Circulating Proteomics to Phenotype the Development and Reversal of Myocardial Remodeling in Aortic Stenosis

Vanderbilt University Medical Center, Nashville TN

Investigators

Linked publications & trials

Abstract

ABSTRACT: Aortic stenosis (AS) carries significant morbidity and mortality and is a highly prevalent heart valve disease of aging (5-10% of those ³65 years). While treatment with aortic valve replacement (AVR) has historically been reserved for symptomatic severe AS, irreversible myocardial remodeling/injury occurs prior to the onset of symptoms, before AS is “severe”, and contributes to death and persistent heart failure (HF) in up to 40% of patients 1 year after AVR. To reduce the morbidity and mortality of AS, there is an invigorated focus on early-stage AS with goals of (1) advancing medical therapy to slow disease progression; and (2) earlier timing of AVR before symptoms and before AS is severe. A major roadblock for operationalizing this paradigm is detecting early-stage pre-symptomatic AS. While an echocardiogram (echo) is the gold standard for AS diagnosis, physical exam (auscultation) and patient history (e.g., dyspnea, chest pain) are the gatekeepers to trigger an echo order, but they are insensitive (missing AS), non-specific (leading to needless echoes), and biased to detect late-stage AS. Universal echo screening for AS would be exceedingly expensive, wasteful, strain capacity, and difficult to disseminate broadly. A widely available and accessible pre-screening strategy— with high sensitivity/specificity—to increase the detection of early-stage AS and efficiently deploy echo in the diagnosis of AS represents a critical unmet need to optimize outcomes for AS. Accordingly, our long-term goal is to develop, validate, and implement a blood-based multi-marker screening test for the detection of AS among those ³65 years of age. Other (pre)screening strategies have substantial real-world implementation barriers, but a blood test is a novel approach to detect AS that would enable widespread deployment in diverse populations and improve the efficiency of echo in AS diagnosis. The central hypothesis of this application is that valve stenosis and myocardial remodeling/dysfunction resulting from pressure overload will be accompanied by alterations in the circulating proteome useful for detecting individuals with AS. To build on our promising pilot data, we propose to discover and prioritize proteins for a multi-marker panel to detect individuals with AS. Existing plasma samples from two discovery cohorts—each with individuals with AS and age/sex/race-matched controls without AS (presence/absence of AS verified by cardiac imaging)—will be used for high-dimensional proteomics. Several statistical approaches, including machine learning, will be utilized to discover a smaller set of known/novel proteins most strongly associated with AS in logistic regression. The proposed project is closely aligned with encouraged avenues of research outlined in the NOSI (NOT-HL-23- 078) and CAROL Act. Completion of the proposed aim in this administrative supplement will pave the way for the development and validation of a custom multiplex panel for the detection of AS.