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Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans

Abstract

Post-traumatic stress disorder (PTSD) is a major problem among military veterans and civilians alike, yet its pathophysiology remains poorly understood. We performed a genome-wide association study and bioinformatic analyses, which included 146,660 European Americans and 19,983 African Americans in the US Million Veteran Program, to identify genetic risk factors relevant to intrusive reexperiencing of trauma, which is the most characteristic symptom cluster of PTSD. In European Americans, eight distinct significant regions were identified. Three regions had values of P < 5 × 10−10: CAMKV; chromosome 17 closest to KANSL1, but within a large high linkage disequilibrium region that also includes CRHR1; and TCF4. Associations were enriched with respect to the transcriptomic profiles of striatal medium spiny neurons. No significant associations were observed in the African American cohort of the sample. Results in European Americans were replicated in the UK Biobank data. These results provide new insights into the biology of PTSD in a well-powered genome-wide association study.

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Fig. 1: Manhattan plots.
Fig. 2: Regional Manhattan plots, chromosome 17.
Fig. 3: eQTLs.
Fig. 4: Manhattan plot of gene-based association results.
Fig. 5: Enrichment analyses.

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Data availability

The GWAS summary statistics generated during and/or analyzed during the current study are available via dbGAP; the dbGaP accession assigned to the Million Veteran Program is phs001672.v1.p. The website is: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001672.v1.p1. Additionally, the data that support the findings of this study are available from the corresponding authors upon reasonable request.

References

  1. Fulton, J. J. et al. The prevalence of posttraumatic stress disorder in operation enduring freedom/operation iraqi freedom (OEF/OIF) veterans: a meta-analysis. J. Anxiety Disord. 31, 98–107 (2015).

    Article  Google Scholar 

  2. Logue, M. W. et al. A genome-wide association study of post-traumatic stress disorder identifies the retinoid-related orphan receptor alpha (RORA) gene as a significant risk locus. Mol. Psychiatry 18, 937–942 (2013).

    Article  CAS  Google Scholar 

  3. Stein, M. B. et al. Genome-wide association studies of posttraumatic stress disorder in 2 cohorts of US army soldiers. JAMA Psychiatry 73, 695–704 (2016).

    Article  Google Scholar 

  4. Xie, P. et al. Genome-wide association study identifies new susceptibility loci for posttraumatic stress disorder. Biol. Psychiatry 74, 656–663 (2013).

    Article  CAS  Google Scholar 

  5. Duncan, L. E. et al. Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol. Psychiatry 23, 666–673 (2018).

    Article  CAS  Google Scholar 

  6. Blanchard, E. B., Jones-Alexander, J., Buckley, T. C. & Forneris, C. A. Psychometric properties of the PTSD Checklist (PCL). Behav. Res. Ther. 34, 669–673 (1996).

    Article  CAS  Google Scholar 

  7. Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

    Article  Google Scholar 

  8. GTEx Consortium. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

  9. Skene, N. G. et al. Genetic identification of brain cell types underlying schizophrenia. Nat. Genet. 50, 825–833 (2018).

    Article  CAS  Google Scholar 

  10. Barbano, A. C. et al. Clinical implications of the proposed ICD-11 PTSD diagnostic criteria. Psychol. Med. 49, 483–490 (2019).

    Article  Google Scholar 

  11. Stefansson, H. et al. A common inversion under selection in Europeans. Nat. Genet. 37, 129–137 (2005).

    Article  CAS  Google Scholar 

  12. Cáceres, A., Sindi, S. S., Raphael, B. J., Cáceres, M. & González, J. R. Identification of polymorphic inversions from genotypes. BMC Bioinformatics 13, 28 (2012).

    Article  Google Scholar 

  13. Amstadter, A. B. et al. Corticotrophin-releasing hormone type 1 receptor gene (CRHR1) variants predict posttraumatic stress disorder onset and course in pediatric injury patients. Dis. Markers 30, 89–99 (2011).

