Metabolomics in early detection and prognosis of acute coronary syndrome

GC-MS validation and analysis of targeted plasma metabolites related to carbonyl stress in type 2 diabetes mellitus patients with and without acute coronary syndrome

Methylglyoxal (MG) is responsible for advanced glycation end-product formation, the mechanisms leading to diabetes pathogenesis and complications like acute coronary syndrome (ACS). Sugar metabolites, amino acids and fatty acids are possible substrates for MG. The study aimed to measure plasma MG substrate levels using a validated gas chromatography-mass spectrometry (GC-MS) method and explore their association with ACS risk in type 2 diabetes mellitus (T2DM). The study included 150 T2DM patients with ACS as cases and 150 T2DM without ACS as controls for the analysis of glucose, fructose, ribulose, sorbitol, glycerol, pyruvate, lactate, glycine, serine, threonine, C16:0, C16:1, C18:0, C18:1, C18:2, C18:3, C20:0 and C22:6 by GC-MS. Validated GC-MS methods were accurate, precise and sensitive. Cases significantly differed in plasma MG and metabolite levels except for lactate, C16:0, C18:0, C18:2, and C18:3 levels compared with controls. On multivariable logistic regression, plasma C20:0, C18:1, glycine and glycerol levels had increased odds of ACS risk. On multivariate receiver operating characteristic analysis, a model containing plasma C20:0, C16:1, C18:1, C18:2, serine, glycerol, lactate and threonine levels had the highest area under the curve value (0.932) for ACS diagnosis. In conclusion, plasma C20:0, C16:1, C18:1, glycine, glycerol and sorbitol levels were associated with ACS risk in T2DM.

The relationship between the new inflammatory markers and disease severity in patients with acute coronary syndrome

BACKGROUND

Inflammation plays a crucial role in the progression of acute coronary syndrome.

AIMS

The aim of this study was to investigate the relationship between the SYNTAX score and new inflammatory markers including albumin-globulin ratio (AGR), C-reactive protein-to-albumin ratio (CAR), fibrinogen-to-albumin ratio (FAR), neutrophil-to-albumin ratio (NAR), and neutrophil percentage-to-albumin ratio (NPAR) in STEMI and NSTEMI patients.

METHODS

The study involved 53 STEMI and 64 NSTEMI patients, and each patient group was evaluated separately. Multivariate linear regression analysis was utilised to identify independent risk factors associated with SYNTAX scores.

RESULTS

Out of the 64 NSTEMI patients, 42 had low SYNTAX score (65.6%), and 22 had high SYNTAX score (34.4%). Patients with high SYNTAX scores had significantly higher levels of age, glucose, fibrinogen, monocyte, and FAR, and lower levels of albumin and total protein. We found that FAR and monocyte levels were independent predictors of the high SYNTAX score. The study also determined that the cut-off value for FAR as 9.99, with a sensitivity of 81% and a specificity of 73% for predicting high SYNTAX score in NSTEMI patients. Out of the 53 STEMI patients, 42 had low SYNTAX score (79.2%), and 11 had high SYNTAX score (20.8%). Patients with high SYNTAX scores exhibited significantly higher total cholesterol, LDL, and glucose levels, and lower albumin and total protein levels.

CONCLUSIONS

The FAR level is significantly linked with the high SYNTAX score and can be a useful marker for predicting the severity of disease in NSTEMI patients.

A Systematic Review and Meta-Analysis of the Diagnostic Value of Galectin-3 in Acute Coronary Syndrome

Background/Objectives: We investigated the potential diagnostic role of galectin-3 (Gal-3) in patients presenting with suspected acute coronary syndromes (ACS). Methods: We searched PubMed Central, Scopus, EMBASE, and the Cochrane Library from inception until 20 June 2024. We measured effect sizes using odds ratios (OR) with 95% CIs for dichotomous data and mean differences (MD) with CIs for continuous data. Random synthesis analysis was performed if I2 was less than 50% or Q test p values were less than 0.05. Otherwise, a fixed pooled meta-analysis was performed. Results: The meta-analysis includes 15 eligible studies. Gal-3 levels were substantially higher in the ACS group (12.84 ± 8.48 ng/mL) compared to the control group (7.23 ± 6.05 ng/mL; MD = 3.89; 95% CI: 2.83 to 4.95; p < 0.001). Gal-3 levels in acute myocardial infarction (AMI) and control groups differed (10.09 ± 8.16 vs. 4.64 ± 3.07 ng/mL, MD = 4.30; 95% CI: 0.41 to 8.18; p < 0.001). Statistical analysis revealed significant differences in Gal-3 levels between ST-elevated myocardial infarction (STEMI) and control groups (10.62 ± 7.34 vs. 5.54 ± 2.96 ng/mL; MD = 5.54; 95% CI: 3.12 to 7.97; p < 0.001). No significant differences were found between the non-ST-elevated myocardial infarction (NSTEMI) vs. control groups or patients with STEMI vs. patients with NSTEMI. Conclusions: Gal-3 may be beneficial for detecting acute coronary syndromes but not NSTEMI or differentiating between ACS types. This meta-analysis is promising, but further research is needed to prove Gal-3's potential diagnostic value, exact cut-offs, and advantages over cardiospecific troponins. Gal-3 may be a useful diagnostic biomarker; however, more clinical trials are needed to prove its utility.

