Cheng Qi, Huang Wanjie, Chen Ning, Shang Yunxiao, Zhang Han
Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Clin Respir J. 2016 Jul;10(4):469-76. doi: 10.1111/crj.12247. Epub 2015 Jan 15.
As a common disease with a complex risk, including genetic and environmental factors, atopic asthma is prevalent but treatable. The aim of the study was to predict the underlying mechanism of asthma and identify target genes for the disease.
The affymetrix chip data, GSE18965, were available from Gene Expression Omnibus and the differentially expressed genes (DEGs) between nine atopic asthmatic specimens and seven healthy nonatopic samples were identified by R. Then Gene Ontology and pathway enrichment analyses were performed to these DEGs. Further, search tool for the retrieval of interacting genes/proteins (STRING) was used to select protein-protein interaction (PPI) for DEGs, and then the network was visualized by Cytoscape. Finally, transcription factor binding site analysis was conducted to the hot gene.
Total 565 DEGs were identified, including 535 upregulated and 30 downregulated genes. The upregulated genes, such as structural maintenance of chromosome (SMC)3, significantly affected cellular component of extracellular matrix (P = 1.56E-04). Otherwise, DEGs were remarkably enriched in three pathways, including transforming growth factor-beta signaling pathway (P = 0.005252649). Further, SMC3 was detected as hot gene in PPI network, and NET (Elk3) was predicted as the significant transcription factor for this gene.
SMC3 may play an important role in atopic asthma development; therefore, it has the potential to be the target for the disease. Moreover, our findings provide more knowledge about the mechanism of atopic asthma and help the researchers to explore it in future.
特应性哮喘作为一种具有复杂风险(包括遗传和环境因素)的常见疾病,较为普遍但可治疗。本研究的目的是预测哮喘的潜在机制并确定该疾病的靶基因。
从基因表达综合数据库获取了Affymetrix芯片数据GSE18965,并通过R软件鉴定了9个特应性哮喘标本与7个健康非特应性样本之间的差异表达基因(DEG)。然后对这些DEG进行基因本体论和通路富集分析。此外,使用检索相互作用基因/蛋白质的搜索工具(STRING)为DEG选择蛋白质-蛋白质相互作用(PPI),然后通过Cytoscape可视化网络。最后,对热点基因进行转录因子结合位点分析。
共鉴定出565个DEG,包括535个上调基因和30个下调基因。上调基因,如染色体结构维持(SMC)3,显著影响细胞外基质的细胞成分(P = 1.56E - 04)。此外,DEG在三个通路中显著富集,包括转化生长因子-β信号通路(P = 0.005252649)。进一步地,SMC3在PPI网络中被检测为热点基因,而NET(Elk3)被预测为该基因的重要转录因子。
SMC3可能在特应性哮喘发展中起重要作用;因此,它有可能成为该疾病的靶点。此外,我们的研究结果提供了更多关于特应性哮喘机制的知识,并有助于研究人员在未来进行探索。