Altered topology in cortical morphometric similarity network in recurrent major depressive disorder

• Published in: Journal of psychiatric research Vol. 181; pp. 206 - 213
• Main Authors: Xu, Ziyun, Zhou, Zhifeng, Tao, Weiqun, Lai, Wentao, Qian, Long, Cui, Wei, Peng, Bo, Zhang, Yingli, Hou, Gangqiang
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.01.2025
• Subjects: Adult; Cerebral Cortex - diagnostic imaging; Cerebral Cortex - pathology; Depressive Disorder, Major - diagnostic imaging; Depressive Disorder, Major - pathology; Diffusion Tensor Imaging; Female; Graph theory; Humans; Image Processing, Computer-Assisted; Inhomogeneous magnetization transfer imaging; Magnetic Resonance Imaging; Male; Middle Aged; Morphometric similarity network; Nerve Net - diagnostic imaging; Nerve Net - pathology; Neural Pathways - diagnostic imaging; Neural Pathways - pathology; Recurrence; Recurrent depressive disorder; Morphometric similarity network; Graph theory; Recurrent depressive disorder; Diffusion tensor imaging; Inhomogeneous magnetization transfer imaging
• ISSN: 0022-3956; 1879-1379; 1879-1379
• DOI: 10.1016/j.jpsychires.2024.11.038

Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD. Here, we integrated multi-modal features from T1-weighted imaging, diffusion tensor imaging (DTI), and inhomogeneous magnetization transfer imaging (ihMT) to construct MSN. We used graph theory to calculate topological changes in MSN and explore their relationship with the severity and recurrence. The topological properties of 42 RDD patients were compared with 56 age, sex, and education-matched healthy controls. RDD subjects showed significantly decreased global efficiency, increased characteristic path length, reduced nodal efficiencies in the parietal lobe, subcortical area, and temporal lobe, increased betweenness centrality in the left supplementary motor area (SMA), decreased intra-modular connections in the parietal module and decreased inter-modular connections between the parietal and prefrontal modules. Notably, the global efficiency, characteristic path length, local efficiency of the right superior parietal gyrus, and inter-modular connections between the parietal and prefrontal modules were significantly associated with the number of depressive episodes. The betweenness centrality in SMA and the intra-modular connections in the parietal module showed a positive relationship with 17-item Hamilton Rating Scale for Depression (HAMD) scores. The altered topology of MSN may serve as potential underlying pathological mechanisms of RDD. The impaired information integration of the network, particularly the disconnection within the fronto-parietal network, may be associated with the recurrence of depression. The SMA and the fronto-parietal network may be related to the severity of depression.