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Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences

Author

Listed:
  • Richard Karlsson Linnér

    (University Amsterdam)

  • Pietro Biroli

    (University of Zurich)

  • Edward Kong

    (Harvard University)

  • S. Fleur W. Meddens

    (University Amsterdam)

  • Robee Wedow

    (University of Colorado, Boulder)

  • Mark Alan Fontana

    (Center for the Advancement of Value in Musculoskeletal Care, Hospital for Special Surgery)

  • Maël Lebreton

    (University of Amsterdam)

  • Abdel Abdellaoui

    (Vrije Universiteit Amsterdam)

  • Anke R. Hammerschlag

    (University Amsterdam)

  • Michel G. Nivard

    (Vrije Universiteit Amsterdam)

  • Aysu Okbay

    (Vrije Universiteit Amsterdam)

  • Cornelius A. Rietveld

    (Erasmus University)

  • Pascal N. Timshel

    (University of Copenhagen)

  • Stephen P. Tino

    (University of Toronto)

  • Maciej Trzaskowski

    (University of Queensland)

  • Ronald de Vlaming

    (Vrije Universiteit Amsterdam)

  • Christian L. Zünd

    (University of Zurich)

  • Yanchun Bao

    (University of Essex)

  • Laura Buzdugan

    (ETH Zurich)

  • Ann H. Caplin

    (Stuyvesant High School)

  • Chia-Yen Chen

    (Massachusetts General Hospital)

  • Peter Eibich

    (University of Oxford)

  • Pierre Fontanillas

    (23andMe)

  • Juan R. Gonzalez

    (Barcelona Institute for Global Health)

  • Peter K. Joshi

    (University of Edinburgh)

  • Ville Karhunen

    (University of Oulu,)

  • Aaron Kleinman

    (23andMe)

  • Remy Z. Levin

    (University of California San Diego)

  • Christina M. Lill

    (University of Lübeck)

  • Gerardus A. Meddens

    (Team Loyalty BV)

  • Gerard Muntané

    (Universitat Pompeu Fabra)

  • Sandra Sanchez-Roige

    (University of California San Diego)

  • Frank J. van Rooji

    (Erasmus University)

  • Erdogan Taskesen

    (Vrije Universiteit Amsterdam)

  • Yang Wu

    (University of Queensland)

  • Futao Zhang

    (University of Queensland)

  • 23andMe Research Team

    (23andMe)

  • eQTLgen Consortium

    (eQTLgen Consortium)

  • International Cannabis Consortium

    (International Cannabis Consortium)

  • Psychiatric Genomics Consortium

    (Psychiatric Genomics Consortium)

  • Social Science Genetic Association Consortium

    (Social Science Genetic Association Consortium)

  • Adam Auton

    (23andMe)

  • Jason D. Boardman

    (University of Colorado Boulder)

  • David W. Clark

    (University of Edinburgh)

  • Andrew Conlin

    (Oulu Business School)

  • Conor C. Dolan

    (Vrije Universiteit Amsterdam)

  • Urs Fischbacher

    (University of Konstanz)

  • Patrick J. F. Groenen

    (Erasmus University)

  • Kathleen Mullan Harris

    (University of North Carolina at Chapel Hill)

  • Gregor Hasler

    (University of Bern)

  • Albert Hofman

    (Erasmus Medical Center)

  • Mohammad A. Ikram

    (Erasmus Medical Center)

  • Sonia Jain

    (University of California San Diego)

  • Robert Karlsson

    (Karolinska Institutet)

  • Ronald C. Kessler

    (Harvard Medical School)

  • Maarten Kooyman

    (SURFsara)

  • James MacKillop

    (McMaster University)

  • Minna Männikkö

    (University of Oulu)

  • Carlos Morcillo-Suarez

    (Universitat Pompeu Fabra)

  • Matthew B. McQueen

    (University of Colorado Boulder)

  • Klaus M. Schmidt

    (University of Munich)

  • Melissa C. Smart

    (University of Essex)

  • Matthias Sutter

    (University of Cologne)

  • A. Roy Thurik

    (Erasmus University)

  • Andre G. Uitterlinden

    (Erasmus Medical Center)

  • Jon White

    (University College London)

  • Harriet de Wit

    (University of Chicago)

  • Jian Yang

    (University of Queensland)

  • Lars Bertram

    (University of Lübeck)

  • Dorret Boomsma

    (Vrije Universiteit Amsterdam)

  • Tõnu Esko

    (University of Tartu)

  • Ernst Fehr

    (University of Zurich)

  • David A. Hinds

    (23andMe)

  • Magnus Johannesson

    (Stockholm School of Economics)

  • Meena Kumari

    (University of Essex)

  • David Laibson

    (Harvard University)

  • Patrik K. E. Magnusson

    (Karolinska Institutet)

  • Michelle N. Meyer

    (Geisinger Health System)

  • Arcadi Navarro

    (Universitat Pompeu Fabra)

  • Abraham A. Palmer

    (University of California San Diego)

