Department of Pediatrics, First Affiliated Hospital of Henan University of Science and Technology, Luoyang, PR China.
Eur Rev Med Pharmacol Sci. 2012 Jul;16(7):867-72.
Asthma prevalence has increased very considerably in recent decades such that it is now one of the commonest chronic disorders in the world. In this present study, We constructed a protein-protein interaction (PPI) network by mapped the differentially expressed genes (DEGs) to the PPI data and performed Gene Ontology (GO) enrichment analysis of the PPI network. We aimed to explore the pathogenesis of atopic asthma by bioinformatics methods.
To explore the pathogenesis of atopic asthma by bioinformatics methods, we obtained the global gene expression profile of pediatric asthmatic epithelium GSE18965 from Gene Expression Omnibus (GEO), and identified the differentially expressed genes between healthy nonatopic samples and atopic asthmatic samples
Total 12 DEGs were selected. Furthermore, we constructed a protein-protein interaction network by mapped the DEGs to the PPI data and performed Gene Ontology enrichment analysis of the PPI network. Total 15 GO terms were enriched and the enriched terms can be generally classified into two groups: cell cycle and immunity.
Our results confirmed the role of cell proliferation and immune system in the pathogenesis of atopic asthma. Besides, our PPI network is useful in investigating the complex interacting mechanisms of transcription factors and their regulated genes in atopic asthma.
在最近几十年中，哮喘的患病率显著增加，因此现在它是世界上最常见的慢性疾病之一。在本研究中，我们通过将差异表达基因（DEGs）映射到蛋白质-蛋白质相互作用（PPI）数据上来构建蛋白质-蛋白质相互作用（PPI）网络，并对 PPI 网络进行基因本体论（GO）富集分析。我们旨在通过生物信息学方法探索特应性哮喘的发病机制。
为了通过生物信息学方法探索特应性哮喘的发病机制，我们从基因表达综合数据库（GEO）中获得了儿科特应性哮喘上皮细胞的全基因表达谱 GSE18965，并鉴定了健康非特应性样本和特应性哮喘样本之间的差异表达基因。
共选择了 12 个 DEGs。此外，我们通过将 DEGs 映射到 PPI 数据来构建蛋白质-蛋白质相互作用网络，并对 PPI 网络进行基因本体论（GO）富集分析。共富集了 15 个 GO 术语，富集的术语可以大致分为两类：细胞周期和免疫。
我们的结果证实了细胞增殖和免疫系统在特应性哮喘发病机制中的作用。此外，我们的 PPI 网络有助于研究特应性哮喘中转录因子及其调控基因的复杂相互作用机制。
