Biological psychiatry · 2026
Neurobiological Signatures of Trauma, Personality, and Depressivity: A Transdiagnostic Machine Learning Study in Adolescents and Young Adults.
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Weyer 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, PRONIA Consortium
Аннотация
BACKGROUND: Adolescence and early adulthood are periods of increased vulnerability for psychiatric disorders, when 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 voxelwise gray matter volume (GMV) and the following 3 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 sample [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 multisite prospective PRONIA (Personalised Prognostic Tools for Early Psychosis Management) cohort, comprising individuals with recent-onset depression or psychosis, psychosis risk syndromes, and healthy control individuals.
RESULTS: We identified the following 3 signatures of interest: 1) depressivity, linked to reduced GMV in limbic regions; 2) childhood trauma, associated with GMV in thalamic, frontotemporal, and parietal regions; and 3) a trauma-personality-depressivity signature, relating childhood trauma, personality, and depressivity to GMV in thalamic, occipital, temporal, and limbic regions. SEM revealed that childhood trauma was associated with depressivity directly and also indirectly via a maladaptive personality structure. The trauma-personality-depressivity signature was the strongest predictor of poor functional outcome (balanced accuracy [BAC]Discovery = 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.
METHODS: We used sparse partial least squares (SPLS) to identify multivariate signatures between voxelwise gray matter volume (GMV) and the following 3 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 sample [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 multisite prospective PRONIA (Personalised Prognostic Tools for Early Psychosis Management) cohort, comprising individuals with recent-onset depression or psychosis, psychosis risk syndromes, and healthy control individuals.
RESULTS: We identified the following 3 signatures of interest: 1) depressivity, linked to reduced GMV in limbic regions; 2) childhood trauma, associated with GMV in thalamic, frontotemporal, and parietal regions; and 3) a trauma-personality-depressivity signature, relating childhood trauma, personality, and depressivity to GMV in thalamic, occipital, temporal, and limbic regions. SEM revealed that childhood trauma was associated with depressivity directly and also indirectly via a maladaptive personality structure. The trauma-personality-depressivity signature was the strongest predictor of poor functional outcome (balanced accuracy [BAC]Discovery = 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.