ArticleFrontiers in immunology2025
Bioinformatics meets machine learning: identifying circulating biomarkers for vitiligo across blood and tissues.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Neuropeptide Y drives vitiligo progression via NPYR-mediated NF-κB activation: a novel therapeutic target.Scientific reports · 2026Article
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6 authors.
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Abstract
Background: Vitiligo is a skin disorder characterized by the progressive loss of pigmentation in the skin and mucous membranes. The exact aetiology and pathogenesis of vitiligo remain incompletely understood. Methods: First, a microarray dataset of blood samples from multiple patients with vitiligo was collected from GEO database.The limma package was used to analyze the microarray data and identify significant differentially expressed genes (DEGs). The merged microarray data were then used for WGCNA to identify modules of features genes. DEGs selected with the limma package and module genes derived from the WGCNA were intersected using the Venn package in R. Enrichment analyses were performed on the overlapping genes, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes methodology. Advanced screening was performed using the least absolute shrinkage and selection operator and support vector machine techniques from the machine learning toolkit. CIBERSORT was used to analyse the immune cell composition in the microarray data to assess the relationships among these genes and immune cells. Biological samples were obtained from the patients, and gene expression analysis was performed to evaluate the levels of core genes throughout the progression of vitiligo. Finally, we obtained the microarray datasets GSE53146 and GSE75819 from the affected skin of vitiligo patients and GSE205155 from healthy skin to perform expression analysis and gene set enrichment analysis of the hub genes. Results: Two hub genes, Conclusion:
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