Yan Chenjue, Jiang Ling, Hu Yibo, You Ting, Chen Jing, Wu Songjiang
Department of Dermatology, the First Affiliated Hospital, Hengyang Medical College, University of South China, Hengyang, Hunan, 421001, People's Republic of China.
Department of Dermatology, the Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha,, Hunan, 410013, People's Republic of China.
Dermatol Ther (Heidelb). 2025 Jun 19. doi: 10.1007/s13555-025-01448-5.
Given that the proteome is a major source of therapeutic targets, we conducted a proteome-wide Mendelian randomization (MR) combined with transcriptome sequencing analysis to identify candidate protein markers and therapeutic targets for vitiligo.
Based on protein quantitative trait loci (pQTLs) and genetic associations with vitiligo obtained from the European Bioinformatics Institute (EBI) database (60 vitiligo cases and 402,672 controls), and the UK Biobank (95 vitiligo cases and 337,064 controls), bidirectional MR and colocalization analyses identified genetically predicted levels of nine proteins collectively linked to vitiligo risk. Based on the RNA-seq data and single-cell RNA-seq data of vitiligo, bioinformatics analysis and model prediction of genes associated with vitiligo progression evaluated the relationship between candidate core proteins and the development of vitiligo.
Four proteins (KLF4, MYL4, TNFRSF13C, TNFSF13B) were associated with lower vitiligo risk, while five proteins (ALPI, CDH1, ITGB1, SERPINH1, TNFSF10) were linked to higher risk. Of these, three proteins (KLF4, TNFRSF13C, and TNFSF10) were high priority with the most convincing evidence. Bioinformatics analysis and model prediction of genes associated with vitiligo progression showed these three protein-coding genes were significantly associated with vitiligo occurrence, and their functions were related to cell cycle, apoptosis, oxidative stress, inflammatory response, and immune infiltration. Mechanistically, the expression of these key candidate molecules was regulated by various miRNAs and transcription factors. The druggability assessment and molecular docking identified some drugs targeting these proteins, such as APTO-2535 and butyric acid.
KLF4, TNFRSF13C, and TNFSF10 may be involved in regulating the occurrence and development of vitiligo, providing potential targets for improving the diagnosis and treatment of vitiligo.
鉴于蛋白质组是治疗靶点的主要来源，我们进行了全蛋白质组孟德尔随机化（MR）结合转录组测序分析，以鉴定白癜风的候选蛋白质标志物和治疗靶点。
基于从欧洲生物信息学研究所（EBI）数据库（60例白癜风病例和402,672例对照）以及英国生物银行（95例白癜风病例和337,064例对照）获得的蛋白质定量性状位点（pQTLs）和与白癜风的遗传关联，双向MR和共定位分析确定了共同与白癜风风险相关的九种蛋白质的遗传预测水平。基于白癜风的RNA-seq数据和单细胞RNA-seq数据，对与白癜风进展相关的基因进行生物信息学分析和模型预测，评估候选核心蛋白与白癜风发展之间的关系。
四种蛋白质（KLF4、MYL4、TNFRSF13C、TNFSF13B）与较低的白癜风风险相关，而五种蛋白质（ALPI、CDH1、ITGB1、SERPINH1、TNFSF10）与较高风险相关。其中，三种蛋白质（KLF4、TNFRSF13C和TNFSF10）具有最令人信服的证据，是高优先级的。对与白癜风进展相关的基因进行生物信息学分析和模型预测表明，这三个蛋白质编码基因与白癜风的发生显著相关，其功能与细胞周期、凋亡、氧化应激、炎症反应和免疫浸润有关。从机制上讲，这些关键候选分子的表达受多种miRNA和转录因子的调节。药物可及性评估和分子对接确定了一些靶向这些蛋白质的药物，如APTO-2535和丁酸。
KLF4、TNFRSF13C和TNFSF10可能参与调节白癜风的发生和发展，为改善白癜风的诊断和治疗提供了潜在靶点。
