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A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci

Molecular Psychiatry volume 27, pages 2264–2272 (2022)Cite this article

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Abstract

To identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR (N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 (p = 3.64 × 10−9) and 1 (p = 3.69 × 10−8). A strong pan-ancestry signal at the Dopamine Receptor D2 locus (p = 1.77 × 10−7) was also identified and subsequently replicated in a large, independent international civilian cohort (p = 7.97 × 10−4). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

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Fig. 1: Manhattan plots summarizing the GWAS results for the pan-ancestry meta-analysis and ancestry-specific GWAS.

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Code availability

Please note that the code used to phenotype suicide attempts and suicidal ideation from VA EHR data in the present study are available through the VA’s Centralized Interactive Phenomics Resource (CIPHER) https://www.research.va.gov/programs/cipher.cfm (VA network access only).

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Acknowledgements

This research is based on data from the Million Veteran Program, Office of Research and Development (ORD), Veterans Health Administration (VHA), and was supported by award #I01CX001729 from the Clinical Science Research and Development (CSR&D) Service of VHA ORD. J.C. Beckham was also supported by a Senior Research Career Scientist Award (#lK6BX003777) from CSR&D. Niamh Mullins was supported by a NARSAD Young Investigator Award from the Brain & Behavior Research Foundation. This publication does not represent the views of the Department of Veteran Affairs or the United States Government. We also thank and acknowledge MVP, the MVP Suicide Exemplar Workgroup, and the ISGC for their contributions to this manuscript. A complete listing of contributors from the MVP, MVP Suicide Exemplar Workgroup, and ISGC is provided in the Supplementary Materials. This work was also supported in part by the joint U.S. Department of Veterans Affairs and US Department of Energy MVP CHAMPION program. This manuscript has been co-authored by UT-Battelle, LLC under contract no. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan, last accessed September 16, 2020). The GWAS summary statistics generated from this study will be available via dbGaP. The dbGaP accession assigned to the Million Veteran Program is phs001672.v1.p.

Author information

Author notes

  1. These authors contributed equally: Nathan A. Kimbrel, Allison E. Ashley-Koch.

Authors and Affiliations

  1. Durham Veterans Affairs (VA) Health Care System, Durham, NC, USA

    Nathan A. Kimbrel, Xue J. Qin, Michelle F. Dennis, Lauren P. Hair, Elizabeth R. Hauser & Jean C. Beckham

  2. VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA

    Nathan A. Kimbrel & Jean C. Beckham

  3. VA Health Services Research and Development Center of Innovation to Accelerate Discovery and Practice Transformation, Durham, NC, USA

    Nathan A. Kimbrel & Jennifer H. Lindquist

  4. Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA

    Nathan A. Kimbrel, Michelle F. Dennis, Lauren P. Hair & Jean C. Beckham

  5. Duke Molecular Physiology Institute, Durham, NC, USA

    Allison E. Ashley-Koch, Xue J. Qin, Melanie E. Garrett, Elizabeth R. Hauser & Michael A. Hauser

  6. Department of Medicine, Duke University Health System, Durham, NC, USA

    Allison E. Ashley-Koch & Michael A. Hauser

  7. Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA

    Jennifer E. Huffman

  8. Biosciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Daniel A. Jacobson

  9. Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee Knoxville, Knoxville, TN, USA

    Daniel A. Jacobson

  10. Department of Psychology, NeuroNet Research Center, University of Tennessee Knoxville, Knoxville, TN, USA

    Daniel A. Jacobson

  11. Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, IL, USA

    Ravi K. Madduri

  12. Data Science and Learning Division, Argonne National Laboratory, Lemont, IL, USA

    Ravi K. Madduri

  13. Program Evaluation and Resource Center, Office of Mental Health and Suicide Prevention, VA Palo Alto Health Care System, Menlo Park, CA, USA

    Jodie A. Trafton

  14. Department of Psychiatry, Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, US

    Hilary Coon & Anna R. Docherty

  15. Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, US

    Hilary Coon

  16. Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, US

    Anna R. Docherty

  17. Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, US

    Jooeun Kang & Douglas M. Ruderfer

  18. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, US

    Niamh Mullins

  19. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, US

    Niamh Mullins

  20. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, US

    Douglas M. Ruderfer

  21. Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, US

    Douglas M. Ruderfer

  22. Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA

    Philip D. Harvey

  23. Research Service Bruce W. Carter VA Medical Center, Miami, FL, USA

    Philip D. Harvey

  24. Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA

    Benjamin H. McMahon

  25. VISN 4 Mental Illness Research, Education, and Clinical Center, Center of Excellence, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA

    David W. Oslin

  26. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    David W. Oslin

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  1. Nathan A. Kimbrel
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  2. Allison E. Ashley-Koch
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  3. Xue J. Qin
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  4. Jennifer H. Lindquist
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  14. Jooeun Kang
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  20. Elizabeth R. Hauser
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  21. Michael A. Hauser
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  22. Jean C. Beckham
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Consortia

the VA Million Veteran Program (MVP)

the MVP Suicide Exemplar Workgroup

the International Suicide Genetics Consortium

Contributions

This study was conceived and designed by NAK, AAK, ERH, MAH, and JCB. Statistical analyses were conducted by XJQ, JHL, and MEG, and were supervised by AAK and ERH. NAK, AAK, ERH, MAH, JCB, RKM, DAJ, JAT, HC, ARD, NM, and DMM reviewed and interpreted statistical findings. NAK, AAK, MFD, LPH, JEH, HC, ARD, JK, NM, DMM, PDH, BHM, DWO, ERH, MAH, and JCB were involved in data acquisition and data preparation. NAK, AAK, XJQ, JHL, and MEG wrote the initial draft of the manuscript. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Nathan A. Kimbrel.

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Kimbrel, N.A., Ashley-Koch, A.E., Qin, X.J. et al. A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci. Mol Psychiatry 27, 2264–2272 (2022). https://doi.org/10.1038/s41380-022-01472-3

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  • DOI: https://doi.org/10.1038/s41380-022-01472-3

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