Abstract
OBJECTIVE: This study aims to explore potential mechanisms associated with differentially abundant proteins and metabolites in rabbit plaques through integrated proteomics and untargeted metabolomics analyses. METHODS: Experimental rabbits were randomly divided into the model group and the sham group. Abdominal aortas were isolated, collected, and treated with proteinase K. Subsequently, a tandem mass tag (TMT)-labeled quantitative proteomics analysis and an untargeted metabolomics analysis via liquid chromatography-mass spectrometry (LC-MS) of abdominal aortas were performed to evaluate the possible protein and metabolite fingerprints in arterial plaques. Acquired data were analyzed using uni- and multivariate statistics. The correlation between differentially abundant proteins and metabolites was analyzed using the Pearson correlation coefficient strategy, and their possibly involved functional pathways were predicted by Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. RESULTS: Advanced plaques develop in the model group. A total of 207 proteins are significantly altered in injured aortas compared to uninjured ones, with 133 upregulated and 74 downregulated proteins (fold changes > 1.2, P < 0.05). In plaques, 234 metabolites are significantly changed under the positive ion mode, and 187 under the negative ion mode. Notably, increases are observed in phosphatidylcholines (PCs) [PC 9:0] and lysophosphatidylcholines (LPCs) [LPC 20:2], two key lipid components. These metabolites are involved in some key metabolic pathways, including purine metabolism and vascular smooth muscle contraction. CONCLUSIONS: The results confirm the potential of integrated proteomics and untargeted metabolomics in exploring the molecular characteristics of atherosclerosis. Identified proteins and metabolites may serve as promising biomarkers for plaque diagnosis.