ArticleDiabetology & metabolic syndrome2025
Unveiling the role of angiogenesis-related biomarkers in diabetic nephropathy via transcriptomics.
Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Vulnerable plaques in atherosclerosis: focus on angiogenesis-associated phenotypic crosstalk.Frontiers in pharmacology · 2025Review
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5 authors.
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Abstract
backgroundDiabetic nephropathy (DN), a common complication of diabetes, is characterized by structural and functional renal damage. Angiogenesis plays a pivotal role in both physiological and pathological renal processes. This study explored angiogenesis-related biomarkers in DN to provide theoretical insights for clinical practice.
methodsIn this study, datasets obtained from public databases were utilized to integrate differential expression analysis with Mendelian randomization (MR) analysis. This approach successfully identified biomarkers that exhibited a causal relationship with DN and facilitated the construction of a nomogram based on these genes. Furthermore, the signaling pathways associated with these biomarkers were investigated, along with the differences in the immune microenvironment between DN and normal tissues. Ultimately, cell types present in DN were annotated to explore their potential roles in the disease. Additionally, the expression levels of biomarkers were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting.
resultsCD44, HSPG2, LPAR1, and PTGES were identified as biomarkers and risk factors for diabetic nephropathy (DN). Specifically, CD44 had an odds ratio (OR) of 1.559 (95% CI: 1.133-2.145, P = 0.006), indicating a significant increase in risk. HSPG2 showed an OR of 1.167 (95% CI: 1.023-1.331, P = 0.022), while PTGES and LPAR1 had ORs of 1.225 (95% CI: 1.000-1.501, P = 0.050) and 1.082 (95% CI: 1.011-1.157, P = 0.022), respectively. A diagnostic nomogram demonstrated strong predictive capability. Immunoinfiltration analysis revealed significant differences in memory B cells, CD8 T cells, and M1 macrophages. Enrichment analysis highlighted pathways of "ECM-receptor interaction". scRNA-seq identified 14 distinct cell types, with CD44 expression highest in Pan leukocytes. Additionally, qRT-PCR confirmed significant upregulation of biomarkers in DN, supported by WB results.
conclusionThis study identified CD44, HSPG2, LPAR1, and PTGES as novel DN biomarkers and confirmed their association with disease risk. These findings provide insights into DN pathogenesis and potential therapeutic targets.
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