A flexible Bayesian model for studying gene-environment interaction.

Abstract:

:An important follow-up step after genetic markers are found to be associated with a disease outcome is a more detailed analysis investigating how the implicated gene or chromosomal region and an established environment risk factor interact to influence the disease risk. The standard approach to this study of gene-environment interaction considers one genetic marker at a time and therefore could misrepresent and underestimate the genetic contribution to the joint effect when one or more functional loci, some of which might not be genotyped, exist in the region and interact with the environment risk factor in a complex way. We develop a more global approach based on a Bayesian model that uses a latent genetic profile variable to capture all of the genetic variation in the entire targeted region and allows the environment effect to vary across different genetic profile categories. We also propose a resampling-based test derived from the developed Bayesian model for the detection of gene-environment interaction. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the Bayesian model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region, which contains a cluster of nicotinic acetylcholine receptor genes and has been shown to be associated with both lung cancer and smoking behavior. We find evidence for gene-environment interaction (P-value = 0.016), with the smoking effect appearing to be stronger in subjects with a genetic profile associated with a higher lung cancer risk; the conventional test of gene-environment interaction based on the single-marker approach is far from significant.

journal_name

PLoS Genet

journal_title

PLoS genetics

authors

Yu K,Wacholder S,Wheeler W,Wang Z,Caporaso N,Landi MT,Liang F

doi

10.1371/journal.pgen.1002482

subject

Has Abstract

pub_date

2012-01-01 00:00:00

pages

e1002482

issue

1

eissn

1553-7390

issn

1553-7404

pii

PGENETICS-D-11-01106

journal_volume

8

pub_type

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