Characterization of the white matter networks in schizophrenia patients with metabolic syndrome undergoing risperidone or clozapine treatment.

Background: The characteristics of the white matter network in schizophrenia patients with metabolic syndrome (MetS) remain unclear. This study analyzed white matter network characteristics in schizophrenia patients with MetS undergoing risperidone or clozapine treatment and explored their potential association with metabolic index and cognitive function. Methods: Diffusion tensor imaging was used to evaluate 19 schizophrenia patients with comorbid MetS (MetS-SZ) and 20 schizophrenia patients without MetS (nMetS-SZ), as well as 25 healthy controls (HC). Differences in these network metrics were compared among these through groups using ANCOVAs and post-hoc testing. Associations between differential network metrics and clinical characteristics were also analyzed. Results: Relative to HC individuals, both MetS-SZ and nMetS-SZ patients exhibited a reduction in bilateral thalamic degree centrality (DC) and nodal efficiency (NE). Relative to the HC group, MetS-SZ patients exhibited reductions in both global efficiency and local efficiency, lower levels of DC in the superior occipital gyrus, and reduced NE in the prefrontal and occipital cortices. Relative to nMetS-SZ patients, MetS-SZ patients also exhibited reduced global efficiency and local efficiency, together with decreases in NE in the prefrontal cortex, medial and paracentral cingulate gyrus, occipital cortex, angular gyrus, and temporal pole. Impairments in executive function were associated with reduced NE values in the right angular gyrus, left medial and paracingulate gyrus. Increases in waist circumference and hip circumference, as well as impairments in executive function, were associated with reductions in NE among patients with schizophrenia. Conclusion: Specific changes in the structure of the white matter network accompanying cognitive deficits were observed in MetS-SZ patients. These results offer new insight into the mechanisms underlying the neural network in schizophrenia patients with MetS.