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

Authors :
Xiaojing Li
Zhijun Zhang
Chang Cheng
Sugai Liang
Guang-Rong Xie
Qi-Jing Bo
Xiufeng Xu
Li Wang
Wei Deng
Yu-Feng Zang
Kaiming Li
Xi-Long Cui
Jia Duan
Chao-Gan Yan
Ying Wang
Ai-Xia Zhang
Chuanyue Wang
Shuqiao Yao
Jun Cao
Fei Wang
Yan-Song Liu
Jian Yang
Yi-Ru Fang
Zhening Liu
Peng Xie
Wenbin Guo
Wei Chen
Hong Yang
Yi-Ting Zhou
Feng Li
Li Kuang
Ying-Ying Yin
Tong-Jian Bai
Yi-Cheng Long
Yu-Shu Shi
Hong Zhang
Qing-Hua Luo
Xi-Nian Zuo
Jingping Zhao
Daihui Peng
Yonggui Yuan
Ru-Bai Zhou
Zheng-Hua Hou
Chunming Xie
Jiang Qiu
Yue-Di Shen
Kai Wang
Xiao-Ping Wu
Jia-Shu Yao
Hai-Tang Qiu
Xinran Wu
Qiang Wang
Guanmao Chen
Kerang Zhang
Xiang Wang
Mingli Li
Chao-Jie Zou
Andrew J. Greenshaw
Yu-Qi Cheng
Xiaohong Ma
Huaqing Meng
Hai-Yan Xie
Lan Hu
Hua Yu
Tian-Mei Si
Tao Li
Qiyong Gong
Source :
NeuroImage : Clinical, NeuroImage: Clinical, Vol 28, Iss, Pp 102514-(2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Highlights • Two subtypes with distinct default mode network profiles exist in major depression. • Subtypes of major depression are robust in validation datasets across brain atlases. • Hyper- & hypo-connectivity DMN subgroups have comparable clinical symptom variables. • Future studies should examine whether two subtypes have differing treatment response.<br />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.

Details

Language :
English
ISSN :
22131582
Volume :
28
Database :
OpenAIRE
Journal :
NeuroImage : Clinical
Accession number :
edsair.doi.dedup.....1b3e54a71b10584b7e851c3ce7b71988