摘要
目的对动脉粥样硬化(AS)基因芯片数据进行生物信息学分析,寻找疾病相关核心(Huh)基因,并探讨其在AS发生发展中的作用。方法利用R语言包对基因表达综合数据库(GEO)中筛选出的AS芯片进行基因差异表达分析,String数据库进行蛋白相互作用分析,并以Cytosrape3.7.2软件插件CytHubba筛选Huh基因,采用DAVID6.8及R语言包对Huh基因行功能注释GO富集分析和KEGG通路富集分析。结果与正常动脉内膜比较,晚期AS斑块中309个基因存在差异表达,其中121个表达上调,188个表达下调,构建PPI网络后,鉴定出21个Huh基因,即:CXCL8,IL1B,CD86,CXCL2,CXCL3,MMP1,CXCL1,CCL7、CXCR4、CCR1、SGF、ADRA2A、ADRA2C、CD69、GAL、HTR1B、ITGA4、ITGAX、PLEK、SPP1、TREM1。Hub基因被富集到253个不同的GO子集中,包括生物学过程(BP)、细胞组分(CC)和分子功能(MF)三个方面,其中各自最显著富集的子集分别为白细胞迁移、白细胞趋化性、细胞趋化性、细胞质膜外侧面、受体配体活性、G蛋白偶联受体结合、细胞因子活性、细胞因子受体结合等。同时,Hub基因被富集到类风湿关节炎信号通路、白细胞介素-17(IL-17)信号通路、核因子κB(NF-κB)信号通路、肿瘤坏死因子(TNF)信号通路趋化因子信号通路、细胞因子-细胞因子受体相互作用等25个信号通路中。结论通过对GEO数据库中AS的芯片数据进行分析,所筛选出的Hub基因涉及AS发生发展的多个炎症信号通路,可为AS发病机制研究或靶向药物的研发提供重要实验理论依据。
Objective To implement bioinformatics analyses about atherosclerosis(AS)gene chip data,so as to find disease-related hub genes,and explore their role in the occurrence and development of AS.Methods The R language packages were used to analyze the differential expression of genes in the AS chips screened in the Gene Expression Omnibus(GEO),and the String database was used to perform the protein-protein interactions.GO and KEGG enrichment analyses for functional annotation and pathway analyses of hub genes were conducted by DAVID6.8 and R language packages.Results Compared with normal intima,309 differentially expressed genes(DEGs)were significant statistically in advanced AS plaques,among which 121 were up-regulated and 188 were down-regulated.Following PPI network construction,21 hub genes were identified,namely CXCL8,ILIB,CD86,CXCL2,CXCL3,MMP1,CXCL1,CCL7,CXCR4,CCRL NGF,ADRA2A,ADRA2C,CD69,GAL,HTR1B,ITGA4,ITGAX,PLEK,SPP1 and TREMl.Hub genes were enriched to 253 different GO terms,including biological process(BP),cell component(CC)and molecular function(MF),and the most significant terms were leukocyte migration,leukocyte chemotaxis,cell chemotaxis,external side of plasma membrane,receptor ligand activity,G protein-coupled receptor binding,cytokine activity,cytokine receptor binding and et al.DEGs were enriched to 25 different signal pathways,including rheumatoid arthritis,IL-17 signaling pathway,NF-kappa B signaling pathway,TNF signaling pathway,chemokine signaling pathway,cytokine-cytokine receptor interaction and et al.Conclusion Through analyzing the chip data of AS in the GEO database,the identified hub genes are involved in multiple inflammatory signaling pathways for the occurrence and development of AS,which might provide important experimental theoretical basis for the research of AS pathogenesis or the development of targeted drugs.
作者
尤红俊
赵倩倩
常凤军
寿锡凌
周娟
韩稳琦
YOU Hong-jun;ZHAO Qian-qian;CHANG Feng-jun;SHOU Xi-ling;ZHOU Juan;HAN Wen-qi(Department of Cardiovascular Medicine,Shaanxi Provincial People's Hospital,Xi'an 710068,China;Department of Clinical Immunology,The First Affiliated Hospital,Air Force Military Medical University,Xi'an 710032,China;Department of Cardiovascular Medicine,The First Affiliated Hospital,Xi'an Jiaotong University,Xi'an 710061,China)
出处
《中国分子心脏病学杂志》
CAS
2021年第6期4326-4334,共9页
Molecular Cardiology of China
基金
国家自然科学基金(81770458)
陕西省分子心脏病学重点实验室开放课题基金(KLMC-2018-05)。
关键词
动脉粥样硬化
基因表达综合数据库
基因差异表达
生物信息学
富集分析
Atherosclerosis
Gene expression omnibus(GEO)database
Gene differential expression:Bioinformatics
Enrichment analysis
