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Wu D, Yu Y, Wang H, Zhang J, You J, Kai Y, Zhao Y, Wu Y, Wang K, Tian Y. Electroconvulsive therapy modulates brain functional stability in patients with major depressive disorder. J Affect Disord 2025; 374:312-322. [PMID: 39818339 DOI: 10.1016/j.jad.2025.01.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2024] [Revised: 01/04/2025] [Accepted: 01/13/2025] [Indexed: 01/18/2025]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but the underlying neuromodulatory mechanisms remain largely unknown. Functional stability represents a newly developed method based on the dynamic functional connectivity framework. This study aimed to explore ECT-evoked changes in functional stability and their relationship with clinical outcomes. METHODS We collected longitudinal resting-state fMRI data from 58 MDD patients (39 of whom experienced remission after ECT, and 19 did not, referred to as remitters and non-remitters, respectively) and 42 age- and sex-matched healthy controls. We utilized voxel-level whole-brain functional stability analysis to examine the neural effects of ECT in MDD patients. RESULTS After ECT, MDD patients showed increased functional stability in the bilateral middle frontal gyrus, orbital part, and bilateral angular gyrus as well as decreased functional stability in the right fusiform gyrus. Additionally, the subgroup analysis revealed that functional stability of the right hippocampus significantly decreased in remitters yet significantly increased in non-remitters after ECT. CONCLUSIONS Our data demonstrated the modulatory effect of ECT on brain functional stability in MDD patients and further revealed the differences in this modulation between patients with and without clinical remission, highlighting the potential usefulness of functional stability as a prognostic biomarker for monitoring ECT efficacy and stratifying MDD patients to optimize treatment strategies.
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Affiliation(s)
- Dongpeng Wu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Yue Yu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Hongping Wang
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Jiahua Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China; School of Mental Health and Psychological Sciences, Anhui Medical University, 230022 Hefei, China
| | - Jingyi You
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China
| | - Yiao Kai
- Department of Anatomy, Anhui Medical University, Hefei 230032, Anhui, China
| | - Yue Zhao
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China
| | - Yue Wu
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, 230022 Hefei, China; School of Mental Health and Psychological Sciences, Anhui Medical University, 230022 Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, 230022 Hefei, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Anhui Province, Hefei 230022, China; Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China.
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Guo Y, Xia M, Ye R, Bai T, Wu Y, Ji Y, Yu Y, Ji GJ, Wang K, He Y, Tian Y. Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder. Biol Psychiatry 2024; 96:929-939. [PMID: 38521158 DOI: 10.1016/j.biopsych.2024.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 02/22/2024] [Accepted: 03/06/2024] [Indexed: 03/25/2024]
Abstract
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.
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Affiliation(s)
- Yuanyuan Guo
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mingrui Xia
- 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
| | - Rong Ye
- 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
| | - Tongjian Bai
- 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
| | - Yue Wu
- Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yue Yu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Gong-Jun Ji
- 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
| | - Kai Wang
- 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
| | - Yong He
- 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.
| | - Yanghua Tian
- 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; Department of Psychology and Sleep Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China.
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Li Y, Yin Y, Yu Y, Hu X, Liu X, Wu S. The potential predictors for treatment-resistance depression after selective serotonin reuptake inhibitors therapy in Han Chinese: A resting-state functional magnetic resonance imaging study. Early Interv Psychiatry 2024; 18:698-709. [PMID: 38320861 DOI: 10.1111/eip.13509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/26/2023] [Accepted: 01/24/2024] [Indexed: 02/08/2024]
Abstract
AIM Selective serotonin reuptake inhibitors (SSRIs) are among the most important antidepressants. However, there is limited research on predicting the occurrence of treatment-resistant depression (TRD) after 5 years. Examining the predictive effect of TRD occurrence using resting-state fMRI in patients initiating SSRIs treatment at the onset of major depressive disorder (MDD) could potentially enhance TRD management. METHODS A total of 60 first-episode drug-naive MDD patients who met the criteria, along with 41 healthy controls of Han Chinese ethnicity, were recruited. All MDD patients received SSRIs as the initial treatment for relieving depressive symptoms. Resting-state fMRI scans were conducted for all subjects. Follow-up assessments were conducted over a period of five years, during which MDD patients were categorized into treatment-resistant depression (TRD) and non-treatment-resistant depression (NRD) groups based on disease progression. Amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and Regional Homogeneity (ReHo) values were calculated and compared among the three groups. Additionally, receiver operating characteristic (ROC) curves were employed to identify potential predictors. RESULTS After 5 years of follow-up, it was found that 43 MDD patients were classified as NRD, while 17 were classified as TRD. In comparison to TRD, NRD exhibited decreased ALFF in the left middle cingulum gyrus (MCG.L) and in the right middle frontal gyrus (MFG.R), as well as decreased ReHo in MCG.L. Furthermore, NRD showed increased fALFF in the left precuneus (PCUN.L). The area under the curve (AUC) values were as follows: 0.724 (MCG.L by ALFF), 0.732 (MFG.R), 0.767 (PCUN.L), 0.774 (MCG.L by ReHo), 0.878 (combined), 0.547 (HAMD), and 0.408 (HAMA) respectively. CONCLUSION The findings suggest that PCUN.L, MFG.R, MCG.L, and the combined measures may indicate the possibility of developing TRD after 5 years when SSRIs are used as the initial therapy for relieving depressive symptoms in MDD patients.
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Affiliation(s)
- Yi Li
- Department of Radiology, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Yan Yin
- Department of Psychosomatic, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Yingyi Yu
- Department of Radiology, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Xiwen Hu
- The sixth ward of Psychiatry Department, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
| | - XiaoYan Liu
- The fifth ward of Psychiatry Department, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Sha Wu
- Department of intensive care unit, Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Hangzhou, China
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Hu X, Cheng B, Tang Y, Long T, Huang Y, Li P, Song Y, Song X, Li K, Yin Y, Chen X. Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder. Brain Res 2024; 1837:148986. [PMID: 38714227 DOI: 10.1016/j.brainres.2024.148986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/06/2024] [Accepted: 05/04/2024] [Indexed: 05/09/2024]
Abstract
The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.
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Affiliation(s)
- Xiao Hu
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuying Tang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Tong Long
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yan Huang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Pei Li
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yu Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Xiyang Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Kun Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yijie Yin
- School of Sociality and Psychology, Southwest Minzu University, Chengdu 610041, China
| | - Xijian Chen
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China.
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Yu X, Chen K, Ma Y, Bai T, Zhu S, Cai D, Zhang X, Wang K, Tian Y, Wang J. Molecular basis underlying changes of brain entropy and functional connectivity in major depressive disorders after electroconvulsive therapy. CNS Neurosci Ther 2024; 30:e14690. [PMID: 38529527 PMCID: PMC10964037 DOI: 10.1111/cns.14690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/03/2024] [Accepted: 02/23/2024] [Indexed: 03/27/2024] Open
Abstract
INTRODUCTION Electroconvulsive therapy (ECT) is widely used for treatment-resistant depression. However, it is unclear whether/how ECT can be targeted to affect brain regions and circuits in the brain to dynamically regulate mood and cognition. METHODS This study used brain entropy (BEN) to measure the irregular levels of brain systems in 46 major depressive disorder (MDD) patients before and after ECT treatment. Functional connectivity (FC) was further adopted to reveal changes of functional couplings. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal genetic and molecular basis of the changes of BEN and functional connectivities. RESULTS Compared to pretreatment, the BEN in the posterior cerebellar lobe (PCL) significantly decreased and FC between the PCL and the right temporal pole (TP) significantly increased in MDD patients after treatment. Moreover, we found that these changes of BEN and FC were closely associated with genes' expression profiles involved in MAPK signaling pathway, GABAergic synapse, and dopaminergic synapse and were significantly correlated with the receptor/transporter density of 5-HT, norepinephrine, glutamate, etc. CONCLUSION: These findings suggest that loops in the cerebellum and TP are crucial for ECT regulation of mood and cognition, which provides new evidence for the antidepressant effects of ECT and the potential molecular mechanism leading to cognitive impairment.
