Abstract
Background: Atherosclerosis is a progressive and complex vascular pathology characterized by cellular heterogeneity, metabolic dysregulation, and chronic inflammation. Despite extensive research, the intricate molecular mechanisms underlying its development and progression remain incompletely understood. Methods: Single-cell RNA sequencing (scRNA-seq) was employed to conduct a comprehensive mapping of immune cell enrichment and interactions within atherosclerotic plaques, aiming to investigate the cellular and molecular complexities of these structures. This approach facilitated a deeper understanding of the heterogeneities present in smooth muscle cells, which were subsequently analyzed using pseudotime trajectory analysis to monitor the developmental trajectories of smooth muscle cell (SMC) subpopulations. An integrative bioinformatics approach, primarily utilizing Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning techniques, identified Cathepsin C (CTSC), transforming growth factor beta-induced protein (TGFBI), and glia maturation factor-γ (GMFG) as critical biomarkers. A diagnostic risk score model was developed and rigorously tested through Receiver Operating Characteristic analysis. To illustrate the functional impact of CTSC on the regulation of plaque formation and SMC viability, both in vitro and in vivo experimental investigations were conducted. Results: An analysis revealed SMCs identified as the most prominent cellular type, exhibiting the highest density of disulfidptosis. Pseudotime trajectory analysis illuminated the dynamic activation pathways in SMCs, highlighting their significant role in plaque development and instability. Further characterization of macrophage subtypes demonstrated intercellular communication with SMCs, which exhibited specific signaling pathways, particularly between the proximal and core areas of plaques. The integrated diagnostic risk score model, which incorporates CTSC, TGFBI, and GMFG, proved to be highly accurate in distinguishing high-risk patients with elevated immune responses and systemic inflammation. Knockdown experiments of CTSC conducted in vitro revealed enhanced SMC survival rates, reduced oxidative stress, and inhibited apoptosis, while in vivo experiments confirmed a decrease in plaque burden and improvement in lipid profiles. Conclusions: This study emphasizes the significance of disulfidptosis in the development of atherosclerosis and identifies CTSC as a potential therapeutic target for stabilizing plaques by inhibiting SMC apoptosis and oxidative damage. Additionally, the risk score model serves as a valuable diagnostic tool for identifying high-risk patients and guiding precision treatment strategies.