Chinese Journal of Dermatology ›› 2022, Vol. 55 ›› Issue (5): 421-425.doi: 10.35541/cjd.20200391

• Research Reports • Previous Articles     Next Articles

Screening and analysis of differentially expressed genes in vitiligo using bioinformatics methods

Ainiwaer·Talifu1, Xiong Cheng1, Refuhati·Saimaiti1, Yusufu·Maitinuer1, Tuerxun·Wufuer1, Akenmujiang·Aierken1, Julaiti·Abuduwayiti1, Maimaitiaili·Kade2   

  1. 1Hospital of Xinjiang Traditional Uyghur Medicine, Urumqi 830049, China; 2Uyghur Medical College of Xinjiang, Urumqi 830011, China
  • Received:2020-04-21 Revised:2021-01-14 Online:2022-05-15 Published:2022-04-29
  • Contact: Yusufu·Maitinuer E-mail:M13209938480@163.com
  • Supported by:
    The Key Research and Development Project of Xinjiang Uygur Autonomous Region(2016B03038-2);The Project of Key Laboratory of Plant Resource Chemistry in Arid Regions, Chinese Academy of Sciences

Abstract: 【Abstract】 Objective To explore potential signaling pathways and genes related to vitiligo progression by using bioinformatics methods. Methods A vitiligo genechip dataset GSE75819 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs)were screened between lesional and non-lesional skin tissues from 15 Indian patients with vitiligo with the dataset GSE75819 by using LMFit and eBayes functions in R LIMma package. The Kyoto Encyclopedia of Genes and Genomes (KEGG)-based pathway analysis, Gene Ontology (GO) analysis and Gene set enrichment analysis (GSEA) were carried out to identify enriched pathways and functions of the DEGs. Protein-protein interaction networks were established to screen hub genes from the DEGs. In addition, lesional and non-lesional skin tissue specimens were obtained from 8 patients of Han nationality with vitiligo vulgaris in Hospital of Xinjiang Traditional Uyghur Medicine between January and June in 2019, and real-time quantitative PCR was performed to verify the expression of the top 10 up- or down-regulated DEGs. Results Compared with the 15 non-lesional skin tissues, a total of 148 DEGs were identified in the 15 lesional skin tissues. Among these DEGs, KRT9, CXCL10, C8ORF59, TPSAB1 and RPL26 were the top 5 up-regulated genes, and SILV, RPPH1, TYRP1, MLANA and LOC401115 were the top 5 down-regulated genes, which were all verified by real-time quantitative PCR in the lesional and non-lesional skin tissues from the 8 patients of Han nationality with vitiligo. GO analysis showed that the DEGs were chiefly enriched in translational initiation, cellular response to lipopolysaccharide, ribosomes, ribosomal subunits and structural constituents of ribosomes. KEGG analysis showed that the DEGs were chiefly enriched in tyrosine metabolism, peroxisome proliferator-activated receptor signaling pathway, oxidative phosphorylation and Toll-like receptor signaling pathway. Four hub genes, including UPF3B, SNRPG, MRPL13 and RPL26L1, were screened out by protein-protein interaction analysis. Conclusion KRT9, CXCL10, C8ORF59, TPSAB1, RPL26, SILV, RPPH1, TYRP1, MLANA and LOC401115 genes may serve as potential diagnostic molecular markers and therapeutic targets for vitiligo.

Key words: Vitiligo, Bioinformatics, Differentially expressed genes, Signaling pathways