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.
白质纤维在传递感觉和运动信息、促进两侧大脑间的通讯及整合不同脑区方面发挥着至关重要的作用。与此同时，感觉运动功能异常是重度抑郁症（MDD）患者的常见症状之一。然而，MDD中异常的感觉运动白质系统的作用大部分仍是未知的。本研究调查了来自DIRECT联盟的233名MDD患者与257名匹配的健康对照（HC）的白质形态脑网络的拓扑结构变化。白质网络是通过结合基于体素的形态学测量（VBM）和三维离散小波变换（3D-DWT）方法，从磁共振成像（MRI）数据中构建出来，通过使用支持向量机（SVM）分析区分MDD和HC。结果表明，在MDD中，节点度、节点效率和节点介数的网络拓扑异常主要位于感觉运动浅表白质系统中。利用网络节点拓扑特性作为分类特征，SVM模型能有效区分MDD和HC。上述发现从白质形态脑网络的视角出发，强调了感觉运动系统在MDD脑机制中的重要性。.
Keywords: Brain network; Magnetic resonance imaging (MRI); Major depressive disorder (MDD); White matter.