Hwang S J, Beaty T H, Liang K Y, Coresh J, Khoury M J
Department of Epidemiology, Johns Hopkins School of Hygiene and Public Health, Baltimore, MD 21205.
Am J Epidemiol. 1994 Dec 1;140(11):1029-37. doi: 10.1093/oxfordjournals.aje.a117193.
As genetic markers become more available, case-control studies will be increasingly important in defining the role of genetic factors in disease causality. The authors estimate the minimum sample size needed to assure adequate statistical power to detect gene-environment interaction. One assumption is made: the prevalence of exposure is independent of marker genotypes among controls. Given the assumption, six parameters (three odds ratios, the prevalence of exposure, the proportion of those with the susceptible genotype, and the ratio of controls to cases) dictate the expected cell sizes in a 2 x 2 x 2 table contrasting genetic susceptibility, exposure, and disease. The three odds ratios reflect the association between disease and 1) exposure among non-susceptibles; 2) susceptible genotypes among nonexposed individuals; and 3) the gene-environment interaction itself, respectively. Given these parameters, the number of cases and controls needed to assure any particular Type I and Type II error rates can be estimated. Results presented here demonstrate that case-control designs can be used to detect gene-environment interaction when there is both a common exposure and a highly polymorphic marker of susceptibility.
随着越来越多的遗传标记可供使用，病例对照研究在确定遗传因素在疾病因果关系中的作用方面将变得越来越重要。作者估计了确保有足够统计效力来检测基因-环境相互作用所需的最小样本量。做出了一个假设：对照组中暴露的患病率与标记基因型无关。基于该假设，六个参数（三个比值比、暴露的患病率、易感基因型个体的比例以及对照组与病例组的比例）决定了一个2×2×2表格中的预期单元格大小，该表格用于对比遗传易感性、暴露和疾病。这三个比值比分别反映了疾病与以下三者之间的关联：1）非易感个体中的暴露；2）未暴露个体中的易感基因型；3）基因-环境相互作用本身。给定这些参数，就可以估计出确保任何特定的I型和II型错误率所需的病例数和对照数。此处给出的结果表明，当存在常见暴露和高度多态的易感性标记时，病例对照设计可用于检测基因-环境相互作用。
