Aging-driven transcriptional programs in diabetic kidney disease: multi-omics discovery of diagnostic biomarkers and drug-repurposing targets

BACKGROUND: Diabetic kidney disease (DKD) is the primary global cause of end-stage renal disease. However, the aging-related gene networks driving its progression remain unclear. METHODS: In this study, we integrated bioinformatics and experiments to screen for age-related hub genes in DKD and explore their diagnostic and therapeutic values. Transcriptomic datasets and aging-related gene databases were combined to obtain candidate differentially expressed genes enriched in the PI3K-Akt and JAK-STAT pathways. LASSO and Random Forest algorithms were applied to screen core hub genes, and a logistic diagnostic model was constructed for verification. Single-cell sequencing was utilized to clarify the main cell populations expressing key genes. Molecular docking and dynamics simulations were performed to analyze the binding stability of candidate drugs and target genes. High-glucose cell models and DKD rat models were established, and RT-qPCR, western blot, and pathological staining assays were used to validate the expression changes of key genes and the regulatory effects of drugs. RESULTS: Nine hub genes (CLU, EGF, SLC16A7, MYC, RPA1, RB1, APOC3, SYK, and NR3C1) were finally screened out. The constructed logistic diagnostic model achieved an AUC of 0.881 in external verification. Glomerular endothelial cells and mesangial cells were identified as the main cell populations expressing these hub genes. Molecular simulation results confirmed the stable binding of fostamatinib to SYK and selexipag to APOC3. In vivo and in vitro validation experiments demonstrated that the two candidate agents could suppress NF-κB pathway activation, inflammatory cytokine release, and cellular senescence. CONCLUSION: In this study, we identified age-related hub genes, constructed a reliable diagnostic signature, and suggested SYK-fostamatinib and APOC3-selexipag as potential drug-repurposing candidates for DKD, which requires further experimental and clinical validation.

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Publication Details

Journal
Clinical Epigenetics
Published
2026-07-16
DOI
https://doi.org/10.1186/s13148-026-02207-9
Primary Topic
Chronic Kidney Disease and Diabetes
Type
article
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article

Aging-driven transcriptional programs in diabetic kidney disease: multi-omics discovery of diagnostic biomarkers and drug-repurposing targets

Yingzhuo Li, Chunjuan Xia, Yang Wang, Yi-Xiang Wang et al.
Clinical Epigenetics
Chronic Kidney Disease and Diabetes
article

Aging-driven transcriptional programs in diabetic kidney disease: multi-omics discovery of diagnostic biomarkers and drug-repurposing targets

Yingzhuo Li, Chunjuan Xia, Yang Wang, Yi-Xiang Wang, Bosheng Luo, Xue Hu
article en

Abstract

BACKGROUND: Diabetic kidney disease (DKD) is the primary global cause of end-stage renal disease. However, the aging-related gene networks driving its progression remain unclear. METHODS: In this study, we integrated bioinformatics and experiments to screen for age-related hub genes in DKD and explore their diagnostic and therapeutic values. Transcriptomic datasets and aging-related gene databases were combined to obtain candidate differentially expressed genes enriched in the PI3K-Akt and JAK-STAT pathways. LASSO and Random Forest algorithms were applied to screen core hub genes, and a logistic diagnostic model was constructed for verification. Single-cell sequencing was utilized to clarify the main cell populations expressing key genes. Molecular docking and dynamics simulations were performed to analyze the binding stability of candidate drugs and target genes. High-glucose cell models and DKD rat models were established, and RT-qPCR, western blot, and pathological staining assays were used to validate the expression changes of key genes and the regulatory effects of drugs. RESULTS: Nine hub genes (CLU, EGF, SLC16A7, MYC, RPA1, RB1, APOC3, SYK, and NR3C1) were finally screened out. The constructed logistic diagnostic model achieved an AUC of 0.881 in external verification. Glomerular endothelial cells and mesangial cells were identified as the main cell populations expressing these hub genes. Molecular simulation results confirmed the stable binding of fostamatinib to SYK and selexipag to APOC3. In vivo and in vitro validation experiments demonstrated that the two candidate agents could suppress NF-κB pathway activation, inflammatory cytokine release, and cellular senescence. CONCLUSION: In this study, we identified age-related hub genes, constructed a reliable diagnostic signature, and suggested SYK-fostamatinib and APOC3-selexipag as potential drug-repurposing candidates for DKD, which requires further experimental and clinical validation.

Clinical Epigenetics
Kunming Medical University (CN)
Openalex Percentile: Top 9%
Chronic Kidney Disease and Diabetes
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