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(Jul. 24) Combining multiple SNPs in Mendelian randomization studies with continuous outcomes

Last updated :2017-07-17

Topic: Combining multiple SNPs in Mendelian randomization studies with continuous outcomes
Speaker:Yanchun Bao (University of Essex)
Time: 10:00-11:00 am, Monday, July 24, 2017
Venue: Room 415, New Mathematics Building, Guangzhou South Campus, SYSU

Abstract:
Mendelian Randomization (MR) uses genetic variants as instrumental variables (IVs) to estimate the causal effects of modifiable exposures on outcomes. The core conditions required for a genetic variant to identify a causal effect are that it 1) is associated with the exposure, 2) has no direct pathway between it and the outcome, and 3) is not associated with any unobserved confounding variables. In practice, individual genetic variants are only weakly associated with exposures so that we would obtain biased estimates, even if the core conditions were satisfied. This has led researchers to consider the use of multiple genetic variants in their analyses. However, even here, the impact of pleiotropy, and other problems such as linkage disequilibrium and population stratification, can lead to bias through failure of core conditions 2) and 3). In this paper, we compare two recently developed methods, MR-Egger regression [1] and median estimator [2], which are claimed to be robust to invalid IVs and which have been applied by other researchers. We also investigate the performance of another new method, sisVIVE [3], which has good theoretical properties but is much less widely used. We discuss the relative performance of these methods through simulation experiments and an application to estimate the causal effect of BMI on social outcomes using genetic data from Understanding Society.

[1] Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal of Epidemiology 2015; 44(2):512–525.
[2] Bowden J, Smith GD, Haycodk PC, Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator, Genetic Epidemiology, 2016; 40(4):304-14. doi: 10.1002/gepi.21965
[3] Kang H, Zhang A, Cai TT, Small DS. Instrumental Variables Estimation with Some Invalid Instruments and its Application to Mendelian Randomization Small DS. Journal of the American Statistical Association, 2016;111(513):132-144, DOI: 10.1080/01621459.2014.994705