Biomedicine

CLC number: R587.2

CPPED1 Links Neutrophil Extracellular Traps to Diabetic Nephropathy: Bioinformatics-Driven Expression Validation

CPPED1关联中性粒细胞胞外诱捕网与糖尿病肾病：生物信息学驱动的表达验证

Department of Nephrology, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China

^† Corresponding author. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 7 May 2025

Abstract

Diabetic nephropathy (DN) begins with diabetes-related disruptions in glucose metabolism, with oxidative stress playing a crucial role. Neutrophil extracellular traps (NETs) are extensive web-like formations composed of cytosolic and granule proteins, which are dependent on oxidative stress for their formation and function. This study aimed to identify potential targets for DN progression, focusing on NETs, using bioinformatic analysis and quantitative Real-Time PCR(qRT-PCR) . We performed differential gene expression (DEG) analysis on two DN-related RNA-seq datasets (GSE142025 and GSE163603) and NETs-related genes. Subsequent analysis included gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), GeneMANIA, and receiver operating characteristic (ROC) curves. Immune cell infiltration levels were assessed via single-sample GSEA, and a regulatory network involving RNA-binding proteins (RBPs) and their associated target mRNA was constructed. qRT-PCR was conducted on high glucose (HG)-treated and control HK-2 cells. Our analysis identified a set of 22 hub genes through the intersection of differentially expressed genes (DEGs) with NETs-related genes. Immune infiltration assessments revealed significant differences across 23 immune cell types among the analyzed groups. Hub genes including calcineurin-like phosphoesterase domain-containing 1 (CPPED1) showed high diagnostic values (AUC over 0.6). qRT-PCR indicated reduced gene expression levels. In summary, this study identified 22 significantly upregulated DEGs that play a vital role in DN by using gene expression omnibus (GEO) database, GSEA, GSVA, immune infiltration analysis and ROC. The expression levels of CPPED1 may serve as novel diagnostic biomarkers and therapeutic targets.

摘要

糖尿病肾病(Diabetic nephropathy，DN)始于与糖尿病相关的葡萄糖代谢紊乱，氧化应激在其中发挥着关键作用。中性粒细胞胞外陷阱(Neutrophil extracellular traps，NETs)是由细胞质和颗粒蛋白组成的松散的网状结构，其形成和功能依赖于氧化应激。本文旨在通过生物信息学分析和实时荧光定量PCR(quantitative Real-Time PCR，qRT-PCR)，识别DN进展的潜在靶点，重点关注NETs。对两个与DN相关的RNA测序数据集(GSE142025和GSE163603)及NETs相关基因进行了差异表达基因分析。随后，进行了基因集富集分析(gene set enrichment analysis，GSEA)、基因集变异分析(gene set variation analysis，GSVA)、GeneMANIA和受试者工作特征曲线(receiver operating characteristic，ROC)分析。我们用单样本GSEA评估了免疫细胞浸润水平，还建立了RNA结合蛋白(RNA-binding proteins，RBP)及其相关靶mRNA的相互作用网络，并对高糖(high glucose，HG)处理和对照的HK-2细胞进行了qRT-PCR实验。通过差异表达基因(differentially expressed genes，DEGs)与NETs相关基因的交集，本研究识别出22个核心基因。免疫细胞浸润评估显示在分析组之间23种免疫细胞类型存在显著差异，包括CPPED1在内的核心基因显示出较高诊断价值，AUC超过0.6。qRT-PCR 结果显示，CPPED1基因表达水平显著降低，提示其有望成为新的诊断生物标志物与治疗靶点。综上，本研究基于 GEO 数据库数据，整合GSEA、GSVA、免疫细胞浸润分析及 ROC 曲线分析等方法，筛选出22个在DN中显著上调且具有关键调控作用的差异表达基因，为DN的分子机制研究与临床诊疗提供了新的参考依据。