Bioinformatics-based identification of potential microRNA biomarkers in frequent and non-frequent exacerbators of COPD

Abstract

Objectives

MicroRNAs (miRNAs) play essential roles in the development of COPD. In this study, we aimed to identify and validate potential miRNA biomarkers in frequent and non-frequent exacerbators of COPD patients using bioinformatic analysis.

Materials and methods

The candidate miRNA biomarkers in COPD were screened from Gene Expression Omnibus (GEO) dataset and identified using GEO2R online tool. Then, we performed bioinformatic analyses including target prediction, gene ontology (GO), pathway enrichment analysis and construction of protein–protein interaction (PPI) network. Furthermore, the expression of the identified miRNAs in peripheral blood monocular cells (PBMCs) of COPD patients was validated using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

MiR-23a, miR-25, miR-145 and miR-224 were identified to be significantly downregulated in COPD patients compared with healthy controls. GO analysis showed the four miRNAs involved in apoptotic, cell differentiation, cell proliferation and innate immune response. Pathway analysis showed that the targets of these miRNAs were associated with p53, TGF-β, Wnt, VEGF and MAPK signal pathway. In healthy controls, the miR-25 and miR-224 levels were significantly decreased in smokers compared with nonsmokers (P<0.001 and P<0.05, respectively). In COPD patients, the levels of miR-23a, miR-25, miR-145 and miR-224 were associated with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages. Notably, miR-23a and miR-145 were significantly elevated in non-frequent exacerbators compared with frequent exacerbators (P<0.05), and miR-23a showed higher area under the receiver–operator characteristic curve (AUROC) than miR-145 (0.707 vs 0.665, P<0.05).

Conclusion

MiR-23a, miR-25, miR-145 and miR-224 were associated with the development of COPD, and miR-23a might be a potential biomarker for discriminating the frequent exacerbators from non-frequent exacerbators.

Keywords:

• COPD
• microRNAs
• bioinformatic analysis
• Gene Expression Omnibus dataset
• biomarkers
• Global Initiative for Chronic Obstructive Lung Disease stages

Acknowledgments

This study was supported by the grants from the Science and Technology Foundation of Shandong Province (grant number: 2007GG3002008, 2015GGH318002 and 2015GSF118064). Xiao Liu and Jingge Qu are the co-first authors.

Disclosure

The authors report no conflicts of interest in this work.