Abstract
BACKGROUND: Vitiligo is a chronic autoimmune disorder characterized by melanocyte loss and depigmented skin patches. Effective treatment options are limited, and therapeutic progress has been hindered by incomplete understanding of its precise pathogenic mechanisms. We aimed to identify candidate protein biomarkers and therapeutic targets for vitiligo by integrating large-scale proteomics and genomic data using Mendelian randomization (MR). METHODS: Using two-sample MR analysis, we leveraged genome-wide association study (GWAS) data for vitiligo (131 cases and 207 482 controls of European descent) and proteomic data comprising 4907 plasma proteins from the Decode cohort (35 559 participants). Causal relationships between genetically predicted plasma protein levels and vitiligo risk were evaluated through five complementary MR methods, along with enrichment analyses to explore their biological implications. Further validation was conducted via independent transcriptomic datasets, single-cell RNA sequencing, and molecular docking analysis to identify potential therapeutic compounds. RESULTS: We identified seven proteins (HEPHL1, PRDX1, DEFA1, CSGALNACT2, HERC4, NDC80, and SPHK2) causally associated with vitiligo risk. Notably, HERC4 and NDC80 exhibited robust expression in vitiligo lesions across validation datasets. Functional enrichment analysis implicated these proteins in oxidative stress regulation, immune modulation, and cellular signaling pathways. Molecular docking analyses further highlighted potential therapeutic agents, including zoledronic acid and gramine. CONCLUSIONS: Our integrative MR analysis identified novel protein biomarkers and promising therapeutic targets for vitiligo, particularly HERC4 and NDC80. These findings offer potential opportunities for improved diagnosis and the development of targeted therapies, advancing precision medicine approaches for vitiligo management.