Identification of Cellular Senescence-Related Hub Genes and Their Association with Immune Infiltration in Abdominal Aortic Aneurysm: A Comprehensive Bioinformatics Analysis

Background Abdominal aortic aneurysm (AAA) is a life-threatening cardiovascular disease marked by progressive aortic dilation and a high risk of rupture. No reliable circulating biomarker currently exists for early detection, and the molecular events driving AAA remain only partly understood. Cellular senescence is a state of irreversible cell-cycle arrest coupled to a pro-inflammatory senescence-associated secretory phenotype (SASP). It has been linked to vascular aging and aneurysm formation, yet a systematic transcriptomic survey of senescence-related genes in AAA has not been reported. Methods Three GEO datasets were used: GSE57691 (49 AAA vs. 10 control) as the training cohort, GSE47472 (14 AAA vs. 8 control) as the external validation cohort with matched controls, and GSE98278 (48 AAA samples without controls) as an independent AAA cohort for exploratory subtype analysis. Differentially expressed genes (DEGs) were identified with the limma package. Senescence-related DEGs (SRDEGs) were obtained by intersecting the DEG list with a 167-gene cellular senescence signature compiled from the CellAge database and published reviews. Functional enrichment (GO, KEGG, GSEA), a protein-protein interaction (PPI) network with an expanded first-order-neighbor extension, and three machine learning algorithms (LASSO, SVM-RFE, random forest) were applied to the six SRDEGs to isolate hub genes. Immune infiltration was estimated by single-sample gene set enrichment analysis (ssGSEA). A two-gene nomogram was built and validated externally in GSE47472. Results Six SRDEGs were recovered: FOXO1, MAP1LC3B, SOD1, IGFBP3 (all downregulated), and IL1B, IL6 (both upregulated). Enrichment pointed to apoptotic regulation, interleukin-1-mediated signaling, insulin secretion, the AGE-RAGE pathway, and cellular senescence. Intersecting three machine learning