Identification and Validation of Autophagy-Related Genes in Chronic Obstructive Pulmonary Disease

Abstract

Purpose

Autophagy plays essential roles in the development of COPD. We aim to identify and validate the potential autophagy-related genes of COPD through bioinformatics analysis and experiment validation.

Methods

The mRNA expression profile dataset GSE38974 was obtained from GEO database. The potential differentially expressed autophagy-related genes of COPD were screened by R software. Then, protein–protein interactions (PPI), correlation analysis, gene-ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for the differentially expressed autophagy-related genes. Finally, RNA expression of top five differentially expressed autophagy-related genes was validated in blood samples from COPD patients and healthy controls by qRT-PCR.

Results

A total of 40 differentially expressed autophagy-related genes (14 up-regulated genes and 26 down-regulated genes) were identified between 23 COPD patients and 9 healthy controls. The PPI results demonstrated that these autophagy-related genes interacted with each other. The GO and KEGG enrichment analysis of differentially expressed autophagy-related genes indicated several enriched terms related to autophagy and mitophagy. The results of qRT-PCR showed that the expression levels of HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 in COPD patients and healthy controls were consistent with the bioinformatics analysis results from mRNA microarray.

Conclusion

We identified 40 potential autophagy-related genes of COPD through bioinformatics analysis. HIF1A, CDKN1A, BAG3, ERBB2 and ATG16L1 may affect the development of COPD by regulating autophagy. These results may expand our understanding of COPD and might be useful in the treatment of COPD.

Keywords:

• autophagy
• COPD
• bioinformatics analysis
• gene expression omnibus dataset

Abbreviations

BP, biological process; BMI, body mass index; CC, cellular component; COPD, chronic obstructive pulmonary disease; GEO, gene expression omnibus dataset; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function; NSCLC, non-small cell lung cancer; PBMCs, peripheral blood mononuclear cells; PCA, principal component analysis; PPI, protein–protein interactions; qRT-PCR, quantitative real-time polymerase chain reaction; SD, standard deviation.

Ethics Approval and Informed Consent

All procedures performed in studies involving humans were reviewed and permitted by the Tianjin Medical University General Hospital. Written informed consent was obtained from all individual participants included in the study. The study was conducted in accordance with the Declaration of Helsinki.

Consent for Publication

All participating authors give their consent for this work to be published.

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (No. 81670084 and No.81970084); and the Tianjin Key Research and Development Program (No. 20YFZCSY00390); and the General Hospital of Tianjin Medical University Youth Incubation Foundation (No. ZYYFY2018030).

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.