Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder
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Published:2019-09-10
Issue:12
Volume:25
Page:3337-3349
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ISSN:1359-4184
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Container-title:Molecular Psychiatry
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language:en
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Short-container-title:Mol Psychiatry
Author:
Dean Kelsey R., , Hammamieh Rasha, Mellon Synthia H., Abu-Amara Duna, Flory Janine D., Guffanti Guia, Wang Kai, Daigle Bernie J., Gautam Aarti, Lee Inyoul, Yang Ruoting, Almli Lynn M., Bersani F. SaverioORCID, Chakraborty Nabarun, Donohue Duncan, Kerley Kimberly, Kim Taek-Kyun, Laska Eugene, Young Lee Min, Lindqvist Daniel, Lori Adriana, Lu Liangqun, Misganaw Burook, Muhie Seid, Newman Jennifer, Price Nathan D.ORCID, Qin Shizhen, Reus Victor I., Siegel Carole, Somvanshi Pramod R., Thakur Gunjan S., Zhou Yong, Hood Leroy, Ressler Kerry J., Wolkowitz Owen M., Yehuda Rachel, Jett Marti, Doyle Francis J., Marmar Charles
Abstract
AbstractPost-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.
Funder
United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office
Publisher
Springer Science and Business Media LLC
Subject
Cellular and Molecular Neuroscience,Psychiatry and Mental health,Molecular Biology
Reference61 articles.
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