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已发表论文
糖尿病肾病患者肾功能相关基因的多组学分析及 Nephroseq 数据库预测潜在靶向药物
Authors Deng L, Yan F , Feng C , Yang Q
Received 31 May 2025
Accepted for publication 29 August 2025
Published 6 October 2025 Volume 2025:18 Pages 3781—3794
DOI https://doi.org/10.2147/DMSO.S526696
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Rebecca Baqiyyah Conway
Ling Deng, Feifan Yan, Changmei Feng, Qiong Yang
Department of Endocrinology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, Guangxi, Zhuang Autonomous Region, 541002, People’s Republic of China
Correspondence: Qiong Yang, Department of Endocrinology Nanxishan Hospital of Guangxi Zhuang Autonomous Region, No. 96 Chongxin Road, Guilin, Guangxi Zhuang Autonomous Region, 541002, People’s Republic of China, Email m17840815669@163.com
Purpose: Diabetic nephropathy (DN), a major complication of type 2 diabetes and leading cause of end-stage renal disease, lacks complete molecular understanding. To elucidate the mechanisms underlying kidney injury in DN, we analyzed mRNA and protein expression changes in mouse kidney tissue, aiming to provide a theoretical foundation for drug development.
Methods: C57BL/6 mice were divided into two groups: a normal control group and a diabetes model group. The type 2 diabetes model was established using a high-fat diet (HFD) combined with streptozotocin (STZ). Fasting blood glucose levels and glucose tolerance tests were performed to evaluate glucose metabolism. Kidney tissues were collected, with the left kidney rapidly frozen in liquid nitrogen for transcriptomic and proteomic analyses, and the right kidney fixed in paraformaldehyde for subsequent preparation of paraffin-embedded blocks and staining.
Results: Diabetic nephropathy (DN) mice showed significant transcriptomic and proteomic alterations in kidney tissues compared to controls. Transcriptomic analysis revealed 4156 upregulated and 1121 downregulated genes, while proteomic analysis identified 887 differentially expressed proteins (DEPs: 687 upregulated, 200 downregulated). 240 genes were synchronously upregulated and 111 synchronously downregulated at both levels, functionally linked to cellular immunity, autophagy, inflammation, and lipid metabolism. CytoHubba identified 10 hub genes: FN1, TTR, APOA1, ITGB2, APOE, PTPRC, STAT3, VTN, ICAM1, and ANXA2. Nephroseq database analysis of human DN patients showed FN1, STAT3, ICAM1, and ANXA2 were significantly upregulated and APOA1 was significantly downregulated in kidney tissues. Furthermore, FN1, ICAM1, and ANXA2 negatively correlated with eGFR, while APOA1 positively correlated with eGFR.
Conclusion: Diabetic mice exhibited varying degrees of pathological changes in the kidneys. Combined transcriptomic and proteomic analyses highlighted four genes—FN1, ICAM1, ANXA2, and APOA1—as potential therapeutic targets for improving diabetic nephropathy.
Keywords: diabetic nephropathy, multi-omics analysis, transcriptomics, proteomics, kidney function, hub genes
Department of Endocrinology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, Guangxi, Zhuang Autonomous Region, 541002, People’s Republic of China
Correspondence: Qiong Yang, Department of Endocrinology Nanxishan Hospital of Guangxi Zhuang Autonomous Region, No. 96 Chongxin Road, Guilin, Guangxi Zhuang Autonomous Region, 541002, People’s Republic of China, Email m17840815669@163.com
Purpose: Diabetic nephropathy (DN), a major complication of type 2 diabetes and leading cause of end-stage renal disease, lacks complete molecular understanding. To elucidate the mechanisms underlying kidney injury in DN, we analyzed mRNA and protein expression changes in mouse kidney tissue, aiming to provide a theoretical foundation for drug development.
Methods: C57BL/6 mice were divided into two groups: a normal control group and a diabetes model group. The type 2 diabetes model was established using a high-fat diet (HFD) combined with streptozotocin (STZ). Fasting blood glucose levels and glucose tolerance tests were performed to evaluate glucose metabolism. Kidney tissues were collected, with the left kidney rapidly frozen in liquid nitrogen for transcriptomic and proteomic analyses, and the right kidney fixed in paraformaldehyde for subsequent preparation of paraffin-embedded blocks and staining.
Results: Diabetic nephropathy (DN) mice showed significant transcriptomic and proteomic alterations in kidney tissues compared to controls. Transcriptomic analysis revealed 4156 upregulated and 1121 downregulated genes, while proteomic analysis identified 887 differentially expressed proteins (DEPs: 687 upregulated, 200 downregulated). 240 genes were synchronously upregulated and 111 synchronously downregulated at both levels, functionally linked to cellular immunity, autophagy, inflammation, and lipid metabolism. CytoHubba identified 10 hub genes: FN1, TTR, APOA1, ITGB2, APOE, PTPRC, STAT3, VTN, ICAM1, and ANXA2. Nephroseq database analysis of human DN patients showed FN1, STAT3, ICAM1, and ANXA2 were significantly upregulated and APOA1 was significantly downregulated in kidney tissues. Furthermore, FN1, ICAM1, and ANXA2 negatively correlated with eGFR, while APOA1 positively correlated with eGFR.
Conclusion: Diabetic mice exhibited varying degrees of pathological changes in the kidneys. Combined transcriptomic and proteomic analyses highlighted four genes—FN1, ICAM1, ANXA2, and APOA1—as potential therapeutic targets for improving diabetic nephropathy.
Keywords: diabetic nephropathy, multi-omics analysis, transcriptomics, proteomics, kidney function, hub genes