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Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

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收录情况： ◇ SCIE

作者：
Xiaoyi Sun [1,2,3,4] * ; Jinrong Sun [5,6,7] ; Xiaowen Lu [5,6,8] ; Qiangli Dong [5,6,9] ; Liang Zhang [5,6,10] ; Wenxu Wang [4] ; Jin Liu [1,2,3] ; Qing Ma [1,2,3,11] ; Xiaoqin Wang [12,13] ; Dongtao Wei [12,13] ; Yuan Chen [14] ; Bangshan Liu [5,6] ; Chu-Chung Huang [15] ; Yanting Zheng [16] ; Yankun Wu [17] ; Taolin Chen [18] ; Yuqi Cheng [19] ; Xiufeng Xu [19] ; Qiyong Gong [18,20] ; Tianmei Si [17] ; Shijun Qiu [16] ; Ching-Po Lin [11,21] ; Jingliang Cheng [14] ; Yanqing Tang [22] ; Fei Wang [22] ; Jiang Qiu [12,13] ; Peng Xie [23,24] ; Lingjiang Li [5,6] ; Yong He [1,2,3,25] ; Mingrui Xia [1,2,3,*1] ; DIDA-MDD Working Group[1] ;
机构： [1]State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China [2]Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China [3]IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China [4]School of Systems Science, Beijing Normal University, Beijing, China [5]Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China [6]Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China [7]Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou Mental Health Centre, Yangzhou, China [8]Affiliated Wuhan Mental Health Center, Huazhong University of Science and Technology, Wuhan, China [9]Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou, China [10]Mental Health Education and Counseling Center, Shanghai University of Medicine and Health Sciences, Shanghai, China [11]Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China [12]Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China. [13]Department of Psychology, Southwest University, Chongqing, China [14]Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China [15]Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China [16]Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China [17]Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China [18]Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China [19]Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China [20]Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China [21]Institute of Neuroscience, National Yang-Ming Chiao-Tung University, Taipei, Taiwan [22]Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China [23]Chongqing Key Laboratory of Neurobiology, Chongqing, China [24]Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China [25]Chinese Institute for Brain Research, Beijing, China
出处：
DOI： 10.1016/j.biopsych.2023.05.021
ISSN：

关键词： resting state fMRI functional connectivity individual difference default mode network depression normative model

摘要：
Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking.Leveraging resting-state functional MRI data from 1,148 MDD patients and 1,079 healthy controls (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. We first characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among MDD patients. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity.Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among MDD patients, which inspired the identification of two reproducible neurophysiological subtypes. Subtype 1 showed severe deviations with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Conversely, subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and predictive ability of baseline deviations for antidepressant treatment outcomes.These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.Copyright © 2023. Published by Elsevier Inc.

基金：
This work was supported by the SIT 2030-Major Projects (2022ZD0211500 to MX), National Natural Science Foundation of China (82071998 and 82021004 to MX; 81920108019, 91649117, 81771344, and 81471251 to SQ), Beijing Nova Program (Z191100001119023 to MX), Beijing United Imaging Research Institute of Intelligent Imaging Foundation (CRIBJZD202102 to MX), Science and Technology Plan Project of Guangzhou (2018-1002-SF-0442 to SQ), Guangzhou Key Laboratory (09002344 to SQ).
语种：
外文
被引次数：
WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2024]版：
无
最新[2023]版：
大类 | 1 区 医学
小类 | 1 区 神经科学 1 区 精神病学
JCR分区：
出版当年[2023]版：
Q1 NEUROSCIENCES Q1 PSYCHIATRY
最新[2023]版：
Q1 NEUROSCIENCES Q1 PSYCHIATRY

影响因子： 最新[2023版] 最新五年平均 出版当年[2023版] 出版当年五年平均 出版前一年[2022版]

第一作者：
第一作者机构： [1]State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China [2]Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China [3]IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China [4]School of Systems Science, Beijing Normal University, Beijing, China
通讯作者：
通讯机构： [1]State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China [2]Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China [3]IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China [*1]State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Key Laboratory of Brain Imaging and Connectomics, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
推荐引用方式(GB/T 7714)：
Xiaoyi Sun,Jinrong Sun,Xiaowen Lu,et al.Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome[J].BIOLOGICAL PSYCHIATRY.2023,94(12):936-947.doi:10.1016/j.biopsych.2023.05.021.
APA：
Xiaoyi Sun,Jinrong Sun,Xiaowen Lu,Qiangli Dong,Liang Zhang...&DIDA-MDD Working Group.(2023).Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome.BIOLOGICAL PSYCHIATRY,94,(12)
MLA：
Xiaoyi Sun,et al."Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome".BIOLOGICAL PSYCHIATRY 94..12(2023):936-947

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