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Intra- and Inter-Network connectivity of the default mode network differentiates Treatment-Resistant depression from Treatment-Sensitive depression.
- Source :
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NeuroImage. Clinical [Neuroimage Clin] 2024; Vol. 43, pp. 103656. Date of Electronic Publication: 2024 Aug 14. - Publication Year :
- 2024
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Abstract
- Understanding why some patients with depression remain resistant to antidepressant medication could be elucidated by investigating their associated neural features. Although research has consistently demonstrated abnormalities in the anterior cingulate cortex (ACC) - a region that is part of the default mode network (DMN) - in treatment-resistant depression (TRD), a considerable research gap exists in discerning how these neural networks distinguish TRD from treatment-sensitive depression (TSD). We aimed to evaluate the resting-state functional connectivity (rsFC) of the ACC with other regions of the DMN to better understand the role of this structure in the pathophysiology of TRD. 35 TRD patients, 35 TSD patients, and 38 healthy controls (HC) underwent a resting-state functional MRI protocol. Seed-based functional connectivity analyses were performed, comparing the three groups for the connectivity between two subregions of the ACC (the subgenual ACC (sgACC) and the rostral ACC (rACC)) and the DMN (p < 0.05 FWE corrected). Furthermore, inter-network connectivity of the DMN with other neural networks was explored by independent component (ICA) analyses (p < 0.01, FDR corrected). The results demonstrated hyperconnectivity between the rACC and the posterior cingulate cortex in TRD relative to TSD and HC (F(2,105) = 5.335, p < 0.05). ICA found DMN connectivity to regions of the visual network (TRD<TSD) and a parietal region of the DMN (TRD>TSD), differentiating the two clinical groups. These results provide confirmatory evidence of DMN hyperconnectivity and preliminary evidence for its interactions with other neural networks as key neural mechanisms underlying treatment non-responsiveness.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships, which may be considered as potential competing interests: Anthony Harris received funding from Takeda Pharmaceutical Company for this project. There are no other financial disclosures related to the work. Mayuresh Korgaonkar received funding from Takeda Pharmaceutical Company for this project. There are no other financial disclosures related to the work. And all other authors have declared that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Humans
Male
Female
Adult
Middle Aged
Connectome methods
Brain physiopathology
Brain diagnostic imaging
Young Adult
Neural Pathways physiopathology
Neural Pathways diagnostic imaging
Brain Mapping methods
Magnetic Resonance Imaging methods
Default Mode Network diagnostic imaging
Default Mode Network physiopathology
Depressive Disorder, Treatment-Resistant diagnostic imaging
Depressive Disorder, Treatment-Resistant physiopathology
Depressive Disorder, Treatment-Resistant drug therapy
Gyrus Cinguli diagnostic imaging
Gyrus Cinguli physiopathology
Nerve Net diagnostic imaging
Nerve Net physiopathology
Subjects
Details
- Language :
- English
- ISSN :
- 2213-1582
- Volume :
- 43
- Database :
- MEDLINE
- Journal :
- NeuroImage. Clinical
- Publication Type :
- Academic Journal
- Accession number :
- 39180979
- Full Text :
- https://doi.org/10.1016/j.nicl.2024.103656