Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm.

This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as the alteration of the regional lymphatic system during the progression of AAA and the influence of lymphatic drainage obstruction on AAA progression. 2957 differentially expressed genes (DEGs) were identified between the AAA patient group and the healthy donor group in Gene Expression Omnibus microarray datasets. Subsequently, the DEGs and the LG gene were intersected, and 93 genes were obtained. Weighted gene co-expression network analysis (WGCNA) was performed to obtain module genes. Module genes intersected with the above 93 genes, and 26 genes were obtained. Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. Additionally, AAA was significantly promoted by ligating lymphatic vessels, which caused lymphatic drainage obstruction around the abdominal aorta. Our findings have the potential to enhance knowledge about the development and diagnosis of AAA.