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Affiliation(s)
- Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
| | - Kexuan Chen
- Medical SchoolKunming University of Science and TechnologyKunmingChina
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
| | - Tongjian Bai
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
| | - Shunli Zhu
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Defang Cai
- The Second People's Hospital of YuxiThe Affiliated Hospital of Kunming University of Science and TechnologyYuxiChina
| | - Xing Zhang
- The Second People's Hospital of YuxiThe Affiliated Hospital of Kunming University of Science and TechnologyYuxiChina
| | - Kai Wang
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
- Anhui Province Clinical Research Center for Neurological DiseaseHefeiChina
| | - Yanghua Tian
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
- Anhui Province Clinical Research Center for Neurological DiseaseHefeiChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiChina
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
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Wang H, Zhang T, Zu M, Fan S, Kai Y, Zhang J, Ji Y, Pang X, Tian Y. Electroconvulsive therapy enhances degree centrality in the orbitofrontal cortex in depressive rumination. Psychiatry Res Neuroimaging 2024; 337:111765. [PMID: 38104485 DOI: 10.1016/j.pscychresns.2023.111765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/13/2023] [Accepted: 12/02/2023] [Indexed: 12/19/2023]
Abstract
Depressive rumination has been implicated in the onset, duration, and treatment response of refractory depression. Electroconvulsive therapy (ECT) is remarkably effective in treatment of refractory depression by modulating the functional coordination between brain hubs. However, the mechanisms by which ECT regulates depressive rumination remain unsolved. We investigated degree centrality (DC) in 32 pre- and post-ECT depression patients as well as 38 matched healthy controls. An identified brain region was defined as the seed to calculate functional connectivity (FC) in whole brains. Rumination was measured by the Ruminative Response Scale (RRS) and its relationships with identified DC and FC alterations were examined. We found a significant negative correlation between DC of the right orbitofrontal cortex (rOFC) before ECT and brooding level before and after treatment. Moreover, rOFC DC increased after ECT. DC of the left superior temporal gyrus (lSTG) was positively correlated with reflective level before intervention, while lSTG DC decreased after ECT. Patients showed elevated FC in the rOFC with default mode network. No significant association was found between decreased RRS scores and changes in DC and FC. Our findings suggest that functional changes in rOFC and lSTG may be associated with the beneficial effects of ECT on depressive rumination.
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Affiliation(s)
- Hongping Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Ting Zhang
- Department of Psychiatry, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Meidan Zu
- Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Siyu Fan
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yiao Kai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jiahua Zhang
- School of Mental Health and Psychological Science, Anhui Medical University, Hefei, Anhui, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiaonan Pang
- Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China; Department of Neurology, Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
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Gao J, Chen M, Xiao D, Li Y, Zhu S, Li Y, Dai X, Lu F, Wang Z, Cai S, Wang J. Classification of major depressive disorder using an attention-guided unified deep convolutional neural network and individual structural covariance network. Cereb Cortex 2023; 33:2415-2425. [PMID: 35641181 DOI: 10.1093/cercor/bhac217] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 11/12/2022] Open
Abstract
Major depressive disorder (MDD) is the second leading cause of disability worldwide. Currently, the structural magnetic resonance imaging-based MDD diagnosis models mainly utilize local grayscale information or morphological characteristics in a single site with small samples. Emerging evidence has demonstrated that different brain structures in different circuits have distinct developmental timing, but mature coordinately within the same functional circuit. Thus, establishing an attention-guided unified classification framework with deep learning and individual structural covariance networks in a large multisite dataset could facilitate developing an accurate diagnosis strategy. Our results showed that attention-guided classification could improve the classification accuracy from primary 75.1% to ultimate 76.54%. Furthermore, the discriminative features of regional covariance connectivities and local structural characteristics were found to be mainly located in prefrontal cortex, insula, superior temporal cortex, and cingulate cortex, which have been widely reported to be closely associated with depression. Our study demonstrated that our attention-guided unified deep learning framework may be an effective tool for MDD diagnosis. The identified covariance connectivities and structural features may serve as biomarkers for MDD.
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Affiliation(s)
- Jingjing Gao
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Mingren Chen
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Die Xiao
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yue Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Shunli Zhu
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yanling Li
- School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China
| | - Xin Dai
- School of Automation, Chongqing University, Chongqing 400044, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Zhengning Wang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Shimin Cai
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China
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Stoyanov D, Khorev V, Paunova R, Kandilarova S, Simeonova D, Badarin A, Hramov A, Kurkin S. Resting-State Functional Connectivity Impairment in Patients with Major Depressive Episode. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14045. [PMID: 36360924 PMCID: PMC9656256 DOI: 10.3390/ijerph192114045] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/14/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
AIM This study aims to develop new approaches to characterize brain networks to potentially contribute to a better understanding of mechanisms involved in depression. METHOD AND SUBJECTS We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed investigating functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were developed at a functional network level, using a false discovery rate method. Linear discriminant analysis was used to differentiate between the two groups. RESULTS AND DISCUSSION Significant differences in functional connectivity (FC) between depressed patients vs. healthy controls was demonstrated, with brain regions including the lingual gyrus, cerebellum, midcingulate cortex and thalamus more prominent in healthy subjects as compared to depression where the orbitofrontal cortex emerged as a key node. Linear discriminant analysis demonstrated that full-connectivity matrices were the most precise in differentiating between depression vs. health subjects. CONCLUSION The study provides supportive evidence for impaired functional connectivity networks in MDE patients.
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Affiliation(s)
- Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Vladimir Khorev
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Denitsa Simeonova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Artem Badarin
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
| | - Alexander Hramov
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
| | - Semen Kurkin
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
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9
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Yi S, Wang Z, Yang W, Huang C, Liu P, Chen Y, Zhang H, Zhao G, Li W, Fang J, Liu J. Neural activity changes in first-episode, drug-naïve patients with major depressive disorder after transcutaneous auricular vagus nerve stimulation treatment: A resting-state fMRI study. Front Neurosci 2022; 16:1018387. [PMID: 36312012 PMCID: PMC9597483 DOI: 10.3389/fnins.2022.1018387] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 09/26/2022] [Indexed: 11/14/2022] Open
Abstract
Introduction Major depressive disorder (MDD) is a disease with prominent individual, medical, and economic impacts. Drug therapy and other treatment methods (such as Electroconvulsive therapy) may induce treatment-resistance and have associated side effects including loss of memory, decrease of reaction time, and residual symptoms. Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel and non-invasive treatment approach which stimulates brain structures with no side-effects. However, it remains little understood whether and how the neural activation is modulated by taVNS in MDD patients. Herein, we used the regional homogeneity (ReHo) to investigate the brain activity in first-episode, drug-naïve MDD patients after taVNS treatment. Materials and methods Twenty-two first-episode, drug-naïve MDD patients were enrolled in the study. These patients received the first taVNS treatment at the baseline time, and underwent resting-state MRI scanning twice, before and after taVNS. All the patients then received taVNS treatments for 4 weeks. The severity of depression was assessed by the 17-item Hamilton Depression Rating Scale (HAMD) at the baseline time and after 4-week’s treatment. Pearson analysis was used to assess the correlation between alterations of ReHo and changes of the HAMD scores. Two patients were excluded due to excessive head movement, two patients lack clinical data in the fourth week, thus, imaging analysis was performed in 20 patients, while correlation analysis between clinical and imaging data was performed in only 18 patients. Results There were significant differences in the ReHo values in first-episode, drug-naïve MDD patients between pre- or post- taVNS. The primary finding is that the patients exhibited a significantly lower ReHo in the left/right median cingulate cortex, the left precentral gyrus, the left postcentral gyrus, the right calcarine cortex, the left supplementary motor area, the left paracentral lobule, and the right lingual gyrus. Pearson analysis revealed a positive correlation between changes of ReHo in the right median cingulate cortex/the left supplementary motor area and changes of HAMD scores after taVNS. Conclusion The decreased ReHo were found after taVNS. The sensorimotor, limbic and visual-related brain regions may play an important role in understanding the underlying neural mechanisms and be the target brain regions in the further therapy.
