Individualized cortical gradient and network topology reveal symptom-linked disruptions and neurobiological subtypes in schizophrenia

Abstract Schizophrenia is conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Multivariate brain-symptom analyses revealed a latent dimension reflecting global symptom severity, with graded contributions, strongest for disorganization and weakest for affective symptoms. This dimension was specific to gradient and topology measures, with cortical thickness showing no regional associations and an inverted symptom ordering. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups, with S1, characterized by anterior cingulate involvement, showing higher positive symptom burden at older ages. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.