Efficient Generalized Least Squares Method for Mixed Population and Family‐based Samples in Genome‐wide Association Studies. Issue 5 (20th May 2014)

• Record Type: Journal Article
• Authors: Li, Jia; Yang, James; Levin, Albert M.; Montgomery, Courtney G.; Datta, Indrani; Trudeau, Sheri; Adrianto, Indra; McKeigue, Paul; Iannuzzi, Michael C.; Rybicki, Benjamin A.
• Is Part Of: Genetic epidemiology. Volume 38:Issue 5(2014)
• Page Start: 430
• Page End: 438
• Publication Date: 2014-05-20
• Subjects: Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.21811
• Languages: English
• ISSNs: 0741-0395

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p>Genome‐wide association studies (GWAS) that draw samples from multiple studies with a mixture of relationship structures are becoming more common. Analytical methods exist for using mixed‐sample data, but few methods have been proposed for the analysis of genotype‐by‐environment (G×E) interactions. Using GWAS data from a study of sarcoidosis susceptibility genes in related and unrelated African Americans, we explored the current analytic options for genotype association testing in studies using both unrelated and family‐based designs. We propose a novel method—generalized least squares (GLX)—to estimate both SNP and G×E interaction effects for categorical environmental covariates and compared this method to generalized estimating equations (GEE), logistic regression, the Cochran–Armitage trend test, and the W_QLS and M_QLS methods. We used simulation to demonstrate that the GLX method reduces type I error under a variety of pedigree structures. We also demonstrate its superior power to detect SNP effects while offering computational advantages and comparable power to detect G×E interactions versus GEE. Using this method, we found two novel SNPs that demonstrate a significant genome‐wide interaction with insecticide exposure—rs10499003 and rs7745248, located in the intronic and 3' UTR regions of the <italic>FUT9</italic> gene on chromosome 6q16.1.</p> </abstract>