Department of Economics and Business Economics

Genetic analyses identify widespread sex-differential participation bias

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Nicola Pirastu, Edinburgh University, Edinburgh
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  • Mattia Cordioli, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland.
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  • Priyanka Nandakumar, Parkinson's Institute, Sunnyvale, California, USA.
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  • Gianmarco Mignogna, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland.
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  • Abdel Abdellaoui, Academic Centre for Dentistry Amsterdam, University of Amsterdam and and VU University Amsterdam, Amsterdam
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  • Benjamin Hollis, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom;
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  • Masahiro Kanai, Massachusetts General Hospital, Boston, Massachusetts, USA.
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  • Veera M Rajagopal, iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research
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  • Pietro Della Briotta Parolo, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland.
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  • Nikolas Baya, Massachusetts General Hospital, Boston, Massachusetts, USA.
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  • Caitlin E Carey, Massachusetts General Hospital, Boston, Massachusetts, USA.
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  • Juha Karjalainen, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland.
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  • Thomas D Als
  • Matthijs D Van der Zee, Institute for Brain and Behavior Amsterdam & Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, van der Boechorststraat 9, 1081BT, Amsterdam, The Netherlands; Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK.
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  • Felix R Day, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom;
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  • Ken K Ong, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom;
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  • Takayuki Morisaki, Univ Tokyo, University of Tokyo, IPMU
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  • Eco de Geus, Institute for Brain and Behavior Amsterdam & Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, van der Boechorststraat 9, 1081BT, Amsterdam, The Netherlands; Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK.
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  • Rino Bellocco, Univ Milano Bicocca, University of Milano-Bicocca, Dipartimento Sci Mat
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  • Yukinori Okada, Osaka University Graduate School of Medicine
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  • Anders D Børglum
  • Peter Joshi, Edinburgh University, Edinburgh
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  • Adam Auton, Parkinson's Institute, Sunnyvale, California, USA.
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  • David Hinds, Parkinson's Institute, Sunnyvale, California, USA.
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  • Benjamin M Neale, Massachusetts General Hospital, Boston, Massachusetts, USA.
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  • Raymond K Walters, Massachusetts General Hospital, Boston, Massachusetts, USA.
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  • Michel G Nivard, Institute for Brain and Behavior Amsterdam & Amsterdam Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, van der Boechorststraat 9, 1081BT, Amsterdam, The Netherlands; Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK.
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  • John R B Perry, Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom; Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom;
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  • Andrea Ganna, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland.
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  • FinnGen Study
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  • 23andMe Research Team
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  • iPSYCH Consortium

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.

Original languageEnglish
JournalNature Genetics
Volume53
Issue5
Pages (from-to)663-671
Number of pages9
ISSN1061-4036
DOIs
Publication statusPublished - May 2021

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