Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury

Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization

Aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM) are distinct disorders leading to left ventricular hypertrophy (LVH), but whether cardiac metabolism substantially differs between these in humans remains to be elucidated. We undertook an invasive (aortic root, coronary sinus) metabolic profiling in patients with severe AS and HCM in comparison with non-LVH controls to investigate cardiac fuel selection and metabolic remodeling. These patients were assessed under different physiological states (at rest, during stress induced by pacing). The identified changes in the metabolome were further validated by metabolomic and orthogonal transcriptomic analysis, in separately recruited patient cohorts. We identified a highly discriminant metabolomic signature in severe AS in all samples, regardless of sampling site, characterized by striking accumulation of long-chain acylcarnitines, intermediates of fatty acid transport across the inner mitochondrial membrane, and validated this in a separate cohort. Mechanistically, we identify a downregulation in the PPAR-α transcriptional network, including expression of genes regulating fatty acid oxidation (FAO). In silico modeling of β-oxidation demonstrated that flux could be inhibited by both the accumulation of fatty acids as a substrate for mitochondria and the accumulation of medium-chain carnitines which induce competitive inhibition of the acyl-CoA dehydrogenases. We present a comprehensive analysis of changes in the metabolic pathways (transcriptome to metabolome) in severe AS, and its comparison to HCM. Our results demonstrate a progressive impairment of β-oxidation from HCM to AS, particularly for FAO of long-chain fatty acids, and that the PPAR-α signaling network may be a specific metabolic therapeutic target in AS.

Pseudo-targeted metabolic profile differences between emergency patients with type 1 and type 2 myocardial infarction diagnosed by optical coherence tomography

BACKGROUND

It is difficult to distinguish type 2 myocardial infarction (T2MI) from type 1 myocardial infarction (T1MI), although their management varies.

OBJECTIVES

Using optical coherence tomography (OCT) and pseudo-targeted metabolomics to identify biomarkers, investigate metabolic differences, and establish a T2MI subclassification.

METHODS

Among 1519 patients with MI, 97 T2MI patients are identified who are 1:1 matched with 97 T1MI patients after considering age, gender, ST-segment elevation, time from onset to coronary angiography, and hs-cTnI on admission by propensity score matching. Plasma pseudo-targeted metabolomics at baseline was determined.

RESULTS

The clinical characteristics of the two groups were comparable, while the T1MI showed more severe coronary lesions than T2MI according to OCT imaging. 90 differential metabolites were identified between the two groups, among 1027 endogenous metabolites in 20 classes. N-Acetyl-L-Leucine, free fatty acid (15:1), Thymidine-5'-triphosphate, Mevalonic acid 5-pyrophosphate, and five oligopeptides were candidate biomarkers (AUC ≥ 0.85) distinguishing T2MI from T1MI. 12 KEGG pathways showed significant differences, mainly involving amino acid, nucleotide, and their derivatives metabolism, and signaling pathways such as mTOR, cGMP-PKG, and cAMP. Other differences were observed in TCA cycle (P = 0.08) and ROS (P = 0.05). Proteolysis and coronary heart disease risk lipid level were lower in T2MI. T2MI had a decrease of differential abundance score in almost all the KEGG enrichment pathways. Furthermore, T2MI can be subdivided into three subtypes by hierarchical cluster analysis of AUCs with causes/triggers of T2MI.

CONCLUSIONS

There are significant metabolic profile differences between T1MI and T2MI. Several candidate metabolic biomarkers can effectively distinguish the two groups.

CLINICAL TRIAL REGISTRATION

ClinicalTrials. gov NCT03297164.

Integrated Functions of Cardiac Energetics, Mechanics, and Purine Nucleotide Metabolism

Purine nucleotides play central roles in energy metabolism in the heart. Most fundamentally, the free energy of hydrolysis of the adenine nucleotide adenosine triphosphate (ATP) provides the thermodynamic driving force for numerous cellular processes including the actin-myosin crossbridge cycle. Perturbations to ATP supply and/or demand in the myocardium lead to changes in the homeostatic balance between purine nucleotide synthesis, degradation, and salvage, potentially affecting myocardial energetics and, consequently, myocardial mechanics. Indeed, both acute myocardial ischemia and decompensatory remodeling of the myocardium in heart failure are associated with depletion of myocardial adenine nucleotides and with impaired myocardial mechanical function. Yet there remain gaps in the understanding of mechanistic links between adenine nucleotide degradation and contractile dysfunction in heart disease. The scope of this article is to: (i) review current knowledge of the pathways of purine nucleotide depletion and salvage in acute ischemia and in chronic heart disease; (ii) review hypothesized mechanisms linking myocardial mechanics and energetics with myocardial adenine nucleotide regulation; and (iii) highlight potential targets for treating myocardial metabolic and mechanical dysfunction associated with these pathways. It is hypothesized that an imbalance in the degradation, salvage, and synthesis of adenine nucleotides leads to a net loss of adenine nucleotides in both acute ischemia and under chronic high-demand conditions associated with the development of heart failure. This reduction in adenine nucleotide levels results in reduced myocardial ATP and increased myocardial inorganic phosphate. Both of these changes have the potential to directly impact tension development and mechanical work at the cellular level. © 2024 American Physiological Society. Compr Physiol 14:5345-5369, 2024.

