Mendelian randomization in cardiometabolic disease: challenges in evaluating causality
Open accessAbstract
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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If the effect of an exposure on an outcome is cumulative over many years, MR can overestimate the effect when compared to short term interventions.
“Likewise, if the effect of an exposure on an outcome is cumulative over many years, MR can overestimate the effect when compared to short term interventions.60 119”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [119]
Leave-one-out analyses can be valuable in assessing the reliance of a Mendelian randomization analysis on a particular variant.
“Leave-one-out analyses (i.e. remove one variant from the analysis and re-estimate the causal effect) can be valuable in assessing the reliance of a Mendelian randomization analysis on a particular variant 100 .”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [100]
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Self-citationAssociations of Adiposity, Circulating Protein Biomarkers, and Risk of Major Vascular Diseases
Pang, Y., Kartsonaki, C., Lv, J., Fairhurst-Hunter, Z., Millwood, I. Y., Yu, C., Guo, Y., Chen, Y., Bian, Z., Yang, L., et al. (2021) · JAMA Cardiology · doi:10.1001/jamacardio.2020.6041 · Cited by 75 · see citing works
Self-citationAshor, A. W., Brown, R., Keenan, P. D., Willis, N. D., Siervo, M., & Mathers, J. C. (2019) · Nutrition Research · doi:10.1016/j.nutres.2018.08.005 · Cited by 66 · see citing works
Revealing the effect of CETP inhibition in cardiovascular disease
Holmes, M. V., & Smith, G. D. (2017) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2017.156 · Cited by 56 · see citing works
Self-citationMendelian Randomization analysis of the causal effect of adiposity on hospital costs
Dixon, P., Hollingworth, W., Harrison, S., Davies, N. M., & Davey Smith, G. (2020) · Journal of Health Economics · doi:10.1016/j.jhealeco.2020.102300 · Cited by 48 · see citing works
Human Genetics and Drug Development
Holmes, M. V. (2019) · New England Journal of Medicine · doi:10.1056/nejme1901565 · Cited by 28 · see citing works
Self-citationMendelian randomisation approaches to the study of prenatal exposures: A systematic review
Diemer, E. W., Labrecque, J. A., Neumann, A., Tiemeier, H., & Swanson, S. A. (2021) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12691 · Cited by 21 · see citing works
Shen, J.-Y., Xu, L., Ding, Y., & Wu, X.-Y. (2023) · World Journal of Clinical Cases · doi:10.12998/wjcc.v11.i23.5468 · Cited by 7 · see citing works
- Authors
- Holmes, M. V., Ala-Korpela, M., & Smith, G. D.
- Affiliations
- National Institute for Health and Care Research (GB)
- University of Bristol (GB)
- Corresponding author
- Holmes, Michael V.
- Venue
- Nature Reviews Cardiology
- Published
- 2017-06-01
- Volume
- 14
- Issue
- 10
- Pages
- 577-590
- ISSN
- 1759-5002 (ISSN-L)
- 1759-5010
- PMC
- PMC5600813
- OpenAlex
- W2620908531
- Cited by
- 679
- References
- 159
- Citations by year
- 2026: 35 · 2025: 77 · 2024: 123 · 2023: 96 · 2022: 74 · 2021: 91 · 2020: 64 · 2019: 57 · 2018: 45 · 2017: 17
- FWCI
- 6.47
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Bristol Research (University of Bristol) (submittedVersion, other-oa)
- Funders
- University of Oxford
- University of Bristol (MC_UU_12013/1)
- Medical Research Council (MC_UU_12013, MCUU12013/1)
- Biocenter, University of Oulu
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- Mendelian randomization, causality, cardiometabolic disease, pleiotropy, branched-chain amino acids, diabetes mellitus, C-reactive protein, coronary artery disease, HDL cholesterol, interleukin-6, alcohol metabolism, extracellular superoxide dismutase, LDL cholesterol, triglycerides, non-HDL cholesterol, genetic variants
- MeSH terms
- Coronary Disease, Humans, Cholesterol, HDL, Cholesterol, LDL, Risk Factors, Genetic Variation, Biomarkers, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Mendelian Randomization Analysis
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