Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Journal article

Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings.

Authors: Holmes, M; Ala-Korpela, M; Smith, G

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer Nature
• Journal: Nature Reviews Cardiology
• Volume: 14
• Issue: 10
• Pages: 577-590
• Publication date: 2017-06-01
• Acceptance date: 2017-01-01
• DOI: 10.1038/nrcardio.2017.78
• EISSN: 1759-5010
• ISSN: 1759-5002
• Pmid: 28569269
• Language: English
• Keywords: Medical research; Pathogenesis; Diabetes; Cardiovascular diseases