1.2 Chronological Versus Vascular Age: Predictive Value for Cardiovascular Events and Identification of Patients with SUPERNOrmal Vascular Aging (SUPERNOVA)

Abstract

Background

Individuals whose arteries appears abnormally healthy in comparison to their CV risk factor burden (supernormal vascular aging, SUPERNOVA) represent an ideal model to discover novel pathways of cardiovascular protection. Purpose: 1) to introduce a novel definition of vascular age, as predicted age based on CV risk factors and PWV; 2) to test the hypothesis that individuals with the largest difference between chronological and vascular age (C-Vage) show a lower rate of CV events, and may thus be defined as SUPERNOVA.

Methods

The best fitting model for age prediction was investigated in the multicenter, European, cross-sectional Reference Values for Arterial stiffness Collaboration Database (n = 11406). A survival analysis on the longitudinal cohort of the Malmo Diet and Cancer Study (MDCS, n = 2663) was then performed. The main outcome was a composite endpoint of fatal and non-fatal major cardiac events and strokes.

Results

In the Reference Values Cohort, the model explained 59.8% of age variance, with PWV being the most relevant predictor (r²: 0.105). The model (derived on population >61 years) was used to calculate vascular age in the MDCS Cohort. In the Cox survival analysis (follow-up 6.6 years, 286 events), C-Vage was significantly and inversely associated with CV events (Figure 1). Individuals in the highest C-Vage decile (>8.8 years) were defined as SUPERNOVA. In the competing risk analysis, SUPERNOVA had a reduced age-adjusted rate of CV events [HR 0.51 (0.34–0.76)].

Conclusion

This proof-of-concept study demonstrated that SUPERNOVA individuals have a disproportionally lower rate of CV events. Future studies are needed to explore genetic/molecular mechanisms for this phenotype.