ArticleFrontiers in genetics2024
Exploring the roles and potential therapeutic strategies of inflammation and metabolism in the pathogenesis of vitiligo: a mendelian randomization and bioinformatics-based investigation.
Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Causal Relationship Between Psoriatic Arthritis and Coronary Heart Disease: A Mendelian Randomization and Bioinformatics Analysis.Psoriasis (Auckland, N.Z.) · 2026Article
- Integrative Proteomics and Genomics Identify Novel Biomarkers and Therapeutic Targets in Vitiligo via Mendelian Randomization.Dermatology and therapy · 2025Article
- Exploring the role of inflammation, immunity, and metabolism in colorectal cancer via mendelian randomization approach.Scientific reports · 2025Article
- TLR4 identified as a major depressive disorder gene signature mediating effects through multiple immune cells.Scientific reports · 2025Article
- Article
- Analyzing the Differential Expression of Vitiligo Genes by Bioinformatics Methods.Dermatology research and practice · 2025Article
- Causal Correlations Between Plasma Metabolites, Inflammatory Proteins, and Chronic Obstructive Pulmonary Disease: A Mendelian Randomization and Bioinformatics-Based Investigation.Journal of inflammation research · 2025Article
- Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.Frontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Vitiligo, a common autoimmune acquired pigmentary skin disorder, poses challenges due to its unclear pathogenesis. Evidence suggests inflammation and metabolism's pivotal roles in its onset and progression. This study aims to elucidate the causal relationships between vitiligo and inflammatory proteins, immune cells, and metabolites, exploring bidirectional associations and potential drug targets. Methods: Mendelian Randomization (MR) analysis encompassed 4,907 plasma proteins, 91 inflammatory proteins, 731 immune cell features, and 1400 metabolites. Bioinformatics analysis included Protein-Protein Interaction (PPI) network construction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Subnetwork discovery and hub protein identification utilized the Molecular Complex Detection (MCODE) plugin. Colocalization analysis and drug target exploration, including molecular docking validation, were performed. Results: MR analysis identified 49 proteins, 39 immune cell features, and 59 metabolites causally related to vitiligo. Bioinformatics analysis revealed significant involvement in PPI, GO enrichment, and KEGG pathways. Subnetwork analysis identified six central proteins, with Interferon Regulatory Factor 3 (IRF3) exhibiting strong colocalization evidence. Molecular docking validated Piceatannol's binding to IRF3, indicating a stable interaction. Conclusion: This study comprehensively elucidates inflammation, immune response, and metabolism's intricate involvement in vitiligo pathogenesis. Identified proteins and pathways offer potential therapeutic targets, with IRF3 emerging as a promising candidate. These findings deepen our understanding of vitiligo's etiology, informing future research and drug development endeavors.
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