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Meta-analysis and Mendelian randomization: A review

Research output: Contribution to journalArticle

  • Jack Bowden
  • Michael V Holmes
Original languageEnglish
Number of pages11
JournalResearch Synthesis Methods
Early online date23 Apr 2019
DOIs
DateAccepted/In press - 11 Feb 2019
DateE-pub ahead of print (current) - 23 Apr 2019

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 amongst 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 rigour of the MR approach.

    Research areas

  • Mendelian randomization, meta-analysis, pleiotropy, two-sample summary data MR

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via Wiley at https://doi.org/10.1002/jrsm.1346 . Please refer to any applicable terms of use of the publisher.

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