Postmortem Alteration of Purine Metabolism in Coronary Artery Disease

A new approach for assisting in the diagnosis of coronary artery disease (CAD) as a cause of death is essential in cases where complete autopsy examinations are not feasible. The purine pathway has been associated with CAD patients, but the understanding of this pathway in postmortem changes needs to be explored. This study investigated the levels of blood purine metabolites in CAD after death. Heart blood samples (n = 60) were collected and divided into CAD (n = 23) and control groups (n = 37). Purine metabolites were measured via proton nuclear magnetic resonance. Guanosine triphosphate (GTP), nicotinamide adenine dinucleotide (NAD), and xanthine levels significantly decreased (p < 0.05); conversely, adenine and deoxyribose 5-phosphate levels significantly increased (p < 0.05) in the CAD group compared to the control group. Decreasing xanthine levels may serve as a marker for predicting the cause of death in CAD (AUC = 0.7). Our findings suggest that the purine pathway was interrupted by physiological processes after death, causing the metabolism of the deceased to differ from that of the living. Additionally, xanthine levels should be studied further to better understand their relationship with CAD and used as a biomarker for CAD diagnosis under decomposition and skeletonization settings.

Metabolomics of early myocardial ischemia

INTRODUCTION

Diagnosing myocardial infarction is difficult during the initial phase. As, acute myocardial ischemia is associated with changes in metabolic pathways, metabolomics may provide ways of identifying early stages of ischemia. We investigated the changes in metabolites after induced ischemia in humans using nuclear magnetic resonance spectroscopy (NMR).

METHODS

We included patients undergoing elective coronary angiography showing normal coronary arteries. These were randomized into 4 groups and underwent coronary artery occlusion for 0, 30, 60 or 90 s. Blood was collected over the next 3 h and analyzed using NMR. We used 2-way ANOVA of time from baseline- and treatment group to find metabolites that changed significantly following the intervention and principal component analysis (PCA) to investigate changes between the 90 s ischemia- and control groups at 15 and 60 min after intervention.

RESULTS

We included 34 patients. The most pronounced changes were observed in the lipid metabolism where 38 of 112 lipoprotein parameters (34%) showed a significant difference between the patients exposed to ischemia and the control group. There was a decrease in total plasma triglycerides over the first hour followed by a normalization. The principal component analysis showed a effects of the treatment after just 15 min. These effects were dominated by changes in high-density lipoprotein. An increase in lactic acid levels was detected surprisingly late, 1-2 h after the ischemia.

CONCLUSION

We investigated the earliest changes in metabolites of patients undergoing brief myocardial ischemia and found that ischemia led to changes throughout the lipid metabolism as early as 15 min post-intervention.

Untargeted metabolomic analysis of ischemic injury in human umbilical vein endothelial cells reveals the involvement of arginine metabolism

OBJECTIVE

In this study, differentially expressed metabolites of vascular endothelial cells were examined to further understand the metabolic regulation of ischemic injury by untargeted metabolomics.

METHOD

Human umbilical vein endothelial cells (HUVECs) were selected to construct an ischemia model using oxygen-glucose deprivation (OGD) and 0, 3, 6, and 9 h of treatment. After that, cell survival levels were determined by CCK8 detection. Flow cytometry, ROS detection, JC-1 detection, and western blotting were used to measure apoptosis and oxidative stress in cells. Then, combined with UPLC Orbitrap/MS, we verified the impacted metabolism pathways by western blotting and RT‒PCR.

RESULTS

CCK8 assays showed that the survival of HUVECs was decreased with OGD treatment. Flow cytometry and the expression of cleaved caspase 3 showed that the apoptosis levels of HUVECs increased following OGD treatment. The ROS and JC-1 results further suggested that oxidative stress injury was aggravated. Then, combined with the heatmap, KEGG and IPA, we found that arginine metabolism was differentially altered during different periods of OGD treatment. Furthermore, the expression of four arginine metabolism-related proteins, ASS1, ARG2, ODC1 and SAT1, was found to change during treatment.

CONCLUSION

Arginine metabolism pathway-related proteins were significantly altered by OGD treatment, which suggests that they may have a potential role in ischemic injury.

