaction on the development of oral stereotypies in calves.

The genetics of music accomplishment: evidence for gene-environment correlation and interaction.

PubMed

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.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

How Genes and the Social Environment Moderate Each Other

PubMed Central

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

Alteration of synaptic activity-regulating genes underlying functional improvement by long-term exposure to an enriched environment in the adult brain.

PubMed

Lee, Min-Young; Yu, Ji Hea; Kim, Ji Yeon; Seo, Jung Hwa; Park, Eun Sook; Kim, Chul Hoon; Kim, Hyongbum; Cho, Sung-Rae

2013-01-01

Housing animals in an enriched environment (EE) enhances behavioral function. However, the mechanism underlying this EE-mediated functional improvement and the resultant changes in gene expression have yet to be elucidated. We attempted to investigate the underlying mechanisms associated with long-term exposure to an EE by evaluating gene expression patterns. We housed 6-week-old CD-1 (ICR) mice in standard cages or an EE comprising a running wheel, novel objects, and social interaction for 2 months. Motor and cognitive performances were evaluated using the rotarod test and passive avoidance test, and gene expression profile was investigated in the cerebral hemispheres using microarray and gene set enrichment analysis (GSEA). In behavioral assessment, an EE significantly enhanced rotarod performance and short-term working memory. Microarray analysis revealed that genes associated with neuronal activity were significantly altered by an EE. GSEA showed that genes involved in synaptic transmission and postsynaptic signal transduction were globally upregulated, whereas those associated with reuptake by presynaptic neurotransmitter transporters were downregulated. In particular, both microarray and GSEA demonstrated that EE exposure increased opioid signaling, acetylcholine release cycle, and postsynaptic neurotransmitter receptors but decreased Na+ / Cl- -dependent neurotransmitter transporters, including dopamine transporter Slc6a3 in the brain. Western blotting confirmed that SLC6A3, DARPP32 (PPP1R1B), and P2RY12 were largely altered in a region-specific manner. An EE enhanced motor and cognitive function through the alteration of synaptic activity-regulating genes, improving the efficient use of neurotransmitters and synaptic plasticity by the upregulation of genes associated with postsynaptic receptor activity and downregulation of presynaptic reuptake by neurotransmitter transporters.

Prevention of asthma: where are we in the 21st century?

PubMed

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.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

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

The interaction of combined effects of the BDNF and PRKCG genes and negative life events in major depressive disorder.

PubMed

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.

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

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

Differential susceptibility to maternal expressed emotion in children with ADHD and their siblings? Investigating plasticity genes, prosocial and antisocial behaviour.

PubMed

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.

Differential Susceptibility to Maternal Expressed Emotion in Children with ADHD and their Siblings? Investigating Plasticity Genes, Prosocial and Antisocial Behaviour

PubMed Central

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

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

PubMed

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.

PubMed

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.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis.

PubMed

Vaessen, Thomas Stephanus Johannes; de Jong, Lea; Schäfer, Annika Theresia; Damen, Thomas; Uittenboogaard, Aniek; Krolinski, Pauline; Nwosu, Chinyere Vicky; Pinckaers, Florentina Maria Egidius; Rotee, Iris Leah Marije; Smeets, Antonius Petrus Wilhelmus; Ermiş, Ayşegül; Kennedy, James L; Nieman, Dorien H; Tiwari, Arun; van Os, Jim; Drukker, Marjan

2018-01-01

Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive. A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl transferase (COMT) polymorphism Val158Met (COMTVal158Met). PubMed, Embase, PsychInfo. All observational studies assessing the interaction between COMTVal158Met and cannabis with any psychosis or psychotic symptoms measure as an outcome. A meta-analysis was performed using the Meta-analysis of Observational Studies in Epidemiology guidelines and forest plots were generated. Thirteen articles met the selection criteria: 7 clinical studies using a case-only design, 3 clinical studies with a dichotomous outcome, and 3 studies analysing a continuous outcome of psychotic symptoms below the threshold of psychotic disorder. The three study types were analysed separately. Validity of the included studies was assessed using "A Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions". For case-only studies, a significant interaction was found between cannabis use and COMTVal158Met, with an OR of 1.45 (95% Confidence Interval = 1.05-2.00; Met/Met as the risk genotype). However, there was no evidence for interaction in either the studies including dichotomous outcomes (B = -0.51, 95% Confidence Interval -1.72, 0.70) or the studies including continuous outcomes (B = -0.04 95% Confidence Interval -0.16-0.08). A substantial part of the included studies used the case-only design, which has lower validity and tends to overestimate true effects. The interaction term between cannabis use and COMTVal158Met was only statistically significant in the case-only studies, but not in studies using other clinical or non-clinical psychosis outcomes. Future additional high quality studies might change current perspectives, yet currently evidence for the interaction remains unconvincing.

GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.

PubMed

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.

Gene-Diet Interactions in Childhood Obesity

PubMed Central

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

ChemiRs: a web application for microRNAs and chemicals.

PubMed

Su, Emily Chia-Yu; Chen, Yu-Sing; Tien, Yun-Cheng; Liu, Jeff; Ho, Bing-Ching; Yu, Sung-Liang; Singh, Sher

2016-04-18

MicroRNAs (miRNAs) are about 22 nucleotides, non-coding RNAs that affect various cellular functions, and play a regulatory role in different organisms including human. Until now, more than 2500 mature miRNAs in human have been discovered and registered, but still lack of information or algorithms to reveal the relations among miRNAs, environmental chemicals and human health. Chemicals in environment affect our health and daily life, and some of them can lead to diseases by inferring biological pathways. We develop a creditable online web server, ChemiRs, for predicting interactions and relations among miRNAs, chemicals and pathways. The database not only compares gene lists affected by chemicals and miRNAs, but also incorporates curated pathways to identify possible interactions. Here, we manually retrieved associations of miRNAs and chemicals from biomedical literature. We developed an online system, ChemiRs, which contains miRNAs, diseases, Medical Subject Heading (MeSH) terms, chemicals, genes, pathways and PubMed IDs. We connected each miRNA to miRBase, and every current gene symbol to HUGO Gene Nomenclature Committee (HGNC) for genome annotation. Human pathway information is also provided from KEGG and REACTOME databases. Information about Gene Ontology (GO) is queried from GO Online SQL Environment (GOOSE). With a user-friendly interface, the web application is easy to use. Multiple query results can be easily integrated and exported as report documents in PDF format. Association analysis of miRNAs and chemicals can help us understand the pathogenesis of chemical components. ChemiRs is freely available for public use at http://omics.biol.ntnu.edu.tw/ChemiRs .

Genomic analysis reveals the major driving forces of bacterial life in the rhizosphere

PubMed Central

Matilla, Miguel A; Espinosa-Urgel, Manuel; Rodríguez-Herva, José J; Ramos, Juan L; Ramos-González, María Isabel

2007-01-01

Background Mutualistic interactions less well known than those between rhizobia and legumes are commonly found between plants and bacteria, frequently pseudomonads, which colonize roots and adjacent soil areas (the rhizosphere). Results A global analysis of Pseudomonas putida genes expressed during their interaction with maize roots revealed how a bacterial population adjusts its genetic program to this lifestyle. Differentially expressed genes were identified by comparing rhizosphere-colonizing populations with three distinct controls covering a variety of nutrients, growth phases and life styles (planktonic and sessile). Ninety rhizosphere up-regulated (rup) genes, which were induced relative to all three controls, were identified, whereas there was no repressed gene in common between the experiments. Genes involved in amino acid uptake and metabolism of aromatic compounds were preferentially expressed in the rhizosphere, which reflects the availability of particular nutrients in root exudates. The induction of efflux pumps and enzymes for glutathione metabolism indicates that adaptation to adverse conditions and stress (oxidative) response are crucial for bacterial life in this environment. The finding of a GGDEF/EAL domain response regulator among the induced genes suggests a role for the turnover of the secondary messenger c-diGMP in root colonization. Several mutants in rup genes showed reduced fitness in competitive root colonization. Conclusion Our results show the importance of two selective forces of different nature to colonize the rhizosphere: stress adaptation and availability of particular nutrients. We also identify new traits conferring bacterial survival in this niche and open a way to the characterization of specific signalling and regulatory processes governing the plant-Pseudomonas association. PMID:17784941

Expression of an isoflavone reductase-like gene enhanced by pollen tube growth in pistils of Solanum tuberosum.

PubMed

van Eldik, G J; Ruiter, R K; Colla, P H; van Herpen, M M; Schrauwen, J A; Wullems, G J

1997-03-01

Successful sexual reproduction relies on gene products delivered by the pistil to create an environment suitable for pollen tube growth. These compounds are either produced before pollination or formed during the interactions between pistil and pollen tubes. Here we describe the pollination-enhanced expression of the cp100 gene in pistils of Solanum tuberosum. Temporal analysis of gene expression revealed an enhanced expression already one hour after pollination and lasts more than 72 h. Increase in expression also occurred after touching the stigma and was not restricted to the site of touch but spread into the style. The predicted CP100 protein shows similarity to leguminous isoflavone reductases (IFRs), but belongs to a family of IFR-like NAD(P)H-dependent oxidoreductases present in various plant species.

Advances in asthma and allergy genetics in 2007.

PubMed

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.

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

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

Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

PubMed

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.

PubMed

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.

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

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

Meta-analysis of the serotonin transporter promoter variant (5-HTTLPR) in relation to adverse environment and antisocial behavior.

PubMed

Tielbeek, Jorim J; Karlsson Linnér, Richard; Beers, Koko; Posthuma, Danielle; Popma, Arne; Polderman, Tinca J C

2016-07-01

Several studies have suggested an association between antisocial, aggressive, and delinquent behavior and the short variant of the serotonin transporter gene polymorphism (5-HTTLPR). Yet, genome wide and candidate gene studies in humans have not convincingly shown an association between these behaviors and 5-HTTLPR. Moreover, individual studies examining the effect of 5-HTTLPR in the presence or absence of adverse environmental factors revealed inconsistent results. We therefore performed a meta-analysis to test for the robustness of the potential interaction effect of the "long-short" variant of the 5-HTTLPR genotype and environmental adversities, on antisocial behavior. Eight studies, comprising of 12 reasonably independent samples, totaling 7,680 subjects with an effective sample size of 6,724, were included in the meta-analysis. Although our extensive meta-analysis resulted in a significant interaction effect between the 5-HTTLPR genotype and environmental adversities on antisocial behavior, the methodological constraints of the included studies hampered a confident interpretation of our results, and firm conclusions regarding the direction of effect. Future studies that aim to examine biosocial mechanisms that influence the etiology of antisocial behavior should make use of larger samples, extend to genome-wide genetic risk scores and properly control for covariate interaction terms, ensuring valid and well-powered research designs. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Testing differential susceptibility: Plasticity genes, the social environment, and their interplay in adolescent response inhibition.

PubMed

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.

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

[Genome-scale sequence data processing and epigenetic analysis of DNA methylation].

PubMed

Wang, Ting-Zhang; Shan, Gao; Xu, Jian-Hong; Xue, Qing-Zhong

2013-06-01

A new approach recently developed for detecting cytosine DNA methylation (mC) and analyzing the genome-scale DNA methylation profiling, is called BS-Seq which is based on bisulfite conversion of genomic DNA combined with next-generation sequencing. The method can not only provide an insight into the difference of genome-scale DNA methylation among different organisms, but also reveal the conservation of DNA methylation in all contexts and nucleotide preference for different genomic regions, including genes, exons, and repetitive DNA sequences. It will be helpful to under-stand the epigenetic impacts of cytosine DNA methylation on the regulation of gene expression and maintaining silence of repetitive sequences, such as transposable elements. In this paper, we introduce the preprocessing steps of DNA methylation data, by which cytosine (C) and guanine (G) in the reference sequence are transferred to thymine (T) and adenine (A), and cytosine in reads is transferred to thymine, respectively. We also comprehensively review the main content of the DNA methylation analysis on the genomic scale: (1) the cytosine methylation under the context of different sequences; (2) the distribution of genomic methylcytosine; (3) DNA methylation context and the preference for the nucleotides; (4) DNA- protein interaction sites of DNA methylation; (5) degree of methylation of cytosine in the different structural elements of genes. DNA methylation analysis technique provides a powerful tool for the epigenome study in human and other species, and genes and environment interaction, and founds the theoretical basis for further development of disease diagnostics and therapeutics in human.

