Differences in cerebral spontaneous neural activity correlate with gene-specific transcriptional signatures in primary angle-closure glaucoma.

Autor: Li XT; Queen Mary School, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, People's Republic of China., Chen L; The Second Clinical Medical College, Jiangxi Medical College, Nanchang University, Nanchang 330006, Jiangxi, People's Republic of China., Wang XM; School of Ophthalmology and Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, People's Republic of China., Zheng CC; School of Ophthalmology and Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, People's Republic of China., Huang X; Department of Ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi 330006, People's Republic of China. Electronic address: 2017103020035@whu.edu.cn.
Jazyk: angličtina
Zdroj: Neuroscience [Neuroscience] 2024 Dec 07; Vol. 565, pp. 399-419. Date of Electronic Publication: 2024 Dec 07.
DOI: 10.1016/j.neuroscience.2024.12.012
Abstrakt: Aims: This study was aimed to investigate frequency-specific LFO changes and their correlation with gene pathways in PACG using transcriptome-neuroimaging analysis.
Methods: Resting-state fMRI (Rs-fMRI) data were acquired from individuals with PACG and healthy controls for evaluating the amplitude of low-frequency oscillations (ALFF) across different frequency bands such as the full band, slow-4 band, and slow-5 band. Transcriptome analysis integrated information from the Allen Human Brain Atlas (AHBA) through gene set enrichment analysis, protein-protein interaction network construction, and specific expression analysis, aiming to clarify the link between ALFF patterns and gene expression profiles in PACG. Statistical analyses, including one-sample t-tests and two-sample t-tests, were used to assess ALFF differences between groups, while partial least squares (PLS) regression was applied to explore the associations between ALFF and transcriptome data.
Results: This study identifies significant variations in ALFF values in PACG patients, observed consistently across multiple frequency bands, including slow-4 and slow-5. Enrichment analysis indicates that these genes are primarily involved in cellular components such as the cytosol and cytoplasm, molecular functions like protein binding, and key pathways, including metabolic and circadian rhythms, epithelial signaling in Helicobacter pylori infection, and glutathione metabolism. Protein-protein interaction (PPI) analysis further underscores the role of PACG-related genes in forming a functional network, highlighting hub genes critical for various biological processes.
Conclusion: This study establishes a connection between the molecular mechanisms of PACG and alterations in brain function and gene expression, providing valuable perspectives on the fundamental processes impacting low-frequency oscillations in PACG.
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.
(Copyright © 2024. Published by Elsevier Inc.)
Databáze: MEDLINE
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