APOE alleles modulate associations of plasma metabolites with variants from multiple genes on chromosome 19q13.3

The APOE ε2, ε3, and ε4 alleles differentially impact various complex diseases and traits. We examined whether these alleles modulated associations of 94 single-nucleotide polymorphisms (SNPs) harbored by 26 genes in 19q13.3 region with 217 plasma metabolites using Framingham Heart Study data. The analyses were performed in the E2 (ε2ε2 or ε2ε3 genotype), E3 (ε3ε3 genotype), and E4 (ε3ε4 or ε4ε4 genotype) groups separately. We identified 31, 17, and 22 polymorphism-metabolite associations in the E2, E3, and E4 groups, respectively, at a false discovery rate P FDR < 0.05. These entailed 51 and 19 associations with 20 lipid and 12 polar analytes. Contrasting the effect sizes between the analyzed groups showed 20 associations with group-specific effects at Bonferroni-adjusted P < 7.14E-04. Three associations with glutamic acid or dimethylglycine had significantly larger effects in the E2 than E3 group and 12 associations with triacylglycerol 56:5, lysophosphatidylethanolamines 16:0, 18:0, 20:4, or phosphatidylcholine 38:6 had significantly larger effects in the E2 than E4 group. Two associations with isocitrate or propionate and three associations with phosphatidylcholines 32:0, 32:1, or 34:0 had significantly larger effects in the E4 than E3 group. Nine of 70 SNP-metabolite associations identified in either E2, E3, or E4 groups attained P FDR < 0.05 in the pooled sample of these groups. However, none of them were among the 20 group-specific associations. Consistent with the evolutionary history of the APOE alleles, plasma metabolites showed higher APOE-cluster-related variations in the E4 than E2 and E3 groups. Pathway enrichment mainly highlighted lipids and amino acids metabolism and citrate cycle, which can be differentially impacted by the APOE alleles. These novel findings expand insights into the genetic heterogeneity of plasma metabolites and highlight the importance of the APOE-allele-stratified genetic analyses of the APOE-related diseases and traits.

Sleep Disorder and Cocaine Abuse Impact Purine and Pyrimidine Nucleotide Metabolic Signatures

Disturbances in the circadian rhythm alter the normal sleep-wake cycle, which increases vulnerability to drug abuse. Drug abuse can disrupt several homeostatic processes regulated by the circadian rhythm and influence addiction paradigms, including cravings for cocaine. The relationship between circadian rhythm and cocaine abuse is complex and bidirectional, and disruption impacts both brain function and metabolic profiles. Therefore, elucidating the impact of circadian rhythm changes and cocaine abuse on the human metabolome may provide new insights into identifying potential biomarkers. We examine the effect of cocaine administration with and without circadian rhythm sleep disruption (CRSD) on metabolite levels and compare these to healthy controls in an in vivo study. A metabolomics analysis is performed on the control, CRSD, cocaine, and CRSD with cocaine groups. Plasma metabolite concentrations are analyzed using a liquid chromatography electrochemical array platform. We identify 242 known metabolites compared to the control; 26 in the CRSD with cocaine group, 4 in the CRSD group, and 22 in the cocaine group are significantly differentially expressed. Intriguingly, in the CRSD with cocaine treatment group, the expression levels of uridine monophosphate (p < 0.008), adenosine 5′-diphosphate (p < 0.044), and inosine (p < 0.019) are significantly altered compared with those in the cocaine group. In summary, alterations in purine and pyrimidine metabolism provide clues regarding changes in the energy profile and metabolic pathways associated with chronic exposure to cocaine and CRSD.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

Perioperative Metabolites Are Associated With Adverse Neonatal Congenital Heart Disease Surgical Outcomes

Background Clinical risk factors in neonatal cardiac surgery do not fully capture discrepancies in outcomes. Targeted metabolomic analysis of plasma from neonates undergoing heart surgery with cardiopulmonary bypass was performed to determine associations with clinical outcomes. Methods and Result Samples and clinical variables from 149 neonates enrolled in the Corticosteroid Therapy in Neonates Undergoing Cardiopulmonary Bypass trial with surgical treatment for congenital heart disease between 2012 and 2016 were included. Blood samples were collected before skin incision, immediately after cardiopulmonary bypass, and 12 hours after surgery. Outcomes include composite morbidity/mortality (death, extracorporeal membrane oxygenation, cardiac arrest, acute kidney injury, and/or hepatic injury) and a cardiac composite (extracorporeal membrane oxygenation, cardiac arrest, or increase in lactate level), hepatic injury, and acute kidney injury. Targeted metabolite levels were determined by high-resolution tandem liquid chromatography and mass spectrometry. Principal component and regression analyses were used to assess associations between metabolic profiles and outcomes, with 2 models created: a base clinical model and a base model+metabolites. Of the 193 metabolites examined, 40 were detected and quantified. The first principal component, principal component 1, was composed mostly of preoperative metabolites and was significantly associated with the composite morbidity/mortality, cardiac composite, and hepatic injury outcomes. In regression models, individual metabolites also improved model performance for the composite morbidity/mortality, cardiac composite, and hepatic injury outcomes. Significant disease pathways included myocardial injury (false discovery rate, 0.00091) and heart failure (false discovery rate, 0.041). Conclusions In neonatal cardiac surgery, perioperative metabolites were associated with postoperative outcomes and improved clinical model outcome associations. Preoperative metabolite levels alone may improve risk models and provide a basis for optimizing perioperative care.

