The Deficits of Individual Morphological Covariance Network Architecture in Schizophrenia Patients With and Without Violence

Background: Schizophrenia is associated with a significant increase in the risk of violence, which constitutes a public health concern and contributes to stigma associated with mental illness. Although previous studies revealed structural and functional abnormalities in individuals with violent schizophrenia, the neural basis of psychotic violence remains controversial. Methods: In this study, high-resolution structural magnetic resonance imaging (MRI) data were acquired from 18 individuals with violent schizophrenia (VSZ), 23 individuals with nonviolent schizophrenia (NSZ), and 22 age- and sex-matched healthy controls (HCs). Whole brain voxel-based morphology and individual morphological covariance networks were analysed to reveal differences in grey matter volume (GMV) and individual morphological covariance network topology. Relationships among abnormal GMV, network topology and clinical assessments were examined using correlation analyses. Results: GMV in the hypothalamus gradually decreased from HC and NSZ to VSZ and showed significant differences between all pairs of groups. Graph theory analyses revealed that morphological covariance networks of HC, NSZ, and VSZ exhibited small-worldness. Significant differences in network topology measures, including global efficiency, shortest path length, and nodal degree, were found. Furthermore, changes in GMV and network topology were closely related to clinical performance in the NSZ and VSZ. Conclusions: These findings revealed the important role of local structural abnormalities of the hypothalamus and global network topological impairments in the neuropathology of NSZ and VSZ, providing new insight into the neural basis of and markers for violent and nonviolent schizophrenia to facilitate future accurate clinical diagnosis and targeted treatment.