检测全基因组关联数据中的基因-环境相互作用。
Detecting gene-environment interactions in genome-wide association data.
机构信息
Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53726-2397, USA.
出版信息
Genet Epidemiol. 2009;33 Suppl 1(Suppl 1):S68-73. doi: 10.1002/gepi.20475.
Abstract
Despite the importance of gene-environment (GxE) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genome-wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 contributions, which introduced a variety of new methods for the detection of GxE interactions in both case-control and family-based data using both cross-sectional and longitudinal study designs. Many of these contributions detected significant GxE interactions. Although these interactions have not yet been confirmed, the results suggest the importance of testing for interactions. Issues of sample size, quantifying the environmental exposure, longitudinal data analysis, family-based analysis, selection of the most powerful analysis method, population stratification, and computational expense with respect to testing GxE interactions are discussed.
摘要
尽管基因-环境（GxE）相互作用在常见疾病的病因学中非常重要，但在全基因组关联研究数据中开发检测这些类型相互作用的方法的工作却很少。这是遗传分析研讨会 16 组 10 的重点贡献，该研究引入了多种新的方法，用于使用横断面和纵向研究设计在病例对照和基于家庭的研究数据中检测 GxE 相互作用。其中许多研究发现了显著的 GxE 相互作用。虽然这些相互作用尚未得到证实，但结果表明有必要进行相互作用的测试。讨论了与检测 GxE 相互作用有关的样本量、环境暴露的量化、纵向数据分析、基于家庭的分析、最有效分析方法的选择、群体分层和计算费用等问题。
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