Abstract

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

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23andMe Research Team:

Michelle Agee12, Babak Alipanahi12, Adam Auton12, Robert K. Bell12, Katarzyna Bryc12, Sarah L. Elson12, Pierre Fontanillas12, Nicholas A. Furlotte12, David A. Hinds12, Bethann S. Hromatka12, Karen E. Huber12, Aaron Kleinman12, Nadia K. Litterman12, Matthew H. McIntyre12, Joanna L. Mountain12, Carrie A. M. Northover12, J. Fah Sathirapongsasuti12, Olga V. Sazonova12, Janie F. Shelton12, Suyash Shringarpure12, Chao Tian12, Joyce Y. Tung12, Vladimir Vacic12, Catherine H. Wilson12 and Steven J. Pitts12

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Acknowledgements

We thank J. Beauchamp, P. Koellinger, Ö. Sandewall, C. Shulman, and R. de Vlaming for helpful comments and P. Bowers, E. Kong, T. Kundu, S. Lee, H. Li, R. Li, and R. Royer for research assistance. This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC). The study was supported by the Ragnar Söderberg Foundation (E9/11, M.J.; E42/15, D.C.), the Swedish Research Council (421-2013-1061, M.J.), the Jan Wallander and Tom Hedelius Foundation (M.J.), an ERC Consolidator Grant (647648 EdGe, P. Koellinger), the Pershing Square Fund of the Foundations of Human Behavior (D.L.), the National Science Foundation’s Graduate Research Fellowship Program (DGE 1144083, R.W.), and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, and T32-AG000186-23 to D. Wise at NBER; P30-AG012810 (D.L.) to NBER; R01-AG042568-02 (D.J.B.) to the University of Southern California; and 1R01-MH107649-03 (B.M.N.), 1R01-MH101244-02 (B.M.N.), and 5U01-MH109539-02 (B.M.N.) to the Broad Institute at Harvard and MIT. This research has also been conducted using the UK Biobank Resource under application number 11425. We thank the research participants and employees of 23andMe for making this work possible. We also thank K. Mullan Harris and Add Health for early access to the data used in our replication and prediction analyses. A full list of acknowledgements is provided in the Supplementary Note.

Author information

Author notes

    • Patrick Turley
    • , David Cesarini
    • , Benjamin M. Neale
    •  & Daniel J. Benjamin

    These authors contributed equally to this work.

  1. A list of members and affiliations appears at the end the paper.

  2. A list of members and affiliations appears in the Supplementary Note.

  3. Patrick Turley, David Cesarini, Benjamin M. Neale and Daniel J. Benjamin contributed equally to this work.

Affiliations

  1. Broad Institute, Cambridge, MA, USA

    • Patrick Turley
    • , Raymond K. Walters
    •  & Benjamin M. Neale
  2. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Cambridge, MA, USA

    • Patrick Turley
    • , Raymond K. Walters
    •  & Benjamin M. Neale
  3. Department of Economics, Harvard University, Cambridge, MA, USA

    • Omeed Maghzian
    •  & David Laibson
  4. Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    • Aysu Okbay
  5. Department of Psychology, University of Minnesota, Minneapolis, MN, USA

    • James J. Lee
  6. Hospital for Special Surgery, New York, NY, USA

    • Mark Alan Fontana
  7. Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA

    • Tuan Anh Nguyen-Viet
    •  & Daniel J. Benjamin
  8. Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA

    • Robbee Wedow
  9. Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA

    • Robbee Wedow
  10. Department of Sociology, University of Colorado Boulder, Boulder, CO, USA

    • Robbee Wedow
  11. Department of Sociology, Harvard University, Cambridge, MA, USA

    • Meghan Zacher
  12. 23andMe, Inc., Mountain View, CA, USA

    • Nicholas A. Furlotte
    • , Michelle Agee
    • , Babak Alipanahi
    • , Adam Auton
    • , Robert K. Bell
    • , Katarzyna Bryc
    • , Sarah L. Elson
    • , Pierre Fontanillas
    • , Nicholas A. Furlotte
    • , David A. Hinds
    • , Bethann S. Hromatka
    • , Karen E. Huber
    • , Aaron Kleinman
    • , Nadia K. Litterman
    • , Matthew H. McIntyre
    • , Joanna L. Mountain
    • , Carrie A. M. Northover
    • , J. Fah Sathirapongsasuti
    • , Olga V. Sazonova
    • , Janie F. Shelton
    • , Suyash Shringarpure
    • , Chao Tian
    • , Joyce Y. Tung
    • , Vladimir Vacic
    • , Catherine H. Wilson
    •  & Steven J. Pitts
  13. Institutionen för Medicinsk Epidemiologi och Biostatistik, Karolinska Institutet, Stockholm, Sweden

    • Patrik Magnusson
  14. Department of Government, Uppsala Universitet, Uppsala, Sweden

    • Sven Oskarsson
  15. Department of Economics, Stockholm School of Economics, Stockholm, Sweden

    • Magnus Johannesson
  16. Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia

    • Peter M. Visscher
  17. Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia

    • Peter M. Visscher
  18. National Bureau of Economic Research, Cambridge, MA, USA

    • David Laibson
    • , David Cesarini
    •  & Daniel J. Benjamin
  19. Department of Economics and Center for Experimental Social Science, New York University, New York, NY, USA

    • David Cesarini
  20. Institutet för Näringslivsforskning, Stockholm, Sweden

    • David Cesarini
  21. Department of Economics, University of Southern California, Los Angeles, CA, USA

    • Daniel J. Benjamin

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Consortia

  1. 23andMe Research Team

  1. Social Science Genetic Association Consortium

    Contributions

    B.M.N., D.J.B., D.C., and P.T. oversaw the study. The theory underlying MTAG was conceived of and developed by P.T., with contributions from B.M.N., D.J.B., D.C., D.L., O.M., P.M.V., and R.K.W. O.M., P.T., and R.K.W. performed the simulations and developed the MTAG software. P.T. and P.M.V. designed the analyses comparing the observed MTAG gains to theoretical expectations. A.O., M.Z., R.W., M.A.F., O.M., and T.A.N.-V. had major roles in data analyses. J.J.L. designed and executed the bioinformatics analyses. N.A.F. conducted the analysis of the data from 23andMe. D.J.B., D.C., and P.T. coordinated the writing of the manuscript. P.M., S.O., and M.J. also contributed to the writing. All authors provided input and revisions for the final manuscript.

    Competing interests

    The authors declare no competing financial interests.

    Corresponding authors

    Correspondence to Patrick Turley or David Cesarini or Benjamin M. Neale or Daniel J. Benjamin.

    Supplementary information

    1. Supplementary Text and Figures

      Supplementary Figures 1–13, Supplementary Tables 4, 6–8, 10–13, 15–18, 30 and 31, and Supplementary Note

    2. Life Sciences Reporting Summary

    3. Supplementary Tables

      Supplementary Tables 1–3, 5, 9, 14 and 19–29.