Gauderman W James
Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA.
Genet Epidemiol. 2003 Dec;25(4):327-38. doi: 10.1002/gepi.10262.
With the increasing availability of genetic data, many studies of quantitative traits focus on hypotheses related to candidate genes, and also gene-environment (G x E) and gene-gene (G x 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 (QTDTM) 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 x E and G x 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 x E and G x G interactions are compared across various QTDT approaches to infer their efficiencies relative to one another. The QTDTM is found to meet or exceed the efficiency of other QTDT approaches. For example, the QTDTM 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 x E interaction, and three times more efficient for testing G x G interaction.
随着基因数据的可获得性不断提高,许多关于数量性状的研究聚焦于与候选基因相关的假设,以及基因-环境(G×E)和基因-基因(G×G)相互作用。在基于人群的样本中,候选基因效应的估计和检验可能会受到种族混杂的影响而产生偏差,种族混杂也被称为群体分层偏差。本文表明,即使是适度的种族混杂也可能导致基因效应检验的I型错误率高到不可接受的程度。本文回顾了亲代-子代三联体设计,并总结了几种形式的数量传递不平衡检验(QTDT)。描述了一种基于具有多个截距(每个亲代交配类型一个截距)的线性回归模型的QTDT变体(QTDTM)。这种模型和其他模型被扩展以允许检验G×E和G×G相互作用。描述了一种使用直接计算来计算所需样本量的方法。比较了各种QTDT方法在基因主效应、G×E和G×G相互作用检验中的样本量要求,以推断它们彼此之间的效率。发现QTDTM达到或超过了其他QTDT方法的效率。例如,在检验基因主效应时,QTDTM比Rabinowitz([1997]《人类遗传学》47:342 - 350)的QTDT效率高约3%,但在检验G×E相互作用时效率可高达两倍,在检验G×G相互作用时效率高三倍。