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.

中文翻译：

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探索炎症和代谢在白癜风发病机制中的作用和潜在治疗策略：孟德尔随机化和基于生物信息学的研究

简介：白癜风是一种常见的自身免疫性获得性色素性皮肤病，由于其发病机制尚不清楚，因此带来了挑战。有证据表明炎症和代谢在其发生和进展中发挥着关键作用。本研究旨在阐明白癜风与炎症蛋白、免疫细胞和代谢物之间的因果关系，探索双向关联和潜在的药物靶点。方法：孟德尔随机化（MR）分析涵盖4,907个血浆蛋白、91个炎症蛋白、731个免疫细胞特征、和1400种代谢物。生物信息学分析包括蛋白质-蛋白质相互作用（PPI）网络构建、基因本体论（GO）和京都基因和基因组百科全书（KEGG）通路分析。子网发现和中心蛋白识别利用分子复合物检测 (MCODE) 插件。进行了共定位分析和药物靶标探索，包括分子对接验证。结果：MR 分析鉴定出与白癜风因果相关的 49 种蛋白质、39 种免疫细胞特征和 59 种代谢物。生物信息学分析揭示了 PPI、GO 富集和 KEGG 通路的显着参与。子网络分析确定了六种中心蛋白，其中干扰素调节因子 3 (IRF3) 表现出强有力的共定位证据。分子对接验证了白皮杉醇与IRF3的结合，表明存在稳定的相互作用。结论：本研究全面阐明了炎症、免疫反应和代谢在白癜风发病机制中的复杂参与。已鉴定的蛋白质和通路提供了潜在的治疗靶点，其中 IRF3 成为一个有前途的候选者。这些发现加深了我们对白癜风病因的理解，为未来的研究和药物开发工作提供了信息。