Exploring Novel Biomarkers for an Acute Coronary Syndrome Diagnosis Utilizing Plasma Metabolomics

Acute coronary syndrome (ACS) is a life-threatening condition that requires a prompt diagnosis and therapeutic intervention. Although serum troponin I and creatinine kinase-MB (CK-MB) are established biomarkers for ACS, reaching diagnostic values for ACS may take several hours. In this study, we attempted to explore novel biomarkers for ACS with higher sensitivity than that of troponin I and CK-MB. The metabolomic profiles of 18 patients with ACS upon hospital arrival and those of the age-matched control (HC) group of 24 healthy volunteers were analyzed using liquid chromatography time-of-flight mass spectrometry. Volcano plots showed 24 metabolites whose concentrations differed significantly between the ACS and HC groups. Using these data, we developed a multiple logistic regression model for the ACS diagnosis, in which lysine, isocitrate, and tryptophan were selected as minimum-independent metabolites. The area under the receiver operating characteristic curve value for discriminating ACS from HC was 1.00 (95% confidence interval [CI]: 1.00-1.00). In contrast, those for troponin I and CK-MB were 0.917 (95% confidence interval [CI]: 0.812-1.00) and 0.988 (95% CI: 0.966-1.00), respectively. This study showed the potential for combining three plasma metabolites to discriminate ACS from HC with a higher sensitivity than troponin I and CK-MB.

Omics-based novel strategies in the diagnosis of endometriosis

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

Elevated circulating inflammatory biomarker levels in the SIRT1-NF-κB-sCD40L pathway in patients with acute myocardial infarction: a case-control study

BACKGROUND

Inflammation plays a key role in atherosclerosis development and progression. However, the role of novel inflammatory biomarker pathways, namely the SIRT1-NF-κB-sCD40L, in the etiopathogenesis of human atherosclerosis remains undefined. This study was designed to evaluate the changes and clinical implications of these inflammatory mediators in the plasma of patients with acute myocardial infarction (AMI).

METHODS

The peripheral arterial blood of 88 participants (68 patients with AMI and 20 age-matched controls), was drawn prior to performing coronary angiography (CAG). The SIRT1, NF-κB, and sCD40L plasma levels were quantified using ELISA. Spearman's analysis was used to evaluate the correlation between the three inflammatory markers, while Pearson's test assessed their potential correlation with cardiac troponin T (TNT) levels. Sensitivity, specificity, and area under the ROC curve (AUC) were calculated as measures of diagnostic accuracy.

RESULTS

Patients with AMI showed higher levels of circulating SIRT1, NF-κB, and sCD40L compared to the age-matched controls (p < 0.05). However, the plasma concentrations of these three inflammatory mediators did not differ between the ST-segment elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI) patients. Additionally, in patients with AMI, the SIRT1 level was positively correlated with NF-κB and sCD40L levels (p < 0.001). Likewise, the levels of SIRT1, NF-κB and sCD40L were positively correlated with TNT levels (p < 0.001). More importantly, the ROC analysis showed that the diagnostic accuracy of AMI was significantly higher when NF-κB or sCD40L level was used in combination with TNT levels (p < 0.05).

CONCLUSIONS

The levels of the circulating inflammatory biomarkers, including SIRT1, NF-κB, and sCD40L, were significantly elevated in patients with AMI. These novel biomarkers can improve the diagnostic accuracy of AMI when combined with TNT.KEY MESSAGESAMI is a potentially lethal CAD and is the leading cause of mortality and morbidity worldwide. Inflammation plays a key role in atherosclerosis development and progression. The levels of the circulating novel inflammatory biomarkers, including SIRT1, NF-κB, and sCD40L, were significantly elevated in patients with AMI.The SIRT1 level was positively correlated with NF-κB and sCD40L levels in patients with AMI.The levels of SIRT1, NF-κB and sCD40L were positively correlated with TNT levels.The ROC analysis showed that the diagnostic accuracy of AMI was significantly higher when NF-κB or sCD40L level was used in combination with TNT levels.SIRT1/NF-κB/sCD40L axis inhibition is a potential new target for AMI treatment.

