Psychiatry research. Neuroimaging · 2026
Abnormal dynamic functional connectivity in different gray matter volume subtypes of patients with major psychiatric disorders.
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Li Shancong, Qin Weiqi, Wei Siyi, Li Bo, Leng Jiahui, Xiao Jian, Chen Yunhui, Shang Tinghuizi, Li Tong, Jiao Yu, Yu Zengyan, Liu Wanqiang, Li Chengchong, Wang Na, Kang Lu, Sun Danhe, Zhao Yuhuan, Lu Sidi, Sun Weidong, Li Ping
Аннотация
BACKGROUND: Major psychiatric disorders (MPDs), including schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and obsessive-compulsive disorder (OCD), have been classified as distinct diagnostic categories based on clinical symptoms. However, neuroimaging studies suggest that these MPDs share similar brain structure and functional characteristics. The present study aim to explore potential subtypes of MPDs based on gray matter volume (GMV) in a trans-diagnostic sample.
METHODS: We involved 84 patients with MPDs (22 SZ, 22 BD, 18 MDD, 22 OCD) and 39 healthy controls (HCs). Voxel-based morphometry (VBM) and dynamic functional connectivity (dFC) analyses were used to investigate the GMV and the dynamic characteristics of the whole brain at rest. The heterogeneity through discriminant analysis (HYDRA) approach was applied to identify the subtypes of MPDs.
RESULTS: Two distinct subtypes were identified, subtype-I (S-I) showed increased GMVs in subcortical brain regions, while subtype-II (S-II) displayed decreased GMVs in cerebral cortex regions. Both S-I and S-II patients showed reduced dFC values within the connected edges at rest. The negative correlation between total GMVs and disease duration were observed in S-II patients.
CONCLUSIONS: The present results may contribute to understand the pathogenesis and biological classification of MPDs.
METHODS: We involved 84 patients with MPDs (22 SZ, 22 BD, 18 MDD, 22 OCD) and 39 healthy controls (HCs). Voxel-based morphometry (VBM) and dynamic functional connectivity (dFC) analyses were used to investigate the GMV and the dynamic characteristics of the whole brain at rest. The heterogeneity through discriminant analysis (HYDRA) approach was applied to identify the subtypes of MPDs.
RESULTS: Two distinct subtypes were identified, subtype-I (S-I) showed increased GMVs in subcortical brain regions, while subtype-II (S-II) displayed decreased GMVs in cerebral cortex regions. Both S-I and S-II patients showed reduced dFC values within the connected edges at rest. The negative correlation between total GMVs and disease duration were observed in S-II patients.
CONCLUSIONS: The present results may contribute to understand the pathogenesis and biological classification of MPDs.