Schizophrenia exhibits significant variability in its neuroanatomical manifestations, particularly in brain atrophy patterns. This variability poses a challenge to the development of consistent biomarkers and targeted treatments. We hypothesized that, despite this heterogeneity, atrophy coordinates would converge onto a common brain network specific to schizophrenia. We tested this hypothesis using the human connectome as a wiring diagram and applied coordinate network mapping (CNM)—a novel method that maps heterogeneous brain coordinates onto a network-level model. We analyzed data from 113 published studies, encompassing over 11,000 individuals, including patients with schizophrenia (n = 3,756), high-risk individuals (n = 1,507), and healthy controls (n = 6,007). Our findings revealed a distinct brain network, termed the 'schizophrenia network', which is preferentially connected to atrophy coordinates in schizophrenia. After correcting for multiple comparisons (FWEp < 0.05), the anterior cingulate cortex and the bilateral mid-insula emerged as key nodes within this network. This network was unique to schizophrenia and was distinct from atrophy patterns observed in high-risk populations, normal aging (n = 4,195), neurodegenerative diseases (n = 3,707), or other psychiatric conditions (n = 3,432). Remarkably, this network remained stable across the course of the disease and various symptom clusters. Additionally, in an independent cohort of patients with penetrating head trauma (n = 181), schizophrenia-related atrophy patterns showed a negative correlation with lesions implicated in psychosis-related thought processes (p < 0.05). To conclude, we have identified a unique and stable brain network associated with schizophrenia. This network's stability across disease progression suggests it may be a potential target for developing biomarkers and therapeutic interventions. Our findings also offer a new perspective on schizophrenia, suggesting that brain atrophy may represent a compensatory mechanism.
A unified brain network associated with heterogeneous atrophy patterns in schizophrenia
Liloia, Donato;
2025-01-01
Abstract
Schizophrenia exhibits significant variability in its neuroanatomical manifestations, particularly in brain atrophy patterns. This variability poses a challenge to the development of consistent biomarkers and targeted treatments. We hypothesized that, despite this heterogeneity, atrophy coordinates would converge onto a common brain network specific to schizophrenia. We tested this hypothesis using the human connectome as a wiring diagram and applied coordinate network mapping (CNM)—a novel method that maps heterogeneous brain coordinates onto a network-level model. We analyzed data from 113 published studies, encompassing over 11,000 individuals, including patients with schizophrenia (n = 3,756), high-risk individuals (n = 1,507), and healthy controls (n = 6,007). Our findings revealed a distinct brain network, termed the 'schizophrenia network', which is preferentially connected to atrophy coordinates in schizophrenia. After correcting for multiple comparisons (FWEp < 0.05), the anterior cingulate cortex and the bilateral mid-insula emerged as key nodes within this network. This network was unique to schizophrenia and was distinct from atrophy patterns observed in high-risk populations, normal aging (n = 4,195), neurodegenerative diseases (n = 3,707), or other psychiatric conditions (n = 3,432). Remarkably, this network remained stable across the course of the disease and various symptom clusters. Additionally, in an independent cohort of patients with penetrating head trauma (n = 181), schizophrenia-related atrophy patterns showed a negative correlation with lesions implicated in psychosis-related thought processes (p < 0.05). To conclude, we have identified a unique and stable brain network associated with schizophrenia. This network's stability across disease progression suggests it may be a potential target for developing biomarkers and therapeutic interventions. Our findings also offer a new perspective on schizophrenia, suggesting that brain atrophy may represent a compensatory mechanism.
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