Abstract 332: Genomically Enhanced Risk Stratification in Abdominal Aortic Aneurysm Repair

OBJECTIVE The purpose of this study was to investigate the association between selected single-nucleotide polymorphisms (SNPs), associated with abdominal aortic aneurysms (AAA) in previous genome-wide association studies, and major adverse events following AAA repair

METHODS Genomic DNA was isolated from blood samples collected from AAA patients and used for genotyping. A genetic risk score was constructed using five SNPs known to be associated with AAA. Epidemiologic data were extracted from the electronic medical record and analyzed retrospectively. Major adverse events were defined as myocardial infarction, cardiac arrest, respiratory failure requiring tracheostomy, renal failure requiring dialysis, colonic ischemia requiring resection, limb ischemia requiring operation, multi-system organ failure or death.

RESULTS Three hundred and twenty one patients (267 male, 83%) with complete genomic and clinical data underwent AAA repair from 2004-2012. Demographics were consistent with a standard AAA population. 204 patients (64%) underwent endovascular repair and 117 (36%) underwent conventional open surgical repair. Quality control checks were performed on the clinical and laboratory data and none of the 5 selected SNPs deviated from the Hardy-Weinberg Equilibrium. Stepwise logistic regression was then used to determine the most parsimonious model of variables associated with adverse outcomes from AAA repair. Serum creatinine, height, resting heart rate, diastolic blood pressure and the genetic risk score remained in the model. The Hosmer and Lemeshow test of deviation from goodness-of-fit (p = 0.56) indicated that the data fit the model well. The regression coefficients from this model will be used to construct a clinician-friendly risk calculator to help identify patients at increased risk for a major adverse event following AAA repair.

CONCLUSIONS Selected SNPs help identify patients at risk for major adverse events following AAA repair. Incorporating genetic data, especially in patients with few clinical risk factors, may result in a better preoperative risk assessment.