Liu Linli, Deng Lingli, Pan Xingyu, Chen Jin, Yu Chunshui
Department of Dermatology, Suining Central Hospital, Suining, Sichuan, China.
Department of Dermatology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
J Cosmet Dermatol. 2025 Sep;24(9):e70420. doi: 10.1111/jocd.70420.
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).
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.
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.
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.
白癜风是一种慢性自身免疫性疾病,其特征为黑素细胞丢失和皮肤色素脱失斑。有效的治疗选择有限,对其确切致病机制的不完全理解阻碍了治疗进展。我们旨在通过使用孟德尔随机化(MR)整合大规模蛋白质组学和基因组数据,来识别白癜风的候选蛋白质生物标志物和治疗靶点。
使用两样本MR分析,我们利用了白癜风的全基因组关联研究(GWAS)数据(131例欧洲血统患者和207482例对照)以及来自Decode队列(35559名参与者)的包含4907种血浆蛋白的蛋白质组学数据。通过五种互补的MR方法评估遗传预测的血浆蛋白水平与白癜风风险之间的因果关系,并进行富集分析以探索其生物学意义。通过独立的转录组数据集、单细胞RNA测序和分子对接分析进行进一步验证,以识别潜在的治疗化合物。
我们鉴定出七种与白癜风风险因果相关的蛋白质(HEPHL1、PRDX1、DEFA1、CSGALNACT2、HERC4、NDC80和SPHK2)。值得注意的是,HERC4和NDC80在各个验证数据集中的白癜风皮损中均表现出强表达。功能富集分析表明这些蛋白质参与氧化应激调节、免疫调节和细胞信号通路。分子对接分析进一步突出了潜在的治疗药物,包括唑来膦酸和禾胺。
我们的综合MR分析鉴定出了白癜风新的蛋白质生物标志物和有前景的治疗靶点,特别是HERC4和NDC80。这些发现为改善诊断和开发靶向治疗提供了潜在机会,推动了白癜风精准医学管理方法的发展。