title: A combination test for detection of gene-environment interaction in cohort studies.
abstract: 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.
authors.affiliation: Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.
authors.forename: Brandon
authors.initials: B
authors.lastname: Coombes
authors.affiliation: Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.
authors.forename: Saonli
authors.identifier: 0000-0003-1200-4546
authors.initials: S
authors.lastname: Basu
authors.affiliation: Department of Psychology, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.
authors.forename: Matt
authors.initials: M
authors.lastname: McGue
mesh_terms: D000428:Alcohol Drinking / Q000235:genetics*; D015982:Bias; D015331:Cohort Studies; D059647:Gene-Environment Interaction; D005819:Genetic Markers / Q000235:genetics*; D005820:Genetic Testing; D055106:Genome-Wide Association Study; D006801:Humans; D008910:Minnesota; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*
chemical_list: D005819:Genetic Markers
keywords: dimension reduction; gene-environment interaction; model selection; score tests