Integrative Multi-Omics and Machine Learning Identify ID1 as a Candidate Gene Associated with Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a fatal vascular disorder driven by immune dysregulation and extracellular matrix (ECM) degradation, yet its molecular mechanisms remain unclear. This study investigated the mechanistic role of ID1 in AAA using an integrative multi-omics and machine learning approach. Two bulk transcriptomic datasets (GSE232911 and GSE183464) were analyzed through differential expression, WGCNA, and three machine learning algorithms (LASSO, Random Forest, and SVM-RFE), followed by immune infiltration analysis via ssGSEA and CIBERSORT. ID1 and CYP4B1 were identified by all three machine learning algorithms, but only ID1 showed stable downregulation and consistent discriminatory ability across independent datasets. (AUC = 0.939 and 0.868). Functional enrichment and immune deconvolution linked low ID1 expression to enhanced adaptive immune signaling, increased M1 macrophages, γδ T cells, and memory B cells, and reduced neutrophil and mast cell activity. Single-cell RNA sequencing (GSE226492) confirmed endothelial- and fibroblast-specific ID1 downregulation in AAA. These findings identify ID1 as a candidate gene associated with vascular immune remodeling and extracellular matrix-related pathways, providing a basis for future mechanistic investigation in AAA.