Dataset Information

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

ABSTRACT:

Background

Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach.

Methods

Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels.

Results

The group of MDD patients showed significantly higher temporal variability, lower temporal correlation coefficient (indicating decreased temporal clustering) and shorter characteristic temporal path length (indicating increased temporal efficiency) compared with healthy controls (corrected p < 3.14×10^-3). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients.

Conclusions

Our findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD.

SUBMITTER: Long Y

PROVIDER: S-EPMC7229351 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

Long Yicheng Y Cao Hengyi H Yan Chaogan C Chen Xiao X Li Le L Castellanos Francisco Xavier FX Bai Tongjian T Bo Qijing Q Chen Guanmao G Chen Ningxuan N Chen Wei W Cheng Chang C Cheng Yuqi Y Cui Xilong X Duan Jia J Fang Yiru Y Gong Qiyong Q Guo Wenbin W Hou Zhenghua Z Hu Lan L Kuang Li L Li Feng F Li Kaiming K Li Tao T Liu Yansong Y Luo Qinghua Q Meng Huaqing H Peng Daihui D Qiu Haitang H Qiu Jiang J Shen Yuedi Y Shi Yushu Y Si Tianmei T Wang Chuanyue C Wang Fei F Wang Kai K Wang Li L Wang Xiang X Wang Ying Y Wu Xiaoping X Wu Xinran X Xie Chunming C Xie Guangrong G Xie Haiyan H Xie Peng P Xu Xiufeng X Yang Hong H Yang Jian J Yao Jiashu J Yao Shuqiao S Yin Yingying Y Yuan Yonggui Y Zhang Aixia A Zhang Hong H Zhang Kerang K Zhang Lei L Zhang Zhijun Z Zhou Rubai R Zhou Yiting Y Zhu Junjuan J Zou Chaojie C Zang Yufeng Y Zhao Jingping J Kin-Yuen Chan Calais C Pu Weidan W Liu Zhening Z

NeuroImage. Clinical 20200107

<h4>Background</h4>Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach.<h4>Methods</h4>Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 4 ...[more]

PMID: 31953148

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Project description:Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Project description:UNLABELLED:Functional magnetic resonance imaging (fMRI) studies have revealed the existence of robust, interconnected brain networks exhibiting correlated low frequency fluctuations during rest, which can be derived by examining inherent spatio-temporal patterns in functional scans independent of any a priori model. In order to explore the electrophysiological underpinnings of these networks, analogous techniques have recently been applied to magnetoencephalography (MEG) data, revealing similar networks that exhibit correlated low frequency fluctuations in the power envelope of beta band (14-30Hz) power. However, studies to date using this technique have concentrated on healthy subjects, and no method has yet been presented for group comparisons. We extended the ICA resting state MEG method to enable group comparisons, and demonstrate the technique in a sample of subjects with major depressive disorder (MDD). We found that the intrinsic resting state networks evident in fMRI appeared to be disrupted in individuals with MDD compared to healthy participants, particularly in the subgenual cingulate, although the electrophysiological correlates of this are unknown. Networks extracted from a combined group of healthy and MDD participants were examined for differences between groups. Individuals with MDD showed reduced correlations between the subgenual anterior cingulate (sgACC) and hippocampus in a network with primary nodes in the precentral and middle frontal gyri. Individuals with MDD also showed increased correlations between insulo-temporal nodes and amygdala compared to healthy controls. To further support our methods and findings, we present test/re-test reliability on independent recordings acquired within the same session. Our results demonstrate that group analyses are possible with the resting state MEG-independent component analysis (ICA) technique, highlighting a new pathway for analysis and discovery. This study also provides the first evidence of altered sgACC connectivity with a motor network. This finding, reliable across multiple sessions, suggests that the sgACC may partially mediate the psychomotor symptoms of MDD via synchronized changes in beta-band power, and expands the idea of the sgACC as a hub region mediating cognitive and emotional symptomatic domains in MDD. Findings of increased connectivity between the amygdala and cortical nodes further support the role of amygdalar networks in mediated depressive symptomatology. CLINICAL TRIALS IDENTIFIER:NCT00024635 (ZIA-MH002927-04).

Dataset Information

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

Background

Methods

Results

Conclusions

Publications

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

Similar Datasets

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