Rumination network dysfunction in major depression: A brain connectome study

• Published in: Progress in neuro-psychopharmacology & biological psychiatry Vol. 98; p. 109819
• Main Authors: Zhang, Ruibin, Kranz, Georg S., Zou, Wenjin, Deng, Yue, Huang, Xuejun, Lin, Kangguang, Lee, Tatia M.C.
• Format: Journal Article
• Language: English
• Published: England Elsevier Inc 02.03.2020
• Subjects: Attentional control; Depression; Functional connectivity; Graph theory; Rumination; Functional connectivity; Depression; Graph theory; Rumination; Attentional control
• ISSN: 0278-5846; 1878-4216; 1878-4216
• DOI: 10.1016/j.pnpbp.2019.109819

Rumination is a central feature of major depressive disorder (MDD). Knowledge of the neural structures that underpin rumination offers significant insight into depressive pathophysiology and may help to develop potential intervention strategies for MDD, a mental illness that has become the leading cause of disability worldwide. Using resting-state fMRI and graph theory, this study adopted a connectome approach to examine the functional topological organization of the neural network associated with rumination in MDD. Data from 96 participants were analyzed, including 51 patients with MDD and 45 healthy controls. We found altered functional integration and segregation of neural networks associated with depressive rumination as indicated by reduced global and local efficiency in MDD patients compared with controls. Interestingly, these metrics correlated positively with depression severity, as measured by the Hamilton Depression Rating Scale. Moreover, mediation analysis indicated that the association between network metrics and depression severity was mediated by the ruminative tendency of patients. Disrupted nodal centralities were located in regions associated with emotional processing, visual mental imagery, and attentional control. Our results highlight rumination as a two-edged sword that reflects a disease-specific neuropathology but also points to a functionality of depressive symptoms with evolutionary meaning. •Ruminative neural network showed small-worldness.•Altered functional network integration and segregation in MDD•Affected regions mainly belonged to the attentional control network.•Network metrics mediated the association between rumination and depression severity.