Yuanyuan Guo , Mingrui Xia , Rong Ye , Tongjian Bai , Yue Wu , Yang Ji , Yue Yu , Gong-Jun Ji , Kai Wang , Yong He , Yanghua Tian
{"title":"电休克疗法可调节重度抑郁症患者大脑连接组的动态变化。","authors":"Yuanyuan Guo , Mingrui Xia , Rong Ye , Tongjian Bai , Yue Wu , Yang Ji , Yue Yu , Gong-Jun Ji , Kai Wang , Yong He , Yanghua Tian","doi":"10.1016/j.biopsych.2024.03.012","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div><span><span>Electroconvulsive therapy (ECT) is an effective treatment for patients with </span>major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain </span>connectome dynamics after ECT in MDD and to explore their associations with treatment outcome.</div></div><div><h3>Methods</h3><div>We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. 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.</div></div><div><h3>Results</h3><div>At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly 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 significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group.</div></div><div><h3>Conclusions</h3><div>We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. 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.</div></div>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":null,"pages":null},"PeriodicalIF":9.6000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder\",\"authors\":\"Yuanyuan Guo , Mingrui Xia , Rong Ye , Tongjian Bai , Yue Wu , Yang Ji , Yue Yu , Gong-Jun Ji , Kai Wang , Yong He , Yanghua Tian\",\"doi\":\"10.1016/j.biopsych.2024.03.012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div><span><span>Electroconvulsive therapy (ECT) is an effective treatment for patients with </span>major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain </span>connectome dynamics after ECT in MDD and to explore their associations with treatment outcome.</div></div><div><h3>Methods</h3><div>We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. 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.</div></div><div><h3>Results</h3><div>At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly 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 significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group.</div></div><div><h3>Conclusions</h3><div>We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. 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.</div></div>\",\"PeriodicalId\":8918,\"journal\":{\"name\":\"Biological Psychiatry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":9.6000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biological Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0006322324011715\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0006322324011715","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder
Background
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.
Methods
We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. 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.
Results
At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly 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 significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group.
Conclusions
We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. 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.
期刊介绍:
Biological Psychiatry is an official journal of the Society of Biological Psychiatry and was established in 1969. It is the first journal in the Biological Psychiatry family, which also includes Biological Psychiatry: Cognitive Neuroscience and Neuroimaging and Biological Psychiatry: Global Open Science. The Society's main goal is to promote excellence in scientific research and education in the fields related to the nature, causes, mechanisms, and treatments of disorders pertaining to thought, emotion, and behavior. To fulfill this mission, Biological Psychiatry publishes peer-reviewed, rapid-publication articles that present new findings from original basic, translational, and clinical mechanistic research, ultimately advancing our understanding of psychiatric disorders and their treatment. The journal also encourages the submission of reviews and commentaries on current research and topics of interest.