Comprehensive analysis for the role of macrophage-driven genes in abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease characterized by chronic inflammation and immune dysregulation, with macrophages playing a critical pathogenic role. However, the molecular determinants underlying macrophage involvement in AAA remain incompletely defined. This study aimed to identify macrophage-related diagnostic biomarkers for AAA through an integrated retrospective analysis of public transcriptomic datasets and experimental validation.

Single-cell RNA sequencing (scRNA-seq) was applied to AAA samples to identify macrophage-enriched cell clusters and extract cell-type-specific gene signatures. Differentially expressed genes (DEGs) were derived from bulk RNA sequencing (RNA-seq) datasets that were retrospectively retrieved from public databases, and intersected with macrophage-specific genes to identify macrophage-related DEGs. A least absolute shrinkage and selection operator (LASSO)-based diagnostic model was constructed and validated with independent cohorts. Gene set variation analysis (GSVA), immune infiltration analysis, and Mendelian randomization (MR) were used to investigate pathway activity, immune contexture, and genetic associations between hub genes and AAA risk. Finally, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed in human AAA tissues (n=3) and normal abdominal aortic specimens (n=3) obtained from patients undergoing vascular surgery who met predefined clinical eligibility criteria (no prior aortic surgery, no active infection or systemic inflammatory disease), and these specimens were collected at Ningxia Medical University General Hospital to validate the expression of hub genes.

Nineteen distinct cell clusters were identified in the scRNA-seq dataset (AAA =6, normal =0), with macrophages as the dominant population. A total of 59 macrophage-related DEGs were obtained, with functional enrichment implicating lipid metabolism and immune response pathways. A five-gene diagnostic model (ARG2, S100A6, VASH1, PI3, and SMU1) was constructed using the bulk RNA-seq training dataset GSE47472 (AAA =14, normal =8) and validated in an independent cohort GSE57691 (AAA =49, normal =10), achieved excellent performance {area under curve (AUC) =0.981 [95% confidence interval (CI): 0.951-0.993] in the training set and 0.935 (95% CI: 0.903-0.998) in the validation set}. Among them, SMU1 was notably upregulated in macrophages and positively correlated with inflammatory response, PI3K-AKT-mTOR, and apoptosis pathways. SMU1 expression was negatively correlated with M2 macrophage infiltration. MR analysis suggested a potential genetic association between spliceosome-related genes and AAA risk. Clinical validation further showed that SMU1 was significantly downregulated in AAA tissues.

SMU1 is a novel macrophage-related gene associated with AAA development, potentially by modulating pro-inflammatory signaling. It holds promise as a diagnostic biomarker and therapeutic target in AAA.