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- Title
Simultaneously testing for marginal genetic association and gene-environment interaction.
- Authors
Dai, James Y; Logsdon, Benjamin A; Huang, Ying; Hsu, Li; Reiner, Alexander P; Prentice, Ross L; Kooperberg, Charles
- 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.
- Publication
American journal of epidemiology, 2012, Vol 176, Issue 2, p164
- ISSN
1476-6256
- Publication type
Journal Article
- DOI
10.1093/aje/kwr521