关键词: NETosis bioinformatics diabetic kidney disease immune characteristics tubulointerstitial injury

Mesh : Diabetic Nephropathies / genetics diagnosis metabolism Humans Biomarkers / metabolism Extracellular Traps / metabolism Gene Expression Profiling Gene Regulatory Networks Databases, Genetic Nephritis, Interstitial / genetics diagnosis Glomerular Filtration Rate

来  源:   DOI:10.1155/2024/4815488   PDF(Pubmed)

Abstract:
Background: Tubulointerstitial injury plays a pivotal role in the progression of diabetic kidney disease (DKD), yet the link between neutrophil extracellular traps (NETs) and diabetic tubulointerstitial injury is still unclear. Methods: We analyzed microarray data (GSE30122) from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with DKD\'s tubulointerstitial injury. Functional and pathway enrichment analyses were conducted to elucidate the involved biological processes (BP) and pathways. Weighted gene coexpression network analysis (WGCNA) identified modules associated with DKD. LASSO regression and random forest selected NET-related characteristic genes (NRGs) related to DKD tubulointerstitial injury. Results: Eight hundred ninety-eight DEGs were identified from the GSE30122 dataset. A significant module associated with diabetic tubulointerstitial injury overlapped with 15 NRGs. The hub genes, CASP1 and LYZ, were identified as potential biomarkers. Functional enrichment linked these genes with immune cell trafficking, metabolic alterations, and inflammatory responses. NRGs negatively correlated with glomerular filtration rate (GFR) in the Neph v5 database. Immunohistochemistry (IHC) validated increased NRGs in DKD tubulointerstitial injury. Conclusion: Our findings suggest that the CASP1 and LYZ genes may serve as potential diagnostic biomarkers for diabetic tubulointerstitial injury. Furthermore, NRGs involved in diabetic tubulointerstitial injury could emerge as prospective targets for the diagnosis and treatment of DKD.
摘要:
背景:肾小管间质损伤在糖尿病肾病(DKD)的进展中起关键作用,然而,中性粒细胞胞外捕获网(NETs)与糖尿病肾小管间质损伤之间的联系仍不清楚.方法:我们分析了来自基因表达综合(GEO)数据库的微阵列数据(GSE30122),以鉴定与DKD的肾小管间质损伤相关的差异表达基因(DEGs)。进行功能和途径富集分析以阐明所涉及的生物过程(BP)和途径。加权基因共表达网络分析(WGCNA)鉴定了与DKD相关的模块。LASSO回归和随机森林选择与DKD肾小管间质损伤相关的NET相关特征基因(NRGs)。结果:从GSE30122数据集中鉴定出八百九十八个DEG。与糖尿病肾小管间质损伤相关的重要模块与15个NRGs重叠。枢纽基因,CASP1和LYZ,被鉴定为潜在的生物标志物。功能富集将这些基因与免疫细胞运输联系起来,代谢改变,和炎症反应。在Nephv5数据库中,NRGs与肾小球滤过率(GFR)呈负相关。免疫组织化学(IHC)验证了DKD肾小管间质损伤中NRG的增加。结论:我们的发现表明,CASP1和LYZ基因可能是糖尿病肾小管间质损伤的潜在诊断生物标志物。此外,参与糖尿病肾小管间质损伤的NRGs可能成为诊断和治疗DKD的潜在目标。
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