Identification of potential key autophagy-related genes in asthma with bioinformatics approaches.

Objectives: Asthma is a chronic respiratory disease characterized by airway remodeling and inflammation. Recent studies have demonstrated that multiple autophagy-related genes are involved in the pathogenesis of asthma. However, the roles of many of these autophagy-related genes in asthma remain unclear, particularly with regard to the diagnosis of asthma.

Methods: In this study, autophagy-related differentially expressed genes (DEGs) in asthma were identified by bioinformatics analysis of the GSE76262 datasets. Hub genes were screened by protein-protein interaction (PPI) network and module analyses. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to explore potential signaling pathways. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of autophagy-related biomarkers in asthma.

Results: A total of 17 autophagy-related DEGs were identified, most of which were involved in autophagy and protein processing in the endoplasmic reticulum signaling pathway. ROC curve analysis demonstrated that the hub genes (, and ) identified from the PPI network exhibited good performance in the diagnosis of asthma. The GSE137268 and GSE43696 databases were used to verify the expression of 17 autophagy-related DEGs in asthma. Interestingly, was an overlapping gene defined by the intersection of hub autophagy-related DEGs and key modules (including , and ). We also analyzed the interaction between miRNAs and mRNAs for 14 autophagy-related DEGs with an area under the curve > 0.7. The identified genes were involved in the glypican, interferon-gamma, and plasma membrane estrogen receptor signaling pathways.

Conclusions: The results of this study indicate that specific signaling pathways and autophagy-related DEGs are potential diagnostic biomarkers related to the inception and progression of asthma.