Genetic analyses identify widespread sex-differential participation bias
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Abstract
Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index–increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio = 1.02, P = 4.4 × 10−36). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow. Genetic analyses identify widespread sex-differential participation bias in population-based studies and show how this bias can lead to incorrect inferences. These findings highlight new challenges for association studies as sample sizes continue to grow.
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Midparental PGS scores, family income, and parent education are factors correlated with participation in research.
“factors correlated with participation in research50.”
From Genetic correlates of phenotypic heterogeneity in autism (2022) · cites this paper as [50]
A key limiting factor for within-family MR is the lack of available data and the low power of these studies as a result.
“A key limiting factor for within-family MR is the lack of available data and the low power of these studies as a result; however, a GWAS of family data for a range of phenotypes has recently been published, enabling further within-family MR in the future.169”
From Mendelian randomization (2022) · cites this paper as [169]
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Pervasive biases in proxy GWAS based on parental history of Alzheimer’s diseasePreprint
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- Authors
- Pirastu, N., Cordioli, M., Nandakumar, P., Mignogna, G., Abdellaoui, A., Hollis, B., Kanai, M., Rajagopal, V. M., Parolo, P. D. B., Baya, N., Carey, C. E., Karjalainen, J., Als, T. D., Van der Zee, M. D., Day, F. R., Ong, K. K., Study, F., 23andMe Research Team, Agee, M., Aslibekyan, S., Bell, R. K., Bryc, K., Clark, S. K., Elson, S. L., Fletez-Brant, K., Fontanillas, P., Furlotte, N. A., Gandhi, P. M., Heilbron, K., Hicks, B., Huber, K. E., Jewett, E. M., Jiang, Y., Kleinman, A., Lin, K.-H., Litterman, N. K., Luff, M. K., McIntyre, M. H., McManus, K. F., Mountain, J. L., Mozaffari, S. V., Noblin, E. S., Northover, C. A. M., O’Connell, J., Petrakovitz, A. A., Pitts, S. J., Poznik, G. D., Sathirapongsasuti, J. F., Shelton, J. F., Shringarpure, S., Tian, C., Tung, J. Y., Tunney, R. J., Vacic, V., Wang, X., Zare, A., iPSYCH Consortium, Mortensen, P. B., Mors, O., Werge, T., Nordentoft, M., Hougaard, D. M., Bybjerg-Grauholm, J., Bækvad-Hansen, M., Morisaki, T., de Geus, E., Bellocco, R., Okada, Y., Børglum, A. D., Joshi, P., Auton, A., Hinds, D., Neale, B. M., Walters, R. K., Nivard, M. G., Perry, J. R. B., & Ganna, A.
- Affiliations
- University of Edinburgh (GB)
- University of Helsinki (FI)
- 23andMe (United States) (US)
- Amsterdam UMC Location University of Amsterdam (NL)
- University of Cambridge (GB)
- Broad Institute (US)
- Aarhus University (DK)
- Karolinska Institutet (SE)
- Aarhus University Hospital (DK)
- Sankt Hans Hospital (DK)
- University of Copenhagen (DK)
- Statens Serum Institut (DK)
- BioBank Japan (JP)
- Corresponding author
- Perry, John R. B.
- Ganna, Andrea
- ORCID
- Pirastu, Nicola
- Cordioli, Mattia
- Mignogna, Gianmarco
- Abdellaoui, Abdel
- Kanai, Masahiro
- Rajagopal, Veera M.
- Baya, Nikolas
- Carey, Caitlin E.
- Karjalainen, Juha
- Als, Thomas D.
- Van der Zee, Matthijs D.
- Day, Felix R.
- Ong, Ken K.
- Aslibekyan, Stella
- Bryc, Katarzyna
- Clark, Sarah K.
- Elson, Sarah L.
- Fontanillas, Pierre
- Furlotte, Nicholas A.
- Gandhi, Pooja M.
- Heilbron, Karl
- Jewett, Ethan M.
- Jiang, Yunxuan
- Litterman, Nadia K.
- Luff, Marie K.
- McIntyre, Matthew H.
- McManus, Kimberly F.
- Mountain, Joanna L.
- Mozaffari, Sahar V.
- Pitts, Steven J.
- Poznik, G. David
- Sathirapongsasuti, J. Fah
- Shringarpure, Suyash
- Tung, Joyce Y.
- Vacic, Vladimir
- Wang, Xin
- Mortensen, Preben Bo
- Mors, Ole
- Werge, Thomas
- Nordentoft, Merete
- Hougaard, David M.
- Morisaki, Takayuki
- Bellocco, Rino
- Okada, Yukinori
- Børglum, Anders D.
- Joshi, Peter
- Auton, Adam
- Hinds, David
- Neale, Benjamin M.
- Walters, Raymond K.
- Nivard, Michel G.
- Perry, John R. B.
- Ganna, Andrea
- Venue
- Nature Genetics
- Published
- 2021-04-22
- Volume
- 53
- Issue
- 5
- Pages
- 663-671
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC7611642
- OpenAlex
- W3152758353
- Cited by
- 251
- References
- 74
- Citations by year
- 2026: 25 · 2025: 29 · 2024: 53 · 2023: 54 · 2022: 55 · 2021: 21 · 2020: 14
- FWCI
- 29.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion, other-oa)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, cc-by)
- VU Research Portal (acceptedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- BOA (University of Milano-Bicocca) (submittedVersion, other-oa)
- Työväentutkimus Vuosikirja (submittedVersion, other-oa)
- Pure Amsterdam UMC (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Pfizer
- AstraZeneca
- GlaxoSmithKline
- Sanofi
- Biogen
- Celgene
- Stichting Volksbond Rotterdam
- Maze Therapeutics
- ZonMw (849200011, 531003014)
- Academy of Finland (323116)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (191G.030, VI.Veni.191G.030, 849200011)
- Lundbeckfonden (R155-2014-1724, R302-2018-2155, R248‐2017‐2003)
- Jacobs Foundation
- Business Finland (UH4386/31/2016, 4685/31/2016, 4386/31/2016, HUS 4685/31/2016 and UH 4386/31/2016, HUS 4685/31/2016)
- Genentech
- Medical Research Council (MC_UU_12015, MC_UU_12015/2, MC_PC_17228)
- Janssen Biotech
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- FTO, body mass index, complex traits, sample size
- MeSH terms
- Adult, Chromosomes, Human, Female, United Kingdom, Humans, Male, Sex Characteristics, Bias, Artifacts, Biological Specimen Banks, Sample Size, Polymorphism, Single Nucleotide, Inheritance Patterns, Genome-Wide Association Study, Genetic Loci
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 ›
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