孟德尔随机化
混淆
概化理论
范围(计算机科学)
稳健性(进化)
结果(博弈论)
因果推理
计算机科学
计量经济学
心理学
医学
生物
遗传变异
遗传学
发展心理学
数学
数理经济学
病理
基因型
程序设计语言
基因
作者
Rebecca C Richmond,George Davey Smith
出处
期刊:Cold Spring Harbor Perspectives in Medicine
[Cold Spring Harbor Laboratory]
日期:2021-08-23
卷期号:12 (1): a040501-a040501
被引量:134
标识
DOI:10.1101/cshperspect.a040501
摘要
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
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