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

Autor: 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
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Oncology
China
medicine.medical_specialty
Cognitive Neuroscience
Precuneus
Neuroimaging
Major depressive disorder
lcsh:Computer applications to medicine. Medical informatics
050105 experimental psychology
lcsh:RC346-429
03 medical and health sciences
0302 clinical medicine
Cortex (anatomy)
Internal medicine
Neural Pathways
Machine learning
medicine
Humans
0501 psychology and cognitive sciences
Radiology
Nuclear Medicine and imaging
Resting-state fMRI
Default mode network
lcsh:Neurology. Diseases of the nervous system
Brain Mapping
Depressive Disorder
Major
Resting state fMRI
medicine.diagnostic_test
business.industry
05 social sciences
Brain
Biotypes
Regular Article
medicine.disease
Magnetic Resonance Imaging
medicine.anatomical_structure
Neurology
Posterior cingulate
lcsh:R858-859.7
Neurology (clinical)
business
Functional magnetic resonance imaging
030217 neurology & neurosurgery
Zdroj: NeuroImage : Clinical
NeuroImage: Clinical, Vol 28, Iss, Pp 102514-(2020)
ISSN: 2213-1582
Popis: 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.
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.
Databáze: OpenAIRE
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