Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator
Smith, George Davey
Haycock, Philip C
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Bowden, J., Smith, G. D., Haycock, P. C., & Burgess, S. (2016). Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genetic Epidemiology, 40 304-314. https://doi.org/10.1002/gepi.21965
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.
Mendelian randomization, instrumental variables, robust statistics, Egger regression, pleiotropy
Jack Bowden is supported by a Methodology Research Fellowship from the Medical Research Council (grant number MR/N501906/1). George Davey Smith is supported by the Medical Research Council (grant number MC UU 12013/1- 9). Philip C Haycock is supported by a Cancer Research UK Population Research Postdoctoral Fellowship. Stephen Burgess is supported by a fellowship from the Wellcome Trust (100114).
Wellcome Trust (100114/Z/12/Z)
British Heart Foundation (RG/08/014/24067)
British Heart Foundation (RG/13/13/30194)
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External DOI: https://doi.org/10.1002/gepi.21965
This record's URL: https://www.repository.cam.ac.uk/handle/1810/253677