Gene-environment interactions in the aetiology of systemic lupus erythematosus.

PubMed

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.

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.

PubMed

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.

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

PubMed Central

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

Genetic susceptibility to family environment: BDNF Val66met and 5-HTTLPR influence depressive symptoms.

PubMed

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.

Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork

PubMed Central

Druka, Arnis; Druka, Ilze; Centeno, Arthur G; Li, Hongqiang; Sun, Zhaohui; Thomas, William TB; Bonar, Nicola; Steffenson, Brian J; Ullrich, Steven E; Kleinhofs, Andris; Wise, Roger P; Close, Timothy J; Potokina, Elena; Luo, Zewei; Wagner, Carola; Schweizer, Günther F; Marshall, David F; Kearsey, Michael J; Williams, Robert W; Waugh, Robbie

2008-01-01

Background A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community. Description Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork . GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them. Conclusion By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets. PMID:19017390

Assessment of Gene-by-Sex Interaction Effect on Bone Mineral Density

PubMed Central

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M.; Amin, Najaf; Evangelou, Evangelos; Li, Guo; Minster, Ryan L.; Carless, Melanie A.; Kammerer, Candace M.; Oei, Ling; Zhou, Yanhua; Alonso, Nerea; Dailiana, Zoe; Eriksson, Joel; García-Giralt, Natalia; Giroux, Sylvie; Husted, Lise Bjerre; Khusainova, Rita I.; Koromila, Theodora; Kung, Annie WaiChee; Lewis, Joshua R.; Masi, Laura; Mencej-Bedrac, Simona; Nogues, Xavier; Patel, Millan S.; Prezelj, Janez; Richards, J Brent; Sham, Pak Chung; Spector, Timothy; Vandenput, Liesbeth; Xiao, Su-Mei; Zheng, Hou-Feng; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza K.; Kollia, Panagoula; Langdahl, Bente Lomholt; Ljunggren, Östen; Lorentzon, Mattias; Marc, Janja; Mellström, Dan; Ohlsson, Claes; Olmos, José M.; Ralston, Stuart H.; Riancho, José A.; Rousseau, François; Urreizti, Roser; Van Hul, Wim; Zarrabeitia, María T.; Castano-Betancourt, Martha; Demissie, Serkalem; Grundberg, Elin; Herrera, Lizbeth; Kwan, Tony; Medina-Gómez, Carolina; Pastinen, Tomi; Sigurdsson, Gunnar; Thorleifsson, Gudmar; vanMeurs, Joyce B.J.; Blangero, John; Hofman, Albert; Liu, Yongmei; Mitchell, Braxton D.; O’Connell, Jeffrey R.; Oostra, Ben A.; Rotter, Jerome I; Stefansson, Kari; Streeten, Elizabeth A.; Styrkarsdottir, Unnur; Thorsteinsdottir, Unnur; Tylavsky, Frances A.; Uitterlinden, Andre; Cauley, Jane A.; Harris, Tamara B.; Ioannidis, John P.A.; Psaty, Bruce M.; Robbins, John A; Zillikens, M. Carola; vanDuijn, Cornelia M.; Prince, Richard L.; Karasik, David; Rivadeneira, Fernando; Kiel, Douglas P.; Cupples, L. Adrienne; Hsu, Yi-Hsiang

2012-01-01

Background Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed eQTL analysis and bioinformatics network analysis. Methods We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS-) and femoral neck (FN-) BMD, in 25,353 individuals from eight cohorts. In a second stage, we followed up the 12 top SNPs (P<1×10−5) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. Results We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 & p-value = 3.0×10−5; female effect = −0.007 & p-value=3.3×10−2) and eleven suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (P<5×10−8) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Conclusion Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found influencing BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. PMID:22692763

On meta- and mega-analyses for gene–environment interactions

PubMed Central

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M.; Whitehead, Alexander S.; Blair, Ian A.; Vachani, Anil; Clapper, Margie L.; Muscat, Joshua E.; Lazarus, Philip; Scheet, Paul; Moore, Jason H.; Chen, Yong

2017-01-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a “mega” data set, which can be fit by a joint “mega-analysis.” Alternatively, analyses can be done at each site, and results across sites can be combined through a “meta-analysis” procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. PMID:29110346

Genetic Influences Can Protect Against Unresponsive Parenting in the Prediction of Child Social Competence

PubMed Central

Van Ryzin, Mark J.; Leve, Leslie D.; Neiderhiser, Jenae M.; Shaw, Daniel S.; Natsuaki, Misaki N.; Reiss, David

2014-01-01

Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this paper, we evaluate the possibility of a gene-by-environment (GxE) interaction in the prediction of social competence in school-age children. Using a longitudinal, multi-method dataset from a sample of children adopted at birth (N = 361), we found a significant interaction between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting. PMID:25581124

Transcriptomic analysis suggests a key role for SQUAMOSA PROMOTER BINDING PROTEIN LIKE, NAC and YUCCA genes in the heteroblastic development of the temperate rainforest tree Gevuina avellana (Proteaceae).

PubMed

Ostria-Gallardo, Enrique; Ranjan, Aashish; Chitwood, Daniel H; Kumar, Ravi; Townsley, Brad T; Ichihashi, Yasunori; Corcuera, Luis J; Sinha, Neelima R

2016-04-01

Heteroblasty, the temporal development of the meristem, can produce diverse leaf shapes within a plant. Gevuina avellana, a tree from the South American temperate rainforest shows strong heteroblasty affecting leaf shape, transitioning from juvenile simple leaves to highly pinnate adult leaves. Light availability within the forest canopy also modulates its leaf size and complexity. Here we studied how the interaction between the light environment and the heteroblastic progression of leaves is coordinated in this species. We used RNA-seq on the Illumina platform to compare the range of transcriptional responses in leaf primordia of G. avellana at different heteroblastic stages and growing under different light environments. We found a steady up-regulation of SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL), NAC, YUCCA and AGAMOUS-LIKE genes associated with increases in age, leaf complexity, and light availability. In contrast, expression of TCP, TPR and KNOTTED1 homeobox genes showed a sustained down-regulation. Additionally, genes involved in auxin synthesis/transport and jasmonate activity were differentially expressed, indicating an active regulation of processes controlled by these hormones. Our large-scale transcriptional analysis of the leaf primordia of G. avellana sheds light on the integration of internal and external cues during heteroblastic development in this species. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

The transcriptomic responses of the eastern oyster, Crassostrea virginica, to environmental conditions.

PubMed

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.

Does Parental Divorce Moderate the Heritability of Body Dissatisfaction? An Extension of Previous Gene-Environment Interaction Effects

PubMed Central

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

Does parental divorce moderate the heritability of body dissatisfaction? An extension of previous gene-environment interaction effects.

PubMed

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.

Detection and characterization of gene-gene and gene-environment interactions in common human diseases and complex clinical endpoints

EPA Science Inventory

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...

Darwin's legacy II: why biology is not physics, or why it has taken a century to see the dependence of genes on the environment.

PubMed

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.

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

PubMed

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.

Interactions Between Secondhand Smoke and Genes That Affect Cystic Fibrosis Lung Disease

PubMed Central

Collaco, J. Michael; Vanscoy, Lori; Bremer, Lindsay; McDougal, Kathryn; Blackman, Scott M.; Bowers, Amanda; Naughton, Kathleen; Jennings, Jacky; Ellen, Jonathan; Cutting, Garry R.

2011-01-01

Context Disease variation can be substantial even in conditions with a single gene etiology such as cystic fibrosis (CF). Simultaneously studying the effects of genes and environment may provide insight into the causes of variation. Objective To determine whether secondhand smoke exposure is associated with lung function and other outcomes in individuals with CF, whether socioeconomic status affects the relationship between secondhand smoke exposure and lung disease severity, and whether specific gene-environment interactions influence the effect of secondhand smoke exposure on lung function. Design, Setting, and Participants Retrospective assessment of lung function, stratified by environmental and genetic factors. Data were collected by the US Cystic Fibrosis Twin and Sibling Study with missing data supplemented by the Cystic Fibrosis Foundation Data Registry. All participants were diagnosed with CF, were recruited between October 2000 and October 2006, and were primarily from the United States. Main Outcome Measures Disease-specific cross-sectional and longitudinal measures of lung function. Results Of 812 participants with data on secondhand smoke in the home, 188 (23.2%) were exposed. Of 780 participants with data on active maternal smoking during gestation, 129 (16.5%) were exposed. Secondhand smoke exposure in the home was associated with significantly lower cross-sectional (9.8 percentile point decrease; P<.001) and longitudinal lung function (6.1 percentile point decrease; P=.007) compared with those not exposed. Regression analysis demonstrated that socioeconomic status did not confound the adverse effect of secondhand smoke exposure on lung function. Interaction between gene variants and secondhand smoke exposure resulted in significant percentile point decreases in lung function, namely in CFTR non-ΔF508 homozygotes (12.8 percentile point decrease; P=.001), TGFβ1-509 TT homozygotes (22.7 percentile point decrease; P=.006), and TGFβ1 codon 10 CC homozygotes (20.3 percentile point decrease; P=.005). Conclusions Any exposure to secondhand smoke adversely affects both cross-sectional and longitudinal measures of lung function in individuals with CF. Variations in the gene that causes CF (CFTR) and a CF-modifier gene (TGFβ1) amplify the negative effects of secondhand smoke exposure. PMID:18230779

Seminar: Developmental Dyslexia

PubMed Central

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

Transcriptome analysis of zebrafish embryos exposed to deltamethrin.

PubMed

Chueh, Tsung-Cheng; Hsu, Li-Sung; Kao, Chin-Ming; Hsu, Tung-Wei; Liao, Hung-Yu; Wang, Kuan-Yi; Chen, Ssu Ching

2017-05-01

Deltamethrin (DTM), a type II pyrethroid, is one of the most commonly used insecticides. The increased use of pyrethroid leads to potential adverse effects, particularly in sensitive populations such as children and pregnant women. None of the related studies was focused on the transcriptome responses in zebrafish embryos after treatment with DTM; therefore, RNA-seq, a high-throughput method, was performed to analyze the global expression of differential expressed genes (DEGs) in zebrafish embryos treated with DTM (40 and 80 μg/L) from fertilization to 48 h postfertilization (hpf) as compared with that in the control group (without DTM treatment). Two cDNA libraries were generated from treated embryos and one cDNA library from nontreated embryos, respectively. Over 92% of reads mapped to the reference in these three libraries. It was observed that many differential genes were expressed in comparison with embryos before and after DTM. The 20 most differentially expressed upregulated or downregulated genes were majorly involved in the signaling transduction. Validation of selected nine genes expression using qRT-PCR confirmed RNA-seq results. The transcriptome sequences were further subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, showing G-protein-coupled receptor signaling pathway and neuroactive ligand-receptor interaction, respectively, were most enriched. The data from this study contributed to a better understanding of the potential consequences of fish exposed to DTM, to an evaluation of the potential threat of DTM to fish populations in aquatic environments. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1548-1557, 2017. © 2016 Wiley Periodicals, Inc.

Interactions between Early Parenting and a Polymorphism of the Child’s Dopamine Transporter Gene in Predicting Future Child Conduct Disorder Symptoms

PubMed Central

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

Gene Expression Changes in the Olfactory Bulb of Mice Induced by Exposure to Diesel Exhaust Are Dependent on Animal Rearing Environment

PubMed Central

Yokota, Satoshi; Hori, Hiroshi; Umezawa, Masakazu; Kubota, Natsuko; Niki, Rikio; Yanagita, Shinya; Takeda, Ken

2013-01-01

There is an emerging concern that particulate air pollution increases the risk of cranial nerve disease onset. Small nanoparticles, mainly derived from diesel exhaust particles reach the olfactory bulb by their nasal depositions. It has been reported that diesel exhaust inhalation causes inflammation of the olfactory bulb and other brain regions. However, these toxicological studies have not evaluated animal rearing environment. We hypothesized that rearing environment can change mice phenotypes and thus might alter toxicological study results. In this study, we exposed mice to diesel exhaust inhalation at 90 µg/m3, 8 hours/day, for 28 consecutive days after rearing in a standard cage or environmental enrichment conditions. Microarray analysis found that expression levels of 112 genes were changed by diesel exhaust inhalation. Functional analysis using Gene Ontology revealed that the dysregulated genes were involved in inflammation and immune response. This result was supported by pathway analysis. Quantitative RT-PCR analysis confirmed 10 genes. Interestingly, background gene expression of the olfactory bulb of mice reared in a standard cage environment was changed by diesel exhaust inhalation, whereas there was no significant effect of diesel exhaust exposure on gene expression levels of mice reared with environmental enrichment. The results indicate for the first time that the effect of diesel exhaust exposure on gene expression of the olfactory bulb was influenced by rearing environment. Rearing environment, such as environmental enrichment, may be an important contributive factor to causation in evaluating still undefined toxic environmental substances such as diesel exhaust. PMID:23940539

Axonal guidance signaling pathway interacting with smoking in modifying the risk of pancreatic cancer: a gene- and pathway-based interaction analysis of GWAS data.

