Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium
BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE(2024)
Univ Rochester | Tel Aviv Univ | Columbia Univ | Univ Haifa | New York State Psychiat Inst & Hosp | Natl Inst Mental Hlth | Univ Wisconsin | Duke Univ | Med Coll Wisconsin | Marquette Univ | Minist Def | Univ New South Wales Sydney | Univ Tours | Univ Toledo | Minneapolis VA Hlth Care Syst | Radboud Univ Nijmegen | Univ Amsterdam | Vrije Univ Amsterdam | Washington Univ | US Dept Vet Affairs | Univ Minnesota | Baylor Univ
Abstract
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.
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Key words
ITRED,Machine learning,PTSD,Re-experiencing,Resting-state functional connectivity,Trauma exposure
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