Wang Zongling, Wang Lizhi, Dai Lina, Wang Yanan, Li Erhong, An Shuyuan, Wang Fengliang, Liu Dan, Pan Wen
Department of internal medicine, Qingdao Fuwai Cardiovascular Hospital, 18th Floor north, 201 Nanjing Road, 266034, Qingdao, Shandong, China.
Clinical laboratory, Qingdao Fuwai Cardiovascular Hospital, Qingdao, China.
Allergy Asthma Clin Immunol. 2022 Dec 22;18(1):108. doi: 10.1186/s13223-022-00744-5.
Asthma is an important non-communicable disease worldwide. DNA methylation is associated with the occurrence and development of asthma. We are aimed at assuring differential expressed genes (DEGs) modified by aberrantly methylated genes (DMGs) and pathways related to asthma by integrating bioinformatics analysis.
One mRNA dataset (GSE64913) and one gene methylation dataset (GSE137716) were selected from the Gene Expression Omnibus (GEO) database. Functional enrichment analysis was performed using GeneCodies 4.0 database. All gene expression matrices were analyzed by Gene set enrichment analysis (GSEA) software. STRING was applied to construct a protein-protein interaction (PPI) network to find the hub genes. Then, electronic validation was performed to verify the hub genes, followed by the evaluation of diagnostic value. Eventually, quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression of hub genes.
In total, 14 hypomethylated/high-expression genes and 10 hypermethylated/low-expression genes were obtained in asthma. Among them, 10 hub genes were identified in the PPI network. Functional analysis demonstrated that the differentially methylated/expressed genes were primarily associated with the lung development, cytosol and protein binding. Notably, HLA-DOA was enriched in asthma. FKBP5, WNT5A, TM4SF1, PDK4, EPAS1 and GMPR had potential diagnostic value for asthma.
The project explored the pathogenesis of asthma, which may provide a research basis for the prediction and the drug development of asthma.
哮喘是一种全球范围内重要的非传染性疾病。DNA甲基化与哮喘的发生发展相关。我们旨在通过整合生物信息学分析，确定由异常甲基化基因（DMGs）修饰的差异表达基因（DEGs）以及与哮喘相关的通路。
从基因表达综合数据库（GEO）中选取一个mRNA数据集（GSE64913）和一个基因甲基化数据集（GSE137716）。使用GeneCodies 4.0数据库进行功能富集分析。所有基因表达矩阵通过基因集富集分析（GSEA）软件进行分析。应用STRING构建蛋白质-蛋白质相互作用（PPI）网络以寻找枢纽基因。然后进行电子验证以验证枢纽基因，随后评估其诊断价值。最终，利用定量实时聚合酶链反应（qRT-PCR）检测枢纽基因的表达。
在哮喘中总共获得了14个低甲基化/高表达基因和10个高甲基化/低表达基因。其中，在PPI网络中鉴定出10个枢纽基因。功能分析表明，差异甲基化/表达的基因主要与肺发育、细胞质和蛋白质结合相关。值得注意的是，HLA-DOA在哮喘中富集。FKBP5、WNT5A、TM4SF1、PDK4、EPAS1和GMPR对哮喘具有潜在的诊断价值。
该项目探索了哮喘的发病机制，可能为哮喘的预测和药物开发提供研究依据。
