Abstract
Background:
The association between autophagy and immunity, including infiltrating immunocytes, immune reaction gene-sets, and HLAs (human leukocyte antigen) gene, remains unclear. The present study aimed to provide a valid diagnostic tool for coronary artery disease (CAD), and explore the pathological mechanisms of CAD based on the association between autophagy and immunity.
Methods:
First, the overlap between differentially expressed genes (DEGs) and autophagy-related genes (ARGs) was identified. Subsequently, machine learning was conducted to screen risk genes closely related to CAD. Diverse autophagy phenotype-related clusters were identified using unsupervised clustering. The connections between different clusters and immune characteristics were evaluated as well.
Results:
The present study identified 27 differentially expressed autophagy-related genes (DEAGRs) in CAD samples compared with healthy conrtrols. A classifier constructing by 9 DEARGs was regarded as an effective diagnostic tool for CAD. Furthermore, three distinct autophagy phenotype - related clusters were identified, each cluster exhibited different immune characteristics. Finally, the gene ontology (GO) analysis of 901 autophagy phenotype-related genes showed that immune response, protein phosphorylation, and innate immune response were remarkable enrichment components.
Conclusions:
This study identified an effective classifier constituted by 9-DEARGs that has good diagnostic performance for CAD, and revealed that autophagy and the immunity may be common critical factors in the occurrence and development of CAD.
Keywords:
Autophagy; Coronary artery disease; Diagnostic classifier; Immunity response.