Metabolomics in early detection and prognosis of acute coronary syndrome

Amiri, Mohammad Pouralijan; Khoshkam, Maryam; Salek, Reza M.; Madadi, Reza; Ganji, Ghassem Faghanzadeh; Ramazani, Ali

doi:10.1016/j.cca.2019.03.1632

Cited by 35 publications

(24 citation statements)

References 132 publications

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“…Omics technology, including genomics, transcriptomics, proteomics and metabolomics, is an important part of systems biology. In the past few decades, there have been remarkable achievements in the single omics study of MI [4,5], but the exact mechanisms of MI are still unclear due to complex biochemical regulation at multiple levels. To reveal the process of MI in a more systematic way, the research of multiomics came into being, to promote the transformation of the MI research paradigm from a single parameter model to a multi parameter system model, and to potentially help with the understanding of the entire biological mechanism [6].…”

Section: Introductionmentioning

confidence: 99%

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

Bai

Sun

et al. 2020

PLoS ONE

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The pathological process and mechanism of myocardial ischemia (MI) is very complicated, and remains unclear. An integrated proteomic-metabolomics analysis was applied to comprehensively understand the pathological changes and mechanism of MI. Male Sprague-Dawley rats were randomly divided into a mock surgery (MS) group and an MI group. The MI model was made by ligating the left anterior descending coronary artery, twenty-four hours after which, echocardiography was employed to assess left ventricular (LV) function variables. Blood samples and left ventricular tissues were collected for ELISA, metabolomics and proteomics analysis. The results showed that LV function, including ejection fraction (EF) and fractional shortening (FS), was significantly reduced and the level of cTnT in the serum increased after MI. iTRAQ proteomics showed that a total of 169 proteins were altered including 52 and 117 proteins with increased and decreased expression, respectively, which were mainly involved in the following activities: complement and coagulation cascades, tight junction, regulation of actin cytoskeleton, MAPK signaling pathway, endocytosis, NOD-like receptor signaling pathway, as well as phagosome coupled with vitamin digestion and absorption. Altered metabolomic profiling of this transition was mostly enriched in pathways including ABC transporters, glycerophospholipid metabolism, protein digestion and absorption and aminoacyl-tRNA biosynthesis. The integrated metabolomics and proteomics analysis indicated that myocardial injury after MI is closely related to several metabolic pathways, especially energy metabolism, amino acid metabolism, vascular smooth muscle contraction, gap junction and neuroactive ligand-receptor interaction. These findings may contribute to understanding the mechanism of MI and have implication for new therapeutic targets.

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Section: Introductionmentioning

confidence: 99%

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

Bai

Sun

et al. 2020

PLoS ONE

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“…In previous studies, LysoPC has been positively associated with inflammation and atherosclerosis and LysoPC species were also evaluated as potential biomarkers for STEMI/NSTEMI (Pouralijan Amiri et al 2019). In our experiments, it was found that LysoPC (18:0) was lower in STEMI, while LysoPC (18:1) level was high in NSTEMI.…”

Section: Discussionmentioning

confidence: 50%

Investigation of the metabolic difference between ST-elevated myocardial infarction and non-ST-elevated myocardial infarction via LC/Q-TOF/MS/MS

et al. 2019

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Acute coronary syndrome (ACS) is a clinical condition caused by a disturbance in myocardial blood flow. ACS can be basically divided into two forms: ST elevation myocardial infarction (STEMI) due to complete occlusion of the coronary artery and non-ST elevation myocardial infarction (NSTEMI) due to partial occlusion of the coronary artery. In this study, we aimed to monitor the metabolite profile of STEMI and NSTEMI patients and compare the results via untargeted metabolomics approach. Serum samples were collected from STEMI and NSTEMI patients, and each group consists of 20 participants. Extraction was achieved by acetonitrile, and chromatographic separation was performed by LC/Q-TOF/MS/MS accompanied with dual AJS ESI positive ion mode. METLIN, MATLAB 2017a-PLS Toolbox7.2, and Human Metabolome Database were utilized for bioinformatics evaluation of obtained findings. In our results, 203 m/z ratio was detected and 163 m/z ratio passed the significance criteria (fold analysis > 1.5 and p < 0.05). Twenty-five metabolites including BCAAs, LysoPC species, lactic acid, succinate, malonic acid, maleic acid, butyric acid, carnitine, and betaine were identified. In conclusion, new biomarker candidates were identified to differentiate the diagnosis of STEMI and NSTEMI. Identified metabolites are indicative of alterations in oxidative stress, hypoxia, TCA cycle, and amino acid metabolism.

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“…The results of these studies indicated that serum metabolite profiling of ACS patients revealed a myriad of differentially occurring metabolites. The heterogeneity of the results might relate to differences in age, sex, ethnicity, geographical region, nutritional intake, medications, and lifestyle factors, as well as differences in analytical methods, which are known to influence metabolite levels ( 49 ). These characteristics are particularly important when analyzing the complex mixtures of metabolites.…”

Section: Discussionmentioning

confidence: 99%

Plasma Metabolomics of Acute Coronary Syndrome Patients Based on Untargeted Liquid Chromatography–Mass Spectrometry

Zhong

Deng

et al. 2021

Front. Cardiovasc. Med.

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Background: Acute coronary syndrome (ACS) is the main cause of death and morbidity worldwide. The present study aims to investigate the altered metabolites in plasma from patients with ACS and sought to identify metabolic biomarkers for ACS.Methods: The plasma metabolomics profiles of 284 ACS patients and 130 controls were carried out based on an untargeted liquid chromatography coupled with tandem mass spectrometry (LC-MS) approach. Multivariate statistical methods, pathway enrichment analysis, and univariate receiver operating characteristic (ROC) curve analysis were performed.Results: A total of 328 and 194 features were determined in positive and negative electrospray ionization mode in the LC-MS analysis, respectively. Twenty-eight metabolites were found to be differentially expressed, in ACS patients relative to controls (p < 0.05). Pathway analysis revealed that these metabolites are mainly involved in synthesis and degradation of ketone bodies, phenylalanine metabolism, and arginine and proline metabolism. Furthermore, a diagnostic model was constructed based on the metabolites identified and the areas under the curve (AUC) for 5-oxo-D-proline, creatinine, phosphatidylethanolamine lyso 16:0, and LPC (20:4) range from 0.764 to 0.844. The higher AUC value of 0.905 was obtained for the combined detection of phosphatidylethanolamine lyso 16:0 and LPC (20:4).Conclusions: Differential metabolic profiles may be useful for the effective diagnosis of ACS and may provide additional insight into the molecular mechanisms underlying ACS.

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Metabolomics in early detection and prognosis of acute coronary syndrome

Cited by 35 publications

References 132 publications

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

Investigation of the metabolic difference between ST-elevated myocardial infarction and non-ST-elevated myocardial infarction via LC/Q-TOF/MS/MS

Plasma Metabolomics of Acute Coronary Syndrome Patients Based on Untargeted Liquid Chromatography–Mass Spectrometry

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