Exploiting gene-environment interaction to detect genetic associations
Exploiting gene-environment interaction to detect genetic associations
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DOI：
10.1159/000099183
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发表时间：
2007-01-01
期刊：
影响因子：
1.8
通讯作者：
Gauderman, W. James
中科院分区：
文献类型：
--
作者：
Kraft, Peter;Yen, Yu-Chun;Gauderman, W. James
根据定义，复杂疾病是遗传和环境因素相互作用的结果。然而，目前尚不清楚如何最好地利用基因-环境相互作用来定位复杂的疾病易感位点，特别是在扫描1,000到1,000,000个标记以寻找与疾病相关的研究背景下。我们对病例对照数据提出了边际关联和基因-环境相互作用的联合检验。我们将此联合检验的功率和样本量要求与其他分析进行比较：遗传关联的边际检验，基于逻辑回归的基因-环境相互作用的标准检验，以及利用基因-环境独立性的相互作用的个案检验。尽管对于许多外显子模型，遗传边际效应和相互作用的联合测试不是最强大的，但它在我们考虑的所有外显子模型中几乎是最优的。特别是，当遗传效应仅限于暴露对象时，它通常比边际试验更有效；当遗传效应不限于特定暴露水平时，它比基因-环境相互作用试验更有效。这使得联合测试成为大规模关联扫描的一个有吸引力的工具，其中真正的基因-环境相互作用模型是未知的。版权所有(c) 2007 S. Karger AG，巴塞尔。
Complex disease by definition results from the interplay of genetic and environmental factors. However, it is currently unclear how gene-environment interaction can best be used to locate complex disease susceptibility loci, particularly in the context of studies where between 1,000 and 1,000,000 markers are scanned for association with disease. We present a joint test of marginal association and gene-environment interaction for case-control data. We compare the power and sample size requirements of this joint test to other analyses: the marginal test of genetic association, the standard test for gene-environment interaction based on logistic regression, and the case-only test for interaction that exploits gene-environment independence. Although for many penetrance models the joint test of genetic marginal effect and interaction is not the most powerful, it is nearly optimal across all penetrance models we considered. In particular, it generally has better power than the marginal test when the genetic effect is restricted to exposed subjects and much better power than the tests of gene-environment interaction when the genetic effect is not restricted to a particular exposure level. This makes the joint test an attractive tool for large-scale association scans where the true gene-environment interaction model is unknown. Copyright (c) 2007 S. Karger AG, Basel.