TY - JOUR
T1 - Intrusive Traumatic Re-Experiencing Domain
T2 - Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium
AU - Suarez-Jimenez, Benjamin
AU - Lazarov, Amit
AU - Zhu, Xi
AU - Zilcha-Mano, Sigal
AU - Kim, Yoojean
AU - Marino, Claire E.
AU - Rjabtsenkov, Pavel
AU - Bavdekar, Shreya Y.
AU - Pine, Daniel S.
AU - Bar-Haim, Yair
AU - Larson, Christine L.
AU - Huggins, Ashley A.
AU - Terri deRoon-Cassini, null
AU - Tomas, Carissa
AU - Fitzgerald, Jacklynn
AU - Kennis, Mitzy
AU - Varkevisser, Tim
AU - Geuze, Elbert
AU - Quidé, Yann
AU - el Hage, Wissam
AU - Wang, Xin
AU - O'Leary, Erin N.
AU - Cotton, Andrew S.
AU - Xie, Hong
AU - Shih, Chiahao
AU - Disner, Seth G.
AU - Davenport, Nicholas D.
AU - Sponheim, Scott R.
AU - Koch, Saskia B. J.
AU - Frijling, Jessie L.
AU - Nawijn, Laura
AU - van Zuiden, Mirjam
AU - Olff, Miranda
AU - Veltman, Dick J.
AU - Gordon, Evan M.
AU - May, Geoffery
AU - Nelson, Steven M.
AU - Jia-Richards, Meilin
AU - Neria, Yuval
AU - Morey, Rajendra A.
N1 - Funding Information: This work was supported by National Institute of Mental Health Grant Nos. K01MH118428 (to BS-J), R01MH131532 (to BS-J), K01MH122774 (to XZ), R01MH105355 (to YN), 1R01MH106574 (to CLL, TdR-C), 1R01MH110483 (to XW), 1R21MH098198 (to XW), 1R21MH125277 (to XW), and R01MH111671 (to RAM); National Eye Institute Core Grant No. P30 EY001319 (to BS-J); Brain and Behavior Research Foundation NARSAD Young Investigator Grants (to BS-J, XZ); Israel Science Foundation Grant No. 374/20 (to AL); National Institute of Mental Health Intramural Research Program Project Grant No. ZIA-MH-002782 (to DSP); the Programme Hospitalier de Recherche Clinique (to WEH); Fondation Pierre Deniker (to WEH); SFR Grant No. FED4226 (to WEH); VA Office of Rehabilitation Research and Development Grant Nos. 1IK2RX000709 (to SGD), I01RX000622 (to NDD), 1K1RX002325 (to SRS), and 1K2RX002922 (to SRS); Congressionally Directed Medical Research Program Grant No. W81XWH-08-2-0038 (to NDD); Netherlands Organization for Health Research and Development Grant No. 40-00812-98-10041 [to SBJK, JLF, LN, MvZ, MO, DJV]); Academic Medical Center Research Council Grant No. 110614 (to SBJK, JLF, LN, MvZ, MO, DJV); VA Clinical Science Research and Development Grant No. 1IK2CX001680 [to EMG, GM, SMN]; and VISN17 Center of Excellence Pilot funding (to EMG, GM, SMN). The funding agencies had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. WEH received support from Air Liquide, CHUGAI, EISAI, Jazz Pharmaceuticals, Janssen, Lundbeck, Otsuka, and UCB for work unrelated to the current study. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by National Institute of Mental Health Grant Nos. K01MH118428 (to BS-J), R01MH131532 (to BS-J), K01MH122774 (to XZ), R01MH105355 (to YN), 1R01MH106574 (to CLL, TdR-C), 1R01MH110483 (to XW), 1R21MH098198 (to XW), and 1R21MH125277 (to XW); National Eye Institute Core Grant No. P30 EY001319 (to BS-J); Brain and Behavior Research Foundation NARSAD Young Investigator Grants (to BS-J, XZ); Israel Science Foundation Grant No. 374/20 (to AL); National Institute of Mental Health Intramural Research Program Project Grant No. ZIA-MH-002782 (to DSP); the Programme Hospitalier de Recherche Clinique (to WEH); Fondation Pierre Deniker (to WEH); SFR Grant No. FED4226 (to WEH); VA Office of Rehabilitation Research and Development Grant Nos. 1IK2RX000709 (to SGD), I01RX000622 (to NDD), 1K1RX002325 (to SRS), and 1K2RX002922 (to SRS); Congressionally Directed Medical Research Program Grant No. W81XWH-08-2-0038 (to NDD); Netherlands Organization for Health Research and Development Grant No. 40-00812-98-10041 [to SBJK, JLF, LN, MvZ, MO, DJV]) ; Academic Medical Center Research Council Grant No. 110614 (to SBJK, JLF, LN, MvZ, MO, DJV); VA Clinical Science Research and Development Grant No. 1IK2CX001680 [to EMG, GM, SMN]; and VISN17 Center of Excellence Pilot funding (to EMG, GM, SMN). The funding agencies had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication. Publisher Copyright: © 2023 The Authors
PY - 2024/1
Y1 - 2024/1
N2 - Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n = 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)–only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network–related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.
AB - Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n = 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)–only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network–related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.
KW - ITRED
KW - Machine learning
KW - PTSD
KW - Re-experiencing
KW - Resting-state functional connectivity
KW - Trauma exposure
UR - http://www.scopus.com/inward/record.url?scp=85169476683&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.bpsgos.2023.05.006
DO - https://doi.org/10.1016/j.bpsgos.2023.05.006
M3 - Article
C2 - 38298781
SN - 2667-1743
VL - 4
SP - 299
EP - 307
JO - Biological Psychiatry Global Open Science
JF - Biological Psychiatry Global Open Science
IS - 1
ER -