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September 23, 2020

Expressing Results From a Mendelian Randomization Analysis: Separating Results From Inferences

Author Affiliations
  • 1Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
  • 2Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
  • 3Cardiology Section, Veteran’s Administration Boston Healthcare System, Boston, Massachusetts
  • 4Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
  • 5Department of Epidemiology and Biostatistics, Medical School Building, St Mary’s Hospital, Imperial College London, London, United Kingdom
  • 6Clinical Pharmacology and Therapeutics Section, St George’s, University of London, London, United Kingdom
JAMA Cardiol. 2021;6(1):7-8. doi:10.1001/jamacardio.2020.4317

Choice of language is important, particularly relating to causal claims. Mendelian randomization is an epidemiologic approach used in biomedical research to assess the evidence for a causal hypothesis using genetic associations estimated in observational data. Increasingly, mendelian randomization investigations are providing evidence supporting the potential effectiveness of treatments for which causality has not been established in a randomized clinical trial. The language used to describe findings from mendelian randomization investigations is inconsistent, with some studies claiming that mendelian randomization can demonstrate that an exposure has a causal effect on an outcome and others making more circumspect claims. As an example, 2 articles investigating height and coronary artery disease (CAD) using mendelian randomization were published in 2015. One article reported on the “causal effect of completed growth, measured by adult height, on coronary heart disease,”1 while the other article reported “a genetic approach to investigate the association between height and CAD.”2 Herein, we explore the assumptions of mendelian randomization and discuss how to interpret and express results findings from such an analysis.

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