  • Tune H. Pers

    (University of Copenhagen)

  • Danielle Posthuma

    (Vrije Universiteit Amsterdam)

  • Daniel Schunk

    (Johannes Gutenberg University)

  • Murray B. Stein

    (University of California San Diego)

  • Rauli Svento

    (University of Oulu)

  • Henning Tiemeier

    (Erasmus Medical Center)

  • Paul R. H. J. Timmers

    (University of Edinburgh)

  • Patrick Turley

    (Massachusetts General Hospital)

  • Robert J. Ursano

    (University Health Science)

  • Gert G. Wagner

    (Max Planck Institute for Human Development)

  • James F. Wilson

    (University of Edinburgh)

  • Jacob Gratten

    (University of Queensland)

  • James J. Lee

    (University of Minnesota Twin Cities)

  • David Cesarini

    (New York University)

  • Daniel Benjamin

    (University of Southern California)

  • Philipp Koellinger

    (University of Amsterdam)

  • Jonathan Beauchamp

    (University of Toronto)

Abstract

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

Suggested Citation

  • Richard Karlsson Linnér & Pietro Biroli & Edward Kong & S. Fleur W. Meddens & Robee Wedow & Mark Alan Fontana & Maël Lebreton & Abdel Abdellaoui & Anke R. Hammerschlag & Michel G. Nivard & Aysu Okba, 2018. "Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences," Working Papers 2018-087, Human Capital and Economic Opportunity Working Group.
    • Handle: RePEc:hka:wpaper:2018-087
    Note: HI,ECI
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    File URL: http://humcap.uchicago.edu/RePEc/hka/wpaper/Linner_Biroli_Kong_etal_2018_genome-wide-association-analyses_supplemental-information.pdf
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    File URL: http://humcap.uchicago.edu/RePEc/hka/wpaper/Linner_Biroli_Kong_etal_2018_genome-wide-association-analyses_tables.xlsx
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    References listed on IDEAS

    as
    1. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    2. Falk, A. & Becker, A. & Dohmen, T.J. & Enke, B. & Huffman, D. & Sunde, U., 2015. "The nature and predictive power of preferences: Global evidence," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson, 2017. "The psychometric and empirical properties of measures of risk preferences," Journal of Risk and Uncertainty, Springer, vol. 54(3), pages 203-237, June.
    4. David Cesarini & Christopher T. Dawes & Magnus Johannesson & Paul Lichtenstein & Björn Wallace, 2009. "Genetic Variation in Preferences for Giving and Risk Taking," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(2), pages 809-842.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Vikesh Amin & Jere R. Behrman & Jason M. Fletcher & Carlos A. Flores & Alfonso Flores‐Lagunes & Hans‐Peter Kohler, 2021. "Genetic risks, adolescent health, and schooling attainment," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2905-2920, November.
    3. Silvia Angerer & E. Glenn Dutcher & Daniela Glätzle-Rützler & Philipp Lergetporer & Matthias Sutter, 2021. "The Formation of Risk Preferences through Small-Scale Events," CESifo Working Paper Series 9270, CESifo.
    4. Jason M. Fletcher & Qiongshi Lu, 2021. "Health policy and genetic endowments: Understanding sources of response to Minimum Legal Drinking Age laws," Health Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 194-203, January.
    5. Andrew E. Clark & Conchita D'Ambrosio & Simone Ghislandi & Anthony Lepinteur & Giorgia Menta, 2021. "Maternal depression and child human capital: a genetic instrumental-variable approach," CEP Discussion Papers dp1749, Centre for Economic Performance, LSE.
    6. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2022.
    7. Zimmermann, Klaus F. & Chowdhury, Shyamal & Sutter, Matthias, 2020. "Economic preferences across generations and family clusters: A large-scale experiment," CEPR Discussion Papers 14998, C.E.P.R. Discussion Papers.
    8. Nicos Nicolaou & Scott Shane, 2019. "Common genetic effects on risk-taking preferences and choices," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 261-279, December.
    9. Atticus Bolyard & Peter Savelyev, 2021. "Understanding the Educational Attainment Polygenic Score and its Interactions with SES in Determining Health in Young Adulthood," Working Papers 2021-026, Human Capital and Economic Opportunity Working Group.
    10. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    11. Andrea G Allegrini & Ville Karhunen & Jonathan R I Coleman & Saskia Selzam & Kaili Rimfeld & Sophie von Stumm & Jean-Baptiste Pingault & Robert Plomin, 2020. "Multivariable G-E interplay in the prediction of educational achievement," PLOS Genetics, Public Library of Science, vol. 16(11), pages 1-20, November.
    12. Barban, Nicola & De Cao, Elisabetta & Francesconi, Marco, 2021. "Gene‐Environment Effects on Female Fertility," CINCH Working Paper Series (since 2020) 74910, Duisburg-Essen University Library, DuEPublico.

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    More about this item

    Keywords

    GWAS; genome-wide association studies; risk taking; risk tolerance;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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