Journal of affective disorders · 2026
Functional brain network topological properties in cognitive subgroups of first-episode drug-naïve major depressive disorder.
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Yang Xin, Li Yuanyuan, Wang Ziwei, Hu Yongbo, Lü Wenqi, Xu Huifang, Xu Haizhen, Lin Chunting, Zhao Yurou, Jiang Xiao, Rao Shan, Tang Xiangdong, Liu Hesheng, Gong Qiyong, Kuang Weihong
Аннотация
BACKGROUND: Major depressive disorder (MDD) is a heterogeneous psychiatric disorder characterized by significant cognitive impairments, which severely affect the treatment outcomes and social functioning of patients. However, little is known about the brain functional topological changes in different cognitive subgroups of MDD.
METHODS: A total of 164 first-episode drug-naïve MDD patients and 68 healthy controls (HC) underwent neuropsychological assessments and resting-state functional magnetic resonance imaging. K-means clustering was employed to identify potential cognitive subgroups of MDD. A recently developed individualized approach parcellated the cerebral cortex into 92 regions of interest, and whole-brain functional networks were constructed by thresholding the Pearson correlation matrices derived from these regions. Topological properties were assessed using static and dynamic graph-theoretical analyses.
RESULTS: Two cognitive subgroups of MDD were identified: a cognitively impaired subgroup (MDD-CI) and a cognitively preserved subgroup (MDD-CP) with performance comparable to HC. No differences were observed in global network metrics. MDD-CI showed a decrease in the node degree at the right lateral occipitotemporal junction in the visual network, which correlated with poorer visual memory. Dynamic graph analyses revealed no significant alterations after Bonferroni correction.
CONCLUSION: Findings highlight cognitive heterogeneity in MDD and show that reduced degree in the visual network is associated with visual memory deficits.
METHODS: A total of 164 first-episode drug-naïve MDD patients and 68 healthy controls (HC) underwent neuropsychological assessments and resting-state functional magnetic resonance imaging. K-means clustering was employed to identify potential cognitive subgroups of MDD. A recently developed individualized approach parcellated the cerebral cortex into 92 regions of interest, and whole-brain functional networks were constructed by thresholding the Pearson correlation matrices derived from these regions. Topological properties were assessed using static and dynamic graph-theoretical analyses.
RESULTS: Two cognitive subgroups of MDD were identified: a cognitively impaired subgroup (MDD-CI) and a cognitively preserved subgroup (MDD-CP) with performance comparable to HC. No differences were observed in global network metrics. MDD-CI showed a decrease in the node degree at the right lateral occipitotemporal junction in the visual network, which correlated with poorer visual memory. Dynamic graph analyses revealed no significant alterations after Bonferroni correction.
CONCLUSION: Findings highlight cognitive heterogeneity in MDD and show that reduced degree in the visual network is associated with visual memory deficits.