孟德尔随机化
因果推理
观察研究
肝病学
因果关系(物理学)
随机化
医学
推论
随机对照试验
内科学
计算机科学
病理
人工智能
生物
遗传学
遗传变异
物理
量子力学
基因
基因型
作者
Yilin Song,Ting Ye,Lewis R. Roberts,Nicholas B. Larson,Stacey J. Winham
出处
期刊:Hepatology
[Lippincott Williams & Wilkins]
日期:2023-10-24
被引量:1
标识
DOI:10.1097/hep.0000000000000649
摘要
Mendelian randomization has become a popular tool to assess causal relationships using existing observational data. While randomized controlled trials are considered the gold standard for establishing causality between exposures and outcomes, it is not always feasible to conduct a trial. Mendelian randomization is a causal inference method that uses observational data to infer causal relationships by using genetic variation as a surrogate for the exposure of interest. Publications using the approach have increased dramatically in recent years, including in the field of hepatology. In this concise review, we describe the concepts, assumptions, and interpretation of Mendelian randomization as related to studies in hepatology. We focus on the strengths and weaknesses of the approach for a non-statistical audience, using an illustrative example to assess the causal relationship between body mass index and NAFLD.
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