ArticleFrontiers in neurology2022
Identification of hub genes and pathophysiological mechanism related to acute unilateral vestibulopathy by integrated bioinformatics analysis.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Identification of Ageing-related Hub Genes in Humans, Mouse and Rat Based on Bioinformatics Analysis.Annals of neurosciences · 2025Article
- Genetic analysis of potential biomarkers and therapeutic targets in neuroinflammation from sporadic Creutzfeldt-Jakob disease.Scientific reports · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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Abstract
Background: Although many pathological mechanisms and etiological hypotheses of acute unilateral vestibulopathy (AUVP) have been reported, but the actual etiology remains to be elucidated. Objective: This study was based on comprehensive bioinformatics to identify the critical genes of AUVP and explore its pathological mechanism. Methods: Gene expression profiles of AUVP and normal samples were collected from GSE146230 datasets of the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was constructed, and the WGCNA R-package extracted significant modules. The limma R-package was applied to identify differentially expressed genes (DEGs). The common genes of practical modules and DEGs were screened for GO and KEGG pathways analysis. The protein-protein interaction (PPI) layout and hub genes validation was created by Cytoscape software using the link from the STRING database. The functions of hub genes were predicted through the CTD (comparative genetics database). Results: A total of 332 common genes were screened from practical modules and DEGs. Functional enrichment analysis revealed that these genes were predominantly associated with inflammation and infection. After construction of PPI, expressions of hub genes, and drawing ROC curves, LILRB2, FPR1, AQP9, and LILRA1 are highly expressed in AUVP ( Conclusion: LILRB2, FPR1, AQP9, and LILRA1 may play essential roles in developing AUVP, providing new ideas for diagnosing and treating AUVP.
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