Bias in Mendelian randomization due to assortative mating
Open accessAbstract
Mendelian randomization (MR) has been increasingly used to strengthen causal inference in observational epidemiology. Methodological developments in the field allow detecting and/or adjusting for different potential sources of bias, mainly bias due to horizontal pleiotropy (or “off‐target” genetic effects). Another potential source of bias is nonrandom matching between spouses (i.e., assortative mating). In this study, we performed simulations to investigate the bias caused in MR by assortative mating. We found that bias can arise due to either cross‐trait assortative mating (i.e., assortment on two phenotypes, such as highly educated women selecting taller men) or single‐trait assortative mating (i.e., assortment on a single phenotype), even if the exposure and outcome phenotypes are not the phenotypes under assortment. The simulations also indicate that bias due to assortative mating accumulates over generations and that MR methods robust to horizontal pleiotropy are also affected by this bias. Finally, we show that genetic data from mother–father–offspring trios can be used to detect and correct for this bias.
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There is clear evidence from both MR and the natural experiment of an increase in the school leaving age that an increase in the number of years in education has a causal protective effect on health behaviours such as smoking.
“For example, there is clear evidence from both MR and the natural experiment of an increase in the school leaving age that an increase in the number of years in education has a causal protective effect on health behaviours such as smoking.156–160”
From Mendelian randomization (2022) · cites this paper as [160]
Simulations might also help understand the plausible size and direction of bias induced by assortative mating, dynastic effects, and time varying effects, if deemed relevant.
“Simulations might also help understand the plausible size and direction of bias induced by assortative mating,62 dynastic effects,9 63 and time varying effects,77 if deemed relevant.”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [62]
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Changing Patterns of Assortative Mating for Educational, Substance Use, and Anthropometric Traits
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- Authors
- Hartwig, F. P., Davies, N. M., & Davey Smith, G.
- Affiliations
- Universidade Federal de Pelotas (BR)
- University of Bristol (GB)
- Medical Research Council Integrative Epidemiology Unit University of Bristol Bristol UK
- Corresponding author
- Hartwig, Fernando Pires
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2018-07-03
- Volume
- 42
- Issue
- 7
- Pages
- 608-620
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- PMC
- PMC6221130
- OpenAlex
- W2810240697
- Cited by
- 99
- References
- 35
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 15 · 2023: 17 · 2022: 14 · 2021: 13 · 2020: 9 · 2019: 13 · 2018: 3 · 2017: 1
- FWCI
- 5.83
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Genetic Epidemiology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (submittedVersion, cc-by)
- Explore Bristol Research (submittedVersion, cc-by)
- Funders
- Medical Research Council (MC_UU_12013/1, MC_UU_12013/9)
- Wellcome Trust (102215/2/13/2)
- 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, assortative mating, bias, horizontal pleiotropy, causal inference, simulation study
- MeSH terms
- Body Height, Child, Computer Simulation, Fathers, Female, Genotype, Humans, Male, Models, Genetic, Mothers, Phenotype, Regression Analysis, Reproduction, Bias, Least-Squares Analysis, Mendelian Randomization Analysis
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