PubMed

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; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolph; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-05-01

Cigarette smoking is the best established modifiable risk factor for pancreatic cancer. Genetic factors that underlie smoking-related pancreatic cancer have previously not been examined at the genome-wide level. Taking advantage of the existing Genome-wide association study (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study in 2028 cases and 2109 controls to examine gene-smoking interactions at pathway/gene/single nucleotide polymorphism (SNP) level. Using the likelihood ratio test nested in logistic regression models and ingenuity pathway analysis (IPA), we examined 172 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, 3 manually curated gene sets, 3 nicotine dependency gene ontology pathways, 17 912 genes and 468 114 SNPs. None of the individual pathway/gene/SNP showed significant interaction with smoking after adjusting for multiple comparisons. Six KEGG pathways showed nominal interactions (P < 0.05) with smoking, and the top two are the pancreatic secretion and salivary secretion pathways (major contributing genes: RAB8A, PLCB and CTRB1). Nine genes, i.e. ZBED2, EXO1, PSG2, SLC36A1, CLSTN1, MTHFSD, FAT2, IL10RB and ATXN2 had P interaction < 0.0005. Five intergenic region SNPs and two SNPs of the EVC and KCNIP4 genes had P interaction < 0.00003. In IPA analysis of genes with nominal interactions with smoking, axonal guidance signaling $$\\left(P=2.12\\times 1{0}^{-7}\\right)$$ and α-adrenergic signaling $$\\left(P=2.52\\times 1{0}^{-5}\\right)$$ genes were significantly overrepresented canonical pathways. Genes contributing to the axon guidance signaling pathway included the SLIT/ROBO signaling genes that were frequently altered in pancreatic cancer. These observations need to be confirmed in additional data set. Once confirmed, it will open a new avenue to unveiling the etiology of smoking-associated pancreatic cancer.

The Dopamine D2 Receptor Gene, Perceived Parental Support, and Adolescent Loneliness: Longitudinal Evidence for Gene-Environment Interactions

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.

PubMed

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.

Screening toll-like receptor markers to predict latent tuberculosis infection and subsequent tuberculosis disease in a Chinese population.

PubMed

Wu, Linlin; Hu, Yi; Li, Dange; Jiang, Weili; Xu, Biao

2015-04-01

We investigated whether polymorphisms in the toll-like receptor genes or gene-gene interactions are associated with susceptibility to latent tuberculosis infection (LTBI) or subsequent pulmonary tuberculosis (PTB) in a Chinese population. Two matched case-control studies were undertaken. Previously reported polymorphisms in the toll-like receptors (TLRs) were compared between 422 healthy controls (HC) and 205 LTBI patients and between 205 LTBI patients and 109 PTB patients, to assess whether these polymorphisms and their interactions are associated with LTBI or PTB. A PCR-based restriction fragment length polymorphism analysis was used to detect genetic polymorphisms in the TLR genes. Nonparametric multifactor dimensionality reduction (MDR) was used to analyze the effects of interactions between complex disease genes and other genes or environmental factors. Sixteen markers in TLR1, TLR2, TLR4, TLR6, TLR8, TLR9, and TIRAP were detected. In TLR2, the frequencies of the CC genotype (OR = 2.262; 95% CI: 1.433-3.570) and C allele (OR = 1.566; 95% CI: 1.223-1.900) in single-nucleotide polymorphism (SNP) rs3804100 were significantly higher in the LTBI group than in the HC group, whereas the GA genotype of SNP rs5743708 was associated with PTB (OR = 6.087; 95% CI: 1.687-21.968). The frequencies of the GG genotype of SNP rs7873784 in TLR4 (OR = 2.136; 95% CI: 1.312-3.478) and the CC genotype of rs3764879 in TLR8 (OR = 1.982; 95% CI: 1.292-3.042) were also significantly higher in the PTB group than in the HC group. The TC genotype frequency of SNP rs5743836 in TLR9 was significantly higher in the LTBI group than in the HC group (OR = 1.664; 95% CI: 1.201-2.306). An MDR analysis of gene-gene and gene-environment interactions identified three SNPs (rs10759932, rs7873784, and rs10759931) that predicted LTBI with 84% accuracy (p = 0.0004) and three SNPs (rs3804100, rs1898830, and rs10759931) that predicted PTB with 80% accuracy (p = 0.0001). Our results suggest that genetic variation in TLR2, 4, 8 and 9, implicating TLR-related pathways affecting the innate immunity response, modulate LTBI and PTB susceptibility in Chinese.

P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Bramer, Lisa M.; Jensen, Jeffrey L.

P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. 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 to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternativelymore » available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).« less

Review: the Contribution of both Nature and Nurture to Carcinogenesis and Progression in Solid Tumours.

PubMed

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.

Genes related to antioxidant metabolism are involved in Methylobacterium mesophilicum-soybean interaction.

PubMed

Araújo, Welington Luiz; Santos, Daiene Souza; Dini-Andreote, Francisco; Salgueiro-Londoño, Jennifer Katherine; Camargo-Neves, Aline Aparecida; Andreote, Fernando Dini; Dourado, Manuella Nóbrega

2015-10-01

The genus Methylobacterium is composed of pink-pigmented methylotrophic bacterial species that are widespread in natural environments, such as soils, stream water and plants. When in association with plants, this genus colonizes the host plant epiphytically and/or endophytically. This association is known to promote plant growth, induce plant systemic resistance and inhibit plant infection by phytopathogens. In the present study, we focused on evaluating the colonization of soybean seedling-roots by Methylobacterium mesophilicum strain SR1.6/6. We focused on the identification of the key genes involved in the initial step of soybean colonization by methylotrophic bacteria, which includes the plant exudate recognition and adaptation by planktonic bacteria. Visualization by scanning electron microscopy revealed that M. mesophilicum SR1.6/6 colonizes soybean roots surface effectively at 48 h after inoculation, suggesting a mechanism for root recognition and adaptation before this period. The colonization proceeds by the development of a mature biofilm on roots at 96 h after inoculation. Transcriptomic analysis of the planktonic bacteria (with plant) revealed the expression of several genes involved in membrane transport, thus confirming an initial metabolic activation of bacterial responses when in the presence of plant root exudates. Moreover, antioxidant genes were mostly expressed during the interaction with the plant exudates. Further evaluation of stress- and methylotrophic-related genes expression by qPCR showed that glutathione peroxidase and glutathione synthetase genes were up-regulated during the Methylobacterium-soybean interaction. These findings support that glutathione (GSH) is potentially a key molecule involved in cellular detoxification during plant root colonization. In addition to methylotrophic metabolism, antioxidant genes, mainly glutathione-related genes, play a key role during soybean exudate recognition and adaptation, the first step in bacterial colonization.

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

PubMed Central

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

Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2.

PubMed

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.

Genetic variation in biotransformation enzymes, air pollution exposures, and risk of spina bifida.

PubMed

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.

Biomarkers of susceptibility to chemical carcinogens: the example of non-Hodgkin lymphomas.

PubMed

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?

PubMed

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.

PubMed

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).

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

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.

Multivariate inference of pathway activity in host immunity and response to therapeutics

PubMed Central

Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.

2014-01-01

Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Uncovering the genetic architecture of Colletotrichum lindemuthianum resistance through QTL mapping and epistatic interaction analysis in common bean

PubMed Central

González, Ana M.; Yuste-Lisbona, Fernando J.; Rodiño, A. Paula; De Ron, Antonio M.; Capel, Carmen; García-Alcázar, Manuel; Lozano, Rafael; Santalla, Marta

2015-01-01

Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs) studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole). A population of 185 recombinant inbred lines (RIL) derived from the cross PMB0225 × PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs) (21 for resistance to race 23 and 18 for resistance to race 1545) involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively) were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS). PMID:25852706

Dependence of the Linker Histone and Chromatin Condensation on the Nucleosome Environment.

PubMed

Perišić, Ognjen; Schlick, Tamar

2017-08-24

The linker histone (LH), an auxiliary protein that can bind to chromatin and interact with the linker DNA to form stem motifs, is a key element of chromatin compaction. By affecting the chromatin condensation level, it also plays an active role in gene expression. However, the presence and variable concentration of LH in chromatin fibers with different DNA linker lengths indicate that its folding and condensation are highly adaptable and dependent on the immediate nucleosome environment. Recent experimental studies revealed that the behavior of LH in mononucleosomes markedly differs from that in small nucleosome arrays, but the associated mechanism is unknown. Here we report a structural analysis of the behavior of LH in mononucleosomes and oligonucleosomes (2-6 nucleosomes) using mesoscale chromatin simulations. We show that the adapted stem configuration heavily depends on the strength of electrostatic interactions between LH and its parental DNA linkers, and that those interactions tend to be asymmetric in small oligonucleosome systems. Namely, LH in oligonucleosomes dominantly interacts with one DNA linker only, as opposed to mononucleosomes where LH has similar interactions with both linkers and forms a highly stable nucleosome stem. Although we show that the LH condensation depends sensitively on the electrostatic interactions with entering and exiting DNA linkers, other interactions, especially by nonparental cores and nonparental linkers, modulate the structural condensation by softening LH and thus making oligonucleosomes more flexible, in comparison to to mono- and dinucleosomes. We also find that the overall LH/chromatin interactions sensitively depend on the linker length because the linker length determines the maximal nucleosome stem length. For mononucleosomes with DNA linkers shorter than LH, LH condenses fully, while for DNA linkers comparable or longer than LH, the LH extension in mononucleosomes strongly follows the length of DNA linkers, unhampered by neighboring linker histones. Thus, LH is more condensed for mononucleosomes with short linkers, compared to oligonucleosomes, and its orientation is variable and highly environment-dependent. More generally, the work underscores the agility of LH whose folding dynamics critically controls genomic packaging and gene expression.

Genetic Expression Outside the Skin: Clues to Mechanisms of Genotype × Environment Interaction

PubMed Central

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

Prevalence of transcription promoters within archaeal operons and coding sequences.

PubMed

Koide, Tie; Reiss, David J; Bare, J Christopher; Pang, Wyming Lee; Facciotti, Marc T; Schmid, Amy K; Pan, Min; Marzolf, Bruz; Van, Phu T; Lo, Fang-Yin; Pratap, Abhishek; Deutsch, Eric W; Peterson, Amelia; Martin, Dan; Baliga, Nitin S

2009-01-01

Despite the knowledge of complex prokaryotic-transcription mechanisms, generalized rules, such as the simplified organization of genes into operons with well-defined promoters and terminators, have had a significant role in systems analysis of regulatory logic in both bacteria and archaea. Here, we have investigated the prevalence of alternate regulatory mechanisms through genome-wide characterization of transcript structures of approximately 64% of all genes, including putative non-coding RNAs in Halobacterium salinarum NRC-1. Our integrative analysis of transcriptome dynamics and protein-DNA interaction data sets showed widespread environment-dependent modulation of operon architectures, transcription initiation and termination inside coding sequences, and extensive overlap in 3' ends of transcripts for many convergently transcribed genes. A significant fraction of these alternate transcriptional events correlate to binding locations of 11 transcription factors and regulators (TFs) inside operons and annotated genes-events usually considered spurious or non-functional. Using experimental validation, we illustrate the prevalence of overlapping genomic signals in archaeal transcription, casting doubt on the general perception of rigid boundaries between coding sequences and regulatory elements.

Insights into the noncoding RNome of nitrogen-fixing endosymbiotic α-proteobacteria.