Untargeted Metabolomics Studies of H9c2 Cardiac Cells Submitted to Oxidative Stress, β-Adrenergic Stimulation and Doxorubicin Treatment: Investigation of Cardiac Biomarkers

One of the biggest challenges in the search for more effective treatments for diseases is understanding their etiology. Cardiovascular diseases (CVD) are an important example of this, given the high number of deaths annually. Oxidative stress (the imbalance between oxidant and antioxidant species in biological system) is one of the factors responsible for CVD occurrence, demanding extensive investigation. Excess of reactive oxygen species (ROS) are primarily responsible for this condition, and clinical and scientific literature have reported a significant increase in ROS when therapeutic drugs, such as doxorubicin and isoproterenol, are administered. In this context, the aim of this study is the investigation of potential biomarkers that might be associated with oxidative stress in cardiomyocytes. For this purpose, H9c2 cardiomyocytes were submitted to oxidative stress conditions by treatment with doxorubicin (DOX), isoproterenol (ISO) and hydrogen peroxide (PER). Metabolomics analyses of the cell extract and the supernatant obtained from the culture medium were then evaluated by CE-ESI(+)-TOF-MS. Following signal processing, statistical analyses, and molecular features annotations, the results indicate changes in the aspartate, serine, pantothenic acid, glycerophosphocholine and glutathione metabolism in the cell extract.

Uptake and Transport of Naringenin and Its Antioxidant Effects in Human Intestinal Epithelial Caco-2 Cells

Naringenin, a flavanone, has been reported for a wide range of pharmacological activities. However, there are few reports on the absorption, transport and antioxidant effects of naringenin. The study was to explore the uptake, transport and antioxidant effects of naringenin in vitro. Cell transmembrane resistance, lucifer yellow transmission rate, and alkaline phosphatase activity were used to evaluate the successful construction of cell model. The results showed that the absorption and transport of naringenin by Caco-2 cells were time- and concentration-dependent. Different temperatures (37 and 4°C) had a significant effect on the uptake and transport of naringenin. Verapamil, potent inhibitor of P-glycoprotein, significantly inhibit naringenin transport in Caco-2 cells. The results revealed that naringenin was a moderately absorbed biological macromolecule and can penetrate Caco-2 cells, mainly mediated by the active transport pathway involved in P-glycoprotein. At the same time, naringenin pretreatment could significantly increase the viability of H₂O₂-induced Caco-2 cells. Twenty four differential metabolites were identified based on cellular metabolite analysis, mainly including alanine, aspartate and glutamate metabolism, histidine metabolism, taurine and hypotaurine metabolism, pyruvate metabolism, purine metabolism, arginine biosynthesis, citrate cycle, riboflavin metabolism, and D-glutamine and D-glutamate metabolism. We concluded that the transport of naringenin by Caco-2 cells is mainly involved in active transport mediated by P-glycoprotein and naringenin may play an important role in oxidative stress-induced intestinal diseases.

Kynurenine Pathway Metabolites as Potential Clinical Biomarkers in Coronary Artery Disease

Coronary artery disease (CAD) is one of the leading cause of mortality worldwide. Several risk factors including unhealthy lifestyle, genetic background, obesity, diabetes, hypercholesterolemia, hypertension, smoking, age, etc. contribute to the development of coronary atherosclerosis and subsequent coronary artery disease. Inflammation plays an important role in coronary artery disease development and progression. Pro-inflammatory signals promote the degradation of tryptophan via the kynurenine pathway resulting in the formation of several immunomodulatory metabolites. An unbalanced kynurenic pathway has been implicated in the pathomechanisms of various diseases including CAD. Significant improvements in detection methods in the last decades may allow simultaneous measurement of multiple metabolites of the kynurenine pathway and such a thorough analysis of the kynurenine pathway may be a valuable tool for risk stratification and determination of CAD prognosis. Nevertheless, imbalance in the activities of different branches of the kynurenine pathway may require careful interpretation. In this review, we aim to summarize clinical evidence supporting a possible use of kynurenine pathway metabolites as clinical biomarkers in various manifestations of CAD.

A Pilot Study on the 1H-NMR Serum Metabolic Profile of Takotsubo Patients Reveals Systemic Response to Oxidative Stress

Takotsubo syndrome (TTS) presents as an acute coronary syndrome characterized by severe left ventricular (LV) dysfunction and non-obstructive coronary artery disease that typically shows spontaneous recovery within days or weeks. The mechanisms behind TTS are mainly related to beta-adrenergic overstimulation and acute endogenous catecholamine surge, both of which could increase oxidative status that may induce further deterioration of cardiac function. Although several studies reported evidence of inflammation and oxidative stress overload in myocardial tissue of TTS models, systemic biochemical evidence of augmented oxidant activity in patients with TTS is lacking. In this study, serum samples of ten TTS patients and ten controls have been analyzed using ¹H-NMR spectroscopy. The results of this pilot study show a marked alteration in the systemic metabolic profile of TTS patients, mainly characterized by significant elevation of ketone bodies, 2-hydroxybutyrate, acetyl-L-carnitine, and glutamate levels, in contrast with a decrease of several amino acid levels. The overall metabolic fingerprint reflects a systemic response to oxidative stress caused by the stressor that triggered the syndrome’s onset.

