The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
Genetic analyses identify widespread sex-differential participation bias
Open accessPublished version of a preprint
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.
Overview
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
Verification
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?
In the citing paper
“factors correlated with participation in research50.”
From Genetic correlates of phenotypic heterogeneity in autism (2022) · cites this paper as [50]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationSudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001779 · Cited by 12,728
The mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434
Self-citationThe UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876
Self-citationThe MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Self-citationGenetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Self-citationAn atlas of genetic correlations across human diseases and traits
ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255
Self-citationFunctional mapping and annotation of genetic associations with FUMA
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083
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
Genome-wide association studies
Uffelmann, E., Huang, Q. Q., Munung, N. S., de Vries, J., Okada, Y., Martin, A. R., Martin, H. C., Lappalainen, T., & Posthuma, D. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00056-9 · Cited by 1,849
Self-citationCollider bias undermines our understanding of COVID-19 disease risk and severity
Griffith, G. J., Morris, T. T., Tudball, M. J., Herbert, A., Mancano, G., Pike, L., Sharp, G. C., Sterne, J., Palmer, T. M., Davey Smith, G., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19478-2 · Cited by 826
Participation bias in the UK Biobank distorts genetic associations and downstream analyses
Schoeler, T., Speed, D., Porcu, E., Pirastu, N., Pingault, J., & Kutalik, Z. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01579-9 · Cited by 437
Self-citationJones, G., Trajanoska, K., Santanasto, A. J., Stringa, N., Kuo, C., Atkins, J. L., Lewis, J. R., Duong, T., Hong, S., Biggs, M. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-20918-w · Cited by 228
Metadata
- 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
- 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 ›
Are you an author, or do you see a problem with this page? Request a review
