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Review
. 2021 Oct 6;11(10):685.
doi: 10.3390/metabo11100685.

Defining Acute Coronary Syndrome through Metabolomics

Arun Surendran  1   2   3 , Negar Atefi  1 , Hannah Zhang  1 , Michel Aliani  4 , Amir Ravandi  1   3   5
Affiliations
Review

Defining Acute Coronary Syndrome through Metabolomics

Arun Surendran et al. Metabolites. .

Abstract

As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.

Keywords: acute coronary syndrome; ischemia/reperfusion injury; lipidomics; metabolomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Classification of acute coronary syndromes. Acute coronary syndromes are categorized into unstable angina (UA), non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation myocardial infarction (STEMI). A complete coronary artery occlusion due to thrombus formation results in STEMI, where the coronary blood flow is completely obstructed. A partial occlusion of the artery (blood flow is not entirely restricted) can result in NSTEMI or UA.
Figure 2
Figure 2
The ‘omics cascade’. It depicts the directional flow of biological information from genes to metabolites. Metabolomics is at the end of the cascade and is closer to the phenotype of an organism than proteomics or genomics.
Figure 3
Figure 3
A standard workflow for untargeted metabolomics. After sample collection and extraction, the samples are analyzed by NMR spectroscopy or mass spectrometry. The raw data are then analyzed using appropriate software followed by statistical analysis to identify metabolites of interest or potential candidate biomarkers. Adapted from “Untargeted Metabolomics for Discovery of Disease Biomarkers”, by BioRender.com (2021). Retrieved from https://app.biorender.com/biorender-templates on August 11, 2021.
Figure 4
Figure 4
Percutaneous coronary intervention (PCI): PCI widens the blocked or narrow coronary arteries, thereby allowing reperfusion of the ischemic myocardium. Adapted from “Percutaneous Coronary Intervention”, by BioRender.com (2021). Retrieved from https://app.biorender.com/biorender-templates on August 11, 2021.
Figure 5
Figure 5
Myocardial ischemia/reperfusion (I/R) injury. Schematic showing the main events in myocardial I/R injury. Abbreviations: Ca2+, Calcium ion; ROS, reactive oxygen species; mPTP, mitochondrial permeability transition pore.
See this image and copyright information in PMC

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