PubMed

Jiménez-Zurdo, José I; Valverde, Claudio; Becker, Anke

2013-02-01

Symbiotic chronic infection of legumes by rhizobia involves transition of invading bacteria from a free-living environment in soil to an intracellular state as differentiated nitrogen-fixing bacteroids within the nodules elicited in the host plant. The adaptive flexibility demanded by this complex lifestyle is likely facilitated by the large set of regulatory proteins encoded by rhizobial genomes. However, proteins are not the only relevant players in the regulation of gene expression in bacteria. Large-scale high-throughput analysis of prokaryotic genomes is evidencing the expression of an unexpected plethora of small untranslated transcripts (sRNAs) with housekeeping or regulatory roles. sRNAs mostly act in response to environmental cues as post-transcriptional regulators of gene expression through protein-assisted base-pairing interactions with target mRNAs. Riboregulation contributes to fine-tune a wide range of bacterial processes which, in intracellular animal pathogens, largely compromise virulence traits. Here, we summarize the incipient knowledge about the noncoding RNome structure of nitrogen-fixing endosymbiotic bacteria as inferred from genome-wide searches for sRNA genes in the alfalfa partner Sinorhizobium meliloti and further comparative genomics analysis. The biology of relevant S. meliloti RNA chaperones (e.g., Hfq) is also reviewed as a first global indicator of the impact of riboregulation in the establishment of the symbiotic interaction.

Robust discovery of genetic associations incorporating gene-environment interaction and independence.

PubMed

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.

Linking Genes to Cardiovascular Diseases: Gene Action and Gene–Environment Interactions

PubMed Central

2016-01-01

A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the “post-genomic” era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how “modifier genes” influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many—practitioners and investigators—to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area. PMID:26545598

Polymorphisms in GEMIN4 and AGO1 Genes Are Associated with the Risk of Lung Cancer: A Case-Control Study in Chinese Female Non-Smokers

PubMed Central

Fang, Xue; Yin, Zhihua; Li, Xuelian; Xia, Lingzi; Zhou, Baosen

2016-01-01

MicroRNA biosynthesis genes can affect the regulatory effect of global microRNAs to target mRNA and hence influence the genesis and development of human cancer. Here, we selected five single nucleotide polymorphisms (SNPs) (rs7813, rs2740349, rs2291778, rs910924, rs595961) in two key microRNA biosynthesis genes (GEMIN4 and AGO1) and systematically evaluated the association between these SNPs, the gene-environment interaction and lung cancer risk. To control the impact of cigarette smoking on lung cancer, we recruited Chinese female non-smokers for the study. The total number of lung cancer cases and cancer-free controls were 473 and 395 in the case-control study. Four SNPs showed statistically significant associations with lung cancer risk. After Bonferroni correction, rs7813 and rs595961 were evidently still associated with lung cancer risk. In the stratified analysis, our results revealed that all five SNPs were associated with the risk of lung adenocarcinoma; after Bonferroni correction, significant association was maintained for rs7813, rs910924 and rs595961. Haplotype analysis showed GEMIN4 haplotype C-A-G-T was a protective haplotype for lung cancer. In the combined unfavorable genotype analysis, with the increasing number of unfavorable genotypes, a progressively increased gene-dose effect was observed in lung adenocarcinoma. We also found that individuals exposed to cooking oil fumes showed a relatively high risk of lung cancer, but no interactions were found between cooking oil fume exposure or passive smoking exposure with these SNPs, either on an additive scale or a multiplicative scale. Overall, this is the first study showing that rs7813 and rs595961 could be meaningful as genetic markers for lung cancer risk. PMID:27669275

Genetic Influences on Peer and Family Relationships Across Adolescent Development: Introduction to the Special Issue.

PubMed

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.

PubMed

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.

The Use of Protein-Protein Interactions for the Analysis of the Associations between PM2.5 and Some Diseases.

PubMed

Zhang, Qing; Zhang, Pei-Wei; Cai, Yu-Dong

2016-01-01

Nowadays, pollution levels are rapidly increasing all over the world. One of the most important pollutants is PM2.5. It is known that the pollution environment may cause several problems, such as greenhouse effect and acid rain. Among them, the most important problem is that pollutants can induce a number of serious diseases. Some studies have reported that PM2.5 is an important etiologic factor for lung cancer. In this study, we extensively investigate the associations between PM2.5 and 22 disease classes recommended by Goh et al., such as respiratory diseases, cardiovascular diseases, and gastrointestinal diseases. The protein-protein interactions were used to measure the linkage between disease genes and genes that have been reported to be modulated by PM2.5. The results suggest that some diseases, such as diseases related to ear, nose, and throat and gastrointestinal, nutritional, renal, and cardiovascular diseases, are influenced by PM2.5 and some evidences were provided to confirm our results. For example, a total of 18 genes related to cardiovascular diseases are identified to be closely related to PM2.5, and cardiovascular disease relevant gene DSP is significantly related to PM2.5 gene JUP.

EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function in the Response to Water Deficit, High Temperature, and Agricultural Environments[OPEN

PubMed Central

Hafemeister, Christoph; Nicotra, Adrienne B.; Jagadish, S.V. Krishna; Bonneau, Richard; Purugganan, Michael

2016-01-01

Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosome-free regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference. PMID:27655842

The interaction of miR-34b/c polymorphisms and negative life events increases susceptibility to major depressive disorder in Han Chinese population.

PubMed

Xu, Cheng; Yang, Chunxia; Zhang, Aixia; Xu, Yong; Li, Xinrong; Liu, Zhifen; Liu, Sha; Sun, Ning; Zhang, Kerang

2017-06-09

Previous studies have shown that microRNAs(miRNAs) are involved in the pathogenesis of MDD; in particular, miR-34b/c has been implicated in MDD risk and found to exert antidepressant effects. However, the effects of miR-34b/c polymorphisms on MDD risk have not been investigated. In this study, we evaluated the effect of miR-34b/c gene polymorphisms and their interaction with negative life events in relation to MDD, using data from 381 Han Chinese patients with MDD and 291 healthy volunteers. Allelic, genotypic, haplotypic, and gene-environment associations were analyzed using UNPHASED and SPSS software. After discarding data with extremely severe negative life events in our study population, we found an association between rs4938723, rs2187473 polymorphisms and MDD in the dominant models (TC/CC vs. TT, OR=1.45, P=0.027; TC/CC vs. TT, OR=3.32, P=0.030). In haplotype analysis, the C-G haplotype (rs4938723/rs28757623) showed the strongest association with MDD (OR=1.95, P=0.026). Additionally, we found significant gene-environment combination rs4938723 C allele, rs28757623 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 3.85; 95% CI, 1.62-9.13). In addition, the combination of (C-C-HN) is of significance (OR, 2.99; 95% CI, 1.36-6.60), indicating that the rs28757623 C allele may contribute to the risk of MDD as well. The sample size was small and the role of miR-34b/c polymorphisms for MDD should be assessed using independent samples from other ethnic populations. Our results suggest that miR-34b/c is a susceptibility factor for MDD stratified by negative life events and that rs4938723 is a significant association locus for gene-environment interaction in relation to MDD risk. Copyright © 2017 Elsevier B.V. All rights reserved.

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

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

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

2016-02-01

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

The dopamine D2 receptor gene and depressive and anxious symptoms in childhood: associations and evidence for gene–environment correlation and gene–environment interaction

PubMed Central

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.

PubMed

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.

Pas de deux: An Intricate Dance of Anther Smut and Its Host.

PubMed

San Toh, Su; Chen, Zehua; Rouchka, Eric C; Schultz, David J; Cuomo, Christina A; Perlin, Michael H

2018-02-02

The successful interaction between pathogen/parasite and host requires a delicate balance between fitness of the former and survival of the latter. To optimize fitness a parasite/pathogen must effectively create an environment conducive to reproductive success, while simultaneously avoiding or minimizing detrimental host defense response. The association between Microbotryum lychnidis-dioicae and its host Silene latifolia serves as an excellent model to examine such interactions. This fungus is part of a species complex that infects species of the Caryophyllaceae, replacing pollen with the fungal spores. In the current study, transcriptome analyses of the fungus and its host were conducted during discrete stages of bud development so as to identify changes in fungal gene expression that lead to spore development and to identify changes associated with infection in the host plant. In contrast to early biotrophic phase stages of infection for the fungus, the latter stages involve tissue necrosis and in the case of infected female flowers, further changes in the developmental program in which the ovary aborts and a pseudoanther is produced. Transcriptome analysis via Illumina RNA sequencing revealed enrichment of fungal genes encoding small secreted proteins, with hallmarks of effectors and genes found to be relatively unique to the Microbotryum species complex. Host gene expression analyses also identified interesting sets of genes up-regulated, including those involving stress response, host defense response, and several agamous-like MADS-box genes (AGL61 and AGL80), predicted to interact and be involved in male gametophyte development. Copyright © 2018 Toh et al.

“Real time” genetic manipulation: a new tool for ecological field studies

PubMed Central

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

Histone Modifications in a Mouse Model of Early Adversities and Panic Disorder: Role for Asic1 and Neurodevelopmental Genes.

PubMed

Cittaro, Davide; Lampis, Valentina; Luchetti, Alessandra; Coccurello, Roberto; Guffanti, Alessandro; Felsani, Armando; Moles, Anna; Stupka, Elia; D' Amato, Francesca R; Battaglia, Marco

2016-04-28

Hyperventilation following transient, CO2-induced acidosis is ubiquitous in mammals and heritable. In humans, respiratory and emotional hypersensitivity to CO2 marks separation anxiety and panic disorders, and is enhanced by early-life adversities. Mice exposed to the repeated cross-fostering paradigm (RCF) of interference with maternal environment show heightened separation anxiety and hyperventilation to 6% CO2-enriched air. Gene-environment interactions affect CO2 hypersensitivity in both humans and mice. We therefore hypothesised that epigenetic modifications and increased expression of genes involved in pH-detection could explain these relationships. Medullae oblongata of RCF- and normally-reared female outbred mice were assessed by ChIP-seq for H3Ac, H3K4me3, H3K27me3 histone modifications, and by SAGE for differential gene expression. Integration of multiple experiments by network analysis revealed an active component of 148 genes pointing to the mTOR signalling pathway and nociception. Among these genes, Asic1 showed heightened mRNA expression, coherent with RCF-mice's respiratory hypersensitivity to CO2 and altered nociception. Functional enrichment and mRNA transcript analyses yielded a consistent picture of enhancement for several genes affecting chemoception, neurodevelopment, and emotionality. Particularly, results with Asic1 support recent human findings with panic and CO2 responses, and provide new perspectives on how early adversities and genes interplay to affect key components of panic and related disorders.

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.

PubMed

Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo

2015-07-01

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.

Response to angiotensin-converting enzyme inhibition is selectively blunted by high sodium in angiotensin-converting enzyme DD genotype: evidence for gene-environment interaction in healthy volunteers.

PubMed

Lely, A Titia; Heerspink, Hiddo J Lambers; Zuurman, Mike; Visser, Folkert W; Kocks, Menno J A; Boomsma, Frans; Navis, Gerjan

2010-12-01

Renin-angiotensin-aldosterone system blockade is a cornerstone in cardiovascular protection. Angiotensin-converting enzyme (ACE)-DD genotype has been associated with resistance to angiotensin-converting enzyme inhibition (ACEi), but data are conflicting. As sodium intake modifies the effect of ACEi as well as the genotype-phenotype relationship, we hypothesize gene-environment interaction between sodium-status, the response to ACEi, and ACE genotype. Thirty-five male volunteers (26 ± 9 years; II n = 6, ID n = 18, DD n = 11) were studied during placebo and ACEi (double blind, enalapril 20 mg/day) on low [7 days 50 mmol Na/day (low salt)] and high [7 days 200 mmol Na/day (high salt)] sodium, with a washout of 6 weeks in-between. After each period mean arterial pressure (MAP) was measured before and during graded infusion of angiotensin II (Ang II). During high salt, ACEi reduced MAP in II and ID, but not in DD [II: 88 (78-94) versus 76 (72-88); ID: 87 (84-91) versus 83 (79-87); both P < 0.05 and DD: 86 (82-96) versus 88 (80-90); ns, P < 0.05 between genotypes]. However, during low salt, ACEi reduced MAP in all genotype groups [II: 83 (78-89) versus 77 (72-83); ID: 88 (84-91) versus 82 (78-86); DD: 84 (80-91) versus 81 (75-85); all P < 0.05]. During high salt + ACEi, the Ang II response was blunted in DD, with an 18% rise in MAP during the highest dose versus 22 and 31% in ID and II (P < 0.05). Low salt annihilated these differences. In healthy participants, the MAP response to ACEi is selectively blunted in DD genotype during high salt, accompanied by blunted sensitivity to Ang II. Low salt corrects both abnormalities. Further analysis of this gene-environment interaction in patients may contribute to strategies for improvement of individual treatment efficacy.

