Exploring omics signature in the cardiovascular response to semaglutide: Mechanistic insights and clinical implications.

Eur J Clin Invest

Department of Medical Sciences, Institute of Biomedicine iBiMED, University of Aveiro, Aveiro, Portugal.

Published: February 2025

AI Article Synopsis

  • Semaglutide is a GLP-1 receptor agonist used to treat type 2 diabetes, showing significant heart health benefits.
  • The review explores how advanced techniques like mass spectrometry and NMR can reveal molecular changes related to insulin, weight management, and heart health linked to semaglutide, while also noting current research challenges.
  • The future potential of combining proteomic and metabolomic data with AI could enhance the prediction of cardiovascular outcomes, leading to better management for patients with type 2 diabetes.

Article Abstract

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.

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Source
http://dx.doi.org/10.1111/eci.14334DOI Listing

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