Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
Open accessPublished version of a preprint
Abstract
Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Within-family genetic association estimates, such as those obtained from samples of siblings, can provide less biased estimates of direct genetic effects because they are unlikely to be affected by demographic and indirect genetic effects of parents.
“Within-family genetic association estimates, such as those obtained from samples of siblings, can provide less biased estimates of direct genetic effects because they are unlikely to be affected by demographic and indirect genetic effects of parents7,17,30–34.”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [7]
GWAS associations for some phenotypes estimated from samples of unrelated individuals also capture effects of demography (assortative mating and population stratification) and indirect genetic effects of relatives.
“However, there is growing evidence that GWAS associations for some phenotypes estimated from samples of unrelated individuals also capture effects of demography7,8 (assortative mating9–11 and population stratification12) and indirect genetic effects of relatives13–19 (Fig. 1).”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [7]
WS-MR is largely robust against demographic and indirect genetic effects that could distort estimates from nonfamily designs.
“WS-MR is largely robust against demographic and indirect genetic effects that could distort estimates from nonfamily designs7,25.”
From Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects (2022) · cites this paper as [7]
As a general rule, if the first-stage F-statistic is greater than 10, the level of weak instrument bias is small.
“As a general rule, if the first-stage F-statistic is greater than 10, the level of this bias is small.58,59”
From Mendelian randomization (2022) · cites this paper as [59]
Pre-registration of study protocols has not been widely adopted in observational epidemiology, although it could in principle be applied and help protect against bias such as publication bias against null results or findings that do not fit the anticipated conclusion.
“Pre-registration of study protocols has not been widely adopted in observational epidemiology, although it could in principle be applied and help protect against bias, such as publication bias against null results or findings that do not fit with the anticipated conclusion.161,162”
From Mendelian randomization (2022) · cites this paper as [161]
A suite of sensitivity analyses can be used to test for evidence of unbalanced (directional) horizontal pleiotropy.
“A suite of sensitivity analyses can be used to test for evidence of unbalanced (directional) horizontal pleiotropy 37 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [37]
Horizontal pleiotropy needs to be formally evaluated, e.g. through robust MR approaches.
“Need to formally evaluate, e.g. through robust MR approaches 37”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [37]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 84 · Cited by 402
Research works printed but not linked: 1
- [73]Heilbron, K. et al. Unhealthy Behaviours and Parkinsons Disease: A Mendelian Randomisation Study. 10.1101/2020.03.25.20039230 http://medrxiv.org/lookup/doi/10.1101/2020.03.25.20039230 (2020). PMC8609708 34275906 · DOI
- Authors
- Brumpton, B., Sanderson, E., Heilbron, K., Hartwig, F. P., Harrison, S., Vie, G. Å., Cho, Y., Howe, L. D., Hughes, A., Boomsma, D. I., Havdahl, A., Hopper, J., Neale, M., Nivard, M. G., Pedersen, N. L., Reynolds, C. A., Tucker-Drob, E. M., Grotzinger, A., Howe, L., Morris, T., Li, S., The Within-family Consortium, Brumpton, B., Sanderson, E., Heilbron, K., Hartwig, F. P., Harrison, S., Vie, G. Å., Cho, Y., Howe, L. D., Hughes, A., Boomsma, D. I., Havdahl, A., Hopper, J., Neale, M., Nivard, M. G., Pedersen, N. L., Reynolds, C. A., Tucker-Drob, E. M., Grotzinger, A., Howe, L., Morris, T., Li, S., Auton, A., Windmeijer, F., Chen, W.-M., Bjørngaard, J. H., Hveem, K., Willer, C., Evans, D. M., Kaprio, J., Smith, G. D., Åsvold, B. O., Hemani, G., Davies, N. M., The 23andMe Research Team, Heilbron, K., Auton, A., Auton, A., Windmeijer, F., Chen, W.-M., Bjørngaard, J. H., Hveem, K., Willer, C., Evans, D. M., Kaprio, J., Davey Smith, G., Åsvold, B. O., Hemani, G., & Davies, N. M.
- ORCID
- Davey Smith, George
- Venue
- Nature Communications
- Published
- 2020-07-14
- Volume
- 11
- Issue
- 1
- Pages
- 3519-3519
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7360778
- OpenAlex
- W3034541161
- Cited by
- 402
- References
- 84
- Citations by year
- 2026: 36 · 2025: 53 · 2024: 91 · 2023: 53 · 2022: 60 · 2021: 64 · 2020: 28 · 2019: 17
- FWCI
- 30.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion, cc-by)
- VU Research Portal (publishedVersion, other-oa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Työväentutkimus Vuosikirja (submittedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Apollo (cc-by)
- Apollo
- Funders
- Stiftelsen Kristian Gerhard Jebsen
- Université Laval
- Norges Teknisk-Naturvitenskapelige Universitet
- Wellcome Trust (MC_UU_00011/1, WT104150, MC_UU_12013/1, 208806/Z/17/Z, MC_UU_12013/9)
- School of Public Health, University of Michigan
- QIMR Berghofer Medical Research Institute
- University of Exeter
- University of Bristol (MC_UU_12013/1, MC_UU_00011/1, MC_UU_12013/9, MC_UU_12013, MR/M020894/1)
- University of Melbourne
- Academy of Finland (308248, 312073, 308 248, #312073)
- Jacobs Foundation
- Istituto Superiore di Sanità
- Karolinska Institutet
- Helse Midt-Norge
- Universidad de Murcia
- Norges Forskningsråd (250335, 295989, ES/N000757/1)
- St. Olavs Hospital Universitetssykehuset i Trondheim
- National Institutes of Health
- Fakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige Universitet
- Medical Research Council (MC_UU_12013/1, MC_UU_12013/9, MC_PC_14135, MC_PC_12026, MC_UU_12013, MC_UU_00017/1, MR/M020894, MC_UU_00011/2, R01AG054628, MCUU12013/1, MR/M020894/1, MC_PC_17228, MC_UU_00011/1, MC_PC_13049, MC_UU_00011, MC_UU_12013/9)
- Economic and Social Research Council (ES/N000757/1, MC_UU_00011/1, ES/S011021/1)
- National Health and Medical Research Council (250335, 1137714, MC_UU_00011/1)
- Faculty of Medicine and Health, University of Sydney
- Norwegian Institute of Public Health
- National Institute on Aging (R01AG060470, R01AG059329, RF1AG058068, R01AG046938, R01AG054628, R01AG018386)
- National Heart, Lung, and Blood Institute (R01HL105756)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD083613, P2CHD042849)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
- Keywords
- family influence, population stratification, assortative mating, confounding, siblings, educational attainment, height, body mass index, diabetes mellitus, blood pressure, genetic epidemiology
- MeSH terms
- Epidemiology, Female, Humans, Male, Risk Factors, Body Mass Index, Polymorphism, Single Nucleotide, Mendelian Randomization Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