Attachment style and oxytocin receptor gene variation interact in influencing social anxiety.

PubMed

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.

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study

PubMed Central

Taylor, Jacquelyn Y.; Sun, Yan V.; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R.; Musani, Solomon K.; Sims, Mario; Jackson, James S.

2017-01-01

Abstract Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination. The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status. Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015). This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population. PMID:29069027

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study.

PubMed

Taylor, Jacquelyn Y; Sun, Yan V; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R; Musani, Solomon K; Sims, Mario; Jackson, James S

2017-10-01

Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination.The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status.Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015).This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population.

Defining a genetic ideotype for crop improvement.

PubMed

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.

Differential C3NET reveals disease networks of direct physical interactions

PubMed Central

2011-01-01

Background Genes might have different gene interactions in different cell conditions, which might be mapped into different networks. Differential analysis of gene networks allows spotting condition-specific interactions that, for instance, form disease networks if the conditions are a disease, such as cancer, and normal. This could potentially allow developing better and subtly targeted drugs to cure cancer. Differential network analysis with direct physical gene interactions needs to be explored in this endeavour. Results C3NET is a recently introduced information theory based gene network inference algorithm that infers direct physical gene interactions from expression data, which was shown to give consistently higher inference performances over various networks than its competitors. In this paper, we present, DC3net, an approach to employ C3NET in inferring disease networks. We apply DC3net on a synthetic and real prostate cancer datasets, which show promising results. With loose cutoffs, we predicted 18583 interactions from tumor and normal samples in total. Although there are no reference interactions databases for the specific conditions of our samples in the literature, we found verifications for 54 of our predicted direct physical interactions from only four of the biological interaction databases. As an example, we predicted that RAD50 with TRF2 have prostate cancer specific interaction that turned out to be having validation from the literature. It is known that RAD50 complex associates with TRF2 in the S phase of cell cycle, which suggests that this predicted interaction may promote telomere maintenance in tumor cells in order to allow tumor cells to divide indefinitely. Our enrichment analysis suggests that the identified tumor specific gene interactions may be potentially important in driving the growth in prostate cancer. Additionally, we found that the highest connected subnetwork of our predicted tumor specific network is enriched for all proliferation genes, which further suggests that the genes in this network may serve in the process of oncogenesis. Conclusions Our approach reveals disease specific interactions. It may help to make experimental follow-up studies more cost and time efficient by prioritizing disease relevant parts of the global gene network. PMID:21777411

Analysis of Multiple Association Studies Provides Evidence of an Expression QTL Hub in Gene-Gene Interaction Network Affecting HDL Cholesterol Levels

PubMed Central

Ma, Li; Ballantyne, Christie; Brautbar, Ariel; Keinan, Alon

2014-01-01

Epistasis has been suggested to underlie part of the missing heritability in genome-wide association studies. In this study, we first report an analysis of gene-gene interactions affecting HDL cholesterol (HDL-C) levels in a candidate gene study of 2,091 individuals with mixed dyslipidemia from a clinical trial. Two additional studies, the Atherosclerosis Risk in Communities study (ARIC; n = 9,713) and the Multi-Ethnic Study of Atherosclerosis (MESA; n = 2,685), were considered for replication. We identified a gene-gene interaction between rs1532085 and rs12980554 (P = 7.1×10−7) in their effect on HDL-C levels, which is significant after Bonferroni correction (P c = 0.017) for the number of SNP pairs tested. The interaction successfully replicated in the ARIC study (P = 7.0×10−4; P c = 0.02). Rs1532085, an expression QTL (eQTL) of LIPC, is one of the two SNPs involved in another, well-replicated gene-gene interaction underlying HDL-C levels. To further investigate the role of this eQTL SNP in gene-gene interactions affecting HDL-C, we tested in the ARIC study for interaction between this SNP and any other SNP genome-wide. We found the eQTL to be involved in a few suggestive interactions, one of which significantly replicated in MESA. Importantly, these gene-gene interactions, involving only rs1532085, explain an additional 1.4% variation of HDL-C, on top of the 0.65% explained by rs1532085 alone. LIPC plays a key role in the lipid metabolism pathway and it, and rs1532085 in particular, has been associated with HDL-C and other lipid levels. Collectively, we discovered several novel gene-gene interactions, all involving an eQTL of LIPC, thus suggesting a hub role of LIPC in the gene-gene interaction network that regulates HDL-C levels, which in turn raises the hypothesis that LIPC's contribution is largely via interactions with other lipid metabolism related genes. PMID:24651390

Transcriptome responses to temperature, water availability and photoperiod are conserved among mature trees of two divergent Douglas-fir provenances from a coastal and an interior habitat.

PubMed

Hess, Moritz; Wildhagen, Henning; Junker, Laura Verena; Ensminger, Ingo

2016-08-26

Local adaptation and phenotypic plasticity are important components of plant responses to variations in environmental conditions. While local adaptation has been widely studied in trees, little is known about plasticity of gene expression in adult trees in response to ever changing environmental conditions in natural habitats. Here we investigate plasticity of gene expression in needle tissue between two Douglas-fir provenances represented by 25 adult trees using deep RNA sequencing (RNA-Seq). Using linear mixed models we investigated the effect of temperature, soil water availability and photoperiod on the abundance of 59189 detected transcripts. Expression of more than 80 % of all identified transcripts revealed a response to variations in environmental conditions in the field. GO term overrepresentation analysis revealed gene expression responses to temperature, soil water availability and photoperiod that are highly conserved among many plant taxa. However, expression differences between the two Douglas-fir provenances were rather small compared to the expression differences observed between individual trees. Although the effect of environment on global transcript expression was high, the observed genotype by environment (GxE) interaction of gene expression was surprisingly low, since only 21 of all detected transcripts showed a GxE interaction. The majority of the transcriptome responses in plant leaf tissue is driven by variations in environmental conditions. The small variation between individuals and populations suggests strong conservation of this response within Douglas-fir. Therefore we conclude that plastic transcriptome responses to variations in environmental conditions are only weakly affected by local adaptation in Douglas-fir.

Assessment of gene-by-sex interaction effect on bone mineral density.

PubMed

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M; Amin, Najaf; Evangelou, Evangelos; Li, Guo; Minster, Ryan L; Carless, Melanie A; Kammerer, Candace M; Oei, Ling; Zhou, Yanhua; Alonso, Nerea; Dailiana, Zoe; Eriksson, Joel; García-Giralt, Natalia; Giroux, Sylvie; Husted, Lise Bjerre; Khusainova, Rita I; Koromila, Theodora; Kung, Annie Waichee; Lewis, Joshua R; Masi, Laura; Mencej-Bedrac, Simona; Nogues, Xavier; Patel, Millan S; Prezelj, Janez; Richards, J Brent; Sham, Pak Chung; Spector, Timothy; Vandenput, Liesbeth; Xiao, Su-Mei; Zheng, Hou-Feng; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza K; Kollia, Panagoula; Langdahl, Bente Lomholt; Ljunggren, Osten; Lorentzon, Mattias; Marc, Janja; Mellström, Dan; Ohlsson, Claes; Olmos, José M; Ralston, Stuart H; Riancho, José A; Rousseau, François; Urreizti, Roser; Van Hul, Wim; Zarrabeitia, María T; Castano-Betancourt, Martha; Demissie, Serkalem; Grundberg, Elin; Herrera, Lizbeth; Kwan, Tony; Medina-Gómez, Carolina; Pastinen, Tomi; Sigurdsson, Gunnar; Thorleifsson, Gudmar; Vanmeurs, Joyce Bj; Blangero, John; Hofman, Albert; Liu, Yongmei; Mitchell, Braxton D; O'Connell, Jeffrey R; Oostra, Ben A; Rotter, Jerome I; Stefansson, Kari; Streeten, Elizabeth A; Styrkarsdottir, Unnur; Thorsteinsdottir, Unnur; Tylavsky, Frances A; Uitterlinden, Andre; Cauley, Jane A; Harris, Tamara B; Ioannidis, John Pa; Psaty, Bruce M; Robbins, John A; Zillikens, M Carola; Vanduijn, Cornelia M; Prince, Richard L; Karasik, David; Rivadeneira, Fernando; Kiel, Douglas P; Cupples, L Adrienne; Hsu, Yi-Hsiang

2012-10-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research. Copyright © 2012 American Society for Bone and Mineral Research.

Genome-wide identification and transcriptional expression analysis of mitogen-activated protein kinase and mitogen-activated protein kinase kinase genes in Capsicum annuum

PubMed Central

Liu, Zhiqin; Shi, Lanping; Liu, Yanyan; Tang, Qian; Shen, Lei; Yang, Sheng; Cai, Jinsen; Yu, Huanxin; Wang, Rongzhang; Wen, Jiayu; Lin, Youquan; Hu, Jiong; Liu, Cailing; Zhang, Yangwen; Mou, Shaoliang; He, Shuilin

2015-01-01

The tripartite mitogen-activated protein kinase (MAPK) signaling cascades have been implicated in plant growth, development, and environment adaptation, but a comprehensive understanding of MAPK signaling at genome-wide level is limited in Capsicum annuum. Herein, genome-wide identification and transcriptional expression analysis of MAPK and MAPK kinase (MAPKK) were performed in pepper. A total of 19 pepper MAPK (CaMAPKs) genes and five MAPKK (CaMAPKKs) genes were identified. Phylogenetic analysis indicated that CaMAPKs and CaMAPKKs could be classified into four groups and each group contains similar exon-intron structures. However, significant divergences were also found. Notably, five members of the pepper MAPKK family were much less conserved than those found in Arabidopsis, and 9 Arabidopsis MAPKs did not have orthologs in pepper. Additionally, 7 MAPKs in Arabidopsis had either two or three orthologs in the pepper genome, and six pepper MAPKs and one MAPKK differing in sequence were found in three pepper varieties. Quantitative real-time RT-PCR analysis showed that the majority of MAPK and MAPKK genes were ubiquitously expressed and transcriptionally modified in pepper leaves after treatments with heat, salt, and Ralstonia solanacearum inoculation as well as exogenously applied salicylic acid, methyl jasmonate, ethephon, and abscisic acid. The MAPKK-MAPK interactome was tested by yeast two-hybrid assay, the results showed that one MAPKK might interact with multiple MAPKs, one MAPK might also interact with more than one MAPKKs, constituting MAPK signaling networks which may collaborate in transmitting upstream signals into appropriate downstream cellular responses and processes. These results will facilitate future functional characterization of MAPK cascades in pepper. PMID:26442088

Integrating genetic and toxicogenomic information for determining underlying susceptibility to developmental disorders.

PubMed

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.

Gene duplications in prokaryotes can be associated with environmental adaptation

PubMed Central

2010-01-01

Background Gene duplication is a normal evolutionary process. If there is no selective advantage in keeping the duplicated gene, it is usually reduced to a pseudogene and disappears from the genome. However, some paralogs are retained. These gene products are likely to be beneficial to the organism, e.g. in adaptation to new environmental conditions. The aim of our analysis is to investigate the properties of paralog-forming genes in prokaryotes, and to analyse the role of these retained paralogs by relating gene properties to life style of the corresponding prokaryotes. Results Paralogs were identified in a number of prokaryotes, and these paralogs were compared to singletons of persistent orthologs based on functional classification. This showed that the paralogs were associated with for example energy production, cell motility, ion transport, and defence mechanisms. A statistical overrepresentation analysis of gene and protein annotations was based on paralogs of the 200 prokaryotes with the highest fraction of paralog-forming genes. Biclustering of overrepresented gene ontology terms versus species was used to identify clusters of properties associated with clusters of species. The clusters were classified using similarity scores on properties and species to identify interesting clusters, and a subset of clusters were analysed by comparison to literature data. This analysis showed that paralogs often are associated with properties that are important for survival and proliferation of the specific organisms. This includes processes like ion transport, locomotion, chemotaxis and photosynthesis. However, the analysis also showed that the gene ontology terms sometimes were too general, imprecise or even misleading for automatic analysis. Conclusions Properties described by gene ontology terms identified in the overrepresentation analysis are often consistent with individual prokaryote lifestyles and are likely to give a competitive advantage to the organism. Paralogs and singletons dominate different categories of functional classification, where paralogs in particular seem to be associated with processes involving interaction with the environment. PMID:20961426

Gene duplications in prokaryotes can be associated with environmental adaptation.

