title: Simultaneously testing for marginal genetic association and gene-environment interaction.
abstract: In this article, the authors propose to simultaneously test for marginal genetic association and gene-environment interaction to discover single nucleotide polymorphisms that may be involved in gene-environment or gene-treatment interaction. The asymptotic independence of the marginal association estimator and various interaction estimators leads to a simple and flexible way of combining the 2 tests, allowing for exploitation of gene-environment independence in estimating gene-environment interaction. The proposed test differs from the 2-df test proposed by Kraft et al. (Hum Hered. 2007;63(2):111-119) in two respects. First, for the genetic association component, it tests for marginal association, which is often the primary objective in inference, rather than the main effect in a model with gene-environment interaction. Second, the gene-environment testing component can easily exploit putative gene-environment independence using either the case-only estimator or the empirical Bayes estimator, depending on whether the goal is gene-treatment interaction in a randomized trial or gene-environment interaction in an observational study. The use of the proposed joint test is illustrated through simulations and a genetic study (1993-2005) from the Women's Health Initiative.
authors: Public Health Science Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. jdai@fhcrc.org
authors: James Y
authors: JY
authors: Dai
authors: Benjamin A
authors: BA
authors: Logsdon
authors: Ying
authors: Y
authors: Huang
authors: Li
authors: L
authors: Hsu
authors: Alexander P
authors: AP
authors: Reiner
authors: Ross L
authors: RL
authors: Prentice
authors: Charles
authors: C
authors: Kooperberg
mesh_terms: D059647:Gene-Environment Interaction; D020022:Genetic Predisposition to Disease / Q000453:epidemiology*; D055106:Genome-Wide Association Study; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical