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Extended methods for gene–environment‐wide interaction scans in studies of admixed individuals with varying degrees of relationships
Author(s) -
Chen Yalei,
Adrianto Indra,
Iannuzzi Michael C.,
Garman Lori,
Montgomery Courtney G.,
Rybicki Benjamin A.,
Levin Albert M.,
Li Jia
Publication year - 2019
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.22196
Subject(s) - covariate , gee , biology , gene–environment interaction , genome wide association study , genetic predisposition , generalized estimating equation , structural equation modeling , kinship , interaction , genetics , econometrics , computational biology , evolutionary biology , statistics , gene , mathematics , single nucleotide polymorphism , genotype , political science , law , agronomy
The etiology of many complex diseases involves both environmental exposures and inherited genetic predisposition as well as interactions between them. Gene–environment‐wide interaction studies (GEWIS) provide a means to identify the interactions between genetic variation and environmental exposures that underlie disease risk. However, current GEWIS methods lack the capability to adjust for the potentially complex correlations in studies with varying degrees of relationships (both known and unknown) among individuals in admixed populations. We developed novel generalized estimating equation (GEE) based methods—GEE‐adaptive and GEE‐joint—to account for phenotypic correlations due to kinship while accounting for covariates, including, measures of genome‐wide ancestry. In simulation studies of admixed individuals, both methods controlled family‐wise error rates, an advantage over the case‐only approach. They demonstrated higher power than traditional case–control methods across a wide range of underlying alternative hypotheses, especially where both marginal and interaction effects were present. We applied the proposed method to conduct a GEWIS of a known sarcoidosis risk factor (insecticide exposure) and risk of sarcoidosis in African Americans and identified two novel loci with suggestive evidence of G × E interaction.