The potential role of SARS-CoV-2 infection in acute coronary syndrome and type 2 myocardial infarction (T2MI): Intertwining spread

Coronavirus disease 2019 (COVID-19) is a novel pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has been shown that SARS-CoV-2 infection-induced inflammatory and oxidative stress and associated endothelial dysfunction may lead to the development of acute coronary syndrome (ACS). Therefore, this review aimed to ascertain the link between severe SARS-CoV-2 infection and ACS. ACS is a spectrum of acute myocardial ischemia due to a sudden decrease in coronary blood flow, ranging from unstable angina to myocardial infarction (MI). Primary or type 1 MI (T1MI) is mainly caused by coronary plaque rupture and/or erosion with subsequent occlusive thrombosis. Secondary or type 2 MI (T2MI) is due to cardiac and systemic disorders without acute coronary atherothrombotic disruption. Acute SARS-CoV-2 infection is linked with the development of nonobstructive coronary disorders such as coronary vasospasm, dilated cardiomyopathy, myocardial fibrosis, and myocarditis. Furthermore, SARS-CoV-2 infection is associated with systemic inflammation that might affect coronary atherosclerotic plaque stability through augmentation of cardiac preload and afterload. Nevertheless, major coronary vessels with atherosclerotic plaques develop minor inflammation during COVID-19 since coronary arteries are not initially and primarily targeted by SARS-CoV-2 due to low expression of angiotensin-converting enzyme 2 in coronary vessels. In conclusion, SARS-CoV-2 infection through hypercytokinemia, direct cardiomyocyte injury, and dysregulation of the renin-angiotensin system may aggravate underlying ACS or cause new-onset T2MI. As well, arrhythmias induced by anti-COVID-19 medications could worsen underlying ACS.

Plasma extracellular vesicles microRNA-208b-3p and microRNA-143-3p as novel biomarkers for sudden cardiac death prediction in acute coronary syndrome

Acute coronary syndrome (ACS) occurs as a result of myocardial ischemia that can give rise to a variety of acute cardiovascular events, including arrhythmia, heart failure and sudden cardiac death (SCD). Currently, there are challenges and insufficient innovations regarding early diagnosis and therapeutic approaches within ACS patients experiencing SCD. Plasma extracellular vesicles (EVs) might serve as biomarkers of many diseases depending on the biological molecules of their cargo, such as miRNAs. This study aims to identify the plasma EVs containing miRNAs as novel biomarkers for the prediction of SCD in ACS patients. A total of 39 ACS patients experiencing SCD and 39 healthy control individuals (HC) were enrolled, among which 9 samples in each group were randomly selected as testing groups for miRNA sequencing in plasma EVs, and the remaining samples were assigned to the validation group. The top 10 significant expression miRNAs were verified by the real-time quantitative polymerase chain reaction. Upregulation of miR-208b-3p, miR-143-3p, miR-145-3p and miR-152-3p, and down-regulation of miR-183-5p were further validated in the validation group. Spearman's correlation analysis and the receiver operating characteristic (ROC) curve showed that both miR-208b-3p and miR-143-3p levels were positively correlated with myoglobin (MYO), and their predictive power for SCD was confirmed. In conclusion, our findings indicate that plasma EVs miR-208b-3p and miR-143-3p may serve as promising biomarkers in predicting SCD in patients with ACS, as well as postmortem forensic diagnosis of the cause of death due to ACS.

Genetic variants, gene expression, and soluble CD36 analysis in acute coronary syndrome: Differential protein concentration between ST-segment elevation myocardial infarction and unstable angina

Background

Atherosclerosis plays an important role in the pathophysiology of acute coronary syndrome (ACS). CD36 is a scavenger receptor involved in lipid metabolism. Some single‐nucleotide variants in the non‐coding region could indirectly alter the expression and the function of the protein.

Objective

The aim of this study was to investigate the gene and protein expression associated with CD36 variants (rs1194182;C > G; rs1049654;C > A, rs1334512;G > T, and rs3211892;G > A) in ACS patients from the western Mexican population.

