孟德尔随机化
因果推理
背景(考古学)
推论
工具变量
因果关系(物理学)
独立性(概率论)
随机化
计量经济学
混淆
计算机科学
因果关系
统计
口译(哲学)
数学
人工智能
医学
随机对照试验
认识论
遗传变异
遗传学
生物
古生物学
外科
哲学
程序设计语言
基因型
物理
基因
量子力学
作者
Y Z Wang,Hongbing Shen
出处
期刊:PubMed
日期:2020-08-10
卷期号:41 (8): 1231-1236
被引量:5
标识
DOI:10.3760/cma.j.cn112338-20200521-00749
摘要
Genetic variation is used as instrumental variable to investigate the causal relationship between exposure and outcome, which can avoid issues of confounding and reserve causation regarding Mendelian randomization studies. However, the instrumental variables in Mendelian randomization studies must satisfy three core assumptions-the relevance assumption, the independence assumption, and the exclusion restriction assumption. In addition to the plausibility of core assumptions, the application of Mendelian randomization studies in causal inference is also subject to other limitations. Findings from the Mendelian randomization studies should be interpreted in the context of existing evidence from other sources. In this article we provide an overview of the assumptions, limitations, and interpretation on causal inference that related to Mendelian randomization studies that can be applied in studies of the same kind.孟德尔随机化(Mendelian randomization,MR)研究使用遗传变异作为工具变量,推断暴露因素与结局之间的因果关系,能够有效克服混杂和反向因果问题所导致的偏倚。然而,MR研究中的工具变量须满足关联性、独立性和排他性3个核心假设。即使核心假设成立,MR研究在因果推断中的应用还受到其他局限性的影响。此外,MR研究结果的解读需要基于综合证据。本文将围绕MR研究应用于因果推断的影响因素和研究结果的解读进行综述,以期为MR研究结果应用提供指导。.
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