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评估多效性在孟德尔随机化研究中的潜在作用。

Evaluating the potential role of pleiotropy in Mendelian randomization studies.

机构信息

MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol.

出版信息

Hum Mol Genet. 2018 Aug 1;27(R2):R195-R208. doi: 10.1093/hmg/ddy163.

Abstract

Pleiotropy, the phenomenon of a single genetic variant influencing multiple traits, is likely widespread in the human genome. If pleiotropy arises because the single nucleotide polymorphism (SNP) influences one trait, which in turn influences another ('vertical pleiotropy'), then Mendelian randomization (MR) can be used to estimate the causal influence between the traits. Of prime focus among the many limitations to MR is the unprovable assumption that apparent pleiotropic associations are mediated by the exposure (i.e. reflect vertical pleiotropy), and do not arise due to SNPs influencing the two traits through independent pathways ('horizontal pleiotropy'). The burgeoning treasure trove of genetic associations yielded through genome wide association studies makes for a tantalizing prospect of phenome-wide causal inference. Recent years have seen substantial attention devoted to the problem of horizontal pleiotropy, and in this review we outline how newly developed methods can be used together to improve the reliability of MR.

摘要

多效性是指单个遗传变异影响多个性状的现象,这种现象在人类基因组中可能很普遍。如果多效性是因为单核苷酸多态性(SNP)影响一个性状,而这个性状又反过来影响另一个性状(“垂直多效性”),那么孟德尔随机化(MR)可以用于估计两个性状之间的因果关系。MR 面临的众多限制中,最关键的问题是无法证明明显的多效性关联是由暴露引起的(即反映垂直多效性),而不是由于 SNP 通过独立途径影响两个性状(“水平多效性”)。通过全基因组关联研究产生的大量遗传关联宝库为全表型因果推断提供了诱人的前景。近年来,人们对水平多效性问题给予了极大的关注,在这篇综述中,我们概述了如何结合使用新开发的方法来提高 MR 的可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75c4/6061876/45d3315ab773/ddy163f1.jpg

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