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Neurocognitive deficits, psychotrauma, and inflammation shape major depressive disorder and its phenome features

Wang, X.; Wang, P.; Niu, M.; Yangyang, C.; Almulla, A. F.; Chen, C.; Li, J.; Zhang, Y.; Maes, M.

2026-02-12 psychiatry and clinical psychology
10.64898/2026.02.11.26346056 medRxiv
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BackgroundMajor depressive disorder (MDD) involves immune-metabolic dysregulation, psychosocial adversity, and multidomain cognitive disturbances, yet single cognitive indices often show small and inconsistent effects. We derived a multivariate Cambridge Neuropsychological Test Automated Battery (CANTAB)-based cognitive phenotype ("cognitype") and tested whether it adds explanatory value beyond adverse childhood experiences (ACEs) and an acute-phase protein (APP) index in acute-phase MDD. MethodsEighty-seven acute-phase MDD patients and 40 healthy controls completed CANTAB testing; key outcomes from DMS, RVP, OTS, and ERT were summarized as a cognitype score (PC1). ACEs were assessed, and peripheral inflammatory markers were combined into an APP index. Logistic and multiple regression models tested discrimination between MDD and controls and prediction of multidimensional phenome features (affective, physio-somatic, vegetative, recurrence-related, personality, and suicidality domains). ResultsIndividual CANTAB outcomes showed limited between-group differences after FDR correction, but multivariable models integrating cognitive measures with ACEs and APP robustly discriminated MDD from controls (AUC up to 0.907). The cognitype independently predicted multiple phenome domains when modeled alongside ACEs and APP, and their combined effects explained [~]40-55% of variance across symptom dimensions. ConclusionA data-driven cognitype derived from core CANTAB tasks captures clinically meaningful cognitive variation in acute-phase MDD and contributes significant predictive value beyond psychosocial adversity and inflammatory activation. Integrating cognition, ACEs, and inflammation improves characterization of symptom heterogeneity and supports precision approaches targeting neurocognitive-immune-environmental mechanisms.

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