scholarly journals A simple approximation to bias in gene-environment interaction estimates when a case might not be the case

2018 ◽  
Author(s):  
Iryna Lobach ◽  
Inyoung Kim ◽  
Alexander Alekseyenko ◽  
Siarhei Lobach ◽  
Li Zhang
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Parameter Estimates ◽  
Environment Interaction ◽  
Finite Samples ◽  
Gene Environment ◽  
Environmental Measures ◽  
Pathologic State

ABSTRACTCase-control genetic association studies are often used to examine the role of the genetic basis in complex diseases, such as cancer and neurodegenerative diseases. The role of the genetic basis might vary by non-genetic (environmental) measures, what is traditionally defined as gene-environment interactions (GxE). A commonly overlooked complication is that the set of clinically diagnosed cases might be contaminated by a subset with a nuisance pathologic state that presents with the same symptoms as the pathologic state of interest. The genetic basis of the pathologic state of interest might differ from that of the nuisance pathologic state. Often frequencies of the pathologically defined states within the clinically diagnosed set of cases vary by the environment. We derive a simple and general approximation to bias in GxE parameter estimates when presence of the nuisance pathologic state is ignored. We then perform extensive simulation studies to show that ignoring presence of the nuisance pathologic state can result in substantial bias in GxE estimates and that the approximation we derived is reasonably accurate in finite samples. We demonstrate the applicability of the proposed approximation in a study of Alzheimer’s disease.

scholarly journals Integrating epidemiology and genetic association: the challenge of gene–environment interaction

2005 ◽  
Vol 360 (1460) ◽  
pp. 1609-1616 ◽  
Author(s):  
Peter Kraft ◽  
David Hunter
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Genetic Locus ◽  
Single Gene ◽  
Genetic Association Studies ◽  
Biologically Active ◽  
Marginal Effect ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment

Recent advances in human genomics have made it possible to better understand the genetic basis of disease. In addition, genetic association studies can also elucidate the mechanisms by which ‘non-genetic’ exogenous and endogenous exposures influence the risk of disease. This is true both of studies that assess the marginal effect of a single gene and studies that look at the joint effect of genes and environmental exposures. For example, gene variants that are known to alter enzyme function or level can serve as surrogates for long-term biomarker levels that are impractical or impossible to measure on many subjects. Evidence that genetic variants modify the effect of an established risk factor may help specify the risk factor's biologically active components. We illustrate these ideas with several examples and discuss design and analysis challenges, particularly for studies of gene–environment interaction. We argue that to increase the power to detect interaction effects and limit the number of false positive results, large sample sizes will be needed, which are currently only available through planned collaborative efforts. Such collaborations also ensure a common approach to measuring variation at a genetic locus, avoiding a problem that has led to difficulties when comparing results from genetic association studies.

On the Genetic and Genomic Basis of Aggression, Violence, and Antisocial Behavior

2018 ◽  
Author(s):  
Kevin M. Beaver ◽  
Eric J. Connolly ◽  
Joseph L. Nedelec ◽  
Joseph A. Schwartz
Keyword(s):  
Antisocial Behavior ◽  
Genetic Basis ◽  
Association Studies ◽  
Molecular Genetic ◽  
Genetic Association Studies ◽  
Genome Wide Association Studies ◽  
Antisocial Behaviors ◽  
Gene Environment ◽  
Genome Wide ◽  
Genomic Basis

There is a great deal of interest in examining the genetic and environmental architecture to aggression, violence, and antisocial behaviors. This interest has resulted in hundreds of studies being published that estimate genetic and environmental effects on antisocial phenotypes. The results generated from these studies have been remarkably consistent and have contributed greatly to the knowledge base on the etiology of antisocial behavior. This chapter reviews the research on the genetic basis to antisocial phenotypes by presenting the results related to the heritability of antisocial phenotypes. It also discusses some of the molecular genetic association studies as well as genome-wide association studies that focus on the development of antisocial behaviors. In doing so, it also reviews findings related to gene–environment interactions. The chapter concludes by discussing some of the ways in which these findings could be used for intervention and prevention programs.

