Linking single nucleotide polymorphisms to signaling blueprints in abdominal aortic aneurysms

Abdominal aortic aneurysms (AAA) is a multifactorial complex disease with life-threatening consequences. While Genome-wide association studies (GWAS) have revealed several single nucleotide polymorphisms (SNPs) located in the genome of individuals with AAA, the link between SNPs with the associated pathological signals, the influence of risk factors on their distribution and their combined analysis is not fully understood. We integrated 86 AAA SNPs from GWAS and clinical cohorts from the literature to determine their phenotypical vulnerabilities and association with AAA risk factors. The SNPs were annotated using snpXplorer AnnotateMe tool to identify their chromosomal position, minor allele frequency, CADD (Combined Annotation Dependent Depletion), annotation-based pathogenicity score, variant consequence, and their associated gene. Gene enrichment analysis was performed using Gene Ontology and clustered using REVIGO. The plug-in GeneMANIA in Cytoscape was applied to identify network integration with associated genes and functions. 15 SNPs affecting 20 genes with a CADD score above ten were identified. AAA SNPs were predominantly located on chromosome 3 and 9. Stop-gained rs5516 SNP obtained high frequency in AAA and associated with proinflammatory and vascular remodeling phenotypes. SNPs presence positively correlated with hypertension, dyslipidemia and smoking history. GO showed that AAA SNPs and their associated genes could regulate lipid metabolism, extracellular matrix organization, smooth muscle cell proliferation, and oxidative stress, suggesting that part of these AAA traits could stem from genetic abnormalities. We show a library of inborn SNPs and associated genes that manifest in AAA. We uncover their pathological signaling trajectories that likely fuel AAA development.

Automated summary

Abdominal aortic aneurysms (AAA) is a complex disease with multiple factors involved. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with AAA, but the relationship between these SNPs, their pathological signals, and the influence of risk factors is not well understood. This study integrated data from GWAS and clinical cohorts to identify SNPs associated with AAA risk factors and determine their phenotypical vulnerabilities. The analysis revealed potential genetic abnormalities related to lipid metabolism, extracellular matrix organization, smooth muscle cell proliferation, and oxidative stress, suggesting their contribution to AAA development.