BACKGROUND: Semaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits.
RESULTS: This review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti-inflammatory activities and lipid metabolism. These "omics" approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility.
CONCLUSION: Future integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.