Testing for Sufficient-Cause Gene-Environment Interactions under the Assumptions of Independence and Hardy-Weinberg Equilibrium
Journal
American Journal of Epidemiology
Journal Volume
182
Journal Issue
1
Pages
9-16
Date Issued
2015
Author(s)
Abstract
To detect gene-environment interactions, a logistic regression model is typically fitted to a set of case-control data, and the focus is on testing of the cross-product terms (gene × environment) in the model. A significant result is indicative of a gene-environment interaction under a multiplicative model for disease odds. Based on the sufficient-cause model for rates, in this paper we put forward a general approach to testing for sufficient-cause gene-environment interactions in case-control studies. The proposed tests can be tailored to detect a particular type of sufficient-cause gene-environment interaction with greater sensitivity. These tests include testing for autosomal dominant, autosomal recessive, and gene-dosage interactions. The tests can also detect trend interactions (e.g., a larger gene-environment interaction with a higher level of environmental exposure) and threshold interactions (e.g., gene-environment interaction occurs only when environmental exposure reaches a certain threshold level). Two assumptions are necessary for the validity of the tests: 1) the rare-disease assumption and 2) the no-redundancy assumption. Another 2 assumptions are optional but, if imposed correctly, can boost the statistical powers of the tests: 3) the gene-environment independence assumption and 4) the Hardy-Weinberg equilibrium assumption. SAS code (SAS Institute, Inc., Cary, North Carolina) for implementing the methods is provided. ? 2015 The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
Other Subjects
cytochrome P450 1A1; environmental factor; epidemiology; gene expression; genotype-environment interaction; logistics; phenotype; regression analysis; testing method; allele; Article; autosomal dominant inheritance; autosomal recessive inheritance; case control study; comparative study; controlled study; environmental exposure; gene dosage; gene frequency; gene interaction; genetic model; genetic polymorphism; genotype environment interaction; Hardy Weinberg Equilibrium; human; major clinical study; rare disease; simulation; smoking; validity; computer simulation; diseases; epidemiology; genetics; population genetics; North Carolina; United States; Case-Control Studies; Computer Simulation; Disease; Epidemiology; Gene-Environment Interaction; Genetics, Population; Humans
Publisher
Oxford University Press
Type
journal article