Does accounting for gene-environment (GxE) interaction increase the power to detect the effect of a gene in a multifactorial disease?
Despite tremendous efforts, few genes involved in the susceptibility for complex disorders have been identified. One explanation is that these disorders are a result of an interaction between genes and environment, and under such conditions, it may be difficult to measure the true genetic effect without accounting for the interaction. Umbach and Weinberg ([2000] Am. J. Hum. Genet. 66:251-261) proposed an association test which looks at the joint effects of genotype and environment, using case-parent trios. In this study, we explore under which conditions accounting for GxE interaction enhances one's ability to detect the role of genetic factors in complex diseases. Using asymptotic power calculations, we investigate the power to detect the gene effect over varying exposure frequencies and different scenarios of GxE interaction. We show that for a given sample size, interaction scenario, and allele frequency, the actual gain in power while accounting for the interaction depends on the magnitude of the exposure frequency: the largest gains are seen for relatively low exposure frequencies. Moreover, a loss of power can be observed when the exposure is frequent and/or the exposure effect is strong. If we consider a gene with a disease allele frequency of 0.2, with no effect in the absence of exposure, an exposure with a 10-fold increase risk and a GxE relative risk of 2, then when the exposure frequency is 0.1, accounting for GxE interaction increases the power to detect the gene effect in 200 trios by 10%; alternatively, when the exposure frequency is 0.9, it decreases the power by 15%.
Selinger-Leneman
Hana
H
INSERM U535, Le Kremlin Bicêtre, France. leneman@kb.inserm.fr
Genin
Emmanuelle
E
Norris
Jill M
JM
Khlat
Myriam
M
D000483:Alleles; D015984:Causality; D004781:Environmental Exposure / Q000706:statistics & numerical data; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D010641:Phenotype