Screening of Key Part in IFN Pathway for Herpes Zoster: Evidence from
Bioinformatics Analysis

Zimeng      Li; Jie      Wu; Shijie      Huang; Zhengqi      Pan; Jing      Huang

doi:10.2174/1386207325666220509182242

Abstract

Background: Herpes zoster is one of the most common diseases in middle and old ages, and the incidence rate is constantly increasing. Long-term, severe neuropathological pain continues to afflict the patients, causing trouble and even the inability to live a normal life. Since the occurrence and development of herpes zoster are related to many mechanisms, there is no uniform conclusion and specific treatment method, and only a limited number of people are currently vaccinated against HZ.

Objective: This study aimed at exploring the potential mechanism or biomarkers for Herpes zoster.

Methods: In this study, a data set GSE165112 containing 12 samples was downloaded, out of which, 6 samples were treated with interferon, and 6 samples were not treated. Differentially expressed genes (DEG) analysis, KEGG, GO enrichment analysis, and GSEA were carried out.

Results: A total of 264 DEGs were identified, including 32 uP-regulated DEGs and 232 downregulated DEGs. DEGs are mainly enriched in immune response, inflammatory response, chemotaxis, etc. Four key pathways were found to be related to HZ, including IL2-STAT5 signaling, inflammatory response, TNF-a signaling via NF-κB, and IFN-α. Moreover, ten hub genes were also identified.

Conclusion: This study shows that exploring DEGs and pathways through bioinformatics analysis is of great significance for understanding the molecular mechanism of HZ, especially the defect of the IFN pathway. It may be helpful in improving the treatment for HZ.

Keywords: Herpes zoster, bioinformatic analysis, protein-protein interaction network, gene ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, interferon.

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DOI https://dx.doi.org/10.2174/1386207325666220509182242	Print ISSN 1386-2073
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Screening of Key Part in IFN Pathway for Herpes Zoster: Evidence from Bioinformatics Analysis

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