Screening Key Genes of Ferroptosis in Atherosclerosis Based on GEO Database Bioinformatics and Experimental Validation
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维普
万方数据
目的 利用生物信息学方法,筛选动脉粥样硬化(atherosclerosis,AS)铁死亡关键基因,并分析关键基因的生物学功能,以便深入了解AS发病机制.方法 从GEO(gene expression omnibus)数据库下载AS基因表达谱芯片数据集GSE100927,以P＜0.05,|logFC＞1|为条件筛选AS的差异基因,并与铁死亡数据集Ferroptosis基因取交集,筛选出AS铁死亡相关基因,并进行基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)富集分析,随后通过STRING在线分析工具联合Cytoscape可视化软件挖掘在AS生物学过程中发挥关键作用的基因,并采用AS数据集GSE9874作为验证集,验证关键基因的表达,最后,收集2023年1～3月所在医院心血管内科30例AS确诊患者血液样本作为实验组,同时收集20例健康志愿者血液样本作为对照组,提取样本RNA,采用实时荧光定量PCR(quantitative real time polymerase chain reaction,qRT-PCR)方法对筛选基因验证.结果 采用生物信息学方法共筛选出10个AS铁死亡相关差异基因.GO功能富集分析结果表明,差异基因主要涉及炎症、细胞凋亡、氧化应激等生物学过程,KEGG通路富集分析表明差异基因主要涉及铁死亡、HIF-1信号通路、白细胞经内皮细胞迁移通路等.蛋白互作网络筛选出7个基因构建的关键模块,分别是FTL,SLC40A1,CYBB,NCF2,HMOX1,DPP4和ALOX5,采用GSE9874进行验证,最终筛选出ALOX5,DPP4,FTL,SLC40A1,NCF2等5个关键基因;qRT-PCR对临床样本中关键基因表达检测显示,相对于对照组,AS 组血液中表达上调的基因有 DPP4(t=1.795,P=0.046),FTL(t=2.218,P=0.029),SLC40A1(t=2.859,P=0.009);表达下调的基因有ALOX5(t=8.039,P＜0.001),NCF2(t=11.867,P＜0.001),差异具有统计学意义;实验结果与生物信息学分析结果一致.亚组分析发现斑块组DPP4表达高于内膜增厚组,差异具有统计学意义(t=2.843,P=0.036).结论 通过生物信息学筛选出AS铁死亡关键基因ALOX5,DPP4,FTL,SLC40A1和NCF2,可能成为AS诊断治疗的潜在靶点,为AS的临床诊疗提供新的思路.
Objective To screen key genes for ferroptosis in atherosclerosis(AS)using bioinformatics methods and analyze the biological functions of key genes to gain an in-depth understanding of the pathogenesis of AS.Methods AS gene expression profile chip dataset GSE100927 was downloaded from the Gene Expression Omnibus(GEO)database.P＜0.05 and|logFC＞1|were used as the conditions to screen the differential genes of AS.These genes were intersected with ferroptosis gene dataset to screen out the genes related to AS ferroptosis.Gene ontology(GO)functional annotation and enrichment analysis of Kyoto Encyclopedia of Genes and Genomes(KEGG)were carried out.The STRING online analysis tool combined with Cytoscape visualization software was subsequently used to mine genes that play a key role in the biological process of AS,and the AS dataset GSE9874 was used as the verification set to verify the expression of key genes.Blood samples from 30 confirmed AS patients in the cardiovascular department of our hospital from January to March 2023 were collected as the experimental group,while blood samples from 20 healthy volunteers were collected as the control group.Sample RNA was extracted,and quantitative real time polymerase chain reaction(qRT-PCR)was used to verify the selected genes.Results A total of 10 differential genes related to ferroptosis were screened by bioinformatics method.GO functional enrichment analysis showed that differential genes were mainly involved in inflammation,apoptosis,oxidative stress and other biological processes,while KEGG pathway enrichment analysis showed that differential genes were mainly involved in ferroptosis,HIF-1 signaling pathway,and leukocyte migration pathway through endothelial cells.Seven key modules of gene construction were screened out through the protein interaction network,which were FTL,SLC40A1,CYBB,NCF2,HMOX1,DPP4 and ALOX5.GSE9874 was used for verification,and 5 key genes including ALOX5,DPP4,FTL,SLC40A1 and NCF2 were finally screened out.The expression detection of key genes in clinical samples by qRT-PCR showed that compared with the control group,the up-regulated genes in blood of AS group were DPP4(t=1.795,P=0.046),FTL(t=2.218,P=0.029)and SLC40A1(t=2.859,P=0.009),and the down-regulated genes were ALOX5(t=8.039,P＜0.001)and NCF2(t=11.867,P＜0.001),and the differences were significant.The experimental results were consistent with the results of bioinformatics analysis.Subgroup analysis showed that DPP4 expression in plaque group was higher than that in intima thickening group,and the difference was significant(t=2.843,P=0.036).Conclusion The key genes of ferroptosis screened by bioinformatics are AS,ALOX5,DPP4,FTL,SLC40A1 and NCF2,which may be potential targets for the diagnosis and treatment of AS,providing new ideas for the clinical diagnosis and treatment of AS.
维普
万方数据