    Article  CAS  Google Scholar 

  14. Kasckow, J. W., Baker, D. & Geracioti, T. D. Jr. Corticotropin-releasing hormone in depression and post-traumatic stress disorder. Peptides 22, 845–851 (2001).

    Article  CAS  Google Scholar 

  15. McFarlane, A. C., Barton, C. A., Yehuda, R. & Wittert, G. Cortisol response to acute trauma and risk of posttraumatic stress disorder. Psychoneuroendocrinology 36, 720–727 (2011).

    Article  CAS  Google Scholar 

  16. Smith, D. J. et al. Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci. Mol. Psychiatry 21, 749–757 (2016).

    Article  CAS  Google Scholar 

  17. Stefansson, H. et al. Common variants conferring risk of schizophrenia. Nature 460, 744–747 (2009).

    Article  CAS  Google Scholar 

  18. Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013).

    Article  Google Scholar 

  19. Ruderfer, D. M.et al. Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia. Mol. Psychiatry 19, 1017–1024 (2014).

    Article  Google Scholar 

  20. McGrath, J. J. et al. Trauma and psychotic experiences: transnational data from the world mental health survey. Br. J. Psychiatry 211, 373–380 (2017).

    Article  Google Scholar 

  21. Waters, F., Blom, J. D., Jardri, R., Hugdahl, K. & Sommer, I. E. C. Auditory hallucinations, not necessarily a hallmark of psychotic disorder. Psychol. Med. 48, 529–536 (2018).

    Article  CAS  Google Scholar 

  22. Ravindran, L. N. & Stein, M. B. The pharmacologic treatment of anxiety disorders: a review of progress. J. Clin. Psychiatry 71, 839–854 (2010).

    Article  CAS  Google Scholar 

  23. Krystal, J. H. et al. Adjunctive risperidone treatment for antidepressant-resistant symptoms of chronic military service-related PTSD: a randomized trial. JAMA 306, 493–502 (2011).

    Article  CAS  Google Scholar 

  24. Gelernter, J. et al. Genome-wide association study of opioid dependence: multiple associations mapped to calcium and potassium pathways. Biol. Psychiatry 76, 66–74 (2014).

    Article  CAS  Google Scholar 

  25. Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016).

    Article  CAS  Google Scholar 

  26. Alexander, M. et al. Rab27-dependent exosome production inhibits chronic inflammation and enables acute responses to inflammatory stimuli. J. Immunol. 199, 3559–3570 (2017).

    Article  CAS  Google Scholar 

  27. Michopoulos, V., Powers, A., Gillespie, C. F., Ressler, K. J. & Jovanovic, T. Inflammation in fear- and anxiety-based disorders: PTSD, GAD, and beyond. Neuropsychopharmacology 42, 254–270 (2017).

    Article  CAS  Google Scholar 

  28. Howard, D. M. et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 22, 343–352 (2019).

    Article  CAS  Google Scholar 

  29. Sumner, J. A. et al. Post-traumatic stress disorder symptoms and risk of hypertension over 22 years in a large cohort of younger and middle-aged women. Psychol. Med. 46, 3105–3116 (2016).

    Article  CAS  Google Scholar 

  30. Roy, S. S., Foraker, R. E., Girton, R. A. & Mansfield, A. J. Posttraumatic stress disorder and incident heart failure among a community-based sample of US veterans. Am. J. Public Health 105, 757–763 (2015).

    Article  Google Scholar 

  31. Raskind, M. A. et al. Trial of prazosin for post-traumatic stress disorder in military veterans. N. Engl. J. Med. 378, 507–517 (2018).

    Article  CAS  Google Scholar 

  32. Gaziano, J. M. et al. Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J. Clin. Epidemiol. 70, 214–223 (2016).

    Article  Google Scholar 

  33. Wilkins, K. C., Lang, A. J. & Norman, S. B. Synthesis of the psychometric properties of the PTSD checklist (PCL) military, civilian, and specific versions. Depress. Anxiety 28, 596–606 (2011).

