Insight and symptoms severity in schizophrenia explained by the flexibility of brain dynamics and pharmacological treatment

Schizophrenias substantial heterogeneity poses a major challenge for understanding its neurobiological mechanisms and predicting treatment response. Moving toward precision psychiatry, we identified clinically meaningful subtypes and characterised their neural and pharmacological profiles. Clustering of multidimensional clinical feature space revealed two distinct patient subtypes, primarily differentiated by degree of illness insight. In parallel, three symptom-severity groups defined by positive and negative psychopathology dimensions provided a complementary stratification framework. Resting-state fMRI analyses revealed that higher-insight patients exhibited greater dynamic reconfiguration of regional functional connectivity, emerging as the primary neuroimaging feature differentiating subtypes. Multivariate classification and feature importance analysis confirmed the discriminative value of neuroimaging metrics. Across both subtyping approaches, regional flexibility was spatially associated with cortical receptor density maps in a subtype-specific manner, particularly for D2 and 5-HT2A when accounting for estimated antipsychotic receptor occupancies. Additionally, pharmacological-clinical associations were stronger and more spatially widespread in specific subtypes, indicating subtype-dependent pharmacodynamic relationships. Furthermore, structural equation modelling demonstrated that neuroimaging measures mediate receptor pharmacologys influence on clinical outcomes. These findings together show that integrating clinical, neuroimaging, and pharmacological data can uncover biologically grounded schizophrenia subtypes, identify functional biomarkers, and inform personalised therapeutic strategies.