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Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns(Open Access)

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收录情况： ◇ SCIE

作者：
Sugai Liang [1,2] * ; Wei Deng [1,2] ; Xiaojing Li [1,2] ; Andrew J. Greenshaw [3] ; Qiang Wang [1,2] ; Mingli Li [1,2] ; Xiaohong Ma [1,2] ; Tong-Jian Bai[4] ; Qi-Jing Bo[5] ; Jun Cao[6] ; Guan-Mao Chen[7] ; Wei Chen[8] ; Chang Cheng[9] ; Yu-Qi Cheng[10] ; Xi-Long Cui[9] ; Jia Duan[11] ; Yi-Ru Fang[12] ; Qi-Yong Gong[13,14] ; Wen-Bin Guo[9] ; Zheng-Hua Hou[15] ; Lan Hu[6] ; Li Kuang[6] ; Feng Li[5] ; Kai-Ming Li[13] ; Yan-Song Liu[16] ; Zhe-Ning Liu[17] ; Yi-Cheng Long[17] ; Qing-Hua Luo[6] ; Hua-Qing Meng[16] ; Dai-Hui Peng[12] ; Hai-Tang Qiu[6] ; Jiang Qiu[18] ; Yue-Di Shen[19] ; Yu-Shu Shi[20] ; Tian-Mei Si[21] ; Chuan-Yue Wang[5] ; Fei Wang[11] ; Kai Wang[5] ; Li Wang[21] ; Xiang Wang[8] ; Ying Wang[7] ; Xiao-Ping Wu[22] ; Xin-Ran Wu[18] ; Chun-Ming Xie[23] ; Guang-Rong Xie[9] ; Hai-Yan Xie[24] ; Peng Xie[25,26,27] ; Xiu-Feng Xu[10] ; Hong Yang[20] ; Jian Yang[28] ; Hua Yu[1,2] ; Jia-Shu Yao[8] ; Shu-Qiao Yao[9] ; Ying-Ying Yin[15] ; Yong-Gui Yuan[15] ; Yu-Feng Zang[29,30] ; Ai-Xia Zhang[28] ; Hong Zhang[22] ; Ke-Rang Zhang[31] ; Zhi-Jun Zhang[23] ; Jing-Ping Zhao[17] ; Ru-Bai Zhou[12] ; Yi-Ting Zhou[1,2] ; Chao-Jie Zou[10] ; Xi-Nian Zuo[32,33,34] ; Chao-Gan Yan [32,33,34,*2] ; Tao Li [1,2,*1] ;
机构： [1]Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China [2]West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China [3]Department of Psychiatry, University of Alberta, Edmonton T6G 2B7, AB, Canada [4]Anhui Medical University, Hefei, 230032, Anhui, China [5]Beijing Anding Hospital, Capital Medical University, Beijing, 100069, China [6]Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China [7]The First Affiliated Hospital of Jinan University, Guangzhou, 510630, Guangdong, China [8]Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China [9]The Second Xiangya Hospital of Central South University, Changsha, 410083, Hunan, China [10]First Affiliated Hospital of Kunming Medical University, Kunming, 650211, Yunnan, China [11]Department of Psychiatry, First Affiliated Hospital, China Medical University, Shenyang, 110001, Liaoning, China [12]Department of Psychiatry, Shanghai Jiao Tong University School of Medicine, Shanghai, 200240, China [13]Huaxi MR Research Center (HMRRC)，Department of Radiology，West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China [14]Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, Chengdu, 610040, Sichuan, China [15]Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, 210096, Jiangsu, China [16]Department of Clinical Psychology, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, 215031, Jiangsu, China [17]The Institute of Mental Health, Second Xiangya Hospital of Central South University, Changsha, 410083, Hunan, China [18]Faculty of Psychology, Southwest University, Chongqing, 400715, China [19]Department of Diagnostics, Affiliated Hospital, Hangzhou Normal University Medical School, Hangzhou, 311121, Zhejiang, China [20]Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China [21]National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China [22]Xi’an Central Hospital, Xi’an, 710032, Shaanxi, China [23]Department of Neurology, Affiliated Zhongda Hospital of Southeast University, Nanjing, 210096, Jiangsu, China [24]Department of Psychiatry, The Fourth Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310058, Zhejiang, China [25]Institute of Neuroscience, Chongqing Medical University, Chongqing, 400016, China [26]Chongqing Key Laboratory of Neurobiology, Chongqing, 400016, China [27]Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China [28]The First Affiliated Hospital of Xi’an Jiaotong University, 710049, Shaanxi, China [29]Center for Cognition and Brain Disorders, Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, 311121, Zhejiang, China [30]Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, 311121, Zhejiang, China [31]First Hospital of Shanxi Medical University, Taiyuan, 030607, Shanxi, China [32]CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China [33]Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China [34]Magnetic Resonance Imaging Research Center and Research Center for Lifespan Development of Mind and Brain (CLIMB), Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
出处：
DOI： 10.1016/j.nicl.2020.102514
ISSN：

