儿童哮喘急性发作的特征基因挖掘及其对哮喘发作的预测前景  

Feature gene mining for prediction of acute exacerbation of childhood asthma

作　　者：黄于艺[1] 张俊艳[1] HUANG Yuyi;ZHANG Junyan(The Second Affiliated Hospital of Guangzhou Medical University,Guangdong Provin-cial Key Laboratory of Allergy&Clinical Immunology,Guangzhou 510260,China)

机构地区：[1]广州医科大学附属第二医院广东省过敏反应与免疫重点实验室,广州510260

出　　处：《中国免疫学杂志》2024年第6期1126-1130,共5页Chinese Journal of Immunology

基　　金：国家自然科学基金(82100025)。

摘　　要：目的:应用生物信息学方法对哮喘急性发作患者的基因表达谱芯片进行分析,以探索哮喘急性发作的机制,寻找精准提前识别哮喘急性发作的检测指标。方法:从GEO平台库获取GSE103166芯片数据集,在对数据集进行清洗和整理后,对急性哮喘发作的儿童和非哮喘儿童的表达谱进行差异分析。利用R语言进行富集分析,对差异表达基因(DEGs)进行功能注释。利用基因互作信息,构建DEGs互作网络,并对网络进行结构拆解,筛选出关键基因和调控子网络。结果:GSE103166数据集包含87例儿童(56例急性哮喘发作的儿童和31例非哮喘儿童)鼻拭子样本。筛选出63个显著DEGs,其中上调基因39个,下调基因24个。DEGs主要富集在内吞小泡与内吞小泡膜中,其中CD163是这两个细胞组件唯一显著上调基因。对互作网络进行结构拆解,得出4个主要互作子网络。其中CD163涉及子网络Ⅰ,此网络由CD163、ARG2、CAT、GSTA2、SCNN1G、MT2A组成,其中ARG2、CAT处于调控网络中心。结论:CD163及CD163、ARG2、CAT、GSTA2、SCNN1G、MT2A组成的基因调控网络可能是哮喘急性发作的关键基因与主要调控网络,为精准提前识别哮喘急性发作的检测指标和治疗靶点提供了研究思路。Objective:Analyzing the gene expression microarray of patients experiencing acute asthma by bioinformatics methods,in order to explore the mechanism of acute asthma and to identify early indicator of acute asthma attacks.Methods:The GSE103166 microarray dataset was retrieved from the GEO database,and after cleaning and organizing the data,differential expres-sion analysis was conducted between children experiencing acute asthma attacks and non-asthmatic children.Enrichment analysis was performed using R language to annotate the functions of the differentially expressed genes(DEGs).Using gene interaction informa-tion,a network of interactions among these genes was constructed,and the network structure was deconstructed to identify key genes and regulatory sub-networks.Results:GSE103166 data set contained 87 nasal swab specimens from children(56 cases of acute asth-ma,31 cases of control).Compared with control group,the acute asthma group had 63 differentially expressed genes(39 upregulated and 24 downregulated).The results of enrichment analysis showed that the DEGs were primarily enriched in endocytic vesicle and en-docytic vesicle membrane.Among these,CD163 was the only gene significantly upregulated in both cellular components.The network dismantling analysis demonstrated four different sub-networks.CD163 was involved in sub-networkⅠ,which was composed of CD163,ARG2,CAT,GSTA2,SCNN1G and MT2A.Among them,ARG2 and CAT were at the regulatory center of the network.Conclusion:CD163 and regulatory networks based on CD163,ARG2,CAT,GSTA2,SCNN1G and MT2A are possible the crucial factors contributing to acute asthma.This study provides research ideas for the precise and early identification of biomarkers and thera-peutic targets for acute asthma attacks.

关 键 词：急性哮喘 基因 调控网络 生物信息学 

分 类 号：R562.25[医药卫生—呼吸系统]