首页|期刊导航|医学信息|基于生物信息学分析糖尿病肾病肾小球自噬相关基因

基于生物信息学分析糖尿病肾病肾小球自噬相关基因OA

Bioinformatics-based Analysis of Glomerular Autophagy-related Genes in Diabetic Nephropathy

中文摘要英文摘要

目的 基于生物信息学技术挖掘糖尿病肾病自噬的生物标志物、机制和潜在的药物.方法 下载 GSE1009 数据集识别糖尿病肾病差异基因,Human Autophagy Database下载自噬相关基因.将自噬相关基因与糖尿病肾病差异基因取交集,获得二者共同基因,对糖尿病肾病自噬相关基因(DE-ATGs)进行 GO 和 KEGG 富集分析,使用PPI 蛋白互作网络识别DE-ATGs的前10 个核心基因,并利用GSE96804 数据集验证核心基因的表达谱,使用Nephropseqv5 进行临床相关性分析,使用The Drug Gene Interaction数据集预测核心基因潜在的靶向药物.结果 GSE1009 数据集中筛选出 1244 个糖尿病肾病差异基因,Human Autophagy Database 数据库下载自噬相关基因 232 个,二者取交集得到 22 个 DE-ATGs.DE-ATGs 生物过程显著富集在regulation of autophagy,autophagy of mitochondrion.KEGG 富集分析显著富集 Autophagy-animal,Longevity regulating pathway,Autophagy-other等信号通路.PPI蛋白互作网络筛选出的前 10 个核心基因为VEGFA、HSPA5、ATG5、MYC、CASP1、EIF4EBP1、BAX、IFNG、RHEB、ATG4B.VEGFA与肾小球滤过率呈正相关,HSPA5,CASP1 与肾小球滤过率呈负相关.靶向药物或成分包括FENOFIBRATE、ENALAPRIL、SILDENAFIL可能会上调VEGFA表达水平,DAPHNETIN能够上调HSPA5 的表达水平.BELNACASAN、DIACEREIN能够抑制CASP1 的表达.结论 VEGFA、HSPA5、CASP1 可能是糖尿病肾病诊断及评估的新标志物.药物-基因相互作用分析为糖尿病肾病治疗提供了可能的候选药物.

Objective To explore the biomarkers,mechanisms and potential drugs of autophagy in diabetic nephropathy based on bioinformatics technology.Methods The GSE1009 dataset was downloaded to identify differentially expressed genes in diabetic nephropathy,and autophagy-related genes were downloaded from the Human Autophagy Database.The intersection of autophagy-related genes and differentially expressed genes in diabetic nephropathy was taken to obtain the common genes.GO and KEGG enrichment analyses were performed on diabetic nephropathy autophagy-related genes(DE-ATGs).In addition,PPI network was used to identify the top 10 hub genes of the DE-ATGs.The expression profiles of the hub genes were validated using the GSE96804 dataset.Clinical correlation analysis was performed using Nephroseqv5.Potential targeted drugs for the hub genes were predicted using The DrugGene Interaction Database.Results A total of 1244 differentially expressed genes in diabetic nephropathy were screened from the GSE1009 dataset,and 232 autophagy-related genes were downloaded from the Human Autophagy Database database,and 22 DE-ATGs were obtained by intersection of the two.DE-ATGs biological processes were significantly enriched in regulation of autophagy,autophagy of mitochondrion.KEGG enrichment analysis significantly enriched in Autophagy-animal,Longevity regulating pathway,Autophagy-other and other signaling pathways.The top 10 core genes screened by PPI protein interaction network were VEGFA,HSPA5,ATG5,MYC,CASP1,EIF4EBP1,BAX,IFNG,RHEB and ATG4B.VEGFA was positively correlated with glomerular filtration rate,HSPA5 and CASP1 were negatively correlated with glomerular filtration rate.Targeted drugs or ingredients including FENOFIBRATE,ENALAPRIL,SILDENAFIL may up-regulate the expression level of VEGFA,and DAPHNETIN can up-regulate the expression level of HSPA5.BELNACASAN and DIACEREIN can inhibit the expression of CASP1.Conclusion VEGFA,HSPA5 and CASP1 may be new markers for the diagnosis and evaluation of diabetic nephropathy.Drug-gene interaction analysis provides a possible candidate drug for the treatment of diabetic nephropathy.

王亚婷;宋凯;黄丽;廖婷;刘昱

四川卫生康复职业学院护理学院,四川 自贡 643000四川卫生康复职业学院康复学院,四川 自贡 643000四川卫生康复职业学院护理学院,四川 自贡 643000四川卫生康复职业学院护理学院,四川 自贡 643000深圳大学附属华南医院肾内科,广东 深圳 518111

医药卫生

糖尿病肾病生物信息学自噬药物预测肾小球滤过率

Diabetic nephropathyBioinformaticsAutophagyDrug predictionGlomerular filtration rate

《医学信息》 2026 (10)

1-9,9

1.自贡市重点科技计划项目(编号:2023RKX01-05)2.四川卫生康复职业学院校级科研团队(编号:CWKY-TD22-06)

10.3969/j.issn.1006-1959.2026.10.001

评论