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糖尿病肾病全凋亡相关基因特征的构建

Construction of a PANoptosis-Related Gene Signature for Diabetic Nephropathy.

作者信息

Geng Li, Liu Yingying, Sun Yunwei, Chen Yan

机构信息

Department of Vascular Surgery, The second hospital of Jilin University, Changchun, China.

Department of Endocrinology, The second hospital of Jilin University, Changchun, China.

出版信息

Kidney Blood Press Res. 2025;50(1):496-512. doi: 10.1159/000546764. Epub 2025 Jun 12.

Abstract

INTRODUCTION

Diabetic nephropathy (DN) is a serious complication of diabetes. In this study, we aimed to develop a diagnostic model for DN based on PANoptosis-related genes.

METHODS

PANoptosis-related differentially expressed gene (DEGs) associated with DN were identified in the GSE96804 and GSE142025 datasets. Pairwise correlations among these genes were assessed via Pearson correlation analysis. Immune cell abundance in DN patients versus controls was compared in GSE96804. Feature genes for DN prediction were selected with machine learning, and a diagnostic model was constructed using LASSO regression. High-risk and low-risk groups were established based on risk scores, with GSEA used to explore enriched biological processes and pathways. The association between risk scores and immune cell infiltration was examined using CIBERSORT. Potential therapeutic drugs were investigated via the DGIdb database.

RESULTS

Six PANoptosis-related DEGs were found. Immune cell analysis showed significant differences in dendritic cells, macrophages, mast cells, and neutrophils between DN patients and controls. A diagnostic model using three genes (PDK4, YWHAH, PRKX) achieved high accuracy (area under the curve = 0.8-1.0) across datasets, with a reliable nomogram for DN prediction. Risk stratification linked higher risk scores to distinct immune infiltration patterns and enriched cellular transport and metabolic pathways in high-risk DN patients. Protein-protein interaction network and correlation analyses revealed complex gene interactions. Potential therapeutic targets (PRKX, PDK4) and drugs were identified, and quantitative PCR validated YWHAH upregulation in patient plasma samples.

CONCLUSION

The integration of PANoptosis-related genes PDK4, YWHAH, and PRKX offers a promising diagnostic model for DN, with YWHAH potentially involved in the pathological progression of DN.

摘要

引言

糖尿病肾病(DN)是糖尿病的一种严重并发症。在本研究中,我们旨在基于泛凋亡相关基因开发一种DN诊断模型。

方法

在GSE96804和GSE142025数据集中鉴定与DN相关的泛凋亡相关差异表达基因(DEG)。通过Pearson相关分析评估这些基因之间的成对相关性。在GSE96804中比较DN患者与对照中的免疫细胞丰度。使用机器学习选择用于DN预测的特征基因,并使用LASSO回归构建诊断模型。基于风险评分建立高风险和低风险组,使用GSEA探索富集的生物学过程和途径。使用CIBERSORT检查风险评分与免疫细胞浸润之间的关联。通过DGIdb数据库研究潜在的治疗药物。

结果

发现六个泛凋亡相关DEG。免疫细胞分析显示DN患者与对照之间在树突状细胞、巨噬细胞、肥大细胞和中性粒细胞方面存在显著差异。使用三个基因(PDK4、YWHAH、PRKX)的诊断模型在各数据集中均实现了高精度(曲线下面积=0.8 - 1.0),并具有用于DN预测的可靠列线图。风险分层将较高的风险评分与不同的免疫浸润模式以及高风险DN患者中富集的细胞转运和代谢途径联系起来。蛋白质 - 蛋白质相互作用网络和相关性分析揭示了复杂的基因相互作用。鉴定了潜在的治疗靶点(PRKX、PDK4)和药物,定量PCR验证了患者血浆样本中YWHAH的上调。

结论

泛凋亡相关基因PDK4、YWHAH和PRKX的整合为DN提供了一种有前景的诊断模型,YWHAH可能参与DN的病理进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bff4/12263135/bcca3b87763f/kbr-2025-0050-0001-546764_F01.jpg

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