Targeted metabolomic analysis of plasma fatty acids in acute myocardial infarction in young adults

BACKGROUND AND AIMS

Acute myocardial infarction (AMI) in young adults has distinct clinical features and risk profile as compared with that in elder adults. The pathophysiologic mechanism of AMI in young adults remains unclear. In this study, we used targeted metabolomics to measure metabolic profile and analyzed plasma fatty acids levels in young adults with AMI, seeking to determine whether circulating fatty acid metabolism was correlated with the occurrence of AMI in young adults.

METHODS AND RESULTS

Consecutive young and elder patients admitted to hospital for AMI were enrolled. Plasma samples of all participants were obtained after overnight fast and then measured using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) based targeted metabolomic platform. A total of 201 plasma metabolites were measured using UPLC-MS/MS. Several plasma fatty acids were significantly altered in young AMI patients compared with control or elder AMI patients, which also showed significant prediction value for AMI in young adults. Percentage of short chain fatty acids (SCFAs) was decreased and long chain increased in AMI as compared with control. Moreover, alpha-linolenic acid and linoleic acid metabolism (ALALAM) pathway metabolites were gradually increased in control, young, and elder AMI patients. Altered fatty acid correlation network further identified fatty acid metabolism disorder in AMI in young adults.

CONCLUSION

By utilizing targeted metabolomic technique, we have found several altered fatty acids and respective pathways that show diagnostic value for AMI in young adults. SCFA and long-chain fatty acid (LCFA) were differentially altered in AMI patients.

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.

Glycerol-3-phosphate and fibroblast growth factor 23 regulation

PURPOSE OF REVIEW

Both classical and nonclassical factors regulate fibroblast growth factor 23 (FGF23), with impacts on gene expression and proteolytic cleavage. Here, we review recent publications that extend current knowledge on these factors.

RECENT FINDINGS

Emerging nonclassical FGF23 regulators such as erythropoietin cause a balanced increase in FGF23 expression and cleavage, with minimal or no increase in biologically active intact FGF23 (iFGF23) in blood. However, circulating FGF23 profiles may not reflect the bone marrow microenvironment. For example, granulocyte colony-stimulating factor increases local marrow iFGF23 levels without impacting circulating iFGF23 levels. The view that phosphate does not increase bone FGF23 production also warrants reconsideration, as phosphate can reduce iFGF23 cleavage and phosphate-containing calciprotein particles increase FGF23 expression. Finally, a screen of renal venous plasma identifies glycerol-3-phosphate as a kidney-derived molecule that circulates to bone and bone marrow, where it is converted to lysophosphatidic acid and signals through a G-protein coupled receptor to increase FGF23 synthesis.

SUMMARY

FGF23 regulation is complex, requiring consideration of known and emerging stimuli, expression and cleavage, and circulating and local levels. Recent work identifies glycerol-3-phosphate as an FGF23 regulator derived from the injured kidney; whether it participates in FGF23 production downstream of classical or nonclassical factors requires further study.

Differential modulation of polyunsaturated fatty acids in patients with myocardial infarction treated with ticagrelor or clopidogrel

Untargeted metabolomics is used to refine the development of biomarkers for the diagnosis of cardiovascular disease. Myocardial infarction (MI) has major individual and societal consequences for patients, who remain at high risk of secondary events, despite advances in pharmacological therapy. To monitor their differential response to treatment, we performed untargeted plasma metabolomics on 175 patients from the platelet inhibition and patient outcomes (PLATO) trial treated with ticagrelor and clopidogrel, two common P₂Y₁₂ inhibitors. We identified a signature that discriminates patients, which involves polyunsaturated fatty acids (PUFAs) and particularly the omega-3 fatty acids docosahexaenoate and eicosapentaenoate. The known cardiovascular benefits of PUFAs could contribute to the efficacy of ticagrelor. Our work, beyond pointing out the high relevance of untargeted metabolomics in evaluating response to treatment, establishes PUFA metabolism as a pathway of clinical interest in the recovery path from MI.

We detect an extreme metabolomic signature of myocardial infarction (MI) in plasma

Polyunsaturated fatty acids (PUFAs) are upregulated in patients taking ticagrelor

PUFA metabolism is a pathway of clinical interest in the recovery path from MI

Data science methods detect biologically meaningful patterns in metabolite signals

Determination of amino acids in human biological fluids by high-performance liquid chromatography: critical review

The quantitation and qualification of amino acids are most commonly used in clinical and epidemiological studies, and provide an excellent way of monitoring compounds in human fluids which have not been monitored previously, to prevent some diseases. Because of this, it is not surprising that scientific interest in evaluating these compounds has resurfaced in recent years and has precipitated the development of a multitude of new analytical techniques. This review considers recent developments in HPLC analytics on the basis of publications from the last few years. It helps to update and systematize knowledge in this area. Particular attention is paid to the progress of analytical methods, pointing out the advantages and drawbacks of the various techniques used for the preparation, separation and determination of amino acids. Depending on the type of sample, the preparation conditions for HPLC analysis change. For this reason, the review has focused on three types of samples, namely urine, blood and cerebrospinal fluid. Despite time-consuming sample preparation before HPLC analysis, an additional derivatization technique should be used, depending on the detection technique used. There are proposals for columns that are specially modified for amino acid separation without derivatization, but the limit of detection of the substance is less beneficial. In view of the fact that amino acid analyses have been performed for years and new solutions may generate increased costs, it may turn out that older proposals are much more advantageous.

