Modeling Aortic Valve Calcification and Risk of Aortic Valve Events In Asymptomatic Individuals from the Multi-Ethnic Study of Atherosclerosis

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Calcific aortic valve disease (CAVD) is slowly progressive and begins in midlife. Calcification of the aortic valve leaflets is the core underlying process leading to severe aortic stenosis with both inflammation and Lp(a) serving as key underlying pathophysiologic contributors. Severe aortic stenosis is the most common heart valve disorder in the US. It predominantly affects older individuals and with an increasing life expectancy in the United States, the proportion of individuals ≥75 years old is expected to be 12% by the year 2050. Accordingly, the number of individuals requiring aortic valve replacement (AVR) is expected to nearly double between 2025 and 2015 to 1.4 million individuals. The only approved treatment available is AVR, although a recent subgroup analysis from the SEAS trial demonstrated a reduced rate of AVR for patients with a LDL >155 mg/dL and mild aortic stenosis who were treated with simvastatin and ezetimibe. There is no accepted risk stratification method for the long-term prediction of which patients are most likely to require AVR. Therefore, it is imperative to develop novel strategies to identify patients with early AVC who have the highest lifetime risk for developing severe aortic stenosis, as these patients are most likely to benefit from new treatment therapies/strategies. The 2011 NIH Working Group on Calcific Aortic Valve Disease highlighted crucial areas for future research including 1) developing imaging modalities to identify early AVC prior to detection by echocardiography, 2) determining whether the measurement of early AVC may identify patients most likely to benefit from earlier pharmacologic interventions, and 3) determining whether there are interactions between risk factors for aortic stenosis. Non-contrast cardiac computed tomography (CT) is the ideal imaging modality for measuring early CAVD, because it provides a precise, absolute, and direct measurement of aortic leaflet damage from the very earliest stage. However, the long-term relationship between AVC and clinical aortic stenosis events is unknown, as prior studies investigating CT visualized AVC have had small sample sizes, used a cross-sectional design, or focused on determining the optimal timing for AVR. By leveraging the AVC measurements from coronary artery calcium scans performed at MESA Visit 1 we will create an adjudicated severe aortic stenosis outcome, making MESA the only NHLBI cohort with the ability to comprehensively describe the long-term relationship between AVC and clinical aortic stenosis events. Accordingly, these results will have a direct impact on 1) long-term personalized risk stratification, 2) identification of high-risk patients most likely to benefit from new or earlier therapies/strategies, and 3) reducing future aortic valve morbidity and mortality.