Characterization of Proteome Features in Patients With Aortic Stenosis Using Data-Independent Acquisition-Based Proteomic Analysis.

Abstract

Background and objectives: Aortic stenosis (AS) is a prevalent valvular heart disease that is increasing due to aging population and longer life expectancy. While most individuals have a tricuspid aortic valve (TAV), some are congenitally born with a bicuspid aortic valve (BAV). The mechanisms underlying AS pathogenesis remain unclear, limiting advancements in clinical treatment and biomedical research. This study aimed to identify differentially expressed protein (DEPs) in aortic valve interstitial cells (VICs) from AS patients with TAV and BAV using quantitative proteomic analysis.

Methods: VICs were isolated from AS patients with TAV (n=10) and BAV (n=10), as well as from normal aortic valves of heart transplant patients (TAV, n=11). Spectral library generation was performed using a data-dependent acquisition approach, followed by data-independent acquisition analysis. Immunohistochemical staining validated key DEPs.

Results: A total of 39 DEPs were identified, including 13 upregulated and 26 downregulated proteins. These were categorized into 4 groups: cellular structural protein (keratin family, SYNPO, PFDN1, COL5A1); kinase and transferase (OXSR1, DNMT1), mitochondrial-related proteins (SOD2, SQOR), and calcification-related proteins (SPARC, MXRA7, PTMA). Comparative analysis revealed 5 common DEPs in TAV- and BAV-AS, including SQOR, 20 TAV-AS-specific proteins (e.g., keratin family, oxidoreductase-related proteins), and 3 BAV-AS-specific proteins (e.g., SPARC, PTMA).

Conclusions: This proteomic analysis identified potential molecular targets associated with AS pathogenesis, providing a foundation for further research on disease mechanism and therapeutic development.