Indian Journal of Dermatology (Apr 2024)

Bioinformatic Analysis of Genes Associated with Autophagy in Vitiligo

  • Yilu Zhao,
  • Kang Ge,
  • Yan Cheng,
  • Ru-zhi Zhang

DOI
https://doi.org/10.4103/ijd.ijd_655_23
Journal volume & issue
Vol. 69, no. 2
pp. 123 – 131

Abstract

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Background: As vitiligo progresses, autophagy becomes more and more important. Objectives: To validate potential genes associated with autophagy in vitiligo through bioinformatics analysis and experimental testing. Materials and Methods: Dataset GSE75819 of mRNA expression profiles was obtained from GEO. After data normalisation, gene set enrichment analyse enrichment analysis and abundance analysis of infiltrating immune cells were performed. A list of autophagy-related differentially expressed genes (ARDEGs) associated with vitiligo was generated using R software. Protein–protein interaction (PPI) analysis, correlation analysis, and enrichment analysis on gene ontology (GO) and Kyoto encyclopaedia of genes and genome (KEGG) pathways were conducted on the ARDEG data. The microRNAs associated with hub genes were predicted using the TargetScan database. Finally, RNA expression of 10 hub genes and Western blotting (WB) of autophagy pathway factors were further verified. Results: From the lesions of 15 vitiligo patients, 44 ARDEGs were identified. PPI analysis demonstrated that these ARDEGs interacted with each other. GO and KEGG analyses of ARDEGs revealed that several enriched terms were associated with macroautophagy (biological process), vacuolar membranes (cellular components), cysteine-type peptidase activity (molecular function), and autophagy in animals, neurodegeneration-multiple disease pathways, and apoptosis. In vitiligo lesions, qRT-PCR and sequencing validation analyses showed expression levels of CCL2, RB1CC1, TP53, and ATG9A that were consistent with bioinformatic analysis of the microarray. WB results also showed that autophagy-related proteins were differentially expressed. Conclusions: Forty-four potential ARDEGs were identified in vitiligo by bioinformatic analysis. Vitiligo may be affected by autophagy regulation through CCL2, RB1CC1, TP53, and ATG9A.

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