Electroconvulsive therapy regulates brain connectome dynamics in patients with major depressive disorder.
Journal: Biological psychiatry
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Affiliated Institutions:
Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China;; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China;; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China;; Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China;; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China;; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China;; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.
Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China.
School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China;; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China;; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China;; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.
Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China;; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China;; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China;; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China;; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China;; Anhui Institute of Translational Medicine, Hefei, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China;; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China;; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China;; Chinese Institute for Brain Research, Beijing, China. Electronic address: yong.he@bnu.edu.cn.
Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China;; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China;; Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China;. Electronic address: ayfytyh@.com.
Abstract summary
Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain connectome dynamics after ECT in MDD and to explore their associations with treatment outcome.We collected longitudinal resting-state fMRI data from 80 MDD patients (50 with suicidal ideation and 30 without; SI and NSI, respectively) before and after ECT and 37 age- and sex-matched healthy controls. A multilayer network model was used to assess modular switching over time in functional connectomes. Support vector regression was used to assess whether pre-ECT network dynamics could predict treatment response in terms of symptom severity.At baseline, MDD patients had lower global modularity and higher modular variability in functional connectomes compared to controls. Network modularity increased and network variability decreased after ECT in MDD patients, predominantly located in the default mode and somatomotor networks. Moreover, ECT was associated with decreased modular variability in the left dorsal anterior cingulate cortex of MDD-SI, but not MDD-NSI patients, and pre-ECT modular variability could significantly predict symptom improvement in the MDD-SI group, but not in the MDD-NSI group.We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with suicidal ideation. This study advances our understanding of the neural mechanisms of ECT from a dynamic brain network perspective and suggests potential prognostic biomarkers for predicting ECT efficacy in patients with MDD.
Authors & Co-authors:
Guo
Xia
Ye
Bai
Wu
Ji
Yu
Ji
Wang
He
Tian
Study Outcome
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