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Affiliation(s)
- Sijie Yi
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhi Wang
- Department of Radiology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wenhan Yang
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chuxin Huang
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ping Liu
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yanjing Chen
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Huiting Zhang
- MR Scientific Marketing, Siemens Healthineers Ltd., Wuhan, China
| | - Guangju Zhao
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Weihui Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Jun Liu,
| | - Jiliang Fang
- Department of Radiology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- Jiliang Fang,
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China
- Department of Radiology Quality Control Center, Changsha, China
- Weihui Li,
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10
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Li Y, Yu X, Ma Y, Su J, Li Y, Zhu S, Bai T, Wei Q, Becker B, Ding Z, Wang K, Tian Y, Wang J. Neural signatures of default mode network in major depression disorder after electroconvulsive therapy. Cereb Cortex 2022; 33:3840-3852. [PMID: 36089839 DOI: 10.1093/cercor/bhac311] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/17/2022] [Accepted: 07/08/2022] [Indexed: 11/12/2022] Open
Abstract
Functional abnormalities of default mode network (DMN) have been well documented in major depressive disorder (MDD). However, the association of DMN functional reorganization with antidepressant treatment and gene expression is unclear. Moreover, whether the functional interactions of DMN could predict treatment efficacy is also unknown. Here, we investigated the link of treatment response with functional alterations of DMN and gene expression with a comparably large sample including 46 individuals with MDD before and after electroconvulsive therapy (ECT) and 46 age- and sex-matched healthy controls. Static and dynamic functional connectivity (dFC) analyses showed increased intrinsic/static but decreased dynamic functional couplings of inter- and intra-subsystems and between nodes of DMN. The changes of static functional connections of DMN were spatially correlated with brain gene expression profiles. Moreover, static and dFC of the DMN before treatment as features could predict depressive symptom improvement following ECT. Taken together, these results shed light on the underlying neural and genetic basis of antidepressant effect of ECT and the intrinsic functional connectivity of DMN have the potential to serve as prognostic biomarkers to guide accurate personalized treatment.
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Affiliation(s)
- Yuanyuan Li
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Jing Su
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Yue Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Shunli Zhu
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Tongjian Bai
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Qiang Wei
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Benjamin Becker
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Zhiyong Ding
- Medical Imaging Department, Maternal and Child Health-care Hospital of Qujing, Qujing 655000, China
| | - Kai Wang
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China.,Anhui Province Clinical Research Center for Neurological Disease, Hefei 230022, China
| | - Yanghua Tian
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China.,Anhui Province Clinical Research Center for Neurological Disease, Hefei 230022, China.,Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.,Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
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11
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Li Y, Li Y, Wei Q, Bai T, Wang K, Wang J, Tian Y. Mapping intrinsic functional network topological architecture in major depression disorder after electroconvulsive therapy. J Affect Disord 2022; 311:103-109. [PMID: 35594966 DOI: 10.1016/j.jad.2022.05.067] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/07/2022] [Accepted: 05/12/2022] [Indexed: 12/22/2022]
Abstract
Disrupted topological organization of functional brain networks has been well documented in major depressive disorder (MDD). However, there is no report about how electroconvulsive therapy (ECT), a rapid way for depression remission, affects whole-brain functional network topological architecture to improve clinical symptoms in individuals with MDD. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for twenty-four MDD patients before and after receiving ECT and 25 gender-, age- and education-matched healthy controls (HC). The functional brain network for each subject was mapped using Brainnetome Atlas and graph-theory was applied to measure topological properties for both binary and weighted network. The results showed that ECT can significantly increase shortest path length and decrease global efficiency in MDD patients. In addition, significant alterations in nodal degree, nodal efficiency as well as between nodal functional connectivity strength were found in MDD patients after ECT. The network nodes showing changed degree, efficiency and connectivity were primarily distributed in default mode network (DMN), fronto-parietal network (FPN), and limbic system. Our findings demonstrates that ECT improves depressive symptoms by reorganizing disrupted network topological architecture in MDD patients and highlights the important role of functional reorganization of DMN, FPN, and limbic network contributing to depression remission.
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Affiliation(s)
- Yuanyuan Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Yue Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Qiang Wei
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China
| | - Tongjian Bai
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China
| | - Kai Wang
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China; Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China; Anhui Province clinical research center for neurological disease, Hefei 230022, China
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China; Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China.
| | - Yanghua Tian
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China; Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China; Anhui Province clinical research center for neurological disease, Hefei 230022, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230022, China.
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12
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Zheng W, He M, Gu LM, Lao GH, Wang DF, Mai JX, Wu HW, Nie S, Huang X. Early improvement as a predictor of final remission in patients with treatment-resistant depression receiving electroconvulsive therapy with ketofol anesthesia. J Affect Disord 2022; 310:223-227. [PMID: 35550826 DOI: 10.1016/j.jad.2022.05.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 03/20/2022] [Accepted: 05/05/2022] [Indexed: 10/18/2022]
Abstract
OBJECTIVE To examine whether early symptom improvement can predict eventual remission following electroconvulsive therapy (ECT) with ketamine plus propofol (ketofol) anesthesia in patients with treatment-resistant depression (TRD). METHODS Thirty Han Chinese subjects suffering from TRD were administered ketofol anesthesia during ECT. Remission was defined as a score of ≤7 on the 17-item Hamilton Depression Rating Scale (HAMD-17). Receiver operating characteristic (ROC) curves were applied to identify the number of ECT sessions (i.e., 1, 2, 3, or 4 ECT sessions) that had the best discriminative capacity for eventual remission. The best definition of early improvement to predict final remission was determined by using the Youden index. RESULTS Of the 30 patients with TRD, 16 (53.3%) and 30 (100%) were classified as remitters and responders, respectively. A 45% reduction in the HAMD-17 score after 3 ECT sessions was the optimum definition of early improvement in the prediction of eventual remission, with relatively good sensitivity (88%) and specificity (93%). Patients with than without early improvement had a greater possibility of achieving favorable ECT outcomes. CONCLUSION Final remission of TRD following ECT with ketofol anesthesia appeared to be predicted by early improvement, as indicated by a 45% reduction in HAMD-17 score after 3 ECT sessions.
