Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
18
12
2018
accepted:
24
06
2019
revised:
15
05
2019
pubmed:
11
9
2019
medline:
15
5
2021
entrez:
11
9
2019
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 31501510
doi: 10.1038/s41380-019-0496-z
pii: 10.1038/s41380-019-0496-z
pmc: PMC7714692
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
3337-3349Investigateurs
David Baxter
(D)
Linda Bierer
(L)
Esther Blessing
(E)
Ji Hoon Cho
(JH)
Michelle Coy
(M)
Frank Desarnaud
(F)
Silvia Fossati
(S)
Allison Hoke
(A)
Raina Kumar
(R)
Meng Li
(M)
Iouri Makotkine
(I)
Stacy-Ann Miller
(SA)
Linda Petzold
(L)
Laura Price
(L)
Meng Qian
(M)
Kelsey Scherler
(K)
Seshamalini Srinivasan
(S)
Anna Suessbrick
(A)
Li Tang
(L)
Xiaogang Wu
(X)
Gwyneth Wu
(G)
Changxin Wu
(C)
Commentaires et corrections
Type : CommentIn
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