Past, Present, and Future of Blood Biomarkers for the Diagnosis of Acute Myocardial Infarction-Promises and Challenges

Despite important advancements in acute myocardial infarction (AMI) management, it continues to represent a leading cause of mortality worldwide. Fast and reliable AMI diagnosis can significantly reduce mortality in this high-risk population. Diagnosis of AMI has relied on biomarker evaluation for more than 50 years. The upturn of high-sensitivity cardiac troponin testing provided extremely sensitive means to detect cardiac myocyte necrosis, but this increased sensitivity came at the cost of a decrease in diagnostic specificity. In addition, although cardiac troponins increase relatively early after the onset of AMI, they still leave a time gap between the onset of myocardial ischemia and our ability to detect it, thus precluding very early management of AMI. Newer biomarkers detected in processes such as inflammation, neurohormonal activation, or myocardial stress occur much earlier than myocyte necrosis and the diagnostic rise of cardiac troponins, allowing us to expand biomarker research in these areas. Increased understanding of the complex AMI pathophysiology has spurred the search of new biomarkers that could overcome these shortcomings, whereas multi-omic and multi-biomarker approaches promise to be game changers in AMI biomarker assessment. In this review, we discuss the evolution, current application, and emerging blood biomarkers for the diagnosis of AMI; we address their advantages and promises to improve patient care, as well as their challenges, limitations, and technical and diagnostic pitfalls. Questions that remain to be answered and hotspots for future research are also emphasized.

Purine metabolite-based machine learning models for risk prediction, prognosis, and diagnosis of coronary artery disease

Alterations in xanthine oxidase activity are known to be pathologically influential on coronary artery disease (CAD), but the association between purine-related blood metabolites and CAD has only been partially elucidated. We performed global metabolomics profiling and network analysis on blood samples from the Wonju and Pyeongchang (WP) cohort study (n = 2055) to elucidate the importance of purine related metabolites associated with potential CAD risk. Then, 5 selected serum metabolites were quantified from the WP cohort, Shinchon cohort (n = 259), and Shinchon case control (n = 424) groups to develop machine learning models for 10-year risk prediction, relapse within 10 years and diagnosis of the disease via 100 repeated 5-fold cross-validations of logistic models. The combination of purine metabolite levels or only xanthine levels in blood could be applied for machine learning model development for major adverse cardiac and cerebrovascular event (MACCE, cerebrovascular death, nonfatal myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass graft, and stroke) risk prediction, relapse of MACCEs among patients with myocardial infarction history and diagnosis of stable CAD. In particular, our research provided initial evidence that blood xanthine and uric acid levels play different roles in the development of machine learning models for primary/secondary prevention or diagnosis of CAD. In this research, we determined that purine-related metabolites in blood are applicable to machine learning model development for CAD risk prediction and diagnosis. Also, our work advances current CAD biomarker discovery strategies mainly relying on clinical features; emphasizes the differential biomarkers in first/secondary prevention or diagnosis studies.

Multi-Omics Approaches to Define Calcific Aortic Valve Disease Pathogenesis

Calcific aortic valve disease sits at the confluence of multiple world-wide epidemics of aging, obesity, diabetes, and renal dysfunction, and its prevalence is expected to nearly triple over the next 3 decades. This is of particularly dire clinical relevance, as calcific aortic valve disease can progress rapidly to aortic stenosis, heart failure, and eventually premature death. Unlike in atherosclerosis, and despite the heavy clinical toll, to date, no pharmacotherapy has proven effective to halt calcific aortic valve disease progression, with invasive and costly aortic valve replacement representing the only treatment option currently available. This substantial gap in care is largely because of our still-limited understanding of both normal aortic valve biology and the key regulatory mechanisms that drive disease initiation and progression. Drug discovery is further hampered by the inherent intricacy of the valvular microenvironment: a unique anatomic structure, a complex mixture of dynamic biomechanical forces, and diverse and multipotent cell populations collectively contributing to this currently intractable problem. One promising and rapidly evolving tactic is the application of multiomics approaches to fully define disease pathogenesis. Herein, we summarize the application of (epi)genomics, transcriptomics, proteomics, and metabolomics to the study of valvular heart disease. We also discuss recent forays toward the omics-based characterization of valvular (patho)biology at single-cell resolution; these efforts promise to shed new light on cellular heterogeneity in healthy and diseased valvular tissues and represent the potential to efficaciously target and treat key cell subpopulations. Last, we discuss systems biology- and network medicine-based strategies to extract meaning, mechanisms, and prioritized drug targets from multiomics datasets.