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Affiliation(s)
- Wei Zheng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Mei He
- Nanning Fifth People's Hospital, Nanning, China
| | - Li-Mei Gu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Guo-Hui Lao
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Dan-Feng Wang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jian-Xin Mai
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hua-Wang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sha Nie
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Xiong Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
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13
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Yang Y, Li X, Cui Y, Liu K, Qu H, Lu Y, Li W, Zhang L, Zhang Y, Song J, Lv L. Reduced Gray Matter Volume in Orbitofrontal Cortex Across Schizophrenia, Major Depressive Disorder, and Bipolar Disorder: A Comparative Imaging Study. Front Neurosci 2022; 16:919272. [PMID: 35757556 PMCID: PMC9226907 DOI: 10.3389/fnins.2022.919272] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/02/2022] [Indexed: 11/29/2022] Open
Abstract
Schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD) are severe psychiatric disorders and share common characteristics not only in clinical symptoms but also in neuroimaging. The purpose of this study was to examine common and specific neuroanatomical features in individuals with these three psychiatric conditions. In this study, 70 patients with SZ, 85 patients with MDD, 42 patients with BD, and 95 healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) analysis was used to explore brain imaging characteristics. Psychopathology was assessed using the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI), the Young Mania Rating Scale (YMRS), and the Positive and Negative Syndrome Scale (PANSS). Cognition was assessed using the digit symbol substitution test (DSST), forward-digital span (DS), backward-DS, and semantic fluency. Common reduced gray matter volume (GMV) in the orbitofrontal cortex (OFC) region was found across the SZ, MDD, and BD. Specific reduced GMV of brain regions was also found. For patients with SZ, we found reduced GMV in the frontal lobe, temporal pole, occipital lobe, thalamus, hippocampus, and cerebellum. For patients with MDD, we found reduced GMV in the frontal and temporal lobes, insular cortex, and occipital regions. Patients with BD had reduced GMV in the medial OFC, inferior temporal and fusiform regions, insular cortex, hippocampus, and cerebellum. Furthermore, the OFC GMV was correlated with processing speed as assessed with the DSST across four groups (r = 0.17, p = 0.004) and correlated with the PANSS positive symptoms sub-score in patients with SZ (r = − 0.27, p = 0.026). In conclusion, common OFC alterations in SZ, MDD, and BD provided evidence that this region dysregulation may play a critical role in the pathophysiology of these three psychiatric disorders.
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Affiliation(s)
- Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xue Li
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yue Cui
- Brainnetome Center and Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Kang Liu
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Haoyang Qu
- Department of Psychiatry, The Second Clinic College of Xinxiang Medical University, Xinxiang, China
| | - Yanli Lu
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luwen Zhang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Jinggui Song
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
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14
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Wu Y, Ji Y, Bai T, Wei Q, Zu M, Guo Y, Lv H, Zhang A, Qiu B, Wang K, Tian Y. Nodal degree changes induced by electroconvulsive therapy in major depressive disorder: Evidence in two independent cohorts. J Affect Disord 2022; 307:46-52. [PMID: 35331825 DOI: 10.1016/j.jad.2022.03.045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/15/2022] [Accepted: 03/17/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVE Electroconvulsive therapy (ECT), a rapidly acting treatment for major depressive disorder (MDD), has been reported to regulate brain networks. Nodes and their connections are the main components of the brain network and are essential for establishing and maintaining effective information transmission. This study aimed to evaluate the role of nodes in mediating antidepressant effects of ECT. METHODS Voxel-based nodal degree analysis was performed in 42 patients with MDD receiving ECT and 42 matched healthy controls at two time points to identify the nodal changes induced by ECT. Verification analysis was evaluated in a second, independent cohort of 23 MDD patients. RESULTS MDD patients showed improved nodal degree of the bilateral angular cortex (AG), precuneus, inferior frontal gyrus (IFG) and the right superior frontal gyrus (SFG) after ECT, and the increased nodal degree index (IND) rate of the AG and precuneus were negatively correlated to the depressive changes following ECT. Furthermore, validation analysis revealed a similar pattern of IND abnormalities in the first and second cohort of MDD patients. CONCLUSION ECT regulates the disrupted nodal degree of the AG and precuneus to achieve an antidepressant effect. This study may provide further insights into the pathogenesis of depression and provide potential targets for antidepressant pharmacotherapies.
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Affiliation(s)
- Yue Wu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Tongjian Bai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
| | - Qiang Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
| | - Meidan Zu
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Yuanyuan Guo
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Huaming Lv
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Aiguo Zhang
- Anhui Mental Health Center, Hefei 230022, China
| | - Bensheng Qiu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China; The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
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15
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Pang Y, Wei Q, Zhao S, Li N, Li Z, Lu F, Pang J, Zhang R, Wang K, Chu C, Tian Y, Wang J. Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder. J Affect Disord 2022; 306:47-54. [PMID: 35304230 DOI: 10.1016/j.jad.2022.03.035] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 01/16/2022] [Accepted: 03/10/2022] [Indexed: 12/22/2022]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response. METHOD Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity. RESULTS MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms. CONCLUSIONS The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.
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Affiliation(s)
- Yajing Pang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Qiang Wei
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Shanshan Zhao
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Nan Li
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Zhihui Li
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Rui Zhang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Kai Wang
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; China National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
| | - Yanghua Tian
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, 650500, China.
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16
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Ping L, Zhou C, Sun S, Wang W, Zheng Q, You Z. Alterations in resting-state whole-brain functional connectivity pattern similarity in bipolar disorder patients. Brain Behav 2022; 12:e2580. [PMID: 35451228 PMCID: PMC9120726 DOI: 10.1002/brb3.2580] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 02/04/2022] [Accepted: 03/20/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Previous neuroimaging studies have extensively demonstrated many signs of functionally spontaneous local neural activity abnormalities in bipolar disorder (BD) patients using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to identify the changes of voxel-wise whole-brain functional connectivity pattern and its corresponding functional connectivity changes remain largely unclear in BD patients. The current study aimed to investigate the voxel-wise changes of functional connectivity patterns in BD patients using publicly available data from the UCLA CNP LA5c Study. METHODS A total of 45 BD patients and 115 healthy control subjects were finally included and whole-brain functional connectivity homogeneity (FcHo) was calculated from their rs-fMRI. Moreover, the alterations of corresponding functional connectivity were subsequently identified using seed-based resting-state functional connectivity analysis. RESULTS Individuals with BD exhibited significantly lower FcHo values in the left middle temporal gyrus (MTG) when compared with controls. Functional connectivity findings further indicated decreased functional connectivities between left MTG and cluster 1 (left superior temporal gyrus, extend to middle temporal gyrus, rolandic operculum), cluster 2 (right postcentral, extend to right precentral) in BD patients. The mean FcHo values of left MTG were positively correlated with insomnia, middle scores and appetite increase scores. The mean functional connectivities of left MTG to cluster 1 were negatively correlated with grandiose delusions scores. While the functional connections between left MTG with cluster 2 were negatively correlated with delusions of reference and positively correlated with insomnia, middle scores in BD patients. CONCLUSIONS Our findings suggested that abnormal FcHo and functional connections in those areas of the brain involving DMN and SMN networks might play a crucial role in the neuropathology of BD.
