Weak-Instrument Robust Tests in Two-Sample Summary-Data Mendelian Randomization

Wang, S.; Kang, H.

doi:10.1101/769562

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bioRxiv · 10.1101/769562

Weak-Instrument Robust Tests in Two-Sample Summary-Data Mendelian Randomization

Wang, S.·Kang, H.

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Abstract

Mendelian randomization (MR) is a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome using genetic variants as instrumental variables (IV), with two-sample summary-data MR being the most popular due to privacy. Unfortunately, many MR methods for two-sample summary data are not robust to weak instruments, a common phenomena with genetic instruments; many of these methods are biased and no existing MR method has Type I error control under weak instruments. In this work, we propose test statistics that are robust to weak instruments by extending Anderson-Rubin, Kleibergen, and conditional likelihood ratio tests in econometrics to the two-sample summary data setting. We conclude with a simulation and an empirical study and show that the proposed tests control size and have better power than current methods.

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Wang, S., Kang, H.. 2019-09-16. Weak-Instrument Robust Tests in Two-Sample Summary-Data Mendelian Randomization. https://doi.org/10.1101/769562

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