Meta-Analysis of Genome-wide Association Studies with Overlapping Subjects
Meta-Analysis of Genome-wide Association Studies with Overlapping Subjects
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DOI：
10.1016/j.ajhg.2009.11.001
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发表时间：
2009-12-11
影响因子：
9.8
通讯作者：
Sullivan, Patrick F.
中科院分区：
文献类型：
--
作者：
Lin, Dan-Yu;Sullivan, Patrick F.
来自多个全基因组关联研究的数据经常被一起分析，目的是整合对同一疾病的多项研究的信息，或者比较不同疾病的研究结果。我们为这种荟萃分析提供了一种有效且高效的方法，该方法考虑到了研究对象的重叠情况。可用数据可能包含个体参与者记录，也可能只有荟萃分析的汇总结果。模拟研究表明，在整合对同一疾病的多项研究结果时，如果不考虑研究对象的重叠情况，会大大增加I型错误；而在比较不同疾病的研究结果时，会大幅降低检验效能。此外，所提出的方法可能比在研究之间拆分重叠对象的简单方法更有效，尤其是在比较不同疾病的研究结果时。新方法的优势通过两组全基因组关联研究的实证数据得以说明。
Data from multiple genome-wide association studies are often analyzed together for the purposes of combining information from several studies of the same disease or comparing results across different disorders. We provide a valid and efficient approach to such meta-analysis, allowing for overlapping study subjects. The available data may contain individual participant records or only meta-analytic summary results. Simulation studies demonstrate that failure to account for overlapping subjects can greatly inflate type I error when combining results from multiple studies of the same disease and can drastically reduce power when comparing results across different disorders. In addition, the proposed approach can be substantially more powerful than the simple approach of splitting the overlapping subjects among studies, especially for comparing results across different disorders. The advantages of the new approach are illustrated with empirical data from two sets of genome-wide association studies.