ArticleJournal of translational medicine2025
Uncovering key markers and therapeutic targets for renal fibrosis in diabetic kidney disease through bulk and single-cell RNA sequencing.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Utilizing urinary single-cell RNA sequencing to explore the pathogenesis of diabetic kidney disease progression.Clinical kidney journal · 2026Article
- Single-cell transcriptomic analysis deciphers heterogeneity and transcriptional regulatory programs of sepsis with different prognosis.Biology direct · 2026Article
- Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Review
- Risk stratification in diabetic kidney disease: a review of prediction models for methodological advances and clinical application.Journal of translational medicine · 2026Review
- Single-nucleus transcriptomics identifies SPON1 as a candidate mediator of the anti-fibrotic effect ofAmerican journal of translational research · 2026Article
- Identification and validation of an explainable prediction model of favorable outcome under integrative medicine treatment exposure in DKD adult patients: a retrospective cohort study.Frontiers in digital health · 2026Article
- Knowledge Mapping of Macrophages in Renal Fibrosis: A Bibliometric Analysis from 2014 to 2025.Journal of inflammation research · 2026Review
- Multi-Omics Analysis and Nephroseq Database of Genes Related to Kidney Function in Diabetic Nephropathy Patients to Predict Potential Target Drugs.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Single-Cell Sequencing Uncovers a TMSB10-Expressing Fibroblast Subpopulation Driving Renal Fibrosis in Diabetic Nephropathy.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
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13 authors.
Funding
Abstract
backgroundDiabetic 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.
methodsGenes 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.
resultsThe 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 accuracy (AUC > 0.9). Immune infiltration analysis of PROM1 was primarily associated with a pro-fibrotic, immunosuppressive environment, while THY1 demonstrated antifibrotic properties. ZINC402830 and ZINC3830400 were screened from the ZINC database and validated through molecular docking. In the STZ mouse model, PROM1 correlated with fibrosis and diminished renal function, whereas THY1 exhibited protective effects.
conclusionPROM1 and THY1 were critical diagnostic biomarkers for renal fibrosis in DKD, with PROM1 promoting kidney fibrosis and THY1 providing protective effects. The FibrosisScore model demonstrated robust predictive performance, and molecular docking revealed potential therapeutic modulators for these targets.
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