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Background <p>Diabetic 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.</p> Methods <p>In 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.</p> Results <p>CD44, 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, <i>P =</i> 0.006), indicating a significant increase in risk. HSPG2 showed an OR of 1.167 (95% CI: 1.023–1.331, <i>P =</i> 0.022), while PTGES and LPAR1 had ORs of 1.225 (95% CI: 1.000-1.501, <i>P =</i> 0.050) and 1.082 (95% CI: 1.011–1.157, <i>P =</i> 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.</p> Conclusion <p>This 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.</p>

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Unveiling the role of angiogenesis-related biomarkers in diabetic nephropathy via transcriptomics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月9日

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  • Shiyu Zhao,
  • Cuiping Yang,
  • Linlin Gao,
  • Xuemei Fan,
  • Shiwei Liu

摘要

Background

Diabetic 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.

Methods

In 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.

Results

CD44, 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.

Conclusion

This 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.