Distinct white matter abnormalities and cognitive impairments in deficit schizophrenia: A cross-sectional diffusion tensor imaging study.

Abstract

Deficit schizophrenia (DS), characterized by persistent and primary negative symptoms, is considered a promising homogeneous subtype of schizophrenia. According to the disconnection hypothesis, abnormalities in white matter fibers are common in schizophrenia. However, comprehensive measurement of white matter metrics and exploration of the relationships between neuroanatomical changes and cognitive functions in DS patients are still unknown. A cross-sectional study was conducted, including 35 DS patients, 37 non-deficit schizophrenia (NDS) patients, and 39 healthy controls (HC), all male and matched for age and education level. The tract-based spatial statistics method was performed to detect differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) among these three groups. Cognitive function in DS and NDS patients was assessed using the Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale. Correlation analyses were performed between diffusion metrics in regions showing differences and clinical scales. The results showed significant differences in diffusion metrics (FA, RD, AD, MD) across DS, NDS, and HC groups, particularly in the corpus callosum, corona radiata, and thalamic radiations. Compare to NDS, DS patients exhibited more reductions in FA and increases in RD, especially in the right posterior thalamic radiation and right superior longitudinal fasciculus. Correlation analysis revealed that lower FA in specific regions was linked to worse cognitive and clinical symptoms. These findings reinforce the dysconnectivity hypothesis of schizophrenia and highlight the distinct pathological mechanisms of white matter impairments in DS. Correlations in crucial white matter regions suggest disruptions in thalamo-cortical feedback loops, potentially contributing to the cognitive impairments observed. This provides a deeper understanding of how structural brain changes relate to clinical symptoms.