Identification of Hub Genes and Molecular Mechanisms in Acute Stanford Type A Aortic Dissection

Abstract

Background: Acute Stanford type A aortic dissection (ATAAD) is a potentially fatal outcome of cardiac surgery with a high mortality rate and an unclear pathogenesis. This study aimed to investigate the prospective diagnostic biomarkers and molecular pathways in ATAAD. Methods: We identified autophagy-related differentially expressed genes (DEGs) between control ATAAD groups using three Gene Expression Omnibus (GEO) datasets (GSE153434, GSE98770, and GSE52093). The potential pathways and biomarkers were then determined through protein-protein interaction (PPI) network and enrichment analysis. The autophagy-related hub genes and their corresponding diagnostic values were determined using receiver operating characteristic analysis and the significant immune-associated pathways were identified using Gene-Set Variation Analysis (GSVA) enrichment. Results: A total of 90 genes were screened as autophagy-related DEGs and 10 hub genes were ultimately identified using a PPI network in patients with ATAAD. Autophagy-related DEGs were enriched in pathways related to autophagy, protein binding, regulation of autophagy, and the relaxin signaling pathway according to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Gene-set enrichment analysis suggested that the regulation of autophagosome assembly, focal adhesion, and calcium-signaling pathways are enriched mainly in ATAAD development. In addition, GSVA showed that DEGs in ATAAD are primarily involved in the metabolic pathways of myocardial diseases and autophagy. Finally, it was found that the immune infiltration between the control and ATAAD groups was significantly different. Conclusions: Through the comprehensive analysis of GEO data, our study provides insights into autophagy-related biomarkers and therapeutic targets to diagnose and treat patients who are susceptible to ATAAD.