Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns | |
Liang, Sugai9,10,11; Deng, Wei9,10,11; Li, Xiaojing9,10,11; Greenshaw, Andrew J.12; Wang, Qiang9,10,11; Li, Mingli9,10,11; Ma, Xiaohong9,10,11; Bai, Tong-Jian13; Bo, Qi-Jing14; Cao, Jun15 | |
刊名 | NeuroImage: Clinical |
2021 | |
通讯作者邮箱 | yancg@psych.ac.cn (c.-g. yan) ; litaohx@scu.edu.cn (t. li). |
卷号 | 28 |
关键词 | Biotypes Default mode network Major depressive disorder Resting-state fMRI Machine learning |
ISSN号 | 2213-1582 |
DOI | 10.1016/j.nicl.2020.102514 |
文献子类 | 实证研究 |
英文摘要 | 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. |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.psych.ac.cn/handle/311026/40742] |
专题 | 心理研究所_中国科学院行为科学重点实验室 |
作者单位 | 1.Xi An Jiao Tong Univ, Affiliated Hosp 1, Xian 710049, Shaanxi, Peoples R China 2.Chinese Acad Sci, Inst Psychol, Res Ctr Lifespan Dev Mind & Brain CLIMB, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Magnet Resonance Imaging Res Ctr, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Dept Psychol, Beijing 100101, Peoples R China 5.Inst Psychol, CAS Key Lab Behav Sci, Beijing 100101, Peoples R China 6.Shanxi Med Univ, Hosp 1, Taiyuan 030607, Shanxi, Peoples R China 7.Zhejiang Key Lab Res Assessment Cognit Impairment, Hangzhou 311121, Zhejiang, Peoples R China 8.Hangzhou Normal Univ, Inst Psychol Sci, Ctr Cognit & Brain Disorders, Hangzhou 311121, Zhejiang, Peoples R China 9.Sichuan Univ, West China Hosp, State Key Lab Biotherapy, Mental Hlth Ctr, 28th Dianxin Nan Str, Chengdu 610041, Sichuan, Peoples R China 10.Sichuan Univ, West China Hosp, State Key Lab Biotherapy, Psychiat Lab, Chengdu 610041, Sichuan, Peoples R China |
推荐引用方式 GB/T 7714 | Liang, Sugai,Deng, Wei,Li, Xiaojing,et al. Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns[J]. NeuroImage: Clinical,2021,28. |
APA | Liang, Sugai.,Deng, Wei.,Li, Xiaojing.,Greenshaw, Andrew J..,Wang, Qiang.,...&Li, Tao.(2021).Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns.NeuroImage: Clinical,28. |
MLA | Liang, Sugai,et al."Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns".NeuroImage: Clinical 28(2021). |
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