title: Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.
abstract: Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.
authors.affiliation: Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Jae Hoon
authors.initials: JH
authors.lastname: Sul
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Michael
authors.initials: M
authors.lastname: Bilow
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Wen-Yun
authors.initials: WY
authors.lastname: Yang
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Emrah
authors.initials: E
authors.lastname: Kostem
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Nick
authors.initials: N
authors.lastname: Furlotte
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Dan
authors.initials: D
authors.lastname: He
authors.affiliation: Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America.|Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, United States of America.
authors.forename: Eleazar
authors.initials: E
authors.lastname: Eskin
mesh_terms: D003198:Computer Simulation; D059647:Gene-Environment Interaction; D005828:Genetics, Population; D015894:Genome, Human; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics