| 引用本文: | 吴伟明,林龙,何雪兰,林伟彤,黄凯鹏.基于生物信息学鉴定糖尿病肾病的[]相关基因和ceRNA网络[J].生物信息学,2026,24(3):274-289. |
| Wu Weiming,Lin Long,He Xuelan,Lin Weitong,Huang Kaipeng.Bioinformatics-based identification of potential diagnostic genes and ceRNA networks in diabetic nephropathy[J].Chinese Journal of Bioinformatics,2026,24(3):274-289. |
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| 基于生物信息学鉴定糖尿病肾病的[]相关基因和ceRNA网络 |
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吴伟明1,2,林龙1,2,何雪兰1,林伟彤1,黄凯鹏1
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(1.广州医科大学附属市八医院 I期临床试验研究室,广州 510440;2.广州医科大学 药学院,广州 514436)
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| 摘要: |
| 糖尿病肾病是糖尿病的主要微血管并发症,其分子机制尚未完全阐明。本研究旨在通过生物信息学方法筛选DN关键基因并探索其潜在机制。从GEO数据库获取GSE142025(27例DNvs.9例对照)和GSE142153(24例DNvs.10例对照)数据集,利用limma包筛选差异表达基因(DEGs,|logFC|>1,adj.P<0.05)。通过CIBERSORTx分析免疫细胞浸润,结合GO/KEGG/GSEA富集分析解析DEGs功能。基于STRING数据库构建蛋白质互作网络,并利用Cytoscape筛选枢纽基因。通过独立数据集GSE30122验证关键基因表达及诊断效能。共鉴定64个共表达DEGs,主要富集于炎症反应(IL-17、NF-κB、TGF-β通路)和细胞外基质代谢。免疫浸润分析显示DN组CD4+ T细胞和M1巨噬细胞减少,而活化树突细胞和中性粒细胞增加(P<0.05)。PPI分析鉴定出4个枢纽基因(IL1B、IL6、MMP9、ATF3),其表达与肾小球滤过率呈显著负相关(P<0.05)。独立验证表明,这些基因在DN组显著上调,且ROC曲线分析显示其诊断效能优异(AUC>0.8)。本研究揭示了DN的炎症和免疫调控特征,筛选出4个关键基因(IL1B、MMP9、ATF3、IL6),其表达与肾功能损伤显著相关,并具有潜在诊断价值,为DN的机制研究和临床诊断提供了新靶点。 |
| 关键词: 糖尿病肾病 生物信息学 差异表达基因 ceRNA网络 免疫浸润 |
| DOI：10.12113/202412011 |
| 分类号:Q344+.13 |
| 文献标识码:A |
| 基金项目: |
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| Bioinformatics-based identification of potential diagnostic genes and ceRNA networks in diabetic nephropathy |
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Wu Weiming1,2, Lin Long1,2, He Xuelan1, Lin Weitong1, Huang Kaipeng1
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(1.Phase I Clinica1 Trial Center, Guangzhou Eighth Peoples Hospital, Guangzhou Medical University, Guangzhou 510440, China;2.School of Pharmaceutical Sciences, Guangzhou Medical University, Guangzhou 514436, China)
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| Abstract: |
| Diabetic nephropathy (DN) is a major microvascular complication of diabetes, and its molecular mechanisms remain incompletely understood. This study aimed to identify key genes and explore their potential mechanisms in DN using bioinformatics approaches. The datasets GSE142025 (27 DN vs. 9 controls) and GSE142153 (24 DN vs. 10 controls) were obtained from the GEO database. Differentially expressed genes (DEGs, |logFC| > 1, adj. P< 0.05) were screened using the limma package. Immune cell infiltration was analyzed via CIBERSORTx, and functional enrichment of DEGs was assessed using GO/KEGG/GSEA analysis. A protein-protein interaction (PPI) network was constructed using the STRING database, and hub genes were identified via Cytoscape. The expression and diagnostic efficacy of key genes were validated using an independent dataset (GSE30122).A total of 64 co-expressed DEGs were identified, primarily enriched in inflammatory responses (IL-17, NF-κB, and TGF-β pathways) and extracellular matrix metabolism. Immune infiltration analysis revealed decreased CD4+ T cells and M1 macrophages, along with increased activated dendritic cells and neutrophils in the DN group (P< 0.05). PPI analysis identified four hub genes (IL1B, IL6, MMP9, and ATF3), whose expression was significantly negatively correlated with glomerular filtration rate (P< 0.05). Independent validation confirmed their significant upregulation in DN, and ROC curve analysis demonstrated excellent diagnostic performance (AUC > 0.8). This study revealed inflammatory and immune regulatory features of DN and identified four key genes (IL1B, MMP9, ATF3, and IL6) associated with renal dysfunction. These genes exhibit potential diagnostic value and may serve as novel biomarkers, providing insights into DN pathogenesis and clinical diagnosis. |
| Key words: Diabetic nephropathy Bioinformatics Differentially expressed genes ceRNA network Immune infiltration |
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