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Affiliation(s)
| | - Cong Zhou
- School of Mental HealthJining Medical UniversityJiningChina
| | - Shan Sun
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Wenqiang Wang
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Qi Zheng
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
| | - Zhiyi You
- Department of PsychiatryXiamen Xianyue HospitalXiamenChina
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17
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Sun K, Liu Z, Chen G, Zhou Z, Zhong S, Tang Z, Wang S, Zhou G, Zhou X, Shao L, Ye X, Zhang Y, Jia Y, Pan J, Huang L, Liu X, Liu J, Tian J, Wang Y. A two-center radiomic analysis for differentiating major depressive disorder using multi-modality MRI data under different parcellation methods. J Affect Disord 2022; 300:1-9. [PMID: 34942222 DOI: 10.1016/j.jad.2021.12.065] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 09/13/2021] [Accepted: 12/19/2021] [Indexed: 01/09/2023]
Abstract
BACKGROUND The present study aimed to explore the difference in the brain function and structure between patients with major depressive disorder (MDD) and healthy controls (HCs) using two-center and multi-modal MRI data, which would be helpful to investigate the pathogenesis of MDD. METHODS The subjects were collected from two hospitals. One including 140 patients with MDD and 138 HCs was used as primary cohort. Another one including 29 patients with MDD and 52 HCs was used as validation cohort. Functional and structural magnetic resonance images (MRI) were acquired to extract four types of features: functional connectivity (FC), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and gray matter volume (GMV). Then classifiers using different combinations among the four types of selected features were respectively built to discriminate patients from HCs. Different templates were applied and the results under different templates were compared. RESULTS The classifier built with the combination of FC, ALFF, and GMV under the AAL template discriminated patients from HCs with the best performance (AUC=0.916, ACC=84.8%). The regions selected in all the different templates were mainly located in the default mode network, affective network, prefrontal cortex. LIMITATIONS First, the sample size of the validation cohort was limited. Second, diffusion tensor imaging data were not collected. CONCLUSION The performance of classifier was improved by using multi-modal MRI imaging. Different templates would be suitable for different types of analysis. The regions selected in all the different templates are possibly the core regions to investigate the pathophysiology of MDD.
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Affiliation(s)
- Kai Sun
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Zhenyu Liu
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Science, Beijing, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhifeng Zhou
- Shenzhen Institute of Mental Health, Shenzhen Kangning Hospital, Shenzhen, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Zhenchao Tang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Shuo Wang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China
| | - Guifei Zhou
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
| | - Xuezhi Zhou
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Lizhi Shao
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Xiaoying Ye
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yingli Zhang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jiyang Pan
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xia Liu
- Shenzhen Institute of Mental Health, Shenzhen Kangning Hospital, Shenzhen, China.
| | - Jiangang Liu
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology.
| | - Jie Tian
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology; School of Artificial Intelligence, University of Chinese Academy of Science, Beijing, China.
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, China.
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18
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Cheng B, Zhou Y, Kwok VPY, Li Y, Wang S, Zhao Y, Meng Y, Deng W, Wang J. Altered Functional Connectivity Density and Couplings in Postpartum Depression with and Without Anxiety. Soc Cogn Affect Neurosci 2021; 17:756-766. [PMID: 34904174 PMCID: PMC9340108 DOI: 10.1093/scan/nsab127] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/28/2021] [Accepted: 12/13/2021] [Indexed: 02/05/2023] Open
Abstract
Postpartum depression (PPD) is the most common psychological health issue among women, which often comorbids with anxiety (PPD-A). PPD and PPD-A showed highly overlapping clinical symptoms. Identifying disorder-specific neurophysiological markers of PDD and PPD-A is important for better clinical diagnosis and treatments. Here, we performed functional connectivity density (FCD) and resting-state functional connectivity (rsFC) analyses in 138 participants (45 unmedicated patients with first-episode PPD, 31 PDD-A patients and 62 healthy postnatal women, respectively). FCD mapping revealed specifically weaker long-range FCD in right lingual gyrus (LG.R) for PPD patients and significantly stronger long-range FCD in left ventral striatum (VS.L) for PPD-A patients. The follow-up rsFC analyses further revealed reduced functional connectivity between dorsomedial prefrontal cortex (dmPFC) and VS.L in both PPD and PPD-A. PPD showed specific changes of rsFC between LG.R and dmPFC, right angular gyrus and left precentral gyrus, while PPD-A represented specifically abnormal rsFC between VS.L and left ventrolateral prefrontal cortex. Moreover, the altered FCD and rsFC were closely associated with depression and anxiety symptoms load. Taken together, our study is the first to identify common and disorder-specific neural circuit disruptions in PPD and PPD-A, which may facilitate more effective diagnosis and treatments.
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Affiliation(s)
- Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China.,Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yushan Zhou
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Veronica P Y Kwok
- Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen 518057, China
| | - Yuanyuan Li
- Key Laboratory for NeuroInformation of the Ministry of Education, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yajun Zhao
- School of Sociality and Psychology, Southwest Minzu University, Chengdu, China
| | - Yajing Meng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Deng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
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19
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Zhang T, Hou Q, Bai T, Ji G, Lv H, Xie W, Jin S, Yang J, Qiu B, Tian Y, Wang K. Functional and structural alterations in the pain-related circuit in major depressive disorder induced by electroconvulsive therapy. J Neurosci Res 2021; 100:477-489. [PMID: 34825381 DOI: 10.1002/jnr.24979] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 08/08/2021] [Accepted: 09/25/2021] [Indexed: 12/12/2022]
Abstract
Approximately two-thirds of major depressive disorder (MDD) patients have pain, which exacerbates the severity of depression. Electroconvulsive therapy (ECT) is an efficacious treatment that can alleviate depressive symptoms; however, treatment for pain and the underlying neural substrate is elusive. We enrolled 34 patients with MDD and 33 matched healthy controls to complete clinical assessments and neuroimaging scans. MDD patients underwent second assessments and scans after ECT. We defined a pain-related network with a published meta-analysis and calculated topological patterns to reveal topologic alterations induced by ECT. Using the amplitude of low-frequency fluctuations (ALFFs), we probed local function aberrations of pain-related circuits in MDD patients. Subsequently, we applied gray matter volume (GMV) to reveal structural alterations of ECT relieving pain. The relationships between functional and structural aberrations and pain were determined. ECT significantly alleviated pain. The neural mechanism based on pain-related circuits indicated that ECT weakened the circuit function (ALFF: left amygdala and right supplementary motor area), while augmenting the structure (GMV: bilateral amygdala/insula/hippocampus and anterior cingulate cortex). The topologic patterns became less efficient after ECT. Correlation analysis between the change in pain and GMV had negative results in bilateral amygdala/insula/hippocampus. Similarity, there was a positive correlation between a change in ALFF in the left amygdala and improved clinical symptoms. ECT improved pain by decreasing brain local function and global network patterns, while increasing structure in pain-related circuits. Functional and structural alterations were associated with improvement in pain.
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Affiliation(s)
- Ting Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Qiangqiang Hou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Gongjun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Huaming Lv
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Wen Xie
- Anhui Mental Health Center, Hefei, China
| | | | - Jinying Yang
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Bensheng Qiu
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
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20
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Song L, Yang H, Yang M, Liu D, Ge Y, Long J, Dong P. Professional chess expertise modulates whole brain functional connectivity pattern homogeneity and couplings. Brain Imaging Behav 2021; 16:587-595. [PMID: 34453664 DOI: 10.1007/s11682-021-00537-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/07/2021] [Indexed: 11/26/2022]
Abstract
Previous studies have revealed changed functional connectivity patterns between brain areas in chess players using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to exactly characterize the voxel-wise whole brain functional connectivity pattern changes in chess players remains unclear. It could provide more convincing evidence for establishing the relationship between long-term chess practice and brain function changes. In this study, we employed newly developed whole brain functional connectivity pattern homogeneity (FcHo) method to identify the voxel-wise changes of functional connectivity patterns in 28 chess master players and 27 healthy novices. Seed-based functional connectivity analysis was used to identify the alteration of corresponding functional couplings. FcHo analysis revealed significantly increased whole brain functional connectivity pattern similarity in anterior cingulate cortex (ACC), anterior middle temporal gyrus (aMTG), primary visual cortex (V1), and decreased FcHo in thalamus and precentral gyrus in chess players. Resting-state functional connectivity analyses identified chess players showing decreased functional connections between V1 and precentral gyrus. Besides, a linear support vector machine (SVM) based classification achieved an accuracy of 85.45%, a sensitivity of 85.71% and a specificity of 85.19% to differentiate chess players from novices by leave-one-out cross-validation. Finally, correlation analyses revealed that the mean FcHo values of thalamus were significantly negatively correlated with the training time. Our findings provide new evidences for the important roles of ACC, aMTG, V1, thalamus and precentral gyrus in chess players. The findings also indicate that long-term professional chess training may enhance the semantic and episodic processing, efficiency of visual-motor transformation, and cognitive ability.