Methods

We recruited 310 ACS patients and 308 subjects in the control group (CG). Genotyping was determined by TaqMan SNP genotyping assays. CD36 expression at the mRNA level was quantified by TaqMan gene expression assays. Soluble CD36 (sCD36) was measured by enzyme‐linked immunosorbent assay.

Results

We show that rs1194182G > C variant provides a protective effect with a 1.7‐fold lower susceptibility to develop ACS (p  = 0.03); however, this association was masked by diabetes and dyslipidemia. We observed a higher sCD36 concentration in patient with ST‐segment elevation myocardial infarction (STEMI) compared with patients with unstable angina (UA) (p  = 0.038). Likewise, in diabetic patients versus non‐diabetic (p < 0.001). We observed in patients an increase in CD36 mRNA expression (1.91 times higher) than in the CG (p  = 0.02).

Conclusion

The rs1194182 seems to be associated with diabetes in a risky manner, in ACS patients and protective for dyslipidemia in both groups. The concentration of sCD36 seems to be associated with the clinical spectrum of the ACS patients and the presence of diabetes, since patients with STEMI present significantly elevated level compared with UA.

Cross-comparative metabolomics reveal sex-age specific metabolic fingerprints and metabolic interactions in acute myocardial infarction

The elucidation of metabolic perturbations and gender-age-specific metabolic characteristics associated with acute myocardial infarction (AMI) is essential for clinical risk stratification and disease management. A comprehensive cross-comparative metabolomics analysis was performed on the sera from 445 healthy controls, 347 AMI patients without cardiovascular disease (CVD), 79 AMI with CVD (AMICVD) patients including 27 deaths. Machine-learning-based integrated biomarker profiling and global network analysis were used to create a multi-biomarker for distinguishing the different AMI outcomes. The changes of most metabolites were dependent on AMI, but gender and age also give additional contributions to the changes of histidine, malonate, O-acetyl-glycoprotein and trimethylamine N-oxide. The altered metabolic pathways included gut dysbiosis, increased amino acid metabolism, glucose metabolism and ketone metabolism, and inactivation of tricarboxylic acid cycle. Enhanced histidine metabolism and microbiota dysbiosis may be one of the key factors during the developing of AMI into AMICVD. For the differential diagnosis of AMI events, three sets of specific multi-biomarkers provided relatively high accuracy with the areas under the curve more than 0.8 and hazard ratio more than 1 in the discovery set, and the results were reproduced and confirmed by the validation set. First use of cross-comparative metabolomics and machine-learning-based integrated biomarker analysis gives great capability to discriminate the different AMI outcomes. Also, the multi-biomarkers seem to be a valid and accurate auxiliary diagnosis biomarker in addition to standard stratification based on clinical parameters.

The interplay of long noncoding RNA HULC with microRNA-128-3p and their correlations with lipid level, stenosis degree, inflammatory cytokines, and cell adhesion molecules in coronary heart disease patients

BACKGROUND

Long noncoding RNA HULC (lnc-HULC) and its target microRNA-128-3p (miR-128-3p) regulate endothelial cell function, blood lipid level, and inflammatory cytokine production, which are involved in the pathogenesis of coronary heart disease (CHD). Based on the above information, this study intended to further investigate the correlation between lnc-HULC and miR-128-3p, as well as their clinical values for CHD management.

METHODS

Totally, 141 CHD patients and 70 controls were enrolled. Lnc-HULC and miR-128-3p in peripheral blood mononuclear cells were detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Serum inflammatory cytokines and cell adhesion molecules were further determined by enzyme-linked immunosorbent assay (ELISA) in CHD patients.

RESULTS

Lnc-HULC was upregulated, while miR-128-3p was downregulated in CHD patients than in controls (both P < 0.001). The ROC curve further displayed that lnc-HULC (AUC: 0.906, 95% CI: 0.867-0.945) and miR-128-3p (AUC: 0.814, 95% CI: 0.756-0.873) had the potential of discriminating CHD patients from controls. Regarding the correlation between lnc-HULC and miR-128-3p, lnc-HULC was negatively associated with miR-128-3p in CHD patients (r_s =  - 0.307, P < 0.001), but this association was not observed in controls (r_s =  - 0.155, P = 0.199). Furthermore, it was discovered that upregulated lnc-HULC was associated with elevated blood lipid levels (TG, LDL-C), inflammatory cytokines (interleukin (IL)-1β, IL-17A), cell adhesion molecules (VCAM-1), and Gensini score (all P < 0.05) in CHD patients. Meanwhile, miR-128-3p was negatively associated with blood lipid level (LDL-C), inflammatory cytokines (TNF-α, IL-1β, IL-6), cell adhesion molecules (VCAM-1, ICAM-1), and Gensini score (all P < 0.05) in CHD patients.

