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 × 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.
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