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Affiliation(s)
- Limei Song
- School of Medical Imaging, Weifang Medical University, Weifang, 261053, Shandong, China.
| | - Huadong Yang
- Department of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Mingdong Yang
- Shouguang People's Hospital, Shouguang, 262700, China
| | - Dianmei Liu
- School of Medical Imaging, Weifang Medical University, Weifang, 261053, Shandong, China
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, 261031, China
| | - Yanming Ge
- School of Medical Imaging, Weifang Medical University, Weifang, 261053, Shandong, China
- Medical Imaging Center, Affiliated Hospital of Weifang Medical University, Weifang, 261031, China
| | - Jinfeng Long
- School of Medical Imaging, Weifang Medical University, Weifang, 261053, Shandong, China
| | - Peng Dong
- School of Medical Imaging, Weifang Medical University, Weifang, 261053, Shandong, China.
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21
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Zhang H, Xia D, Wu X, Liu R, Liu H, Yang X, Yin X, Chen S, Ma M. Abnormal Intrinsic Functional Interactions Within Pain Network in Cervical Discogenic Pain. Front Neurosci 2021; 15:671280. [PMID: 33935644 PMCID: PMC8079815 DOI: 10.3389/fnins.2021.671280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 03/22/2021] [Indexed: 11/13/2022] Open
Abstract
Cervical discogenic pain (CDP) is mainly induced by cervical disc degeneration. However, how CDP modulates the functional interactions within the pain network remains unclear. In the current study, we studied the changed resting-state functional connectivities of pain network with 40 CDP patients and 40 age-, gender-matched healthy controls. We first defined the pain network with the seeds of the posterior insula (PI). Then, whole brain and seed-to-target functional connectivity analyses were performed to identify the differences in functional connectivity between CDP and healthy controls. Finally, correlation analyses were applied to reveal the associations between functional connectivities and clinical measures. Whole-brain functional connectivity analyses of PI identified increased functional connectivity between PI and thalamus (THA) and decreased functional connectivity between PI and middle cingulate cortex (MCC) in CDP patients. Functional connectivity analyses within the pain network further revealed increased functional connectivities between bilateral PI and bilateral THA, and decreased functional connectivities between left PI and MCC, between left postcentral gyrus (PoCG) and MCC in CDP patients. Moreover, we found that the functional connectivities between right PI and left THA, between left PoCG and MCC were negatively and positively correlated with the visual analog scale, respectively. Our findings provide direct evidence of how CDP modulates the pain network, which may facilitate understanding of the neural basis of CDP.
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Affiliation(s)
- Hong Zhang
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Dongqin Xia
- Department of Ultrasound, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoping Wu
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Run Liu
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Hongsheng Liu
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Xiangchun Yang
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Xiaohui Yin
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Song Chen
- Department of Radiology, The Affiliated Xi'an XD Group Hospital, Shaanxi University of Traditional Chinese Medicine, Xi'an, China
| | - Mingyue Ma
- Department of Radiology, The Affiliated Xi'an Central Hospital, Xi'an Jiaotong University, Xi'an, China
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22
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Sinha P, Joshi H, Ithal D. Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms. Front Hum Neurosci 2021; 14:616054. [PMID: 33551779 PMCID: PMC7859100 DOI: 10.3389/fnhum.2020.616054] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 12/15/2020] [Indexed: 12/25/2022] Open
Abstract
Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.
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Affiliation(s)
- Preeti Sinha
- ECT Services, Noninvasive Brain Stimulation (NIBS) Team, Department of Psychiatry, Bengaluru, India.,Geriatric Clinic and Services, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Himanshu Joshi
- Geriatric Clinic and Services, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India.,Multimodal Brain Image Analysis Laboratory, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Dhruva Ithal
- ECT Services, Noninvasive Brain Stimulation (NIBS) Team, Department of Psychiatry, Bengaluru, India.,Accelerated Program for Discovery in Brain Disorders, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
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23
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Wang J, Liu P, Zhang A, Yang C, Liu S, Wang J, Xu Y, Sun N. Specific Gray Matter Volume Changes of the Brain in Unipolar and Bipolar Depression. Front Hum Neurosci 2021; 14:592419. [PMID: 33505257 PMCID: PMC7829967 DOI: 10.3389/fnhum.2020.592419] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 12/08/2020] [Indexed: 01/10/2023] Open
Abstract
To identify the common and specific structural basis of bipolar depression (BD) and unipolar depression (UD) is crucial for clinical diagnosis. In this study, a total of 85 participants, including 22 BD patients, 36 UD patients, and 27 healthy controls, were enrolled. A voxel-based morphology method was used to identify the common and specific changes of the gray matter volume (GMV) to determine the structural basis. Significant differences in GMV were found among the three groups. Compared with healthy controls, UD patients showed decreased GMV in the orbital part of the left inferior frontal gyrus, whereas BD patients showed decreased GMV in the orbital part of the left middle frontal gyrus. Compared with BD, UD patients have increased GMV in the left supramarginal gyrus and middle temporal gyrus. Our results revealed different structural changes in UD and BD patients suggesting BD and UD have different neurophysiological underpinnings. Our study contributes toward the biological determination of morphometric changes, which could help to discriminate between UD and BD.
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Affiliation(s)
- Junyan Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Penghong Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Aixia Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Chunxia Yang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jizhi Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yong Xu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Mental Health, Shanxi Medical University, Taiyuan, China
| | - Ning Sun
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Mental Health, Shanxi Medical University, Taiyuan, China
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24
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Zhang Y, Chen H, Zeng M, He J, Qi G, Zhang S, Liu R. Abnormal Whole Brain Functional Connectivity Pattern Homogeneity and Couplings in Migraine Without Aura. Front Hum Neurosci 2020; 14:619839. [PMID: 33362498 PMCID: PMC7759668 DOI: 10.3389/fnhum.2020.619839] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 11/18/2020] [Indexed: 02/05/2023] Open
Abstract
Previous studies have reported abnormal amplitude of low-frequency fluctuation and regional homogeneity in patients with migraine without aura using resting-state functional magnetic resonance imaging. However, how whole brain functional connectivity pattern homogeneity and its corresponding functional connectivity changes in patients with migraine without aura is unknown. In the current study, we employed a recently developed whole brain functional connectivity homogeneity (FcHo) method to identify the voxel-wise changes of functional connectivity patterns in 21 patients with migraine without aura and 21 gender and age matched healthy controls. Moreover, resting-state functional connectivity analysis was used to reveal the changes of corresponding functional connectivities. FcHo analyses identified significantly decreased FcHo values in the posterior cingulate cortex (PCC), thalamus (THA), and left anterior insula (AI) in patients with migraine without aura compared to healthy controls. Functional connectivity analyses further found decreased functional connectivities between PCC and medial prefrontal cortex (MPFC), between AI and anterior cingulate cortex, and between THA and left precentral gyrus (PCG). The functional connectivities between THA and PCG were negatively correlated with pain intensity. Our findings indicated that whole brain FcHo and connectivity abnormalities of these regions may be associated with functional impairments in pain processing in patients with migraine without aura.