PubMed

Bratlie, Marit S; Johansen, Jostein; Sherman, Brad T; Huang, Da Wei; Lempicki, Richard A; Drabløs, Finn

2010-10-20

Gene duplication is a normal evolutionary process. If there is no selective advantage in keeping the duplicated gene, it is usually reduced to a pseudogene and disappears from the genome. However, some paralogs are retained. These gene products are likely to be beneficial to the organism, e.g. in adaptation to new environmental conditions. The aim of our analysis is to investigate the properties of paralog-forming genes in prokaryotes, and to analyse the role of these retained paralogs by relating gene properties to life style of the corresponding prokaryotes. Paralogs were identified in a number of prokaryotes, and these paralogs were compared to singletons of persistent orthologs based on functional classification. This showed that the paralogs were associated with for example energy production, cell motility, ion transport, and defence mechanisms. A statistical overrepresentation analysis of gene and protein annotations was based on paralogs of the 200 prokaryotes with the highest fraction of paralog-forming genes. Biclustering of overrepresented gene ontology terms versus species was used to identify clusters of properties associated with clusters of species. The clusters were classified using similarity scores on properties and species to identify interesting clusters, and a subset of clusters were analysed by comparison to literature data. This analysis showed that paralogs often are associated with properties that are important for survival and proliferation of the specific organisms. This includes processes like ion transport, locomotion, chemotaxis and photosynthesis. However, the analysis also showed that the gene ontology terms sometimes were too general, imprecise or even misleading for automatic analysis. Properties described by gene ontology terms identified in the overrepresentation analysis are often consistent with individual prokaryote lifestyles and are likely to give a competitive advantage to the organism. Paralogs and singletons dominate different categories of functional classification, where paralogs in particular seem to be associated with processes involving interaction with the environment.

Host Genotype and Harvest Practices Shape the Leaf and Root Microbiomes of the Biofuel Crop Switchgrass

NASA Astrophysics Data System (ADS)

Singer, E.; Gonzalez, J.; Juenger, T. E.; Woyke, T.

2016-12-01

Growing energy demands and concerns for climate change have urgently pushed forward the timeline for the implementation of biofuel energies. Switchgrass (Panicum virgatum) is a leading biofuel crop in the United States. Bacteria living on and inside leaves and roots affect plant health, hence a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. We present a large-scale field experiment to untangle the effects of genotype, environment, soil horizon and harvest treatment practices on prokaryotic and fungal communities associated with leaves and roots of switchgrass. Using V4 16S rRNA and ITS gene as well as metagenome sequencing, we show that host genotype is significant in both, leaves and roots, and varies among sites. Microbiome composition along the rhizosphere also shifts with soil depth. Furthermore, plant harvest significantly changes both, leaf surface and rhizosphere communities, which can be seen a year after the harvest event. Gene function analysis shows that rhizosphere communities are enriched in genes encoding nitrate reduction, carbohydrate transport and metabolism, motility, and sensory and signal transduction proteins relative to leaf surface communities. Our results demonstrate how genotype-environment interactions contribute to the complexity of microbiome assembly in natural environments.

Association of Polyaminergic Loci With Anxiety, Mood Disorders, and Attempted Suicide

PubMed Central

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.

PubMed

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

PubMed Central

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

Bacterial plasmid-mediated quinolone resistance genes in aquatic environments in China

PubMed Central

Yan, Lei; Liu, Dan; Wang, Xin-Hua; Wang, Yunkun; Zhang, Bo; Wang, Mingyu; Xu, Hai

2017-01-01

Emerging antimicrobial resistance is a major threat to human’s health in the 21st century. Understanding and combating this issue requires a full and unbiased assessment of the current status on the prevalence of antimicrobial resistance genes and their correlation with each other and bacterial groups. In aquatic environments that are known reservoirs for antimicrobial resistance genes, we were able to reach this goal on plasmid-mediated quinolone resistance (PMQR) genes that lead to resistance to quinolones and possibly also to the co-emergence of resistance to β-lactams. Novel findings were made that qepA and aac-(6′)-Ib genes that were previously regarded as similarly abundant with qnr genes are now dominant among PMQR genes in aquatic environments. Further statistical analysis suggested that the correlation between PMQR and β-lactam resistance genes in the environment is still weak, that the correlations between antimicrobial resistance genes could be weakened by sufficient wastewater treatment, and that the prevalence of PMQR has been implicated in environmental, pathogenic, predatory, anaerobic, and more importantly, human symbiotic bacteria. This work provides a comprehensive analysis of PMQR genes in aquatic environments in Jinan, China, and provides information with which combat with the antimicrobial resistance problem may be fought. PMID:28094345

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

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.

Semiparametric Bayesian analysis of gene-environment interactions with error in measurement of environmental covariates and missing genetic data.

PubMed

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.

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis.

PubMed

Del Sorbo, Maria Rosaria; Balzano, Walter; Donato, Michele; Draghici, Sorin

2013-11-01

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components. Copyright © 2013. Published by Elsevier Ireland Ltd.

MIPS: analysis and annotation of proteins from whole genomes in 2005

PubMed Central

Mewes, H. W.; Frishman, D.; Mayer, K. F. X.; Münsterkötter, M.; Noubibou, O.; Pagel, P.; Rattei, T.; Oesterheld, M.; Ruepp, A.; Stümpflen, V.

2006-01-01

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein–protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (). PMID:16381839

MIPS: analysis and annotation of proteins from whole genomes in 2005.

PubMed

Mewes, H W; Frishman, D; Mayer, K F X; Münsterkötter, M; Noubibou, O; Pagel, P; Rattei, T; Oesterheld, M; Ruepp, A; Stümpflen, V

2006-01-01

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

GENE-ENVIRONMENT INTERACTIONS: A REVIEW OF EFFECTS ON REPRODUCTION AND DEVELOPMENT

EPA Science Inventory

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 ...

Syntrophic growth of Desulfovibrio alaskensis requires genes for H2 and formate metabolism as well as those for flagellum and biofilm formation.

PubMed

Krumholz, Lee R; Bradstock, Peter; Sheik, Cody S; Diao, Yiwei; Gazioglu, Ozcan; Gorby, Yuri; McInerney, Michael J

2015-04-01

In anaerobic environments, mutually beneficial metabolic interactions between microorganisms (syntrophy) are essential for oxidation of organic matter to carbon dioxide and methane. Syntrophic interactions typically involve a microorganism degrading an organic compound to primary fermentation by-products and sources of electrons (i.e., formate, hydrogen, or nanowires) and a partner producing methane or respiring the electrons via alternative electron accepting processes. Using a transposon gene mutant library of the sulfate-reducing Desulfovibrio alaskensis G20, we screened for mutants incapable of serving as the electron-accepting partner of the butyrate-oxidizing bacterium, Syntrophomonas wolfei. A total of 17 gene mutants of D. alaskensis were identified as incapable of serving as the electron-accepting partner. The genes identified predominantly fell into three categories: membrane surface assembly, flagellum-pilus synthesis, and energy metabolism. Among these genes required to serve as the electron-accepting partner, the glycosyltransferase, pilus assembly protein (tadC), and flagellar biosynthesis protein showed reduced biofilm formation, suggesting that each of these components is involved in cell-to-cell interactions. Energy metabolism genes encoded proteins primarily involved in H2 uptake and electron cycling, including a rhodanese-containing complex that is phylogenetically conserved among sulfate-reducing Deltaproteobacteria. Utilizing an mRNA sequencing approach, analysis of transcript abundance in wild-type axenic and cocultures confirmed that genes identified as important for serving as the electron-accepting partner were more highly expressed under syntrophic conditions. The results imply that sulfate-reducing microorganisms require flagellar and outer membrane components to effectively couple to their syntrophic partners; furthermore, H2 metabolism is essential for syntrophic growth of D. alaskensis G20. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Syntrophic Growth of Desulfovibrio alaskensis Requires Genes for H2 and Formate Metabolism as Well as Those for Flagellum and Biofilm Formation

PubMed Central

Bradstock, Peter; Sheik, Cody S.; Diao, Yiwei; Gazioglu, Ozcan; Gorby, Yuri; McInerney, Michael J.

2015-01-01

In anaerobic environments, mutually beneficial metabolic interactions between microorganisms (syntrophy) are essential for oxidation of organic matter to carbon dioxide and methane. Syntrophic interactions typically involve a microorganism degrading an organic compound to primary fermentation by-products and sources of electrons (i.e., formate, hydrogen, or nanowires) and a partner producing methane or respiring the electrons via alternative electron accepting processes. Using a transposon gene mutant library of the sulfate-reducing Desulfovibrio alaskensis G20, we screened for mutants incapable of serving as the electron-accepting partner of the butyrate-oxidizing bacterium, Syntrophomonas wolfei. A total of 17 gene mutants of D. alaskensis were identified as incapable of serving as the electron-accepting partner. The genes identified predominantly fell into three categories: membrane surface assembly, flagellum-pilus synthesis, and energy metabolism. Among these genes required to serve as the electron-accepting partner, the glycosyltransferase, pilus assembly protein (tadC), and flagellar biosynthesis protein showed reduced biofilm formation, suggesting that each of these components is involved in cell-to-cell interactions. Energy metabolism genes encoded proteins primarily involved in H2 uptake and electron cycling, including a rhodanese-containing complex that is phylogenetically conserved among sulfate-reducing Deltaproteobacteria. Utilizing an mRNA sequencing approach, analysis of transcript abundance in wild-type axenic and cocultures confirmed that genes identified as important for serving as the electron-accepting partner were more highly expressed under syntrophic conditions. The results imply that sulfate-reducing microorganisms require flagellar and outer membrane components to effectively couple to their syntrophic partners; furthermore, H2 metabolism is essential for syntrophic growth of D. alaskensis G20. PMID:25616787

The influence of gene-environment interactions on GHR and IGF-1 expression and their association with growth in brook charr, Salvelinus fontinalis (Mitchill)

PubMed Central

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

PubMed Central

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

Expression of Olfactory Signaling Genes in the Eye

PubMed Central

Velmeshev, Dmitry; Faghihi, Mohammad; Shestopalov, Valery I.; Slepak, Vladlen Z.

2014-01-01

Purpose To advance our understanding how the outer eye interacts with its environment, we asked which cellular receptors are expressed in the cornea, focusing on G protein-coupled receptors. Methods Total RNA from the mouse cornea was subjected to next-generation sequencing using the Illumina platform. The data was analyzed with TopHat and CuffLinks software packages. Expression of a representative group of genes detected by RNA-seq was further analyzed by RT-PCR and in situ hybridization using RNAscope technology and fluorescent microscopy. Results We generated more than 46 million pair-end reads from mouse corneal RNA. Bioinformatics analysis revealed that the mouse corneal transcriptome reconstructed from these reads represents over 10,000 gene transcripts. We identified 194 GPCR transcripts, of which 96 were putative olfactory receptors. RT-PCR analysis confirmed the presence of several olfactory receptors and related genes, including olfactory marker protein and the G protein associated with olfaction, Gαolf. In situ hybridization showed that mRNA for olfactory marker protein, Gαolf and possibly some olfactory receptors were found in the corneal epithelial cells. In addition to the corneal epithelium, Gαolf was present in the ganglionic and inner nuclear layers of the retina. One of the olfactory receptors, Olfr558, was present primarily in vessels of the eye co-stained with antibodies against alpha-smooth muscle actin, indicating expression in arterioles. Conclusions Several species of mRNA encoding putative olfactory receptors and related genes are expressed in the mouse cornea and other parts of the eye indicating they may play a role in sensing chemicals in the ocular environment. PMID:24789354

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

PubMed

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.

