This study aimed to identify the key genes involved in the development of AAA by various bioinformatics methods and explore their potential mechanisms. Feature genes were screened by machine learning and other methods, and ROC curves were used to verify the model performance in the internal and external validation sets. Cluster analysis and immune infiltration analysis were then performed, and two key genes were finally determined and experimentally verified. GSEA, GO and KEGG analyses were performed. DEGs were identified by the “limma” package. DENETs were obtained by intersecting DEGs with NETs. GSEA, GO and KEGG analyses revealed that these genes were enriched in pathways such as cell response to lipopolysaccharide and chemokine signaling. Cluster analysis was performed to compare the expression differences of 25 DENETs between clusters, and immune infiltration analysis revealed immune dysregulation in AAA. Then, IL6 and PADI4 were finally identified as DENETs, and further GSEA analysis revealed that they were related to inflammation and immune response. In the wet experiment, IL6 and PADI4 finally showed expression trends consistent with the results of bioinformatics analysis. Our study identified IL6 and PADI4 as hub genes. They play an important role in promoting the development of AAA through inflammation, providing potential molecular targets for further treatment and intervention of AAA in the future.
Liu et al. (Mon,) studied this question.