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Affiliation(s)
- Yingxia Zhang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Hong Chen
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Min Zeng
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Junwei He
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Guiqiang Qi
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Shaojin Zhang
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Rongbo Liu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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25
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Mo Y, Wei Q, Bai T, Zhang T, Lv H, Zhang L, Ji G, Yu F, Tian Y, Wang K. Bifrontal electroconvulsive therapy changed regional homogeneity and functional connectivity of left angular gyrus in major depressive disorder. Psychiatry Res 2020; 294:113461. [PMID: 33038791 DOI: 10.1016/j.psychres.2020.113461] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 09/15/2020] [Indexed: 12/11/2022]
Abstract
Electroconvulsive therapy (ECT) is a rapid and effective treatment for MDD. However, the mechanism of ECT for MDD has not been clarified. In this study, we used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the mechanism of ECT. Two groups of subjects were recruited: healthy controls (HCs) and MDD patients who received bifrontal ECT. MDD patients and HCs underwent rs-fMRI scans and clinical assessments (Hamilton Depression Rating Scale, Rey-Auditory Verbal Learning Test (RAVLT), and the verbal fluency test). Regional homogeneity (ReHo) and functional connectivity were evaluated for the analysis of rs-fMRI data. The results showed that ReHo values in the left angular gyrus (LAG) significantly increased in MDD patients after ECT, and the functional connectivity of the LAG with bilateral inferior temporal gyrus, bilateral middle frontal gyrus, left superior frontal gyrus, left middle temporal gyrus, left precuneus, left posterior cingulate gyrus, and right angular gyrus was found to be strengthened after ECT. The scores of delayed recall trial in the RAVLT of MDD patients were related to the functional connectivity of the LAG with the left inferior temporal gyrus and the left posterior cingulate gyrus. It indicated LAG palyed an important role in the mechanism of ECT in MDD.
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Affiliation(s)
- Yuting Mo
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Qiang Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Tongjian Bai
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Ting Zhang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Huaming Lv
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Anhui Mental Health Center, Hefei, Anhui, China
| | - Li Zhang
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Anhui Mental Health Center, Hefei, Anhui, China
| | - Gongjun Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Department of medical psychology, Anhui Medical University, Hefei, China
| | - Fengqiong Yu
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Department of medical psychology, Anhui Medical University, Hefei, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China; Department of medical psychology, Anhui Medical University, Hefei, China.
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26
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Gao J, Li Y, Wei Q, Li X, Wang K, Tian Y, Wang J. Habenula and left angular gyrus circuit contributes to response of electroconvulsive therapy in major depressive disorder. Brain Imaging Behav 2020; 15:2246-2253. [PMID: 33244628 DOI: 10.1007/s11682-020-00418-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 10/21/2020] [Accepted: 11/02/2020] [Indexed: 10/22/2022]
Abstract
The habenula (Hb), one of the hottest structures in depression, has been widely demonstrated to be involved in the neurobiology of depression. Although the structural and functional abnormalities of Hb have been reported in major depressive disorders (MDD) patients, the role of Hb in treatment response in MDD remains unclear. In this study, resting-state functional connectivity (RSFC) and Granger causality analysis (GCA) were performed to investigate the intrinsic and causal changes of Hb in MDD after ECT. Moreover, support vector classification was applied to find out whether the changed functional and causal connections of Hb can effectively distinguish the MDD patients from healthy controls. The RSFC and GCA identified increased RSFC strength between bilateral Hb and left angular gyrus (AG), decreased causal connectivity strength from left AG to left Hb, from right Hb to left AG, and bidirectional interactions between left and right Hb in MDD patients after ECT. The changed causal connectivities from left AG to left Hb, and from right Hb to left AG were correlated with the changed depression symptoms and impaired delay memory recall performances. Furthermore, the functional and causal connectivities between left AG and bilateral Hb could serve as a biomarker to differentiate MDD from HCs. These results provided new evidence for the importance of Hb in depression and revealed that the interactions between Hb and left AG contribute to ECT response in MDD. Our findings will facilitate the future treatment of depression with the target of Hb in MDD and other brain disorders.
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Affiliation(s)
- Jingjing Gao
- School of Information and Communication Engineer, University of Electronic Science and Technology of China, Chengdu, 625014, China
| | - Yuanyuan Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China
| | - Qiang Wei
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei, 230022, China
| | - Xuemei Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China
| | - Kai Wang
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei, 230022, China.,Department of Medical Psychology, Anhui Medical University, 230022, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, 230022, Hefei, China.,Collaborative Innovation Center for Neuropsychiatric Disorders and Mental Health, 230022, Hefei, China
| | - Yanghua Tian
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei, 230022, China.
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China. .,Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 518060, China.
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27
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Guo M, Wang T, Zhang Z, Chen N, Li Y, Wang Y, Yao Z, Hu B. Diagnosis of major depressive disorder using whole-brain effective connectivity networks derived from resting-state functional MRI. J Neural Eng 2020; 17:056038. [PMID: 32987369 DOI: 10.1088/1741-2552/abbc28] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
OBJECTIVE It is important to improve identification accuracy for possible early intervention of major depressive disorder (MDD). Recently, effective connectivity (EC), defined as the directed influence of spatially distant brain regions on each other, has been used to find the dysfunctional organization of brain networks in MDD. However, little is known about the ability of whole-brain resting-state EC features in identification of MDD. Here, we employed EC by whole-brain analysis to perform MDD diagnosis. APPROACH In this study, we proposed a high-order EC network capturing high-level relationship among multiple brain regions to discriminate 57 patients with MDD from 60 normal controls (NC). In high-order EC networks and traditional low-order EC networks, we utilized the network properties and connection strength for classification. Meanwhile, the support vector machine (SVM) was employed for model training. Generalization of the results was supported by 10-fold cross-validation. MAIN RESULTS The classification results showed that the high-order EC network performed better than the low-order EC network in diagnosing MDD, and the integration of these two networks yielded the best classification precision with 95% accuracy, 98.83% sensitivity, and 91% specificity. Furthermore, we found that the abnormal connections of high-order EC in MDD patients involved multiple widely concerned functional subnets, particularly the default mode network and the cerebellar network. SIGNIFICANCE The current study indicates whole-brain EC networks, measured by our high-order method, may be promising biomarkers for clinical diagnosis of MDD, and the complementary between high-order and low-order EC will better guide patients to get early interventions as well as treatments.
