Westmead Hospital, Westmead, Australia, (C.L.).
School of Public Health, Faculty of Medicine and Health, The University of Sydney, Australia. Westmead Millennium Institute for Medical Research (A.T-P.).
Circ Cardiovasc Qual Outcomes. 2021 Jan;14(1):e005623. doi: 10.1161/CIRCOUTCOMES.119.005623. Epub 2021 Jan 5.
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.
孟德尔随机化是一种利用观察性数据进行因果推断的流行病学方法。它利用个体遗传组成的自然随机化，类似于随机对照试验的研究设计，并使用工具变量分析，其中遗传变异是工具（类似于随机分配到随机对照试验中的治疗组）。与任何工具变量一样，必须对遗传工具做出 3 个假设：（1）它与暴露相关（不一定是因果关系）（相关性条件）；（2）它仅通过暴露与结果相关（排除限制条件）；（3）它与结果没有共同原因（即遗传工具和结果没有混杂因素，独立性条件）。我们以 2 型糖尿病和冠状动脉疾病为例，演示了该方法如何用于研究因果关系，并讨论了潜在的益处和陷阱。我们得出的结论是，尽管孟德尔随机化研究通常不能单独确定因果关系，但它们可以为证据基础做出有用的贡献，并增加我们对减少心血管疾病干预措施有效性（或无效性）的确定性。
