Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection

Abstract

Background: Aortic dissection is one of the most detrimental cardiovascular diseases with a high risk of mortality and morbidity. This study aimed to examine the key genes and microRNAs associated with Stanford type A aortic dissection (AAD). Methods: The expression data of AAD and healthy samples were downloaded from two microarray datasets in the Gene Expression Omnibus (GEO) database to identify highly preserved modules by weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were selected and functionally annotated. The predicted interactions between the DEGs and DEmiRNAs were further illustrated. Results: In two highly preserved modules, 459 DEGs were identified. These DEGs were functionally enriched in the HIF1, Notch, and PI3K/Akt pathways. Furthermore, 6 DEmiRNAs that were enriched in the regulation of vasculature development and HIF1 pathway, were predicted to target 23 DEGs. Conclusions: Our study presented several promising modulators, both DEGs and DEmiRNAs, as well as possible pathological pathways for AAD, which narrows the scope for further fundamental research.