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已发表论文

白癜风中氧化应激相关基因及免疫浸润模式的生物信息学分析

 

Authors Yang M, Wang H, Zhang R

Received 18 September 2024

Accepted for publication 12 February 2025

Published 28 February 2025 Volume 2025:18 Pages 475—489

DOI http://doi.org/10.2147/CCID.S496781

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Jeffrey Weinberg

Mingmei Yang,1,2 Huiying Wang,1 Ruzhi Zhang1 

1Department of Dermatology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu Province, 213003, People’s Republic of China; 2Department of Dermatology, Affiliated Changzhou Children’s Hospital of Nantong University, Changzhou, Jiangsu Province, 213003, People’s Republic of China

Correspondence: Ruzhi Zhang, Email zhangruzhi628@163.com

Background: Vitiligo is an autoimmune disorder characterized by pigment loss, and current treatment options remain inadequate.
Objective: This study aims to identify oxidative stress-related biomarkers and hub genes associated with vitiligo diagnosis through genomic analysis and to examine the role of immune cell infiltration in the pathogenesis of vitiligo.
Methods: The mRNA expression profile dataset GSE75819 was retrieved from the GEO database. Differential expression of oxidative stress-related genes in vitiligo was analyzed using R software. Protein-protein interaction (PPI) analysis, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted on the differentially expressed genes (DEGs). Immune cell infiltration between vitiligo and normal control groups was assessed using the CIBERSORT algorithm. Additionally, two machine learning algorithms were employed to identify hub genes, perform enrichment analyses, and evaluate their correlation with immune infiltration.
Results: A total of 415 Oxidative Stress-DEGs were identified in vitiligo, including 317 up-regulated and 98 down-regulated genes. PPI analysis highlighted the significance of certain ribosomal protein genes. KEGG enrichment analysis suggested an association between vitiligo and various neurodegenerative conditions, particularly through pathways such as oxidative phosphorylation and ribosome biogenesis. GO enrichment analysis indicated that the hub genes were significantly enriched in mitochondrial-related activities. Significant differences in immune infiltration patterns were observed between vitiligo patients and normal controls. Machine learning algorithms identified oxidative stress-related key genes associated with vitiligo, notably the DCT gene, whose expression was strongly linked to the activity of specific immune cell subsets and melanin biosynthetic pathways.
Conclusion: Oxidative stress-related DEGs, ribosomal proteins, immune infiltration, and hub genes related to melanin biosynthesis, particularly DCT, are closely associated with the pathogenesis of vitiligo. These findings enhance our understanding of vitiligo and may aid in identifying therapeutic targets for the disease.

Keywords: vitiligo, oxidative stress, DEGs, hub gene, DCT, immune infiltration

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