    Article  Google Scholar 

  34. Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).

    Article  CAS  Google Scholar 

  35. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  Google Scholar 

  36. Abraham, G. & Inouye, M. Fast principal component analysis of large-scale genome-wide data. PLoS ONE 9, e93766 (2014).

    Article  Google Scholar 

  37. Auton, A. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

    Article  Google Scholar 

  38. Zhan, X., Hu, Y., Li, B., Abecasis, G. R. & Liu, D. J. RVTESTS: an efficient and comprehensive tool for rare variant association analysis using sequence data. Bioinformatics 32, 1423–1426 (2016).

    Article  CAS  Google Scholar 

  39. de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).

    Article  Google Scholar 

  40. Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. FUMA: functional mapping and annotation of genetic associations. Preprint at: https://doi.org/10.1101/110023 (2017).

  41. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    Article  CAS  Google Scholar 

  42. Bulik-Sullivan, B. K., Loh, P. R., Finucane, H. K., Ripke, S. & Yang, J. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

    Article  CAS  Google Scholar 

  43. Zheng, J. et al. HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics. Bioinformatics 33, 79–86 (2017).

    Article  CAS  Google Scholar 

  44. Zheng, J. et al. LD hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017).

    Article  CAS  Google Scholar 

  45. Bycroft, C. et al. Genome-wide genetic data on ~500,000 UK Biobank participants. Preprint at https://doi.org/10.1101/166298 (2017).

  46. Aulchenko, Y. S., Ripke, S., Isaacs, A. & van Duijn, C. M. GenABEL: an R library for genome-wide association analysis. Bioinformatics 23, 1294–1296 (2007).

    Article  CAS  Google Scholar 

  47. Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).

    Article  CAS  Google Scholar 

  48. Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).

    Article  CAS  Google Scholar 

  49. Szklarczyk, D. et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 45, D362–D368 (2017).

    Article  CAS  Google Scholar 

  50. Euesden, J., Lewis, C. M. & O’Reilly, P. F. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015).

    Article  CAS  Google Scholar 

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Acknowledgements

This research is based on data from the Million Veteran Program (MVP), Office of Research and Development, Veterans Health Administration, and was supported by the MVP and the VA Cooperative Studies Program (CSP) study no. 575B. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

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Contributions

Genotyping effort: S.P., Y.S. and H.H.-Z. Analyses team: N.S., J.B., Q.L., Y.H., B.L., R. Polimanti, Q.C. and D.F.L. CSP575B team (database, phenotype and analytic efforts): K.R., M.A., K.H.C., Y.L., N.R., F.S., K.H., K.C., R.Q. and R. Pietrzak. MVP leadership (overall MVP design and supervision): J.M.G. and J.C. Analysis design: R. Polimanti, P.F.S., H.Z., J.G. and M.B.S. Project design and project leadership: J.G., J.C. and M.B.S. Writing leads: J.G. and M.B.S.

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Correspondence to Joel Gelernter.

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Competing interests

J.G. is named as a co-inventor on PCT patent application no. 15/878,640 entitled: “Genotype-guided dosing of opioid agonists,” filed 24 January 2018. M.B.S. has in the past 3 years been a consultant for Actelion, Aptinyx, Bionomics, Dart Neuroscience, Healthcare Management Technologies, Janssen, Jazz Pharmaceuticals, Neurocrine Biosciences, Oxeia Biopharmaceuticals, Pfizer, and Resilience Therapeutics. M.B.S. owns founders shares and stock options in Resilience Therapeutics and has stock options in Oxeia Biopharmaceuticals.

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Gelernter, J., Sun, N., Polimanti, R. et al. Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans. Nat Neurosci 22, 1394–1401 (2019). https://doi.org/10.1038/s41593-019-0447-7

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