A1 Refereed original research article in a scientific journal

Neurobiological Signatures of Trauma, Personality, and Depressivity: A Transdiagnostic Machine Learning Study in Adolescents and Young Adults




AuthorsWeyer, Clara; Sarisik, Elif; Tovar, Perdomo Santiago; Vetter, Clara; Dwyer, Dominic B.; Antonucci, Linda A.; Lichtenstein, Theresa; Kambeitz-Ilankovic, Lana; Kambeitz, Joseph; Ruhrmann, Stephan; Chisholm, Katharine; Schultze-Lutter, Frauke; Falkai, Peter; Schiltz, Kolja; Pergola, Giulio; Blasi, Giuseppe; Bertolino, Alessandro; Romer, Georg; Lencer, Rebekka; Dannlowski, Udo; Upthegrove, Rachel; Salokangas, Raimo K.R.; Pantelis, Christos; Meisenzahl, Eva; Wood, Stephen J.; Brambilla, Paolo; Borgwardt, Stefan; Koutsouleris, Nikolaos; Popovic, David; for the PRONIA Consortium

PublisherElsevier BV

Publication year2026

Journal: Biological Psychiatry

Volume100

Issue6

First page 662

Last page676

ISSN0006-3223

eISSN1873-2402

DOIhttps://doi.org/10.1016/j.biopsych.2026.03.994

Publication's open availability at the time of reportingNo Open Access

Publication channel's open availability Partially Open Access publication channel

Web address https://doi.org/10.1016/j.biopsych.2026.03.994


Abstract

Background: Adolescence and early adulthood are vulnerable phases for psychiatric disorders, where trauma and personality development converge on shared and distinct, often unknown brain signatures.

Methods: We used Sparse Partial Least Squares (SPLS) to identify multivariate signatures between voxel-wise grey matter volume (GMV) and three domains: childhood trauma, personality, and depressivity. We performed structural equation modeling (SEM) among these domains, predicted functional outcome at 9-month follow-up via support vector machine classification, and correlated the SPLS signatures with resilience, coping and visual dysfunctions. All models were cross-validated in the discovery (n=633; 52.9% female, mean(SD) age=25.41(5.98) years) and validated in the replication sample (n=343; 53.0% female, 24.69(5.72) years) of the multi-site prospective PRONIA cohort, comprising individuals with recent-onset depression or psychosis, psychosis risk syndromes, and healthy controls.

Results: We identified three signatures of interest: (1) depressivity, linked to reduced GMV in limbic regions; (2) childhood trauma, associated with GMV in thalamic, frontotemporal, and parietal regions; (3) a trauma-personality-depressivity signature relating childhood trauma, personality, and depressivity, to GMV in thalamic, occipital, temporal, and limbic regions. Through SEM, childhood trauma was directly associated with depressivity and indirectly via a maladaptive personality structure. The trauma-personality-depressivity signature was the strongest predictor of poor functional outcome (BACDiscovery=75.8%, BACReplication=83.2%). The depressivity and trauma-personality-depressivity signatures were linked to deficient resilience and coping styles as well as visual dysfunctions.

Conclusions: Childhood trauma, personality, and depressivity are associated with shared and distinct brain signatures spanning the affective-psychotic spectrum. If these factors converge, current and future mental health may be compromised.



Last updated on 20/08/2026 02:11:57 PM