Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects
Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects
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DOI：
10.1093/aje/kwy177
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发表时间：
2018-12-01
影响因子：
5
通讯作者：
Hsu, Li
中科院分区：
文献类型：
--
作者：
Dai, James Y.;Peters, Ulrike;Hsu, Li
诊断多效性对于评估孟德尔随机化（MR）分析的有效性至关重要。流行的MR-Egger方法评估在一组候选遗传工具变量中是否存在产生偏倚的多效性的证据。在这篇文章中，我们提出了一种统计方法--直接效应的整体和个体检验（GLIDE）--用于系统地评估遗传变异集中的多效性（例如，单核苷酸多态性（SNPs））用于MR。作为一个全球性的测试，模拟实验表明，GLIDE是几乎一致更强大的比theMR-Egger方法。作为敏感性分析，GLIDE能够检测个体变异水平多效性中的离群值，以获得一组精细的遗传工具变量。我们使用GLIDE分析了来自结直肠癌遗传学和流行病学联盟和结肠癌家族登记处（多项研究）的数据中体重指数和身高与结直肠癌风险的相关性。在与体重指数相关的SNP和与身高相关的SNP中，几个个体变体显示出多效性的证据。去除这些潜在的多效性SNP导致因果效应的各自估计值的衰减。总之，GLIDE方法是有用的敏感性分析，提高了MR的有效性。
Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than theMR-Eggermethod. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both bodymass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDEmethod is useful for sensitivity analyses and improves the validity of MR.