CONCLUSION

Lnc-HULC and its target miR-128-3p relate to lipid level, stenosis degree, inflammatory cytokines, and cell adhesion molecules in CHD patients.

Valosin Containing Protein as a Specific Biomarker for Predicting the Development of Acute Coronary Syndrome and Its Complication

Background

Acute coronary syndrome (ACS) consists of a range of acute myocardial ischemia-related manifestations. The adverse events of ACS are usually associated with ventricular dysfunction (VD), which could finally develop to heart failure. Currently, there is no satisfactory indicator that could specifically predict the development of ACS and its prognosis. Valosin-containing protein (VCP) has recently been proposed to protect against cardiac diseases. Hence, we aimed to assess whether VCP in serum can serve as a valuable biomarker for predicting ACS and its complication.

Methods

Human serum samples from 291 participants were collected and classified into four groups based on their clinical diagnosis, namely healthy control (n = 64), ACS (n = 40), chronic coronary syndrome (CCS, n = 99), and nonischemic heart disease (non-IHD, n = 88). Clinical characteristics of these participants were recorded and their serum VCP levels were detected by enzyme-linked immunosorbent assay (ELISA). Association of serum VCP with the development of ACS and its complication VD was statistically studied. Subsequently, GWAS and eQTL analyses were performed to explore the association between VCP polymorphism and monocyte count. A stability test was also performed to investigate whether VCP is a stable biomarker.

Results

Serum VCP levels were significantly higher in the ACS group compared with the rest groups. Besides, the VCP levels of patients with ACS with VD were significantly lower compared to those without VD. Multivariate logistic regression analysis revealed that VCP was associated with both the risk of ACS (P = 0.042, OR = 1.222) and the risk of developing VD in patients with ACS (P = 0.035, OR = 0.513) independently. The GWAS analysis also identified an association between VCP polymorphism (rs684562) and monocyte count, whereas the influence of rs684562 on VCP mRNA expression level was further verified by eQTL analysis. Moreover, a high stability of serum VCP content was observed under different preservation circumstances.

Conclusion

Valosin-containing protein could act as a stable biomarker in predicting the development of ACS and its complication VD.

Application of Metabolomics to Identify Potential Biomarkers for the Early Diagnosis of Coronary Heart Disease

Coronary heart disease (CHD) is one of the leading causes of deaths globally. Identification of serum metabolic biomarkers for its early diagnosis is thus much desirable. Serum samples were collected from healthy controls (n = 86) and patients with CHD (n = 166) and subjected to untargeted and targeted metabolomics analyses. Subsequently, potential biomarkers were detected and screened, and a clinical model was developed for diagnosing CHD. Four dysregulated metabolites, namely PC(17:0/0:0), oxyneurine, acetylcarnitine, and isoundecylic acid, were identified. Isoundecylic acid was not found in Human Metabolome Database, so we could not validate differences in its relative abundance levels. Further, the clinical model combining serum oxyneurine, triglyceride, and weight was found to be more robust than that based on PC(17:0/0:0), oxyneurine, and acetylcarnitine (AUC = 0.731 vs. 0.579, sensitivity = 83.0 vs. 75.5%, and specificity = 64.0 vs. 46.5%). Our findings indicated that serum metabolomics is an effective method to identify differential metabolites and that serum oxyneurine, triglyceride, and weight appear to be promising biomarkers for the early diagnosis of CHD.

NMR-Based Metabolomics Analysis Predicts Response to Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most fatal type of breast cancer (BC). Due to the lack of relevant targeted drug therapy, in addition to surgery, chemotherapy is still the most common treatment option for TNBC. TNBC is heterogeneous, and different patients have an unusual sensitivity to chemotherapy. Only part of the patients will benefit from chemotherapy, so neoadjuvant chemotherapy (NAC) is controversial in the treatment of TNBC. Here, we performed an NMR spectroscopy–based metabolomics study to analyze the relationship between the patients’ metabolic phenotypes and chemotherapy sensitivity in the serum samples. Metabolic phenotypes from patients with pathological partial response, pathological complete response, and pathological stable disease (pPR, pCR, and pSD) could be distinguished. Furthermore, we conducted metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with three groups of TNBC patients. We evaluated the discriminative ability of metabolites related to significantly disturbed metabolic pathways by using the multi-receiver–operating characteristic (ROC) curve analysis. Three significantly disturbed metabolic pathways of glycine, serine, and threonine metabolism, valine, leucine, and isoleucine biosynthesis, and alanine, aspartate, and glutamate metabolism could be used as potential predictive models to distinguish three types of TNBC patients. These results indicate that a metabolic phenotype could be used to predict whether a patient is suitable for NAC. Metabolomics research could provide data in support of metabolic phenotypes for personalized treatment of TNBC.

