학술논문

Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder
Document Type
article
Source
Molecular Psychiatry. 25(12)
Subject
Genetics
Post-Traumatic Stress Disorder (PTSD)
Brain Disorders
Behavioral and Social Science
Clinical Research
Mental Health
Prevention
Anxiety Disorders
4.2 Evaluation of markers and technologies
Detection
screening and diagnosis
4.1 Discovery and preclinical testing of markers and technologies
Generic health relevance
Good Health and Well Being
Biomarkers
Brain
Humans
Male
Military Personnel
Stress Disorders
Post-Traumatic
Veterans
PTSD Systems Biology Consortium
Biological Sciences
Medical and Health Sciences
Psychology and Cognitive Sciences
Psychiatry
Language
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.