The DOI matches its Crossref record; 119 of the 119 references it cites were found in a registry or an index.
Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
Open accessAbstract
We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.
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![Fig. 1 Google Scholar citations to the papers that heralded a marked upturn in use of the terms “causal inference” [8] and “Mendelian randomization” [2] within epidemiology](/paper-figures/3ee85e2be3a74c3692d33a8b2c346dbf/mendels-laws-mendelian-randomization-and-causal-inference-in-observational-data-figure-1.jpg)
![Fig. 2 Exemplar of misleading epidemiological research, used to illustrate the need to develop alternatives to naïve observational analyses, in an early review of MR (reproduced from [24]). Vitamin E supplement use and risk of CHD in two observational studies [9, 10] and in a meta-analysis of RCTs [111]. RR: relative risk](/paper-figures/5ca04536d2734d5c849336dc9976b401/mendels-laws-mendelian-randomization-and-causal-inference-in-observational-data-figure-2.jpg)
![Fig. 3 Relative risk of coronary heart disease by daily alcohol consumption, compared to non-drinkers. Data from Rimm et al. [25]](/paper-figures/afcf8fc5bb384e679837bae930c18346/mendels-laws-mendelian-randomization-and-causal-inference-in-observational-data-figure-3.jpg)
![Fig. 4 A Relative risk (RR) of stroke according to drinking patterns (left hand panel) and MR analyses (right hand panel) in men. B RR of coronary heart disease according to drinking patterns (left hand panel) and MR analyses (right hand panel) in men [51]](/paper-figures/a3b030bb880d4dabbb097729396c5716/mendels-laws-mendelian-randomization-and-causal-inference-in-observational-data-figure-4.jpg)
![Fig. 5 CHD odds ratio (TT versus CC MTHFR C677T genotype) in each probable folate status category, from a meta-analyses of 19 unpublished datasets. US United States, ANZ Australia, New Zealand) [92]](/paper-figures/e5550f3f13084170a3ba2cf6077eceed/mendels-laws-mendelian-randomization-and-causal-inference-in-observational-data-figure-5.jpg)
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“Multiple trials of drugs targeting LDL- C lowering show cardiovascular benefit 39,116”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [39]
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Cites
1 retracted
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RetractedTesting for Weak Instruments in Linear IV Regression
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Mendelian randomization: genetic anchors for causal inference in epidemiological studies
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Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians
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Vitamin E Consumption and the Risk of Coronary Disease in Women
Stampfer, M. J., Hennekens, C. H., Manson, J. E., Colditz, G. A., ROSNER, B. A., & Willett, W. C. (1993) · New England Journal of Medicine · doi:10.1056/nejm199305203282003 · Cited by 2,085
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Cited by
Sorted by citations
Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229
Self-citationThe MRC IEU OpenGWAS data infrastructurePreprint
Elsworth, B., Lyon, M., Alexander, T., Liu, Y., Matthews, P., Hallett, J., Bates, P., Palmer, T., Haberland, V., Smith, G. D., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.10.244293 · Cited by 946
Mendelian Randomization: Concepts and Scope
Richmond, R. C., & Davey Smith, G. (2022) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a040501 · Cited by 841
Using Mendelian Randomization to Improve the Design of Randomized Trials
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Metadata
- Authors
- Davey Smith, G., Holmes, M. V., Davies, N. M., & Ebrahim, S.
- Affiliations
- University of Oxford (GB)
- University of Bristol (GB)
- London School of Hygiene & Tropical Medicine (GB)
- Venue
- European Journal of Epidemiology
- Published
- 2020-02
- Volume
- 35
- Issue
- 2
- Pages
- 99-111
- ISSN
- 0393-2990 (ISSN-L)
- 1573-7284
- PMC
- PMC7125255
- OpenAlex
- W3012912937
- Cited by
- 287
- References
- 118
- Citations by year
- 2026: 19 · 2025: 44 · 2024: 112 · 2023: 36 · 2022: 37 · 2021: 30 · 2020: 8
- FWCI
- 16.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- European Journal of Epidemiology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Explore Bristol Research (acceptedVersion, cc-by)
- Funders
- Medical Research Council (MC_UU_00011/1)
- British Heart Foundation (FS/18/23/33512)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- Mendelian randomization, Mendel's laws, causal inference, observational data, nomenclature, alcohol consumption, cardiovascular disease, population stratification, confounding, weak instrument bias, pleiotropy
- MeSH terms
- Cardiovascular Diseases, Humans, Genetic Variation, Molecular Epidemiology, Mendelian Randomization Analysis, Genetic Pleiotropy
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