Multivariate Resting-State Functional Connectivity Features Linked to Transdiagnostic Psychopathology in Early Psychosis

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Abstract

Background: Early psychosis (EP) is characterized by neurobiological changes, including alterations in resting-state functional connectivity (RSFC). We now understand that symptoms and neural changes may overlap across EP diagnostic categories. However, the relationship between RSFC patterns and transdiagnostic symptom dimensions remains poorly understood. Methods: We employed Partial Least Squares correlation to examine multivariate relationships between whole-brain RSFC and clinical symptoms in 124 EP patients (aged 16-35 years) diagnosed with schizophrenia, schizoaffective disorder, or a psychotic mood disorder. RSFC was computed among 216 cortical and subcortical regions. Clinical assessment included 41 symptom measures spanning positive, negative, general psychopathology, and manic dimensions. Results: Analysis revealed one significant latent component (p<0.001) capturing 41.6% of the RSFC-symptom covariance. This component was characterized by increased between-network connectivity, particularly involving sensory-motor, default mode, and subcortical regions including the amygdala and thalamus. The associated symptom profile included cognitive rigidity and arousal dysregulation (stereotyped thinking, anxiety, and somatic concerns), rather than traditional positive or negative symptoms. This brain-behavior relationship was consistent across diagnoses and independent of medication and substance use. The clinical relevance was validated through significant correlations with standardized measures of hostility (r=0.23), negative affect (r=0.25), and perceived stress (r=0.22). Conclusions: Our findings reveal a distinct transdiagnostic phenotype in EP characterized by cognitive inflexibility and arousal dysregulation that is associated with altered integration between sensory, default mode, and subcortical networks. This work suggests that specific patterns of network-level functional connectivity may relate to symptom dimensions that cut across conventional diagnostic boundaries, potentially informing more targeted therapeutic approaches.

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