The glycine betaine role in neurodegenerative, cardiovascular, hepatic, and renal diseases: Insights into disease and dysfunction networks

Glycine betaine (N, N, N-trimethyl amine) is an osmolyte accumulated in cells that is key for cell volume and turgor regulation, is the principal methyl donor in the methionine cycle and is a DNA and proteins stabilizer. In humans, glycine betaine is synthesized from choline and can be obtained from some foods. Glycine betaine (GB) roles are illustrated in chemical, metabolic, agriculture, and clinical medical studies due to its chemical and physiological properties. Several studies have extensively described GB role and accumulation related to specific pathologies, focusing mainly on analyzing its positive and negative role in these pathologies. However, it is necessary to explain the relationship between glycine betaine and different pathologies concerning its role as an antioxidant, ability to methylate DNA, interact with transcription factors and cell receptors, and participate in the control of homocysteine concentration in liver, kidney and brain. This review summarizes the most important findings and integrates GB role in neurodegenerative, cardiovascular, hepatic, and renal diseases. Furthermore, we discuss GB impact on other dysfunctions as inflammation, oxidative stress, and glucose metabolism, to understand their cross-talks and provide reliable data to establish a base for further investigations.

Defining Acute Coronary Syndrome through Metabolomics

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.

Perturbations in cardiac metabolism in a human model of acute myocardial ischaemia

INTRODUCTION

Acute myocardial ischaemia and the transition from reversible to irreversible myocardial injury are associated with abnormal metabolic patterns. Advances in metabolomics have extended our capabilities to define these metabolic perturbations on a metabolome-wide scale.

OBJECTIVES

This study was designed to identify cardiac metabolic changes in serum during the first 5 min following early myocardial ischaemia in humans, applying an untargeted metabolomics approach.

METHODS

Peripheral venous samples were collected from 46 patients in a discovery study (DS) and a validation study (VS) (25 for DS, 21 for VS). Coronary sinus venous samples were collected from 7 patients (4 for DS, 3 for VS). Acute myocardial ischaemia was induced by transient coronary occlusion during percutaneous coronary intervention (PCI). Plasma samples were collected at baseline (prior to PCI) and at 1 and 5 min post-coronary occlusion. Samples were analyzed by Ultra Performance Liquid Chromatography-Mass Spectrometry in an untargeted metabolomics approach.

RESULTS

The study observed changes in the circulating levels of metabolites at 1 and 5 min following transient coronary ischaemia. Both DS and VS identified 54 and 55 metabolites as significant (P < 0.05) when compared to baseline levels, respectively. Fatty acid beta-oxidation and anaerobic respiration, lysoglycerophospholipids, arachidonic acid, docosahexaenoic acid, tryptophan metabolism and sphingosine-1-phosphate were identified as mechanistically important.

CONCLUSION

Using an untargeted metabolomics approach, the study identified important cardiac metabolic changes in peripheral and coronary sinus plasma, in a human model of controlled acute myocardial ischaemia. Distinct classes of metabolites were shown to be involved in the rapid cardiac response to ischemia and provide insights into diagnostic and interventional targets.

On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update

Infectious and many non-infectious diseases share common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins, and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, both produce metabolic alterations that influence the pathogenesis of the disease. In this review, we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, inducing migration and infiltration of immune cells in target tissues and disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.

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

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.

Serum Metabonomic Study of Patients With Acute Coronary Syndrome Using Ultra-Performance Liquid Chromatography Orbitrap Mass Spectrometer

