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A robust and efficient method for Mendelian randomization with hundreds of genetic variants

Research output: Contribution to journalArticle

  • Stephen Burgess
  • Christopher N Foley
  • Elias Allara
  • James R Staley
  • Joanna M M Howson
Original languageEnglish
Pages (from-to)376
JournalNature Communications
Volume11
Issue number1
DOIs
DateAccepted/In press - 17 Dec 2019
DatePublished (current) - 17 Jan 2020

Abstract

Mendelian randomization (MR) is an epidemiological technique that uses genetic variants to distinguish correlation from causation in observational data. The reliability of a MR investigation depends on the validity of the genetic variants as instrumental variables (IVs). We develop the contamination mixture method, a method for MR with two modalities. First, it identifies groups of genetic variants with similar causal estimates, which may represent distinct mechanisms by which the risk factor influences the outcome. Second, it performs MR robustly and efficiently in the presence of invalid IVs. Compared to other robust methods, it has the lowest mean squared error across a range of realistic scenarios. The method identifies 11 variants associated with increased high-density lipoprotein-cholesterol, decreased triglyceride levels, and decreased coronary heart disease risk that have the same directions of associations with various blood cell traits, suggesting a shared mechanism linking lipids and coronary heart disease risk mediated via platelet aggregation.

    Structured keywords

  • Bristol Population Health Science Institute

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