ABSTRACT
Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstructed airflow from the lungs. DNA methylation can regulate gene expression. Understanding the potential molecular mechanism of COPD is of great importance. The aim of this study was to find differentially methylated/expressed genes in COPD. DNA methylation and gene expression profiles in COPD were downloaded from the dataset, followed by functional analysis of differentially-methylated/expressed genes. The potential diagnostic value of these differentially-methylated/expressed genes was determined by receiver operating characteristic (ROC) analysis. Expression validation of differentially-methylated/expressed genes was performed by in vitro experiment and extra online datasets. Totally, 81 hypermethylated-low expression genes and 121 hypomethylated-high expression genes were found in COPD. Among which, 9 core hypermethylated-low expression genes (CD247, CCR7, CD5, IKZF1, SLAMF1, IL2RB, CD3E, CD7 and IL7R) and 8 core hypomethylated-high expression genes (TREM1, AQP9, CD300LF, CLEC12A, NOD2, IRAK3, NLRP3 and LYZ) were identified in the protein-protein interaction (PPI) network. Moreover, these genes had a potential diagnostic utility for COPD. Some signaling pathways were identified in COPD, including T cell receptor signaling pathway, cytokine-cytokine receptor interaction, hematopoietic cell lineage, HTLV-I infection, endocytosis and Jak-STAT signaling pathway. In conclusion, differentially-methylated/expressed genes and involved signaling pathways are likely to be associated with the process of COPD.
Subject(s)
Pulmonary Disease, Chronic Obstructive , Humans , Gene Regulatory Networks , DNA Methylation , Protein Interaction Maps/genetics , Lung , Gene Expression Profiling , Receptors, Mitogen/genetics , Lectins, C-Type/geneticsABSTRACT
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: The project explored the pathogenesis of asthma, which may provide a research basis for the prediction and the drug development of asthma.
