ArticleEuropean journal of medical research2024
Identification and validation of key extracellular proteins as the potential biomarkers in diabetic nephropathy.
Article in European journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Baicalein alleviates high glucose-induced mesangial cell fibrosis and inflammation in diabetic nephropathy: roles of AMPK activation and TGF-β1 inhibition.Genes & genomics · 2026Article
- Shenqi Dihuang Decoction Attenuates ALOX5-Mediated Ferroptosis in Diabetic Nephropathy via AMPK/mTOR and TGF-Journal of diabetes research · 2026Article
- Inhibition of complement system-related gene ITGB2 attenuates epithelial-mesenchymal transition and inflammation in diabetic nephropathy.European journal of medical research · 2025Article
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5 authors.
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Abstract
objectiveAccumulation of extracellular matrix (ECM) proteins in the glomerular mesangial region is a typical hallmark of diabetic nephropathy (DN). However, the molecular mechanism underlying ECM accumulation in the mesangium of DN patients remains unclear. The present study aims to establish a connection between extracellular proteins and DN with the goal of identifying potential biomarkers for this condition.
methodsDifferentially expressed genes (DEGs) between DN kidney tissue and healthy kidney tissue were analyzed using the public data GSE166239. Two gene lists encoding extracellular proteins were then utilized to identify extracellular protein-differentially expressed genes (EP-DEGs). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were performed on these EP-DEGs. A protein-protein interaction (PPI) network was established to identify key EP-DEGs. Furthermore, the diagnostic ability, immune cell infiltration, and clinical relevance of these EP-DEGs were investigated. Immunohistochemistry (IHC) staining of paraffin-embedded renal tissues was performed to validate the accuracy of the bioinformatic results.
resultsA total of 1204 DEGs were identified, from which 162 EP-DEGs were further characterized by overlapping with extracellular protein gene lists. From the PPI network analysis, five EP-DEGs (e.g., TNF, COL1A1, FN1, MMP9, and TGFB1) were identified as candidate biomarkers. TNF, COL1A1, and MMP9 had a high diagnostic accuracy for DN. Assessment of immune cell infiltration revealed that the expression of TNF was positively associated with resting dendritic cells (DCs) (r = 0.85, P < 0.001) and M1 macrophages (r = 0.62, P < 0.05), whereas negatively associated with regulatory T cells (r = - 0.62, P < 0.05). Nephroseq v5 analysis demonstrated a negative correlation between the estimated glomerular filtration rate (eGFR) and TNF expression (r = - 0.730, P = 0.025). Gene set enrichment analysis (GSEA) revealed significant enrichment of glycosaminoglycan (GAG) degradation in the high-TNF subgroup. IHC staining of renal tissues confirmed significantly elevated TNF-a expression and decreased hyaluronic acid (HA) levels in the DN group compared to controls (both P < 0.05), with a negative correlation observed between TNF-a and HA (r = - 0.691, P = 0.026).
conclusionOur findings suggest that TNF may play a pivotal role in the progress of DN by driving ECM accumulation, and this process might involve GAG degradation pathway activation.
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