Candidate gene association analysis for a quantitative trait, using parent-offspring trios

Abstract

With the increasing availability of genetic data, many studies of quantitative traits focus on hypotheses related to candidate genes, and also gene-environment (G×E) and gene-gene (G×G) interactions. In a population-based sample, estimates and tests of candidate gene effects can be biased by ethnic confounding, also known as population stratification bias. This paper demonstrates that even a modest degree of ethnic confounding can lead to unacceptably high type I error rates for tests of genetic effects. The parent-offspring trio design is reviewed, and several forms of the quantitative transmission disequilibrium test (QTDT) are summarized. A variation of the QTDT (QTDT_M) is described that is based on a linear regression model with multiple intercepts, one per parental mating type. This and other models are expanded to allow testing of G×E and G×G interactions. A method for computing required sample sizes using direct computations is described. Sample size requirements for tests of genetic main effects and G×E and G×G interactions are compared across various QTDT approaches to infer their efficiencies relative to one another. The QTDT_M is found to meet or exceed the efficiency of other QTDT approaches. For example, the QTDT_M is approximately 3% more efficient than the QTDT of Rabinowitz ([1997] Hum. Hered. 47:342–350) for testing a genetic main effect, but can be as much as twice as efficient for testing G×E interaction, and three times more efficient for testing G×G interaction. Genet Epidemiol 25:327–338, 2003. © 2003 Wiley-Liss, Inc.