Blood-Derived Lipid and Metabolite Biomarkers in Cardiovascular Research from Clinical Studies: A Recent Update

Cells. 2023 Dec 8;12(24):2796. doi: 10.3390/cells12242796.

Abstract

The primary prevention, early detection, and treatment of cardiovascular disease (CVD) have been long-standing scientific research goals worldwide. In the past decades, traditional blood lipid profiles have been routinely used in clinical practice to estimate the risk of CVDs such as atherosclerotic cardiovascular disease (ASCVD) and as treatment targets for the primary prevention of adverse cardiac events. These blood lipid panel tests often fail to fully predict all CVD risks and thus need to be improved. A comprehensive analysis of molecular species of lipids and metabolites (defined as lipidomics and metabolomics, respectively) can provide molecular insights into the pathophysiology of the disease and could serve as diagnostic and prognostic indicators of disease. Mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based lipidomics and metabolomics analysis have been increasingly used to study the metabolic changes that occur during CVD pathogenesis. In this review, we provide an overview of various MS-based platforms and approaches that are commonly used in lipidomics and metabolomics workflows. This review summarizes the lipids and metabolites in human plasma/serum that have recently (from 2018 to December 2022) been identified as promising CVD biomarkers. In addition, this review describes the potential pathophysiological mechanisms associated with candidate CVD biomarkers. Future studies focused on these potential biomarkers and pathways will provide mechanistic clues of CVD pathogenesis and thus help with the risk assessment, diagnosis, and treatment of CVD.

Keywords: biomarkers; cardiovascular disease; lipidomics; metabolipidomics; metabolomics.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers / metabolism
  • Cardiovascular Diseases* / metabolism
  • Cardiovascular System* / metabolism
  • Humans
  • Lipids / analysis
  • Metabolomics / methods

Substances

  • Lipids
  • Biomarkers

Grants and funding

All authors acknowledge the support of the “Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen” and “Berliner Senatsverwaltung für Wissenschaft, Gesundheit und Pflege”. This work was partly funded by the “Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) under the funding reference 161L0271”.