Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Authors

• Adam X. Maihofer, University of California San Diego, La Jolla, CA
• Karmel W. Choi, Harvard T.H. Chan School of Public Health, Boston, MA
• Jonathan R. I. Coleman, King's College London, London, United Kingdom
• Nikolaos P. Daskalakis, Harvard Medical School, Boston, MA
• Christy A. Denckla, Harvard T.H. Chan School of Public Health, Boston, MA
• Elizabeth Ketema, University of California San Diego, La Jolla, CA
• Rajendra A. Morey, Duke University School of Medicine, Durham, NC
• Renato Polimanti, Veterans Affairs Connecticut Healthcare System, West Haven, CT
• Andrew Ratanatharathorn, Harvard T.H. Chan School of Public Health, Boston, MA
• Katy Torres, University of California San Diego, La Jolla, CA
• Aliza P. Wingo, Atlanta Veterans Affairs Medical Center, Decatur, GA
• Clement C. Zai, Harvard T.H. Chan School of Public Health, Boston, MA
• Meghan Brashear, LSU Health Sciences Center - New Orleans
• Edward S. Peters, LSU Health Sciences Center - New OrleansFollow
• Ariane Rung, LSU Health Sciences Center - New OrleansFollow
• Edward Trapido, LSU Health Sciences Center - New OrleansFollow
• et al

Document Type

Article

Publication Date

9-28-2021

Publication Title

Biological Psychiatry

Abstract

Background: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

First Page

626

Last Page

636

PubMed ID

34865855

Volume

91

Issue

7

Comments

See article for full author list.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Maihofer, Adam X.; Choi, Karmel W.; Coleman, Jonathan R. I.; Daskalakis, Nikolaos P.; Denckla, Christy A.; Ketema, Elizabeth; Morey, Rajendra A.; Polimanti, Renato; Ratanatharathorn, Andrew; Torres, Katy; Wingo, Aliza P.; Zai, Clement C.; Brashear, Meghan; Peters, Edward S.; Rung, Ariane; Trapido, Edward; and al, et, "Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information" (2021). School of Public Health Faculty Publications. 565.
https://digitalscholar.lsuhsc.edu/soph_facpubs/565
10.1016/j.biopsych.2021.09.020