Parent–child pair design for detecting gene–environment interactions in complex diseases

Abstract

It is becoming clear that the etiology of complex diseases involves not only genetic and environmental factors but also gene-environment (GE) interactions. Therefore, it is important to take account of all these factors to improve the power of an epidemiological study design. We propose here a novel parent-child pair (PCP) design for this purpose. In comparison with conventional designs, this approach has the following advantages: (a) PCP is a 4 x 16 design consisting of pairs of parent-child (PC) genotype statuses, PC exposure statuses and PC disease statuses. Therefore, it utilizes more information than the traditional approaches in association studies; (b) It can determine whether findings in studies of association between disease and genetic or environmental factors and their interaction are spurious, arising from Hardy-Weinberg disequilibrium or the other factors; (c) Since the information from both parents and children of the PC pairs are used in this design, it has high power for detecting association of candidate gene, exposure with a complex disease and GE interaction. We also present a set of estimates of relative risks of candidate genes, exposures and GE interactions under the multiplicative model and a method for computing the sample size requirements to test for these relative risks in the context of the PCP design.