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Mol Psychiatry. 2019 Sep 10. doi: 10.1038/s41380-019-0496-z. [Epub ahead of print]

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

Author information

1
Department of Systems Biology, Harvard University, Cambridge, MA, USA.
2
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
3
Integrative Systems Biology, US Army Medical Research and Materiel Command, USACEHR, Fort Detrick, Frederick, MD, USA.
4
Department of Obstetrics, Gynecology, & Reproductive Sciences, University of California, San Francisco, CA, USA.
5
Department of Psychiatry, New York Langone Medical School, New York, NY, USA.
6
Department of Psychiatry, James J. Peters VA Medical Center, Bronx, NY, USA.
7
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
8
Department of Psychiatry, McLean Hospital, Belmont, MA, USA.
9
Institute for Systems Biology, Seattle, WA, USA.
10
Departments of Biological Sciences and Computer Science, The University of Memphis, Memphis, TN, USA.
11
Advanced Biomedical Computing Center, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
12
Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA.
13
Department of Psychiatry, University of California, San Francisco, CA, USA.
14
Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy.
15
USACEHR, The Geneva Foundation, Frederick, MD, USA.
16
Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Sweden.
17
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA. frank_doyle@seas.harvard.edu.

Abstract

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.

PMID:
31501510
DOI:
10.1038/s41380-019-0496-z

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