title: Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits.
abstract: The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects.
authors.affiliation: Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America.
authors.forename: K Alaine
authors.initials: KA
authors.lastname: Broadaway
authors.affiliation: Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Richard
authors.initials: R
authors.lastname: Duncan
authors.affiliation: Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Karen N
authors.initials: KN
authors.lastname: Conneely
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Lynn M
authors.initials: LM
authors.lastname: Almli
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia, United States of America.|Department of Veterans Affairs, Atlanta VA Medical Center, Atlanta, Georgia, United States of America.
authors.forename: Bekh
authors.initials: B
authors.lastname: Bradley
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Kerry J
authors.initials: KJ
authors.lastname: Ressler
authors.affiliation: Department of Human Genetics, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Epstein
mesh_terms: D002874:Chromosome Mapping; D003198:Computer Simulation; D059647:Gene-Environment Interaction; D056726:Genetic Association Studies / Q000379:methods*; D015894:Genome, Human; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D040641:Quantitative Trait Loci / Q000235:genetics*; D012984:Software; D013313:Stress Disorders, Post-Traumatic / Q000235:genetics*
keywords: GWAS; gene mapping; gene-environment interaction; quantitative human traits