Genome-wide approach identifies a novel gene-maternal pre-pregnancy BMI interaction on preterm birth

PubMed Central

Hong, Xiumei; Hao, Ke; Ji, Hongkai; Peng, Shouneng; Sherwood, Ben; Di Narzo, Antonio; Tsai, Hui-Ju; Liu, Xin; Burd, Irina; Wang, Guoying; Ji, Yuelong; Caruso, Deanna; Mao, Guangyun; Bartell, Tami R.; Zhang, Zhongyang; Pearson, Colleen; Heffner, Linda; Cerda, Sandra; Beaty, Terri H.; Fallin, M. Daniele; Lee-Parritz, Aviva; Zuckerman, Barry; Weeks, Daniel E.; Wang, Xiaobin

2017-01-01

Preterm birth (PTB) contributes significantly to infant mortality and morbidity with lifelong impact. Few robust genetic factors of PTB have been identified. Such ‘missing heritability' may be partly due to gene × environment interactions (G × E), which is largely unexplored. Here we conduct genome-wide G × E analyses of PTB in 1,733 African-American women (698 mothers of PTB; 1,035 of term birth) from the Boston Birth Cohort. We show that maternal COL24A1 variants have a significant genome-wide interaction with maternal pre-pregnancy overweight/obesity on PTB risk, with rs11161721 (PG × E=1.8 × 10−8; empirical PG × E=1.2 × 10−8) as the top hit. This interaction is replicated in African-American mothers (PG × E=0.01) from an independent cohort and in meta-analysis (PG × E=3.6 × 10−9), but is not replicated in Caucasians. In adipose tissue, rs11161721 is significantly associated with altered COL24A1 expression. Our findings may provide new insight into the aetiology of PTB and improve our ability to predict and prevent PTB. PMID:28598419

Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).

PubMed

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.

Coexpression network based on natural variation in human gene expression reveals gene interactions and functions

PubMed Central

Nayak, Renuka R.; Kearns, Michael; Spielman, Richard S.; Cheung, Vivian G.

2009-01-01

Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including CHCHD2 and TMEM111, and provided experimental evidence that TMEM111 is part of the endoplasmic reticulum-associated secretory pathway. We also found that IFIH1, a susceptibility gene of type 1 diabetes, interacts with YES1, which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes. PMID:19797678

Moderation of maltreatment effects on childhood borderline personality symptoms by gender and oxytocin receptor and FK506 binding protein 5 genes.

PubMed

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.

Interaction between PON1 and population density in amyotrophic lateral sclerosis.

PubMed

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.

Gene-environment interactions in geriatric depression.

PubMed

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.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

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

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

PubMed

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.

Genotypes Do Not Confer Risk For Delinquency ut Rather Alter Susceptibility to Positive and Negative Environmental Factors: Gene-Environment Interactions of BDNF Val66Met, 5-HTTLPR, and MAOA-uVNTR

PubMed Central

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

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta – analysis

PubMed Central

Schäfer, Annika Theresia; Damen, Thomas; Uittenboogaard, Aniek; Krolinski, Pauline; Nwosu, Chinyere Vicky; Pinckaers, Florentina Maria Egidius; Rotee, Iris Leah Marije; Ermiş, Ayşegül; Kennedy, James L.; Nieman, Dorien H.; Tiwari, Arun; van Os, Jim

2018-01-01

Background Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive. Objective A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl transferase (COMT) polymorphism Val158Met (COMTVal158Met). Data sources PubMed, Embase, PsychInfo. Study eligibility criteria All observational studies assessing the interaction between COMTVal158Met and cannabis with any psychosis or psychotic symptoms measure as an outcome. Study appraisal and synthesis methods A meta-analysis was performed using the Meta-analysis of Observational Studies in Epidemiology guidelines and forest plots were generated. Thirteen articles met the selection criteria: 7 clinical studies using a case-only design, 3 clinical studies with a dichotomous outcome, and 3 studies analysing a continuous outcome of psychotic symptoms below the threshold of psychotic disorder. The three study types were analysed separately. Validity of the included studies was assessed using "A Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions". Results For case-only studies, a significant interaction was found between cannabis use and COMTVal158Met, with an OR of 1.45 (95% Confidence Interval = 1.05–2.00; Met/Met as the risk genotype). However, there was no evidence for interaction in either the studies including dichotomous outcomes (B = -0.51, 95% Confidence Interval -1.72, 0.70) or the studies including continuous outcomes (B = -0.04 95% Confidence Interval -0.16–0.08). Limitation A substantial part of the included studies used the case-only design, which has lower validity and tends to overestimate true effects. Conclusion The interaction term between cannabis use and COMTVal158Met was only statistically significant in the case-only studies, but not in studies using other clinical or non-clinical psychosis outcomes. Future additional high quality studies might change current perspectives, yet currently evidence for the interaction remains unconvincing. PMID:29444152

Gene-environment interplay in the etiology of psychosis.

PubMed

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.

Is Lead Exposure in Early Life An Environmental Risk Factor for Schizophrenia? Neurobiological Connections and Testable Hypotheses

PubMed Central

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

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

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.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

PubMed

Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

De-novo assembly and characterization of the transcriptome of Metschnikowia fructicola reveals differences in gene expression following interaction with Penicillium digitatum and grapefruit peel

PubMed Central

2013-01-01

Background The yeast Metschnikowia fructicola is an antagonist with biological control activity against postharvest diseases of several fruits. We performed a transcriptome analysis, using RNA-Seq technology, to examine the response of M. fructicola with citrus fruit and with the postharvest pathogen, Penicillium digitatum. Results More than 26 million sequencing reads were assembled into 9,674 unigenes. Approximately 50% of the unigenes could be annotated based on homology matches in the NCBI database. Based on homology, sequences were annotated with a gene description, gene ontology (GO term), and clustered into functional groups. An analysis of differential expression when the yeast was interacting with the fruit vs. the pathogen revealed more than 250 genes with specific expression responses. In the antagonist-pathogen interaction, genes related to transmembrane, multidrug transport and to amino acid metabolism were induced. In the antagonist-fruit interaction, expression of genes involved in oxidative stress, iron homeostasis, zinc homeostasis, and lipid metabolism were induced. Patterns of gene expression in the two interactions were examined at the individual transcript level by quantitative real-time PCR analysis (RT-qPCR). Conclusion This study provides new insight into the biology of the tritrophic interactions that occur in a biocontrol system such as the use of the yeast, M. fructicola for the control of green mold on citrus caused by P. digitatum. PMID:23496978

Antioxidant Defense Enzyme Genes and Asthma Susceptibility: Gender-Specific Effects and Heterogeneity in Gene-Gene Interactions between Pathogenetic Variants of the Disease

PubMed Central

Polonikov, Alexey V.; Ivanov, Vladimir P.; Bogomazov, Alexey D.; Freidin, Maxim B.; Illig, Thomas; Solodilova, Maria A.

2014-01-01

Oxidative stress resulting from an increased amount of reactive oxygen species and an imbalance between oxidants and antioxidants plays an important role in the pathogenesis of asthma. The present study tested the hypothesis that genetic susceptibility to allergic and nonallergic variants of asthma is determined by complex interactions between genes encoding antioxidant defense enzymes (ADE). We carried out a comprehensive analysis of the associations between adult asthma and 46 single nucleotide polymorphisms of 34 ADE genes and 12 other candidate genes of asthma in Russian population using set association analysis and multifactor dimensionality reduction approaches. We found for the first time epistatic interactions between ADE genes underlying asthma susceptibility and the genetic heterogeneity between allergic and nonallergic variants of the disease. We identified GSR (glutathione reductase) and PON2 (paraoxonase 2) as novel candidate genes for asthma susceptibility. We observed gender-specific effects of ADE genes on the risk of asthma. The results of the study demonstrate complexity and diversity of interactions between genes involved in oxidative stress underlying susceptibility to allergic and nonallergic asthma. PMID:24895604

Interaction effects between the 5-hydroxy tryptamine transporter-linked polymorphic region (5-HTTLPR) genotype and family conflict on adolescent alcohol use and misuse.

PubMed

Kim, Jueun; Park, Aesoon; Glatt, Stephen J; Eckert, Tanya L; Vanable, Peter A; Scott-Sheldon, Lori A J; Carey, Kate B; Ewart, Craig K; Carey, Michael P

2015-02-01

To investigate whether the effects of family conflict on adolescent drinking differed as a function of 5-hydroxy tryptamine transporter-linked polymorphic region (5-HTTLPR) genotype cross-sectionally and prospectively in two independent samples of adolescents. Path analysis and multi-group analysis of two prospective datasets were conducted. United States and United Kingdom. Sample 1 was 175 adolescents in the United States (mean age = 15 at times 1 and 2 with a 6-month interval); Sample 2 was 4916 adolescents in the United Kingdon (mean age = 12 at time 1 and 15 at time 2). In both samples, demographics, tri-allelic 5-HTTLPR genotype and perceived family conflict were assessed at time 1. Alcohol use (frequency of drinking) and alcohol misuse (frequency of intoxication, frequency of drinking three or more drinks, maximum number of drinks) were assessed at times 1 and 2. A significant gene-environment interaction on alcohol misuse at time 1 was found in both sample 1 (β = 0.57, P = 0.001) and sample 2 (β = 0.19, P = 0.01), indicating that the 5-HTTLPR low-activity allele carriers exposed to higher levels of family conflict were more likely to engage in alcohol misuse than non-carriers. A significant gene-environment interaction effect on change in alcohol misuse over time was found only in sample 1 (β = 0.48, P = 0.04) but not in sample 2. Compared with non-carriers, adolescents carrying the 5-HTTLPR low-activity allele are more susceptible to the effects of family conflict on alcohol misuse. © 2014 Society for the Study of Addiction.

Developmental programming: Interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep.

PubMed

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

PubMed Central

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

Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the post-genomic age.

PubMed

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.

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways

PubMed Central

Jo, Kyuri; Jung, Inuk; Moon, Ji Hwan; Kim, Sun

2016-01-01

Motivation: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. Results: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein–protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-Pathway map in time clock. TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. Availability and Implementation: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: sunkim.bioinfo@snu.ac.kr PMID:27307609

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

DOE PAGES

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

Ethylene-responsive transcription factors interact with promoters of ADH and PDC involved in persimmon (Diospyros kaki) fruit de-astringency

PubMed Central

Min, Ting; Yin, Xue-ren; Chen, Kun-song

2012-01-01

The persimmon fruit is a particularly good model for studying fruit response to hypoxia, in particular, the hypoxia-response ERF (HRE) genes. An anaerobic environment reduces fruit astringency by converting soluble condensed tannins (SCTs) into an insoluble form. Although the physiology of de-astringency has been widely studied, its molecular control is poorly understood. Both CO2 and ethylene treatments efficiently removed the astringency from ‘Mopan’ persimmon fruit, as indicated by a decrease in SCTs. Acetaldehyde, the putative agent for causing de-astringency, accumulated during these treatments, as did activities of the key enzymes of acetaldehyde synthesis, alcohol dehydrogenase (ADH), and pyruvate decarboxylase (PDC). Eight DkADH and DkPDC genes were isolated, and three candidates for a role in de-astringency, DkADH1, DkPDC1, and DkPDC2, were characterized by transcriptional analysis in different tissues. The significance of these specific isoforms was confirmed by principal component analysis. Transient expression in leaf tissue showed that DkPDC2 decreased SCTs. Interactions of six hypoxia-responsive ERF genes and target promoters were tested in transient assays. The results indicated that two hypoxia-responsive ERF genes, DkERF9 and DkERF10, were involved in separately regulating the DkPDC2 and DkADH1 promoters. It is proposed that a DkERF–DkADH/DkPDC cascade is involved in regulating persimmon de-astringency. PMID:23095993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzales-Vigil, Eliana; Bianchetti, Christopher M.; Phillips, Jr., George N.

Gene duplication is a major source of plant chemical diversity that mediates plant-herbivore interactions. There is little direct evidence, however, that novel chemical traits arising from gene duplication reduce herbivory. Higher plants use threonine deaminase (TD) to catalyze the dehydration of threonine (Thr) to {alpha}-ketobutyrate and ammonia as the committed step in the biosynthesis of isoleucine (Ile). Cultivated tomato and related Solanum species contain a duplicated TD paralog (TD2) that is coexpressed with a suite of genes involved in herbivore resistance. Analysis of TD2-deficient tomato lines showed that TD2 has a defensive function related to Thr catabolism in the gutmore » of lepidopteran herbivores. During herbivory, the regulatory domain of TD2 is removed by proteolysis to generate a truncated protein (pTD2) that efficiently degrades Thr without being inhibited by Ile. We show that this proteolytic activation step occurs in the gut of lepidopteran but not coleopteran herbivores, and is catalyzed by a chymotrypsin-like protease of insect origin. Analysis of purified recombinant enzymes showed that TD2 is remarkably more resistant to proteolysis and high temperature than the ancestral TD1 isoform. The crystal structure of pTD2 provided evidence that electrostatic interactions constitute a stabilizing feature associated with adaptation of TD2 to the extreme environment of the lepidopteran gut. These findings demonstrate a role for gene duplication in the evolution of a plant defense that targets and co-opts herbivore digestive physiology.« less

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single software environment with the added capability to interact with public data sources and visual analytic tools for HTP data analysis at a systems level. BRM is developed using Java™ and other open-source technologies for free distribution (http://www.sysbio.org/dataresources/brm.stm). PMID:23174015

Impact of retinoic acid exposure on midfacial shape variation and manifestation of holoprosencephaly in Twsg1 mutant mice

PubMed Central

Billington, Charles J.; Schmidt, Brian; Marcucio, Ralph S.; Hallgrimsson, Benedikt; Gopalakrishnan, Rajaram; Petryk, Anna

2015-01-01

Holoprosencephaly (HPE) is a developmental anomaly characterized by inadequate or absent midline division of the embryonic forebrain and midline facial defects. It is believed that interactions between genes and the environment play a role in the widely variable penetrance and expressivity of HPE, although direct investigation of such effects has been limited. The goal of this study was to examine whether mice carrying a mutation in a gene encoding the bone morphogenetic protein (BMP) antagonist twisted gastrulation (Twsg1), which is associated with a low penetrance of HPE, are sensitized to retinoic acid (RA) teratogenesis. Pregnant Twsg1+/− dams were treated by gavage with a low dose of all-trans RA (3.75 mg/kg of body weight). Embryos were analyzed between embryonic day (E)9.5 and E11.5 by microscopy and geometric morphometric analysis by micro-computed tomography. P19 embryonal carcinoma cells were used to examine potential mechanisms mediating the combined effects of increased BMP and retinoid signaling. Although only 7% of wild-type embryos exposed to RA showed overt HPE or neural tube defects (NTDs), 100% of Twsg1−/− mutants exposed to RA manifested severe HPE compared to 17% without RA. Remarkably, up to 30% of Twsg1+/− mutants also showed HPE (23%) or NTDs (7%). The majority of shape variation among Twsg1+/− mutants was associated with narrowing of the midface. In P19 cells, RA induced the expression of Bmp2, acted in concert with BMP2 to increase p53 expression, caspase activation and oxidative stress. This study provides direct evidence for modifying effects of the environment in a genetic mouse model carrying a predisposing mutation for HPE in the Twsg1 gene. Further study of the mechanisms underlying these gene-environment interactions in vivo will contribute to better understanding of the pathogenesis of birth defects and present an opportunity to explore potential preventive interventions. PMID:25468951

Interactive Effects of Snps Located Within CD28/B7Pathway and Environment on Susceptibility to Recurrent Spontaneous Abortion.

PubMed

Wang, Guiling; Sun, Jing

2017-01-01

This study was aimed to explore the interaction between environment and CD28/B7 pathway to provide the potential epidemiology for prevention and treatment of recurrent spontaneous abortion (RSA). The retrospective study included 630 RSA cases and 1320 healthy women during their middle and late prenatal care. Their living environment was investigated, and the influence of environmental factors on pregnancy abortion was analyzed. The genomic DNAs were extracted from the study subjects, and the polymorphisms of CD28 and B7 were analyzed. Finally, the interaction of gene and environment on RSA was analyzed with the logistic regression analyses. The multi-variate regression analysis indicated that vitamin supplement, intake of fresh fruits or vegetables, night shift, staying up late, history miscarriage, as well as history induced abortion were, independently, risk factors for RSA (all P< 0.05). Moreover, rs3116496 (T>C), rs3181098 (G>A) and rs3181100 (G>C) of CD28, rs1915087 (C>T) of B7-2, as well as rs6804441 (A>G) and rs41271391 (G>T) of B7-1 were correlated with modified RSA risk (all P< 0.05). The haplotypes TGT and TAG could also regulate the risk of RSA (both P< 0.05). The synthetic influences of the aforementioned SNPs and environmental factors could also significantly affect the susceptibility to RSA (all P< 0.05). The interaction of environment and SNPs of CD28/B7 pathway on RSA risk was distinct from CD28/B7 pathway or environment alone. © 2017 The Author(s). Published by S. Karger AG, Basel.

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization.

PubMed

Jung, Sang-Kyu; McDonald, Karen

2011-08-16

Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer. The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment. Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net.

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization

PubMed Central

2011-01-01

Background Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer. Results The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment. Conclusion Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net. PMID:21846353

Genetic and environmental factors affecting cryptic variations in gene regulatory networks

PubMed Central

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.

PubMed

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.

Understanding the Molecular Mechanisms Underpinning Gene by Environment Interactions in Psychiatric Disorders: The FKBP5 Model.

PubMed

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.

Somatic polyploidy is associated with the upregulation of c-MYC interacting genes and EMT-like signature

PubMed Central

Vazquez-Martin, Alejandro; Anatskaya, Olga V.; Giuliani, Alessandro; Erenpreisa, Jekaterina; Huang, Sui; Salmina, Kristine; Inashkina, Inna; Huna, Anda; Nikolsky, Nikolai N.; Vinogradov, Alexander E.

2016-01-01

The dependence of cancer on overexpressed c-MYC and its predisposition for polyploidy represents a double puzzle. We address this conundrum by cross-species transcription analysis of c-MYC interacting genes in polyploid vs. diploid tissues and cells, including human vs. mouse heart, mouse vs. human liver and purified 4n vs. 2n mouse decidua cells. Gene-by-gene transcriptome comparison and principal component analysis indicated that c-MYC interactants are significantly overrepresented among ploidy-associated genes. Protein interaction networks and gene module analysis revealed that the most upregulated genes relate to growth, stress response, proliferation, stemness and unicellularity, as well as to the pathways of cancer supported by MAPK and RAS coordinated pathways. A surprising feature was the up-regulation of epithelial-mesenchymal transition (EMT) modules embodied by the N-cadherin pathway and EMT regulators from SNAIL and TWIST families. Metabolic pathway analysis also revealed the EMT-linked features, such as global proteome remodeling, oxidative stress, DNA repair and Warburg-like energy metabolism. Genes associated with apoptosis, immunity, energy demand and tumour suppression were mostly down-regulated. Noteworthy, despite the association between polyploidy and ample features of cancer, polyploidy does not trigger it. Possibly it occurs because normal polyploidy does not go that far in embryonalisation and linked genome destabilisation. In general, the analysis of polyploid transcriptome explained the evolutionary relation of c-MYC and polyploidy to cancer. PMID:27655693

Gene-Environment Interplay in the Association between Pubertal Timing and Delinquency in Adolescent Girls

PubMed Central

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

A novel differential susceptibility gene: CHRNA4 and moderation of the effect of maltreatment on child personality.

PubMed

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.

Gene-environment interaction between the oxytocin receptor (OXTR) gene and parenting behaviour on children's theory of mind.

PubMed

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.

Gene-Environment Interplay in Physical, Psychological, and Cognitive Domains in Mid to Late Adulthood: Is APOE a Variability Gene?

PubMed

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.

How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects

PubMed Central

Choi, Lin; DeNieu, Michael; Sonnenschein, Anne; Hummel, Kristen; Marier, Christian; Victory, Andrew; Porter, Cody; Mammel, Anna; Holms, Julie; Sivaratnam, Gayatri

2017-01-01

For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development) of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis. PMID:29166655

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…

Single cell dual adherent-suspension co-culture micro-environment for studying tumor-stromal interactions with functionally selected cancer stem-like cells.

PubMed

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.

Life Events, Genetic Susceptibility, and Smoking among Adolescents

PubMed Central

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

Beyond main effects of gene-sets: harsh parenting moderates the association between a dopamine gene-set and child externalizing behavior.

PubMed

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.

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Genetic influences can protect against unresponsive parenting in the prediction of child social competence.

PubMed

Van Ryzin, Mark J; Leve, Leslie D; Neiderhiser, Jenae M; Shaw, Daniel S; Natsuaki, Misaki N; Reiss, David

2015-01-01

Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this article, the possibility of a Gene x Environment (G × E) interaction in the prediction of social competence in school-age children is evaluated. Using a longitudinal, multimethod data set from a sample of children adopted at birth (N = 361), a significant interaction was found between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.

Genetic and environmental contributions to children's prosocial behavior: brief review and new evidence from a reanalysis of experimental twin data.

PubMed

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.

Cortico-limbic connectivity in MAOA-L carriers is vulnerable to acute tryptophan depletion.

PubMed

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.

PubMed

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.

Vantage Sensitivity: Environmental Sensitivity to Positive Experiences as a Function of Genetic Differences.

PubMed

Pluess, Michael

2017-02-01

A large number of gene-environment interaction studies provide evidence that some people are more likely to be negatively affected by adverse experiences as a function of specific genetic variants. However, such "risk" variants are surprisingly frequent in the population. Evolutionary analysis suggests that genetic variants associated with increased risk for maladaptive development under adverse environmental conditions are maintained in the population because they are also associated with advantages in response to different contextual conditions. These advantages may include (a) coexisting genetic resilience pertaining to other adverse influences, (b) a general genetic susceptibility to both low and high environmental quality, and (c) a coexisting propensity to benefit disproportionately from positive and supportive exposures, as reflected in the recent framework of vantage sensitivity. After introducing the basic properties of vantage sensitivity and highlighting conceptual similarities and differences with diathesis-stress and differential susceptibility patterns of gene-environment interaction, selected and recent empirical evidence for the notion of vantage sensitivity as a function of genetic differences is reviewed. The unique contribution that the new perspective of vantage sensitivity may make to our understanding of social inequality will be discussed after suggesting neurocognitive and molecular mechanisms hypothesized to underlie the propensity to benefit disproportionately from benevolent experiences. © 2015 Wiley Periodicals, Inc.

Epigenetics and obesity: the devil is in the details.

PubMed

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.

Music training and speech perception: a gene-environment interaction.

PubMed

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.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

PubMed

Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

Estimates of genetics and phenotypics parameters for the yield and quality of soybean seeds.

PubMed

Zambiazzi, E V; Bruzi, A T; Guilherme, S R; Pereira, D R; Lima, J G; Zuffo, A M; Ribeiro, F O; Mendes, A E S; Godinho, S H M; Carvalho, M L M

2017-09-27

Estimating genotype x environment (GxE) parameters for quality and yield in soybean seed grown in different environments in Minas Gerais State was the goal of this study, as well as to evaluate interaction effects of GxE for soybean seeds yield and quality. Seeds were produced in three locations in Minas Gerais State (Lavras, Inconfidentes, and Patos de Minas) in 2013/14 and 2014/15 seasons. Field experiments were conducted in randomized blocks in a factorial 17 x 6 (GxE), and three replications. Seed yield and quality were evaluated for germination in substrates paper and sand, seedling emergence, speed emergency index, mechanical damage by sodium hypochlorite, electrical conductivity, speed aging, vigor and viability of seeds by tetrazolium test in laboratory using completely randomized design. Quadratic component genotypic, GXE variance component, genotype determination coefficient, genetic variation coefficient and environmental variation coefficient were estimated using the Genes software. Percentage analysis of genotypes contribution, environments and genotype x environment interaction were conducted by sites combination two by two and three sites combination, using the R software. Considering genotypes selection of broad adaptation, TMG 1179 RR, CD 2737 RR, and CD 237 RR associated better yield performance at high physical and physiological potential of seed. Environmental effect was more expressive for most of the characters related to soybean seed quality. GxE interaction effects were expressive though genotypes did not present coincidental behavior in different environments.