Acute coronary syndrome (ACS) can cause arrhythmia, heart failure, and even sudden death. Our aim in this study was to identify potential metabolic biomarkers in patients with ACS. The serum metabonomics approach based on ultra-performance liquid chromatography (UPLC)/Orbitrap mass spectrometer (MS) was used to analyze the serum samples from 45 patients with ACS and 29 healthy controls. Multivariate statistical analysis was used to screen for ACS biomarkers. In total, 69 biomarkers were identified to be enriched in 19 metabolic pathways; 43 biomarkers were significantly up-regulated, while 26 biomarkers were significantly down-regulated in the ACS group. The main classes were lyso-sphingolipid (SM), cinnamic acids, cholines, and primary amides. Receiver operating characteristic (ROC) curve analysis showed that lysoPC(20:4(8Z,11Z,14Z,17Z)/0:0) (ROC area under the curve, AUC = 0.936), SM(d18:0/16:0) (ROC AUC = 0.932), and SM(d18:1/14:0) (ROC AUC = 0.923) had a high ACS diagnostic ability. The AUC value of the diagnostic model constructed using these combined biomarkers was 0.96. Therefore, these biomarkers may improve the diagnostic efficacy of ACS. The findings of this study also implied that glycerophospholipid metabolism; the biosynthesis of unsaturated fatty acids; linoleic acid metabolism; and valine, leucine, and isoleucine biosynthesis played important roles in ACS. Network analysis by ingenuity pathway analysis (IPA) showed these biomarkers were correlated to the cardiac hypertrophy signaling pathway, ERK/MAPK signaling pathway, NF-kappa B signaling pathway, nitric oxide (NO) signaling pathway in cardiovascular system, and TLR-signaling pathway. These findings will help to improve the ability of accurate diagnosis and intervention of ACS.

Correlation of the severity of coronary artery disease with patients' metabolic profile- rationale, design and baseline patient characteristics of the CorLipid trial

Background

Coronary artery disease (CAD) remains one of the leading causes of mortality and morbidity worldwide. As oxygen and nutrient supply to the myocardium significantly decrease during ischemic periods, important changes occur regarding myocardial intermediary energy metabolism. Metabolomics is an emerging field in systems biology, which quantifies metabolic changes in response to disease progression. This study aims to evaluate the diagnostic utility of plasma metabolomics-based biomarkers for determining the complexity and severity of CAD, as it is assessed via the SYNTAX score.

Methods

Corlipid is a prospective, non-interventional cohort trial empowered to enroll 1065 patients with no previous coronary intervention history, who undergo coronary angiography in University Hospital AHEPA, Thessaloniki. Venous blood samples are collected before coronary angiography. State-of the-art analytical methods are performed to calculate the serum levels of novel biomarkers: ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and the ratio of apolipoprotein B/apolipoprotein A1. Furthermore, all patients will be categorized based on the indication for coronary angiography (acute coronary syndrome, chronic coronary syndrome, preoperative coronary angiography) and on the severity of CAD using the SYNTAX score. Follow-up of 12 months after enrollment will be performed to record the occurrence of major adverse cardiovascular events. A risk prediction algorithm will be developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD based on their metabolite signatures. The first patient was enrolled in July 2019 and completion of enrollment is expected until May 2021.

Discussion

CorLipid is an ongoing trial aiming to investigate the correlation between metabolic profile and complexity of coronary artery disease in a cohort of patients undergoing coronary angiography with the potential to suggest a decision-making tool with high discriminative power for patients with CAD. To our knowledge, Corlipid is the first study aspiring to create an integrative metabolomic biomarkers-based algorithm by combining metabolites from multiple classes, involved in a wide range of pathways with well-established biochemical markers.

Trial registration CorLipid trial registration: ClinicalTrials.gov number: NCT04580173. Registered 8 October 2020—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04580173.

Combining Field-Enabled Capillary Vibrating Sharp-Edge Spray Ionization with Microflow Liquid Chromatography and Mass Spectrometry to Enhance 'Omics Analyses

Field-enabled capillary vibrating sharp-edge spray ionization (cVSSI) has been combined with high-flow liquid chromatography (LC) and mass spectrometry (MS) to establish current ionization capabilities for metabolomics and proteomics investigations. Comparisons are made between experiments employing cVSSI and a heated electrospray ionization probe representing the state-of-the-art in microflow LC-MS methods for 'omics studies. For metabolomics standards, cVSSI is shown to provide an ionization enhancement by factors of 4 ± 2 for both negative and positive ion mode analyses. For chymotryptic peptides, cVSSI is shown to provide an ionization enhancement by factors of 5 ± 2 and 2 ± 1 for negative and positive ion mode analyses, respectively. Slightly broader high-performance liquid chromatography peaks are observed in the cVSSI datasets, and several studies suggest that this results from a slightly decreased post-split flow rate. This may result from partial obstruction of the pulled-tip emitter over time. Such a challenge can be remedied with the use of LC pumps that operate in the 10 to 100 μL·min-1 flow regime. At this early stage, the proof-of-principle studies already show ion signal advantages over state-of-the-art electrospray ionization (ESI) for a wide variety of analytes in both positive and negative ion mode. Overall, this represents a ∼20-50-fold improvement over the first demonstration of LC-MS analyses by voltage-free cVSSI. Separate comparisons of the ion abundances of compounds eluting under identical solvent conditions reveal ionization efficiency differences between cVSSI and ESI and may suggest varied contributions to ionization from different physicochemical properties of the compounds. Future investigations of parameters that could further increase ionization gains in negative and positive ion mode analyses with the use of cVSSI are briefly presented.

