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Meta-analysis and Mendelian randomization: A review.

Authors
  • Bowden, Jack1
  • Holmes, Michael V1, 2, 3, 4
  • 1 Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  • 2 Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.
  • 3 Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • 4 National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK.
Type
Published Article
Journal
Research synthesis methods
Publication Date
Dec 01, 2019
Volume
10
Issue
4
Pages
486–496
Identifiers
DOI: 10.1002/jrsm.1346
PMID: 30861319
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Mendelian randomization (MR) uses genetic variants as instrumental variables to infer whether a risk factor causally affects a health outcome. Meta-analysis has been used historically in MR to combine results from separate epidemiological studies, with each study using a small but select group of genetic variants. In recent years, it has been used to combine genome-wide association study (GWAS) summary data for large numbers of genetic variants. Heterogeneity among the causal estimates obtained from multiple genetic variants points to a possible violation of the necessary instrumental variable assumptions. In this article, we provide a basic introduction to MR and the instrumental variable theory that it relies upon. We then describe how random effects models, meta-regression, and robust regression are being used to test and adjust for heterogeneity in order to improve the rigor of the MR approach. © 2019 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

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