Simultaneously Testing for Marginal Genetic Association and Gene-environment Interaction

Overview

Journal Am J Epidemiol

Publisher Oxford University Press

Specialty Public Health

Date 2012 Jul 10

PMID 22771729

Citations 28

Authors

James Y Dai

Benjamin A Logsdon

Ying Huang

Li Hsu

Alexander P Reiner

Ross L Prentice

Charles Kooperberg

Affiliations

Soon will be listed here.

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.

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