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Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.
Suarez-Jimenez, Benjamin; Lazarov, Amit; Zhu, Xi; Zilcha-Mano, Sigal; Kim, Yoojean; Marino, Claire E; Rjabtsenkov, Pavel; Bavdekar, Shreya Y; Pine, Daniel S; Bar-Haim, Yair; Larson, Christine L; Huggins, Ashley A; Tomas, Carissa; Fitzgerald, Jacklynn; Kennis, Mitzy; Varkevisser, Tim; Geuze, Elbert; Quidé, Yann; El Hage, Wissam; Wang, Xin; O'Leary, Erin N; Cotton, Andrew S; Xie, Hong; Shih, Chiahao; Disner, Seth G; Davenport, Nicholas D; Sponheim, Scott R; Koch, Saskia B J; Frijling, Jessie L; Nawijn, Laura; van Zuiden, Mirjam; Olff, Miranda; Veltman, Dick J; Gordon, Evan M; May, Geoffery; Nelson, Steven M; Jia-Richards, Meilin; Neria, Yuval; Morey, Rajendra A.
Afiliación
  • Suarez-Jimenez B; Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York.
  • Lazarov A; Department of Clinical Psychology, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel.
  • Zhu X; Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York.
  • Zilcha-Mano S; Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York.
  • Kim Y; Department of Psychology, University of Haifa, Mount Carmel, Haifa, Israel.
  • Marino CE; Department of Psychiatry, New York State Psychiatric Institute, New York, New York.
  • Rjabtsenkov P; Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York.
  • Bavdekar SY; Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York.
  • Pine DS; Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York.
  • Bar-Haim Y; Section on Developmental Affective Neuroscience, National Institute of Mental Health, Bethesda, Maryland.
  • Larson CL; Department of Clinical Psychology, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel.
  • Huggins AA; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
  • Terri deRoon-Cassini; University of Wisconsin-Milwaukee, Milwaukee, Wisconsin.
  • Tomas C; Duke University, Durham, North Carolina.
  • Fitzgerald J; Medical College of Wisconsin, Milwaukee, Wisconsin.
  • Kennis M; Medical College of Wisconsin, Milwaukee, Wisconsin.
  • Varkevisser T; Marquette University, Milwaukee, Wisconsin.
  • Geuze E; Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands.
  • Quidé Y; Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands.
  • El Hage W; Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands.
  • Wang X; Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands.
  • O'Leary EN; Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands.
  • Cotton AS; Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Xie H; School of Psychology, University of New South Wales Sydney, Sydney, New South Wales, Australia.
  • Shih C; Neuroscience Research Australia, Randwick, New South Wales, Australia.
  • Disner SG; Unité Mixte de Recherche 1253, Institut National de la Santé et de la Recherche Médicale, Université de Tours, Tours, France.
  • Davenport ND; Centre d'investigation Clinique 1415, Institut National de la Santé et de la Recherche Médicale, Centre Hospitalier Régional Universitaire de Tours, Tours, France.
  • Sponheim SR; University of Toledo, Toledo, Ohio.
  • Koch SBJ; University of Toledo, Toledo, Ohio.
  • Frijling JL; University of Toledo, Toledo, Ohio.
  • Nawijn L; University of Toledo, Toledo, Ohio.
  • van Zuiden M; University of Toledo, Toledo, Ohio.
  • Olff M; Minneapolis VA Health Care System, Minneapolis, Minnesota.
  • Veltman DJ; Minneapolis VA Health Care System, Minneapolis, Minnesota.
  • Gordon EM; Minneapolis VA Health Care System, Minneapolis, Minnesota.
  • May G; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands.
  • Nelson SM; Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
  • Jia-Richards M; Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
  • Neria Y; Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Morey RA; Department of Psychiatry, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands.
Biol Psychiatry Glob Open Sci ; 4(1): 299-307, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38298781
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.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Biol Psychiatry Glob Open Sci Año: 2024 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Biol Psychiatry Glob Open Sci Año: 2024 Tipo del documento: Article