Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator.
Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator.
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DOI：
10.1002/gepi.21965
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发表时间：
2016-05
影响因子：
2.1
通讯作者：
Burgess S
中科院分区：
文献类型：
--
作者：
Bowden J;Davey Smith G;Haycock PC;Burgess S
全基因组关联研究的发展和总结遗传关联数据的日益可用性使得孟德尔随机化的应用相对简单。然而，从孟德尔随机化研究中获得可靠的结果仍然存在问题，因为传统的逆方差加权方法只有在分析中的所有遗传变异都是有效的工具变量时才能给出一致的估计值。我们提出了一种新的加权中位数估计多个遗传变异的数据组合成一个单一的因果估计。这个估计是一致的，即使高达50%的信息来自无效的工具变量。在模拟分析中，它被证明比逆方差加权方法具有更好的有限样本类型1错误率，并且与最近提出的MR-Egger（孟德尔随机化-Egger）回归方法互补。在分析低密度脂蛋白胆固醇和高密度脂蛋白胆固醇对冠状动脉疾病风险的因果效应时，逆方差加权法表明两种脂质组分都有因果效应，而加权中位数和MR-Egger回归法表明高密度脂蛋白胆固醇的零效应与实验证据一致。基于中位数的回归方法和MR-Egger回归方法均应被视为多个遗传变异的孟德尔随机化研究的敏感性分析。
Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.