Examining the Heritability of a Laboratory-Based Smoking Endophenotype: Initial Results From an Experimental Twin Study

2007 ◽  
Vol 10 (4) ◽  
pp. 546-553 ◽  
Author(s):  
Lara A. Ray ◽  
Soo Hyun Rhee ◽  
Michael C. Stallings ◽  
Valerie Knopik ◽  
Kent E. Hutchison
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Multivariate Models ◽  
Tension Reduction ◽  
Sibling Pairs ◽  
Additive Genetic Effects ◽  
Best Fit ◽  
Initial Results

AbstractThe objective of this study was to examine the heritability of an endophenotype relevant to nicotine dependence, namely tension reduction after smoking. This study also examined whether common genetic, shared environmental, and nonshared environmental factors influence this endophenotype measured repeatedly during an experimental paradigm. Twin and sibling pairs, all of whom were regular smokers, completed a laboratory paradigm in which they reported on levels of tension at baseline and after smoking each of 3 cigarettes. Univariate twin analyses suggested a sizeable role of additive genetic effects on tension reduction, with heritability estimates ranging between 47 and 68%. Result of multivariate Cholesky analyses indicated that there were additive genetic influences common to tension reduction assessed after cigarettes 1, 2, and 3. Multivariate models including genetic and nonshared environmental effects provided the best fit to the data. To the best of our knowledge, this is the first study to examine the genetic basis of a laboratory smoking endophenotype, in this case tension reduction after smoking. Implications for genetic association studies are discussed.

scholarly journals Estimating the effective sample size in association studies of quantitative traits

2021 ◽  
Author(s):  
Andrey Ziyatdinov ◽  
Jihye Kim ◽  
Dmitry Prokopenko ◽  
Florian Privé ◽  
Fabien Laporte ◽  
...  
Keyword(s):  
Statistical Power ◽  
Quantitative Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Effective Sample Size ◽  
Environment Interaction ◽  
Uk Biobank ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
The Uk

Abstract The effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals Investigation of gene–environment interactions in relation to tic severity

2021 ◽  
Author(s):  
Mohamed Abdulkadir ◽  
Dongmei Yu ◽  
Lisa Osiecki ◽  
Robert A. King ◽  
Thomas V. Fernandez ◽  
...  
Keyword(s):  
Tourette Syndrome ◽  
Association Studies ◽  
Autism Spectrum ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Linear Regression Models ◽  
Compulsive Disorder ◽  
Gene Environment ◽  
Tic Severity

AbstractTourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive–compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene–environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene–environment studies.

scholarly journals Gene-Gene and Gene-Environment Interactions in Meta-Analysis of Genetic Association Studies

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0124967 ◽  
Author(s):  
Chin Lin ◽  
Chi-Ming Chu ◽  
John Lin ◽  
Hsin-Yi Yang ◽  
Sui-Lung Su
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Association Studies ◽  
Gene Environment

scholarly journals Gene–environment interaction: the role of SULT1A1 and CYP3A5 polymorphisms as risk modifiers for squamous cell carcinoma of the oesophagus

2005 ◽  
Vol 27 (4) ◽  
pp. 791-797 ◽  
Author(s):  
Collet Dandara ◽  
Dong-Ping Li ◽  
Gabi Walther ◽  
M.Iqbal Parker
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Risk Modifiers

Genetic Basis of Positive and Negative Symptom Domains in Schizophrenia

2017 ◽  
Vol 19 (5) ◽  
pp. 559-575 ◽  
Author(s):  
Rose Mary Xavier ◽  
Allison Vorderstrasse
Keyword(s):  
Negative Symptoms ◽  
Genetic Basis ◽  
Neuronal Development ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Key Words Schizophrenia ◽  
Genetics Research ◽  
Symptom Domains ◽  
Heritable Disorder ◽  
Underlying Mechanisms

Schizophrenia is a highly heritable disorder, the genetic etiology of which has been well established. Yet despite significant advances in genetics research, the pathophysiological mechanisms of this disorder largely remain unknown. This gap has been attributed to the complexity of the polygenic disorder, which has a heterogeneous clinical profile. Examining the genetic basis of schizophrenia subphenotypes, such as those based on particular symptoms, is thus a useful strategy for decoding the underlying mechanisms. This review of literature examines the recent advances (from 2011) in genetic exploration of positive and negative symptoms in schizophrenia. We searched electronic databases PubMed, Web of Science, and Cumulative Index to Nursing and Allied Health Literature using key words schizophrenia, symptoms, positive symptoms, negative symptoms, cognition, genetics, genes, genetic predisposition, and genotype in various combinations. We identified 115 articles, which are included in the review. Evidence from these studies, most of which are genetic association studies, identifies shared and unique gene associations for the symptom domains. Genes associated with neurotransmitter systems and neuronal development/maintenance primarily constitute the shared associations. Needed are studies that examine the genetic basis of specific symptoms within the broader domains in addition to functional mechanisms. Such investigations are critical to developing precision treatment and care for individuals afflicted with schizophrenia.

Vulnerability to early stressful life events: The moderating role of HOMER1 gene in the gene × environment interaction

2022 ◽  
pp. 1-23
Author(s):  
Yidi Chen ◽  
Lizhong Wang ◽  
Dongdong Jiang ◽  
Shanshan Zhu ◽  
WeGene Research Team ◽  
...  
Keyword(s):  
Life Events ◽  
Stressful Life Events ◽  
Stressful Life ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Moderating Role
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