Abstract Body: Background: Calcific aortic stenosis (AS) is associated with significant morbidity and mortality. Currently, echocardiography is used to assess disease progression, but proteomic studies have the potential to identify proteins associated with worsening transvalvular stenosis.
Research Questions and Goals: In this exploratory study, we compared plasma protein expression in AS patients with age-matched controls to identify potential biomarkers.
Methods: Blood samples were collected from 29 patients ≥75 years with normal left ventricular systolic function undergoing cardiac catheterization with either severe AS (n=17) or structurally normal aortic valves by echocardiography (n=12). Samples underwent immunoaffinity depletion of high-abundance proteins and were analyzed by liquid chromatography–tandem mass spectrometry. Proteins were identified and quantified with Spectronaut v20 (Biognosys). Logistic regression with lasso regularization was used to model the probability that a sample belongs to an AS patient versus a control.
Results: The mean age was 82 ± 6 years, 59% were female and 24% had diabetes. The mean aortic valve area in the cases was 0.7 ± 0.2 cm². Levels of 1,974 proteins were measured with 126 showing significant differences between groups (log2 fold change of < -0.6 or > +0.6; p<0.05). Proteins upregulated in AS patients were involved in immune responses, lipid metabolism, metabolic signaling, and biosynthetic/catabolic pathways. Downregulated proteins were more numerous and functionally diverse. Higher levels of poliovirus receptor (PVR)/CD155, a type I transmembrane protein involved in the establishment of intercellular adherens junctions, and lower levels of Cysteine Rich With EGF Like Domains 1 (CRELD1), a protein linked to congenital heart diseases involving heart valves and septa, were associated with severe AS. The selected proteins demonstrated strong predictive power in support vector machine modeling.
Conclusion: Plasma proteins involved in immune responses, lipid metabolism and biosynthetic/catabolic pathways were differentially expressed in patients with severe calcified AS. PVR and CRELD1 were identified as the proteins most predictive of severe AS and potentially could serve as biomarkers of AS.