Identification and Experimental Validation of NETosis-Mediated Abdominal Aortic Aneurysm Gene Signature Using Multi-omics, Machine Learning, and Mendelian Randomization.

Abstract

Abdominal aortic aneurysm (AAA) is a life-threatening disorder with limited therapeutic options. Neutrophil extracellular traps (NETs) are formed by a process known as "NETosis" that has been implicated in AAA pathogenesis, yet the roles and prognostic significance of NET-related genes in AAA remain poorly understood. This study aimed to identify key AAA- and NET-related genes (AAA-NETs-RGs), elucidate their potential mechanisms in contributing to AAA, and explore potential therapeutic compounds for AAA therapy. Through bioinformatics analysis of multiomics and machine learning, we identified six AAA-NETs-RGs: DUSP26, FCN1, MTHFD2, GPRC5C, SEMA4A, and CCR7, which exhibited strong diagnostic potential for predicting AAA progression, were significantly enriched in pathways related to cytokine-cytokine receptor interaction and chemokine signaling. Immune infiltration analysis revealed a causal association between AAA-NETs-RGs and immune cell infiltration. Cell-cell communication analysis indicated that AAA-NETs-RGs predominantly function in smooth muscle cells, B cells, T cells, and NK cells, primarily through cytokine and chemokine signaling. Gene profiling revealed that CCR7 and MTHFD2 exhibited the most significant upregulation in AAA patients compared to non-AAA controls, as well as in in vitro AAA models. Notably, genetic depletion of CCR7 and MTHFD2 strongly inhibited Ang II-induced phenotypic switching, functional impairment, and senescence in vascular smooth muscle cells (VSMCs). Based on AAA-NETs-RGs, molecular docking analysis combined with the Connectivity Map (CMap) database identified mirdametinib as a potential therapeutic agent for AAA. Mirdametinib effectively alleviated Ang II-induced phenotypic switching, biological dysfunction, and senescence. These findings provide valuable insights into understanding the pathophysiology of AAA and highlight promising therapeutic strategies targeting AAA-NETs-RGs.