Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology.
Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology.
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DOI：
10.1038/s41467-022-34164-1
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发表时间：
2022-10-30
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
--
作者：
孟德尔随机化（MR）利用遗传变异作为工具变量（IV），使用全基因组关联研究的汇总统计量研究暴露对结果的因果影响。当IV与未测量的混杂因素相关时，违反了经典的MR假设，即，当相关水平多效性（CHP）出现时。这些混杂因素可能是共同的基因或暴露和结果的相互关联的途径。我们提出了MR-CUE（MR with Correlated horizontal pleiotropy Unraveling shared Etiology and confounding），用于估计因果效应，同时识别具有CHP的IV并考虑估计不确定性。对于这些IV，我们绘制了它们的顺式相关基因和丰富的途径，以告知暴露和结局的共同遗传病因。我们应用MR-CUE研究白细胞介素6对多种性状/疾病的影响，并确定了几个S100基因参与共同的遗传病因。我们评估了欧洲和东亚人群中多次暴露对2型糖尿病的影响。孟德尔随机化使用遗传变异来研究暴露对结果的因果影响，但结果可能会受到混杂因素（如水平多效性）的影响。在这里，作者提出了MR-CUE，一种通过考虑相关和不相关的水平多效性效应来确定因果效应的方法。
Mendelian randomization (MR) harnesses genetic variants as instrumental variables (IVs) to study the causal effect of exposure on outcome using summary statistics from genome-wide association studies. Classic MR assumptions are violated when IVs are associated with unmeasured confounders, i.e., when correlated horizontal pleiotropy (CHP) arises. Such confounders could be a shared gene or inter-connected pathways underlying exposure and outcome. We propose MR-CUE (MR with Correlated horizontal pleiotropy Unraveling shared Etiology and confounding), for estimating causal effect while identifying IVs with CHP and accounting for estimation uncertainty. For those IVs, we map their cis-associated genes and enriched pathways to inform shared genetic etiology underlying exposure and outcome. We apply MR-CUE to study the effects of interleukin 6 on multiple traits/diseases and identify several S100 genes involved in shared genetic etiology. We assess the effects of multiple exposures on type 2 diabetes across European and East Asian populations. Mendelian randomization uses genetic variation to study the causal effect of exposure on outcome, but results can be biased by confounders, such as horizontal pleiotropy. Here, the authors present MR-CUE, a method to determine causal effects by accounting for correlated and uncorrelated horizontal pleiotropic effects.
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DOI：
10.1093/biostatistics/kxy027
发表时间：
2020-01-01
期刊：
Biostatistics (Oxford, England)
影响因子：
--
作者：
Berzuini C;Guo H;Burgess S;Bernardinelli L
通讯作者：
Bernardinelli L
影响因子：
14.9
作者：
Fairley, Susan;Lowy-Gallego, Ernesto;Flicek, Paul
通讯作者：
Flicek, Paul
影响因子：
30.8
作者：
Bulik-Sullivan B;Finucane HK;Anttila V;Gusev A;Day FR;Loh PR;ReproGen Consortium;Psychiatric Genomics Consortium;Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3;Duncan L;Perry JR;Patterson N;Robinson EB;Daly MJ;Price AL;Neale BM
通讯作者：
Neale BM
影响因子：
4.6
作者：
Cheng Q;Yang Y;Shi X;Yeung KF;Yang C;Peng H;Liu J
通讯作者：
Liu J
影响因子：
5.8
作者：
Cheng, Qing;Qiu, Tingting;Liu, Jin
通讯作者：
Liu, Jin