Allelic Heterogeneity in Genetic Association Meta-Analysis: An Application to DTNBP1 and Schizophrenia
Allelic Heterogeneity in Genetic Association Meta-Analysis: An Application to DTNBP1 and Schizophrenia
复制标题
DOI：
10.1159/000264445
复制
发表时间：
2010-01-01
期刊：
影响因子：
1.8
通讯作者：
Kendler, Kenneth S.
中科院分区：
文献类型：
--
作者：
Maher, Brion S.;Reimers, Mark A.;Kendler, Kenneth S.
背景/目的：遗传关联研究的荟萃分析是一种有用的方法，当单个调查没有产生研究意义上的显著结果，但跨研究的证据是适度和均匀的。当前的荟萃分析方法通过降低研究权重作为研究间方差的函数来解释异质性。我们认为目前的方法可能会模糊遗传关联数据中有趣的现象。然而，缺乏一种适当的方法来检查研究的异质性。方法：我们开发了一种基于EM算法的新方法来检测等位基因异质性，识别亚种群并为这些亚种群分配研究。然后，我们将这些方法应用于DTNBP1与精神分裂症（Scz）之间的关联，这是复杂疾病遗传学中研究最多的关系之一。我们检查了32项已发表和未发表的基于人群和家庭的关联研究，其中包含多达14个跨DTNBP1位点的snp。结果：我们通过多种方式探索了异质性，包括meta回归和旨在探索特定SNP异质性研究混合的方法。我们在多个基因座上发现了关联分布混合的重要证据。结论：我们提出了一种广泛适用的新方法，可用于大规模遗传关联荟萃分析，以检测显著的等位基因异质性。版权所有(C) 2009 S. Karger AG，巴塞尔
Background/Aims: Meta-analysis of genetic association studies is a useful approach when individual investigations do not yield studywise significant results but the evidence across studies is modest and homogeneous. Current meta-analysis methods account for heterogeneity by down-weighting studies as a function of between-study variance. We contend that current approaches may obscure interesting phenomena in genetic association data. However, an appropriate approach to examining heterogeneity across studies is lacking. Methods: We develop a novel approach, based on the EM algorithm, to detect allelic heterogeneity, identify subpopulations and assign studies to those subpopulations. We then apply these methods to the association between DTNBP1 and schizophrenia (Scz), one of the most studied relationships in complex disease genetics. We examined 32 published and unpublished population and family-based association studies containing up to 14 SNPs spanning the DTNBP1 locus. Results: We explored heterogeneity in several ways including meta-regression and approaches aimed at exploring the mixture of heterogeneous studies at a particular SNP. We found significant evidence for a mixture of association distributions at multiple loci. Conclusion: We propose a novel approach that is broadly applicable and may be useful in large scale genetic association meta-analyses to detect significant allelic heterogeneity. Copyright (C) 2009 S. Karger AG, Basel