关键词： Biotypes Default mode network Machine learning Major depressive disorder Resting-state fMRI

摘要：
Background: Major depressive disorder (MDD) is heterogeneous disorder associated with aberrant functional connectivity within the default mode network (DMN). This study focused on data-driven identification and validation of potential DMN-pattern-based MDD subtypes to parse heterogeneity of the disorder. Methods: The sample comprised 1397 participants including 690 patients with MDD and 707 healthy controls (HC) registered from multiple sites based on the REST-meta-MDD Project in China. Baseline resting-state functional magnetic resonance imaging (rs-fMRI) data was recorded for each participant. Discriminative features were selected from DMN between patients and HC. Patient subgroups were defined by K-means and principle component analysis in the multi-site datasets and validated in an independent single-site dataset. Statistical significance of resultant clustering were confirmed. Demographic and clinical variables were compared between identified patient subgroups. Results: Two MDD subgroups with differing functional connectivity profiles of DMN were identified in the multi-site datasets, and relatively stable in different validation samples. The predominant dysfunctional connectivity profiles were detected among superior frontal cortex, ventral medial prefrontal cortex, posterior cingulate cortex and precuneus, whereas one subgroup exhibited increases of connectivity (hyperDMN MDD) and another subgroup showed decreases of connectivity (hypoDMN MDD). The hyperDMN subgroup in the discovery dataset had age-related severity of depressive symptoms. Patient subgroups had comparable demographic and clinical symptom variables. Conclusions: Findings suggest the existence of two neural subtypes of MDD associated with different dysfunctional DMN connectivity patterns, which may provide useful evidence for parsing heterogeneity of depression and be valuable to inform the search for personalized treatment strategies. © 2020 The Author(s)

基金：
This work was supported by the National Natural Science Foundation of China (81801326 to S.G.L., 81630030 to T.L., 81671774 to C.G.Y., 81630031 to C.G.Y., 81461168029 to T.L., and 81471740 to X.N.Z.), the National Key R&D Program of China (2017YFC1309902 to C.G.Y. & 2016YFC0904300 to T.L.), State 863 Project of China (2015AA020513 to M.H.X.), the Hundred Talents Program and the 13th Five-year Informatization Plan (XXH13505) of Chinese Academy of Sciences, Beijing Municipal Science & Technology Commission (Z161100000216152 to C.G.Y. and Z171100000117016 to T.M.S.), Department of Science and Technology, Zhejiang Province (2015C03037 to Y.F.Z.), Special Foundation for Brain Research from Science and Technology Program of Guangdong (2018B030334001 to T.L.), and 1.3.5 Project for disciplines of excellence from West China Hospital of Sichuan University (ZY2016103 and ZY2016203 to T.L. and X.H.M.). Dr. Xi-Nian Zuo was partly supported by the National R&D Infrastructure and Facility Development Program of China, “Fundamental Science Data Sharing Platform” (DKA2019-12-02-21), and the Key Realm R&D Program of Guangdong Province (2019B030335001)
语种：
外文
被引次数：
WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2021]版：
大类 | 2 区 医学
小类 | 3 区 神经成像
最新[2023]版：
大类 | 2 区 医学
小类 | 2 区 神经成像
JCR分区：
出版当年[2020]版：
Q2 NEUROIMAGING
最新[2023]版：
Q2 NEUROIMAGING

影响因子： 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

第一作者：
第一作者机构： [1]Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China [2]West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
通讯作者：
通讯机构： [*1]Mental Health Center & Psychiatric Laboratory, State Key Laboratory of Biotherapy,West China Hospital, Sichuan University,No. 28th Dianxin Nan Str. Chengdu,Sichuan, 610041, China [*2]CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang District, Beijing 100101, China
推荐引用方式(GB/T 7714)：
Sugai Liang,Wei Deng,Xiaojing Li,et al.Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns(Open Access)[J].NEUROIMAGE-CLINICAL.2020,28:doi:10.1016/j.nicl.2020.102514.
APA：
Sugai Liang,Wei Deng,Xiaojing Li,Andrew J. Greenshaw,Qiang Wang...&Tao Li.(2020).Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns(Open Access).NEUROIMAGE-CLINICAL,28,
MLA：
Sugai Liang,et al."Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns(Open Access)".NEUROIMAGE-CLINICAL 28.(2020)

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