孟德尔随机化
因果推理
随机对照试验
因果关系(物理学)
随机化
结果(博弈论)
疾病
计量经济学
混淆
工具变量
医学
观察研究
遗传学
生物
遗传变异
内科学
数学
病理
数理经济学
基因型
物理
基因
量子力学
作者
Katy Bell,Clement T. Loy,Anne Ε. Cust,Armando Teixeira‐Pinto
标识
DOI:10.1161/circoutcomes.119.005623
摘要
Mendelian randomization is an epidemiological approach to making causal inferences using observational data. It makes use of the natural randomization that occurs in the generation of an individual’s genetic makeup in a way that is analogous to the study design of a randomized controlled trial and uses instrumental variable analysis where the genetic variant(s) are the instrument (analogous to random allocation to treatment group in an randomized controlled trial). As with any instrumental variable, there are 3 assumptions that must be made about the genetic instrument: (1) it is associated (not necessarily causally) with the exposure (relevance condition); (2) it is associated with the outcome only through the exposure (exclusion restriction condition); and (3) it does not share a common cause with the outcome (ie, no confounders of the genetic instrument and outcome, independence condition). Using the example of type II diabetes and coronary artery disease, we demonstrate how the method may be used to investigate causality and discuss potential benefits and pitfalls. We conclude that although Mendelian randomization studies can usually not establish causality on their own, they may usefully contribute to the evidence base and increase our certainty about the effectiveness (or otherwise) of interventions to reduce cardiovascular disease.
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