Metabolic Signatures in Coronary Artery Disease: Results from the BioHEART-CT Study

Despite effective prevention programs targeting cardiovascular risk factors, coronary artery disease (CAD) remains the leading cause of death. Novel biomarkers are needed for improved risk stratification and primary prevention. To assess for independent associations between plasma metabolites and specific CAD plaque phenotypes we performed liquid chromatography mass-spectrometry on plasma from 1002 patients in the BioHEART-CT study. Four metabolites were examined as candidate biomarkers. Dimethylguanidino valerate (DMGV) was associated with presence and amount of CAD (OR) 1.41 (95% Confidence Interval [CI] 1.12-1.79, p = 0.004), calcified plaque, and obstructive CAD (p < 0.05 for both). The association with amount of plaque remained after adjustment for traditional risk factors, ß-coefficient 0.17 (95% CI 0.02-0.32, p = 0.026). Glutamate was associated with the presence of non-calcified plaque, OR 1.48 (95% CI 1.09-2.01, p = 0.011). Phenylalanine was associated with amount of CAD, ß-coefficient 0.33 (95% CI 0.04-0.62, p = 0.025), amount of calcified plaque, (ß-coefficient 0.88, 95% CI 0.23-1.53, p = 0.008), and obstructive CAD, OR 1.84 (95% CI 1.01-3.31, p = 0.046). Trimethylamine N-oxide was negatively associated non-calcified plaque OR 0.72 (95% CI 0.53-0.97, p = 0.029) and the association remained when adjusted for traditional risk factors. In targeted metabolomic analyses including 53 known metabolites and controlling for a 5% false discovery rate, DMGV was strongly associated with the presence of calcified plaque, OR 1.59 (95% CI 1.26-2.01, p = 0.006), obstructive CAD, OR 2.33 (95% CI 1.59-3.43, p = 0.0009), and amount of CAD, ß-coefficient 0.3 (95% CI 0.14-0.45, p = 0.014). In multivariate analyses the lipid and nucleotide metabolic pathways were both associated with the presence of CAD, after adjustment for traditional risk factors. We report novel associations between CAD plaque phenotypes and four metabolites previously associated with CAD. We also identified two metabolic pathways strongly associated with CAD, independent of traditional risk factors. These pathways warrant further investigation at both a biomarker and mechanistic level.

Macrophage Metabolic Signaling during Ischemic Injury and Cardiac Repair

Macrophages are instrumental for the repair of organs that become injured due to ischemia, yet their potential for healing is sensitive to the availability of metabolites from the surrounding milieu. This sensitivity extends beyond anabolic and catabolic reactions, as metabolites are also leveraged to control production of secreted factors that direct intercellular crosstalk. In response to limiting extracellular oxygen, acute-phase macrophages activate hypoxia-inducible transcription factors that repurpose cellular metabolism. Subsequent repair-phase macrophages secrete cytokines to activate stromal cells, the latter which contribute to matrix deposition and scarring. As we now appreciate, these distinct functions are calibrated by directing flux of carbons and cofactors into specific metabolic shunts. This occurs through glycolysis, the pentose phosphate shunt, the tricarboxylic acid cycle, oxidative phosphorylation, nicotinamide adenine dinucleotides, lipids, amino acids, and through lesser understood pathways. The integration of metabolism with macrophage function is particularly important during injury to the ischemic heart, as glucose and lipid imbalance lead to inefficient repair and permanent loss of non-regenerative muscle. Here we review macrophage metabolic signaling under ischemic stress with implications for cardiac repair.

Narrative review of metabolomics in cardiovascular disease

Cardiovascular diseases are accompanied by disorders in the cardiac metabolism. Furthermore, comorbidities often associated with cardiovascular disease can alter systemic and myocardial metabolism contributing to worsening of cardiac performance and health status. Biomarkers such as natriuretic peptides or troponins already support diagnosis, prognosis and treatment of patients with cardiovascular diseases and are represented in international guidelines. However, as cardiovascular diseases affect various pathophysiological pathways, a single biomarker approach cannot be regarded as ideal to reveal optimal clinical application. Emerging metabolomics technology allows the measurement of hundreds of metabolites in biological fluids or biopsies and thus to characterize each patient by its own metabolic fingerprint, improving our understanding of complex diseases, significantly altering the management of cardiovascular diseases and possibly personalizing medicine. This review outlines current knowledge, perspectives as well as limitations of metabolomics for diagnosis, prognosis and treatment of cardiovascular diseases such as heart failure, atherosclerosis, ischemic and non-ischemic cardiomyopathy. Furthermore, an ongoing research project tackling current inconsistencies as well as clinical applications of metabolomics will be discussed. Taken together, the application of metabolomics will enable us to gain more insights into pathophysiological interactions of metabolites and disease states as well as improving therapies of patients with cardiovascular diseases in the future.

