Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naive MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.
基金:
National Key R&D Program of China [2017YFC1309902]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [81671774, 81630031, 81471740, 81621003, 81371488]; Hundred Talents ProgramChinese Academy of Sciences; 13th Five-Year Informatization Plan of the Chinese Academy of Sciences [XXH13505]; Beijing Municipal Science & Technology CommissionBeijing Municipal Science & Technology Commission [Z161100000216152, Z171100000117016, Z161100002616023, Z171100000117012]; Department of Science and Technology, Zhejiang ProvinceDepartment of Science & Technology (India) [2015C03037]; National Basic Research (973) ProgramNational Basic Research Program of China [2015CB351702]
第一作者机构:[1]Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100101, Peoples R China;[2]Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China;[3]Chinese Acad Sci, Magnet Resonance Imaging Res Ctr, Beijing 100101, Peoples R China;[4]Chinese Acad Sci, Inst Psychol, Res Ctr Lifespan Dev Mind & Brain, Beijing 100101, Peoples R China;[5]NYU, Sch Med, Dept Child & Adolescent Psychiat, New York, NY 10016 USA;
通讯作者:
通讯机构:[1]Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100101, Peoples R China;[2]Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China;[3]Chinese Acad Sci, Magnet Resonance Imaging Res Ctr, Beijing 100101, Peoples R China;[4]Chinese Acad Sci, Inst Psychol, Res Ctr Lifespan Dev Mind & Brain, Beijing 100101, Peoples R China;[5]NYU, Sch Med, Dept Child & Adolescent Psychiat, New York, NY 10016 USA;[12]Cent S Univ, Xiangya Hosp 2, Dept Psychiat, Changsha 410011, Hunan, Peoples R China;[34]Hangzhou Normal Univ, Inst Psychol Sci, Ctr Cognit & Brain Disorders, Hangzhou 311121, Zhejiang, Peoples R China;[35]Zhejiang Key Lab Res Assessment Cognit Impairment, Hangzhou 311121, Zhejiang, Peoples R China
推荐引用方式(GB/T 7714):
Yan Chao-Gan,Chen Xiao,Li Le,et al.Reduced default mode network functional connectivity in patients with recurrent major depressive disorder[J].PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA.2019,116(18):9078-9083.doi:10.1073/pnas.1900390116.
APA:
Yan, Chao-Gan,Chen, Xiao,Li, Le,Castellanos, Francisco Xavier,Bai, Tong-Jian...&Zang, Yu-Feng.(2019).Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,116,(18)
MLA:
Yan, Chao-Gan,et al."Reduced default mode network functional connectivity in patients with recurrent major depressive disorder".PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 116..18(2019):9078-9083