The Serum Metabolic Biomarkers in Early Diagnosis and Risk Stratification of Acute Coronary Syndrome

Despite advances in the treatment of coronary diseases, acute coronary syndrome (ACS) remains the leading cause of death worldwide. ACS is associated with metabolic abnormalities of lipid oxidation stress. In this study, based on liquid chromatograph mass spectrometry technique, we conducted the metabolic profiling analysis of serum samples from stable plaques (SPs) and vulnerable plaques (VPs) in ACS patients for exploring the potential biomarkers of plaque stability. The results showed that four differential metabolites were identified between the SPs and VPs, including betaine, acetylcarnitine, 1-heptadecanoyl-sn-glycero-3-phosphocholine, and isoundecylic acid. Meanwhile, the diagnostic model was identified using stepwise logistic regression and internally validated with 10-fold cross-validation. We analyzed the correlations between serum metabolic perturbations and plaque stability, and the serum betaine and ejection fraction-based model was established with a good diagnostic efficacy [area under the curve (AUC) = 0.808, sensitivity = 70.6%, and specificity = 80.0%]. In summary, we firstly illustrate the comprehensive serum metabolic profiles in ACS patients, suggesting that the combined model of serum betaine and ejection fraction seems to be used as the potential diagnostic biomarker for the vulnerability of plaque stability.

The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies

BACKGROUND

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

AIM OF REVIEW

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze-thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

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

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.

Signaling lipids as diagnostic biomarkers for ocular surface cicatrizing conjunctivitis

Abstract

Metabolomics has been applied to diagnose diseases, predict disease progression, and design therapeutic strategies in various areas of medicine. However, it remains to be applied to the ocular surface diseases, where biological samples are often of limited quantities. We successfully performed proof-of-concept metabolomics assessment of volume-limited cytology samples from a clinical form of chronic inflammatory cicatrizing conjunctivitis, i.e., ocular MMP and discovered metabolic changes of signaling lipid mediators upon disease onset and progression. The metabolomics assessment revealed active oxylipins, lysophospholipids, fatty acids, and endocannabinoids alterations, from which potential biomarkers linked to inflammatory processes were identified. Possible underlying mechanisms such as dysregulated enzyme activities (e.g., lipoxygenases, cytochrome P450, and phospholipases) were suggested which may be considered as potential therapeutic targets in future studies.

Key messages

Metabolic profile of the ocular surface can be measured using impression cytology samples.

Metabolomics analysis of ocular pemphigoid is presented for the first time.

The metabolomics assessment of OCP patients revealed active oxylipins, lysophospholipids, fatty acids, and endocannabinoids alterations.

Several oxylipins are identified as diagnostic biomarkers for OCP.

NMR-based plasma metabolic profiling in patients with unstable angina

OBJECTIVES

Unstable angina (UA) is a form of the acute coronary syndrome (ACS) that affects more than a third of the population before age 70. Due to the limitations of diagnostic tests, appropriate identification of UA is difficult. In this study, we proceeded to investigate metabolite profiling in UA patients compared with controls to determine potential candidate biomarkers.

MATERIALS AND METHODS

Ninety-four plasma samples from UA and 32 samples from controls were analyzed based on 1H NMR spectroscopy. The raw data were processed, analyzed, and subjected to partial least squares-discrimination analysis (PLS-DA), a supervised classification method with a good separation of control and UA patients was observed. The most important variables (VIP) ≥1 were selected and submitted to MetaboAnalyst pathway enrichment to identify the most important ones.

RESULTS

We identified 17 disturbed metabolites in UA patients in comparison with the controls. These metabolites are involved in various biochemical pathways such as steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, and lysine degradation. Some of the metabolites were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone. In order to determine test applicability in diagnosing UA, a diagnostic model was further created using the receiver operator characteristic (ROC) curve. The areas under the curve (AUC), sensitivity, specificity, and precision were 0.87, 90%, 65%, and 91%, respectively, for diagnosing of UA.

CONCLUSION

These metabolites could not only be useful for the diagnosis of UA patients but also provide more information for further deciphering of the biological processes of UA.

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

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.