Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder

Research output: Contribution to journalArticle


Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.


  • Kelsey R. Dean
  • Rasha Hammamieh
  • Synthia H. Mellon
  • Duna Abu-Amara
  • Janine D. Flory
  • Guia Guffanti
  • Kai Wang
  • Bernie J. Daigle
  • Aarti Gautam
  • Inyoul Lee
  • Ruoting Yang
  • Lynn M. Almli
  • F. Saverio Bersani
  • Nabarun Chakraborty
  • Duncan Donohue
  • Kimberly Kerley
  • Taek Kyun Kim
  • Eugene Laska
  • Min Young Lee
  • Daniel Lindqvist
  • Adriana Lori
  • Liangqun Lu
  • Burook Misganaw
  • Seid Muhie
  • Jennifer Newman
  • Nathan D. Price
  • Shizhen Qin
  • Victor I. Reus
  • Carole Siegel
  • Pramod R. Somvanshi
  • Gunjan S. Thakur
  • Yong Zhou
  • The PTSD Systems Biology Consortium
  • Leroy Hood
  • Kerry J. Ressler
  • Owen M. Wolkowitz
  • Rachel Yehuda
  • Marti Jett
  • Francis J. Doyle III
  • Charles Marmar
External organisations
  • Harvard University
  • Icahn School of Medicine at Mount Sinai
  • Institute for Systems Biology, Seattle
  • University of Memphis
  • National Cancer Institute at Frederick
  • Emory University
  • Sapienza University of Rome
  • University of California, San Francisco
  • US Army Medical Research and Materiel Command
  • James J. Peters Veterans Administration Medical Center
  • McLean Hospital
  • U.S. Army Center for Environmental Health Research
  • NYU Langone
  • New York University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Psychiatry
  • Cell and Molecular Biology
Original languageEnglish
Pages (from-to)3337-3349
Number of pages13
JournalMolecular Psychiatry
Issue number12
Early online date2019 Sep 10
Publication statusPublished - 2020 Dec
Publication categoryResearch