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Affiliation(s)
- Man Guo
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, People's Republic of China
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28
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Zeng M, Wang L, Cheng B, Qi G, He J, Xu Z, Han T, Liu C, Wang Y. Transcutaneous Spinal Cord Direct-Current Stimulation Modulates Functional Activity and Integration in Idiopathic Restless Legs Syndrome. Front Neurosci 2020; 14:873. [PMID: 32982669 PMCID: PMC7475652 DOI: 10.3389/fnins.2020.00873] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 07/27/2020] [Indexed: 11/13/2022] Open
Abstract
Idiopathic restless legs syndrome (RLS) is a sensorimotor disorder and is suggested to be caused by central nervous system abnormalities. Non-invasive transcutaneous spinal direct-current stimulation (tsDCS) was recently used for RLS therapy. However, the neurophysiological basis of tsDCS treatment is still unknown. In this study, we explored the neural basis of tsDCS in 15 RLS patients and 20 gender- and age-matched healthy controls using resting-state functional magnetic resonance imaging. We calculated the whole-brain voxel-wise fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and weighted degree centrality (DC) to characterize the intrinsic functional activities and the local and global functional integration. We found that tsDCS can effectively improve the sleep and RLS symptoms in RLS patients. Moreover, after tsDCS therapy, the RLS patients showed decreased fALFF in the right anterior insula/temporal pole, decreased ReHo in the supplementary motor area, increased weighted DC in the left primary visual cortex, and decreased weighted DC in the right posterior cerebellum. The changed patterns were consistent with that found between RLS patients and healthy controls. The weighted DC in the left primary visual cortex after treatment and the fALFF in the right anterior insula/temporal pole before treatment were significantly and marginally correlated with sleep and RLS symptom scores, respectively. These results revealed that tsDCS can normalize the functional patterns of RLS patients and is an effective way for RLS therapy. Our findings provide the neurophysiological basis for tsDCS treatment and may facilitate understanding the neuropathology of RLS and directing other neuromodulation treatments.
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Affiliation(s)
- Min Zeng
- Department of Radiology, Pidu District People's Hospital, Chengdu, China
| | - Li Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, China
| | - Guiqiang Qi
- Department of Radiology, Pidu District People's Hospital, Chengdu, China
| | - Junwei He
- Department of Radiology, Pidu District People's Hospital, Chengdu, China
| | - Zhexue Xu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Tao Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Chunyan Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
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29
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Ma M, Zhang H, Liu R, Liu H, Yang X, Yin X, Chen S, Wu X. Static and Dynamic Changes of Amplitude of Low-Frequency Fluctuations in Cervical Discogenic Pain. Front Neurosci 2020; 14:733. [PMID: 32760245 PMCID: PMC7372087 DOI: 10.3389/fnins.2020.00733] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 06/22/2020] [Indexed: 02/01/2023] Open
Abstract
Cervical discogenic pain (CDP) is a clinically common pain syndrome caused by cervical disk degeneration. A large number of studies have reported that CDP results in brain functional impairments. However, the detailed dynamic brain functional abnormalities in CDP are still unclear. In this study, using resting-state functional magnetic resonance imaging, we explored the neural basis of CDP with 40 CDP patients and 40 age-, gender-matched healthy controls to delineate the changes of the voxel-level static and dynamic amplitude of low frequency fluctuations (ALFF). We found increased static ALFF in left insula (INS) and posterior precuneus (PCu), and decreased static ALFF in left precentral/postcentral gyrus (PreCG/PoCG), thalamus (THA), and subgenual anterior cingulate cortex in CPD patients compared to healthy controls. We also found decreased dynamic ALFF in left PreCG/PoCG, right posterior middle temporal gyrus, and bilateral THA. Moreover, we found that static ALFF in left PreCG/PoCG and dynamic ALFF in THA were significantly negatively correlated with visual analog scale and disease duration, respectively. Our findings provide the neurophysiological basis for CDP and facilitate understanding the neuropathology of CDP.
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Affiliation(s)
- Mingyue Ma
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Hong Zhang
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Run Liu
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Hongsheng Liu
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiangchun Yang
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaohui Yin
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Song Chen
- Department of Radiology, The Affiliated Xi'an XD Group Hospital of Shanxi University of Traditional Chinese Medicine, Xi'an, China
| | - Xiaoping Wu
- Department of Radiology, The Affiliated Xi'an Central Hospital of Xi'an Jiaotong University, Xi'an, China
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30
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Wang Y, Zhang A, Yang C, Li G, Sun N, Liu P, Wang Y, Zhang K. Enhanced Functional Connectivity Within Executive Function Network in Remitted or Partially Remitted MDD Patients. Front Psychiatry 2020; 11:538333. [PMID: 33584355 PMCID: PMC7875881 DOI: 10.3389/fpsyt.2020.538333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 12/18/2020] [Indexed: 12/30/2022] Open
Abstract
Background: Impaired executive function (EF) is associated with a range of typical clinical characteristics and psychosocial dysfunction in major depressive disorder (MDD). However, because of the lack of objective cognitive tests, inconsistencies in research results, and improvement in patients' subjective experience, few clinicians are concerned with the persistent impairment of EF in euthymia. The study makes a further investigation for EF in remitted and partially remitted MDD patients via multiple EF tests and fMRI, so as to explore the executive function of patients in euthymia. Methods: We recruited 19 MDD patients and 17 age-, gender-, and education-matched healthy controls (HCs). All participants completed EF tests and fMRI scanning. Bilateral dorsolateral prefrontal cortex (dlPFC) regions were selected as the region of interests (ROIs) to conduct seed-based functional connectivity (FC). We conducted fractional amplitude of low-frequency fluctuations (fALFF) analysis for all ROIs and whole brain. Results: All MDD patients were in remission or partial remission, and they were comparable with HCs on all the EF tests. MDD group showed increased positive FC between left dlPFC and cerebellar Crus I, right dlPFC and supramarginal gyrus after 8-weeks treatment, even taking residual depressive symptoms into account. We did not find group difference of fALFF value. Conclusion: MDD patients persisted with EF impairment despite the remission or partially remission of depressive symptoms. Clinicians should focus on residual cognitive symptoms, which may contribute to maximize the efficacy of routine therapy.
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Affiliation(s)
- Yuchen Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Medical Psychology, College of Humanities and Social Science, Shanxi Medical University, Taiyuan, China
| | - Aixia Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Chunxia Yang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Gaizhi Li
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Ning Sun
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.,College of Nursing, Shanxi Medical University, Taiyuan, China
| | - Penghong Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yanfang Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Kerang Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China
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31
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Long J, Xu J, Wang X, Li J, Rao S, Wu H, Kuang W. Altered Local Gyrification Index and Corresponding Functional Connectivity in Medication Free Major Depressive Disorder. Front Psychiatry 2020; 11:585401. [PMID: 33424661 PMCID: PMC7793885 DOI: 10.3389/fpsyt.2020.585401] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 11/24/2020] [Indexed: 02/05/2023] Open
Abstract
A lot of previous studies have documented that major depressive disorder (MDD) is a developmental disorder. The cortical surface measure, local gyrification index (LGI), can well reflect the fetal and early postnatal neurodevelopmental processes. Thus, LGI may provide new insight for the neuropathology of MDD. The previous studies only focused on the surface structural abnormality, but how the structural abnormality lead to functional connectivity changes is unexplored. In this study, we investigated LGI and corresponding functional connectivity difference in 28 medication-free MDD patients. We found significantly decreased LGI in left lingual gyrus (LING) and right posterior superior temporal sulcus (bSTS), and the changed LGI in bSTS was negatively correlated with disease onset age and anxiety scores. The following functional connectivity analyses identified decreased functional connectivities between LING and right LING, precentral gyrus, and middle temporal gyrus. The decreased functional connectivities were correlated with disease duration, onset, and depression symptoms. Our findings revealed abnormal LGI in LING and bSTS indicating that the abnormal developmental of visual and social cognition related brain areas may be an early biomarker for depression.
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Affiliation(s)
- Jiang Long
- Deparment of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xue Wang
- Deparment of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Jin Li
- Deparment of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Shan Rao
- Deparment of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, China
| | - Weihong Kuang
- Department of Psychiatry and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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