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Identification of Hidradenitis Suppurativa-Related mRNA Expression Patterns Through Analysis of Gene Expression Omnibus

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, follicular, and inflammatory skin disease with multifactorial pathogenesis, and its definite molecule mechanism is still not fully elucidated. OBJECTIVE: The purpose of this research was to identify crucial differentially expressed genes (DEGs)...

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Detalles Bibliográficos
Autores principales: Teng, Yan, Tao, Xiaohua, Lu, Wei, Huang, Youming, Xu, Danfeng, Li, Meng, Fan, Yibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383683/
https://www.ncbi.nlm.nih.gov/pubmed/32782449
http://dx.doi.org/10.1177/1559325820942646
Descripción
Sumario:BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, follicular, and inflammatory skin disease with multifactorial pathogenesis, and its definite molecule mechanism is still not fully elucidated. OBJECTIVE: The purpose of this research was to identify crucial differentially expressed genes (DEGs) and biological processes and pathways involved in HS through bioinformatics analysis. METHODS: A total of 30 tissues from patients with HS, 17 lesional and 13 healthy, were obtained from the GSE72702 data set of the Gene Expression Omnibus database. The DEGs were sorted by GEO2R and analyzed by Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. MCODE analysis was visualized using Cytoscape. RESULTS: Of the 723 identified DEGs, 364 were upregulated and 359 were downregulated. Upregulated DEGs were significantly enriched in immune response, inflammatory response, tumor necrosis factor signaling pathway, and so on and downregulated DEGs were enriched in the positive regulation of the peroxisome proliferators-activated receptor pathways, the regulation of lipolysis in adipocytes, and so on. The most significant DEGs group of 35 genes were screened. CONCLUSION: The internal biological information in HS can be revealed by bioinformatic methods, providing direction for further research and potential therapeutic targets.