Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy

Chin Yang Shapland*, Qingyuan Zhao, Jack Bowden

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

Two-sample summary data Mendelian randomisation (MR) is a popular method for assessing causality in epidemiology, by using genetic variants as instrumental variables. If genes exert pleiotropic effects on the outcome not through the exposure of interest, this can lead to heterogeneous and (potentially) biased estimates of causal effect. We investigate the use of Bayesian model averaging (BMA) to preferentially search the space of models with the highest posterior likelihood. We develop a bespoke Metropolis-Hasting algorithm to perform the search using the recently developed Robust Adjusted Profile Likelihood (MR-RAPS) of Zhao et al as the basis for defining a posterior distribution that efficiently accounts for pleiotropic and weak instrument bias. We demonstrate how our general modelling approach can be extended from a standard one-parameter causal model to a two-parameter model, to allow a large proportion of SNPs to violate the Instrument Strength Independent of Direct Effect (InSIDE) assumption. We use Monte Carlo simulations to illustrate our methods and compare it to several related approaches. We finish by applying our approach in practice to investigate the changes in causal effect of their resulting high risk metabolite on the development age-related macular degeneration.
Original languageEnglish
Pages (from-to)1100-1119
Number of pages20
JournalStatistics in Medicine
Volume41
Issue number6
Early online date20 Jan 2022
DOIs
Publication statusPublished - 24 Feb 2022

Bibliographical note

Funding Information:
We thank the reviewers and associate editor for providing comments and suggestions to improve this article. Chin Yang Shapland works in a unit that receives support from the Medical Research Council Integrative Epidemiology Unit at the University of Bristol (code: MC_UU_00011/3). Qingyuan Zhao was partly funded by the Issac Newton Trust. Jack Bowden is funded by an Expanding Excellence in England (E3) grant awarded to the University of Exeter.

Funding Information:
information Expanding Excellence in England (E3), Issac Newton Trust, Medical Research Council, MC_UU_00011/3We thank the reviewers and associate editor for providing comments and suggestions to improve this article. Chin Yang Shapland works in a unit that receives support from the Medical Research Council Integrative Epidemiology Unit at the University of Bristol (code: MC_UU_00011/3). Qingyuan Zhao was partly funded by the Issac Newton Trust. Jack Bowden is funded by an Expanding Excellence in England (E3) grant awarded to the University of Exeter.

Publisher Copyright:
© 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Keywords

  • Bayesian model averaging
  • horizontal pleiotropy
  • InSIDE violation
  • two-sample summary dataMendelian randomization
  • weak instruments

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