Uncovering key markers and therapeutic targets for renal fibrosis in diabetic kidney disease through bulk and single-cell RNA sequencing

作者：Lijuan Li, Tao Mi, Xueyun Gao, Quan Cao, Zejing Liao, Feng Chen, Ayinigaer Yusufu, Haihang Nie, Ziyue Zeng, Kai Huang, Xuan Deng, Ping Gao, Xiaoyan Wu · 发表于：Journal of Translational Medicine · 年份：2025 · DOI：10.1186/s12967-025-06554-8 · 被引用次数：10 · 研究领域：Chronic Kidney Disease and Diabetes、Single-cell and spatial transcriptomics、Ferroptosis and cancer prognosis

BACKGROUND: Diabetic kidney disease (DKD) is the major cause of chronic kidney failure, with tubulointerstitial fibrosis playing a crucial role in disease development. Identifying fibrosis-related genes is crucial for improving diagnosis and developing novel therapies due to the necessity for early detection and effective treatments. METHODS: Genes associated with fibrosis were identified by WGCNA, and a FibrosisScore model was constructed based on ssGSEA scores from two DKD datasets. Essential genes were subsequently confirmed by machine learning and single-cell RNA sequencing (scRNA-seq). Potential therapeutic compounds were identified by screening the ZINC database and confirmed via molecular docking. Critical genes involved in renal fibrosis were analyzed in a streptozotocin (STZ)-induced mouse model of DKD, alongside clinical data from the Nephroseq V5 database. RESULTS: The FibrosisScore model exhibited strong predictive accuracy in both training and validation datasets (AUCs: 0.803, 0.992, 0.891). Patients classified as high-risk demonstrated an increase in M2 macrophages, whereas those identified as low-risk presented a higher prevalence of pro-inflammatory cells. PROM1 and THY1 were recognized as key genes associated with fibrosis. Single-cell RNA analysis revealed that PROM1 is predominantly expressed in proximal tubule cells, while THY1 is enriched in fibroblasts, indicating their distinct roles in fibrosis progression, with both genes exhibiting high diagnostic ac...