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. 2023 Dec 11:17:1308551.
doi: 10.3389/fnins.2023.1308551. eCollection 2023.

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

Yao Zhu #  1 , Tianming Huang #  2 , Ruolin Li  3 , Qianrong Yang  2 , Chaoyue Zhao  1 , Ming Yang  1 , Bin Lin  4 ; DIRECT Consortium; Xuzhou Li  4
Affiliations

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

Yao Zhu et al. Front Neurosci. .

Abstract

Introduction: Previous studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).

Methods: This study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.

Results: Our findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.

Conclusion: These findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

Keywords: brain networks; effective connectivity; first-episode and recurrent; major depressive disorder; resting-state fMRI.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Brain networks from DOS-160 atlas used in the present study. DMN, default mode network; FPN, fronto-parietal network; CON, cingulo-opercular network; SMN, sensorimotor network; VN, visual network; CN, cerebellum network.
Figure 2
Figure 2
Differences between groups in effective connectivity of brain networks. FEDN, first-episode drug-naïve; RMDD, recurrent major depression disorder; vlPFC, ventral lateral prefrontal cortex; FPN, fronto-parietal network; SMN, sensorimotor network; CN, cerebellum network. **p < 0.05; ***p < 0.001.
Figure 3
Figure 3
Inter-network differences in effective connectivity between groups. FEDN, first-episode drug-naïve; RMDD, recurrent major depression disorder; FPN, fronto-parietal network; SMN, sensorimotor network; VN, visual network. **p < 0.05; ***p < 0.001.
Figure 4
Figure 4
Correlation between effective connectivity and HAMD score. The effective connectivity from CON to SMN shows a significant negative correlation with the HAMD score in the FEDN group.
See this image and copyright information in PMC

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