Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors
Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors
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DOI：
10.1016/j.jclinepi.2015.08.001
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发表时间：
2016-01-01
影响因子：
7.2
通讯作者：
Thompson, John R.
中科院分区：
文献类型：
--
作者：
Burgess, Stephen;Butterworth, Adam S.;Thompson, John R.
目的：孟德尔随机化是评估和估计危险因素因果效应的一种流行技术。如果作为一种风险因素的工具变量的基因变异被证明与疾病结果有额外的联系，那么这种风险因素就是疾病的原因。然而，在许多情况下，工具变量假设是不合理的，或者是有疑问的。在本文中，我们提供了一个理论分类的情景，其中因果结论被证明或不被证明，并讨论因果效应估计的解释。结果：基于“Bradford Hill标准”的指南列表，用于从应用孟德尔随机化研究中判断因果发现的合理性。我们还提供了一个框架，用于执行和解释孟德尔随机化风格的调查，但其中遗传变异的选择是统计上的，而不是生物学上的动机。这种分析不应被赋予与孟德尔随机化调查相同的证据权重。结论：我们讨论了这些调查的作用（以孟德尔随机化的方式），以及它们增加了我们对潜在因果机制的理解。如果仅仅根据统计标准选择遗传变异，而不调查遗传变异的生物学作用，这可能比从精心设计的经典观察性研究中学到的东西要少得多。(C) 2016年作者。Elsevier Inc.出版。
Objective: Mendelian randomization is a popular technique for assessing and estimating the causal effects of risk factors. If genetic variants which are instrumental variables for a risk factor are shown to be additionally associated with a disease outcome, then the risk factor is a cause of the disease. However, in many cases, the instrumental variable assumptions are not plausible, or are in doubt. In this paper, we provide a theoretical classification of scenarios in which a causal conclusion is justified or not justified, and discuss the interpretation of causal effect estimates.Results: A list of guidelines based on the 'Bradford Hill criteria' for judging the plausibility of a causal finding from an applied Mendelian randomization study is provided. We also give a framework for performing and interpreting investigations performed in the style of Mendelian randomization, but where the choice of genetic variants is statistically, rather than biologically motivated. Such analyses should not be assigned the same evidential weight as a Mendelian randomization investigation.Conclusion: We discuss the role of such investigations (in the style of Mendelian randomization), and what they add to our understanding of potential causal mechanisms. If the genetic variants are selected solely according to statistical criteria, and the biological roles of genetic variants are not investigated, this may be little more than what can be learned from a well-designed classical observational study. (C) 2016 The Authors. Published by Elsevier Inc.