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Nat Rev Cardiol. 2017 Oct;14(10):577-590. doi: 10.1038/nrcardio.2017.78. Epub 2017 Jun 1.

Mendelian randomization in cardiometabolic disease: challenges in evaluating causality.

Holmes MV1,2,3,4, Ala-Korpela M4,5,6, Smith GD4,6.

Author information

1
Medical Research Council Population Health Research Unit, University of Oxford, Roosevelt Drive, Oxford OX3 7LF, UK.
2
Clinical Trial Service Unit &Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7BN, UK.
3
National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Old Road, Oxford OX3 7LE, UK.
4
Medical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
5
Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, University of Oulu, Aapistie 5A, 90014, Oulu, Finland.
6
School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.

Abstract

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.

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