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  Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

Popovic, D., Ruef, A., Dwyer, D. B., Antonucci, L. A., Eder, J., Sanfelici, R., et al. (2020). Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes. BIOLOGICAL PSYCHIATRY, 88(11), 829-842. doi:10.1016/j.biopsych.2020.05.020.

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 Creators:
Popovic, David1, Author           
Ruef, Anne, Author
Dwyer, Dominic B., Author
Antonucci, Linda A., Author
Eder, Julia, Author
Sanfelici, Rachele, Author
Kambeitz-Ilankovic, Lana, Author
Oeztuerk, Oemer Faruk1, Author           
Dong, Mark S., Author
Paul, R, Riya, Author
Paolini, Marco, Author
Hedderich, Dennis, Author
Haidl, Theresa, Author
Kambeitz, Joseph, Author
Ruhrmann, Stephan, Author
Chisholm, Katharine, Author
Schultze-Lutter, Frauke, Author
Falkai, Peter, Author
Pergola, Giulio, Author
Blasi, Giuseppe, Author
Bertolino, Alessandro, AuthorLencer, Rebekka, AuthorDannlowski, Udo, AuthorUpthegrove, Rachel, AuthorSalokangas, Raimo K. R., AuthorPantelis, Christos, AuthorMeisenzahl, Eva, AuthorWood, Stephen J., AuthorBrambilla, Paolo, AuthorBorgwardt, Stefan, AuthorKoutsouleris, Nikolaos2, Author            more..
Affiliations:
1IMPRS Translational Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society, Kraepelinstr. 2-10, 80804 Munich, DE, ou_3318616              
2Max Planck Fellow Group Precision Psychiatry, Max Planck Institute of Psychiatry, Max Planck Society, ou_3318615              

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Free keywords: QUALITY-OF-LIFE; PREFRONTAL CORTEX; INITIAL RELIABILITY; SCHIZOPHRENIA; MALTREATMENT; PERSONALITY; DEPRESSION; CEREBELLAR; PSYCHOSIS; COGNITIONNeurosciences & Neurology; Psychiatry;
 Abstract: BACKGROUND: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. METHODS: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested crossvalidation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. RESULTS: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. CONCLUSIONS: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published in print
 Pages: 14
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
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Title: BIOLOGICAL PSYCHIATRY
Source Genre: Journal
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Publ. Info: STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA : ELSEVIER SCIENCE INC
Pages: - Volume / Issue: 88 (11) Sequence Number: - Start / End Page: 829 - 842 Identifier: ISSN: 0006-3223