Aberrant network topological structure of sensorimotor superficial white-matter system in major depressive disorder.

Peng WANG; Yanling BAI; Yang XIAO; Yuhong ZHENG; Li SUN; The Direct CONSORTIUM; Jinhui WANG; Shaowei XUE

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Aberrant network topological structure of sensorimotor superficial white-matter system in major depressive disorder.

Author: Peng WANG ¹ ; Yanling BAI ² ; Yang XIAO ³ ; Yuhong ZHENG ¹ ; Li SUN ¹ ; The Direct CONSORTIUM ¹ ; Jinhui WANG ⁴ ; Shaowei XUE ^{5
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Author Information

1. Center for Cognition and Brain Disorders / Department of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 311121, China.
2. Jing Hengyi School of Education, Hangzhou Normal University, Hangzhou 311121, China.
3. Institute of Mental Health, Peking University Sixth Hospital, Peking University, Beijing 100191, China.
4. Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China.
5. Center for Cognition and Brain Disorders / Department of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 311121, China. xuedrm@
6. com.
Publication Type:Journal Article
Keywords: Brain network; Magnetic resonance imaging (MRI); Major depressive disorder (MDD); White matter
MeSH: Humans; Depressive Disorder, Major/pathology*; White Matter/pathology*; Male; Female; Support Vector Machine; Adult; Magnetic Resonance Imaging; Middle Aged; Case-Control Studies; Sensorimotor Cortex; Brain
From: Journal of Zhejiang University. Science. B 2024;26(1):39-51
CountryChina
Language:English
Abstract: White-matter tracts play a pivotal role in transmitting sensory and motor information, facilitating interhemispheric communication and integrating different brain regions. Meanwhile, sensorimotor disturbance is a common symptom in patients with major depressive disorder (MDD). However, the role of aberrant sensorimotor white-matter system in MDD remains largely unknown. Herein, we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls (HCs) from the DIRECT consortium. White-matter networks were derived from magnetic resonance imaging (MRI) data by combining voxel-based morphometry (VBM) and three-dimensional discrete wavelet transform (3D-DWT) approaches. Support vector machine (SVM) analysis was performed to discriminate MDD patients from HCs. The results indicated that the network topological changes in node degree, node efficiency, and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD. Using network nodal topological properties as classification features, the SVM model could effectively distinguish MDD patients from HCs. These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.