Using shared genetic controls in studies of gene-environment interactions
by Professor Ray Carroll
Abstract: With the advent of modern genomic methods for adjustment for population stratification, use of external or publicly available controls has become an attractive option to reduce the cost of large-scale case-control genetic association studies. We study the problem of estimation of joint effects of genetic and environmental exposures from a case-control study where data on genome-wide markers are available on the cases and a set of external controls, and data on environmental exposures are available on the cases and a set of internal controls. We show that under such a design one can exploit an assumption of gene-environment independence in the underlying population to estimate all the parameters of the gene-environment joint effects, after proper adjustment for population stratification. We develop a semiparametric profile likelihood method as well as related pseudolikelihood and working likelihood methods that are easy to implement in practice. We propose variance estimators for the methods based on asymptotic theory. Simulation studies are used to study the performance of the alternative methods. Data from a multi-center genome-wide association study of bladder cancer is further used to illustrate the methods.
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