Revealing lncRNA Biomarkers Related to Chronic Obstructive Pulmonary Disease Based on Bioinformatics

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common chronic disease of the respiratory tract, with high prevalence, high disability, and poor prognosis. However, the molecular mechanism of COPD needs to be further revealed. METHODS: We obtained the gene expression profile and miRNA expression profile of COPD patients from Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmis) in COPD were identified. Subsequently, the COPD-related ceRNA network was constructed based on the interaction between lncRNA, miRNA, and mRNA using the lncACTdb database. Finally, the Cytoscape software was used to analyze the network topology and COPD-related lncRNAs. RESULTS: Firstly, the 519 DEGs and 17 DEmis were identified from COPD GEO datasets. GO enrichment showed that leukocyte chemotaxis, cell chemotaxis, and myeloid leukocyte migration were upregulated, and muscle and membrane repolarization-related biological progress were downregulated in COPD. KEGG pathway enrichment shows that the p53 pathway was upregulated in COPD. Hallmark enrichment showed that chronic neutrophil inflammation was a sign of the pathogenesis of COPD. Next, a ceRNA network including 93 DEGs, 2 DEmi, 463 lncRNAs, and 1157 DEG-lncRNA, DEmi-lncRNA, and DEmi-DEG interactions were obtained. The hub-lncRNA (the network is ranked in the top 10) as the core marker of COPD, including SNHG12, SLFNL1-AS1, KCNQ1OT1, XIST, EAF1-AS1, FOXD2-AS1, NORAD, PINK1-AS and RP11-69E11.4. And the cytoHubba analysis identified ATM, SMAD7 and HIF1A as hub genes of ceRNA network. CONCLUSION: This study provides a landscape of ceRNA network of COPD, which help to reveal the underlying pathophysiological mechanisms of COPD and shed light on novel therapeutic strategies for COPD.