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

Research output: Contribution to journalArticle

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Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder. / 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. Saverio; 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.; Qin, Shizhen; Reus, Victor I.; Siegel, Carole; Somvanshi, Pramod R.; Thakur, Gunjan S.; Zhou, Yong; The PTSD Systems Biology Consortium; Hood, Leroy; Ressler, Kerry J.; Wolkowitz, Owen M.; Yehuda, Rachel; Jett, Marti; Doyle III, Francis J.; Marmar, Charles.

In: Molecular Psychiatry, Vol. 25, No. 12, 12.2020, p. 3337-3349.

Research output: Contribution to journalArticle

Harvard

Dean, KR, Hammamieh, R, Mellon, SH, Abu-Amara, D, Flory, JD, Guffanti, G, Wang, K, Daigle, BJ, Gautam, A, Lee, I, Yang, R, Almli, LM, Bersani, FS, Chakraborty, N, Donohue, D, Kerley, K, Kim, TK, Laska, E, Young Lee, M, Lindqvist, D, Lori, A, Lu, L, Misganaw, B, Muhie, S, Newman, J, Price, ND, Qin, S, Reus, VI, Siegel, C, Somvanshi, PR, Thakur, GS, Zhou, Y, The PTSD Systems Biology Consortium, Hood, L, Ressler, KJ, Wolkowitz, OM, Yehuda, R, Jett, M, Doyle III, FJ & Marmar, C 2020, 'Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder', Molecular Psychiatry, vol. 25, no. 12, pp. 3337-3349. https://doi.org/10.1038/s41380-019-0496-z

APA

Dean, K. R., Hammamieh, R., Mellon, S. H., Abu-Amara, D., Flory, J. D., Guffanti, G., Wang, K., Daigle, B. J., Gautam, A., Lee, I., Yang, R., Almli, L. M., Bersani, F. S., Chakraborty, N., Donohue, D., Kerley, K., Kim, T. K., Laska, E., Young Lee, M., ... Marmar, C. (2020). Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder. Molecular Psychiatry, 25(12), 3337-3349. https://doi.org/10.1038/s41380-019-0496-z

CBE

Dean KR, Hammamieh R, Mellon SH, Abu-Amara D, Flory JD, Guffanti G, Wang K, Daigle BJ, Gautam A, Lee I, Yang R, Almli LM, Bersani FS, Chakraborty N, Donohue D, Kerley K, Kim TK, Laska E, Young Lee M, Lindqvist D, Lori A, Lu L, Misganaw B, Muhie S, Newman J, Price ND, Qin S, Reus VI, Siegel C, Somvanshi PR, Thakur GS, Zhou Y, The PTSD Systems Biology Consortium, Hood L, Ressler KJ, Wolkowitz OM, Yehuda R, Jett M, Doyle III FJ, Marmar C. 2020. Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder. Molecular Psychiatry. 25(12):3337-3349. https://doi.org/10.1038/s41380-019-0496-z

MLA

Vancouver

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. Saverio ; 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. ; Qin, Shizhen ; Reus, Victor I. ; Siegel, Carole ; Somvanshi, Pramod R. ; Thakur, Gunjan S. ; Zhou, Yong ; The PTSD Systems Biology Consortium ; Hood, Leroy ; Ressler, Kerry J. ; Wolkowitz, Owen M. ; Yehuda, Rachel ; Jett, Marti ; Doyle III, Francis J. ; Marmar, Charles. / Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder. In: Molecular Psychiatry. 2020 ; Vol. 25, No. 12. pp. 3337-3349.

RIS

TY - JOUR

T1 - Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder

AU - Dean, Kelsey R.

AU - Hammamieh, Rasha

AU - Mellon, Synthia H.

AU - Abu-Amara, Duna

AU - Flory, Janine D.

AU - Guffanti, Guia

AU - Wang, Kai

AU - Daigle, Bernie J.

AU - Gautam, Aarti

AU - Lee, Inyoul

AU - Yang, Ruoting

AU - Almli, Lynn M.

AU - Bersani, F. Saverio

AU - Chakraborty, Nabarun

AU - Donohue, Duncan

AU - Kerley, Kimberly

AU - Kim, Taek Kyun

AU - Laska, Eugene

AU - Young Lee, Min

AU - Lindqvist, Daniel

AU - Lori, Adriana

AU - Lu, Liangqun

AU - Misganaw, Burook

AU - Muhie, Seid

AU - Newman, Jennifer

AU - Price, Nathan D.

AU - Qin, Shizhen

AU - Reus, Victor I.

AU - Siegel, Carole

AU - Somvanshi, Pramod R.

AU - Thakur, Gunjan S.

AU - Zhou, Yong

AU - The PTSD Systems Biology Consortium

AU - Hood, Leroy

AU - Ressler, Kerry J.

AU - Wolkowitz, Owen M.

AU - Yehuda, Rachel

AU - Jett, Marti

AU - Doyle III, Francis J.

AU - Marmar, Charles

PY - 2020/12

Y1 - 2020/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85073953764&partnerID=8YFLogxK

U2 - 10.1038/s41380-019-0496-z

DO - 10.1038/s41380-019-0496-z

M3 - Article

C2 - 31501510

AN - SCOPUS:85073953764

VL - 25

SP - 3337

EP - 3349

JO - Molecular Psychiatry

JF - Molecular Psychiatry

SN - 1359-4184

IS - 12

ER -