Repository logo
 

Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy

Published version
Peer-reviewed

Change log

Authors

Rees, JMB 

Abstract

Methods have been developed for Mendelian randomization that can obtain consistent causal estimates while relaxing the instrumental variable assumptions. These include multivariable Mendelian randomization, in which a genetic variant may be associated with multiple risk factors so long as any association with the outcome is via the measured risk factors (measured pleiotropy), and the MR-Egger (Mendelian randomization-Egger) method, in which a genetic variant may be directly associated with the outcome not via the risk factor of interest, so long as the direct effects of the variants on the outcome are uncorrelated with their associations with the risk factor (unmeasured pleiotropy). In this paper, we extend the MR-Egger method to a multivariable setting to correct for both measured and unmeasured pleiotropy. We show, through theoretical arguments and a simulation study, that the multivariable MR-Egger method has advantages over its univariable counterpart in terms of plausibility of the assumption needed for consistent causal estimation, and power to detect a causal effect when this assumption is satisfied. The methods are compared in an applied analysis to investigate the causal effect of high-density lipoprotein cholesterol on coronary heart disease risk. The multivariable MR-Egger method will be useful to analyse high-dimensional data in situations where the risk factors are highly related and it is difficult to find genetic variants specifically associated with the risk factor of interest (multivariable by design), and as a sensitivity analysis when the genetic variants are known to have pleiotropic effects on measured risk factors.

Description

Keywords

invalid instruments, Mendelian randomization, MR-Egger, multivariable, pleiotropy

Journal Title

Statistics in Medicine

Conference Name

Journal ISSN

0277-6715
1097-0258

Volume Title

Publisher

Wiley-Blackwell
Sponsorship
Wellcome Trust (204623/Z/16/Z)
Medical Research Council (G0700463)
Medical Research Council (MR/L003120/1)
British Heart Foundation (None)
British Heart Foundation (None)
Medical Research Council (MC_UU_00002/7)
Jessica Rees is supported by the British Heart Foundation (grant number FS/14/59/31282). Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 204623/Z/16/Z).