Metabolic phenotyping and cardiovascular disease: an overview of evidence from epidemiological settings

Metabolomics, the comprehensive measurement of low-molecular-weight molecules in biological fluids used for metabolic phenotyping, has emerged as a promising tool to better understand pathways underlying cardiovascular disease (CVD) and to improve cardiovascular risk stratification. Here, we present the main methodologies for metabolic phenotyping, the methodological steps to analyse these data in epidemiological settings and the associated challenges. We discuss evidence from epidemiological studies linking metabolites to coronary heart disease and stroke. These studies indicate the systemic nature of CVD and identify associated metabolic pathways such as gut microbial cometabolism, branched-chain amino acids, glycerophospholipid and cholesterol metabolism, as well as activation of inflammatory processes. Integration of metabolomic with genomic data can provide new evidence for involved biochemical pathways and potential for causality using Mendelian randomisation. The clinical utility of metabolic biomarkers for cardiovascular risk stratification in healthy individuals has not yet been established. As sample sizes with high-dimensional molecular data increase in epidemiological settings, integration of metabolomic data across studies and platforms with other molecular data will lead to new understanding of the metabolic processes underlying CVD and contribute to identification of potentially novel preventive and pharmacological targets. Metabolic phenotyping offers a powerful tool in the characterisation of the molecular signatures of CVD, paving the way to new mechanistic understanding and therapies, as well as improving risk prediction of CVD patients. However, there are still challenges to face in order to contribute to clinically important improvements in CVD.

Estrogen Deprivation and Myocardial Infarction: Role of Aerobic Exercise Training, Inflammation and Metabolomics

In general, postmenopausal women present higher mortality, and worse prognosis after myocardial infarction (MI) compared to men, due to estrogen deficiency. After MI, cardiovascular alterations occur such as the autonomic imbalance and the pro-inflammatory cytokines increase. In this sense, therapies that aim to minimize deleterious effects caused by myocardial ischemia are important. Aerobic training has been proposed as a promising intervention in the prevention of cardiovascular diseases. On the other hand, some studies have attempted to identify potential biomarkers for cardiovascular diseases or specifically for MI. For this purpose, metabolomics has been used as a tool in the discovery of cardiovascular biomarkers. Therefore, the objective of this work is to discuss the changes involved in ovariectomy, myocardial infarction, and aerobic training, with emphasis on inflammation and metabolism.

The Molecular Basis of Predicting Atherosclerotic Cardiovascular Disease Risk

Atherosclerotic cardiovascular disease (ASCVD) proceeds through a series of stages: initiation, progression (or regression), and complications. By integrating known biology regarding molecular signatures of each stage with recent advances in high-dimensional molecular data acquisition platforms (to assay the genome, epigenome, transcriptome, proteome, metabolome, and gut microbiome), snapshots of each phase of atherosclerotic cardiovascular disease development can be captured. In this review, we will summarize emerging approaches for assessment of atherosclerotic cardiovascular disease risk in humans using peripheral blood molecular signatures and molecular imaging approaches. We will then discuss the potential (and challenges) for these snapshots to be integrated into a personalized movie providing dynamic readouts of an individual's atherosclerotic cardiovascular disease risk status throughout the life course.

From Prevention to Disease Perturbations: A Multi-Omic Assessment of Exercise and Myocardial Infarctions

While a molecular assessment of the perturbations and injury arising from diseases is essential in their diagnosis and treatment, understanding changes due to preventative strategies is also imperative. Currently, complex diseases such as cardiovascular disease (CVD), the leading cause of death worldwide, suffer from a limited understanding of how the molecular mechanisms taking place following preventive measures (e.g., exercise) differ from changes occurring due to the injuries caused from the disease (e.g., myocardial infarction (MI)). Therefore, this manuscript assesses lipidomic changes before and one hour after exercise treadmill testing (ETT) and before and one hour after a planned myocardial infarction (PMI) in two separate patient cohorts. Strikingly, unique lipidomic perturbations were observed for these events, as could be expected from their vastly different stresses on the body. The lipidomic results were then combined with previously published metabolomic characterizations of the same patients. This integration provides complementary insights into the exercise and PMI events, thereby giving a more holistic understanding of the molecular changes associated with each.

Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels

Aortic valve stenosis (AVS) is a prevalent condition among the elderly population that eventually requires aortic valve replacement. The lack of reliable biomarkers for AVS poses a challenge for its early diagnosis and the application of preventive measures. Untargeted gas chromatography mass spectrometry (GC-MS) metabolomics was applied in 46 AVS cases and 46 controls to identify plasma and urine metabolites underlying AVS risk. Multivariate data analyses were performed on pre-processed data (e.g. spectral peak alignment), in order to detect changes in metabolite levels in AVS patients and to evaluate their performance in group separation and sensitivity of AVS prediction, followed by regression analyses to test for their association with AVS. Through untargeted analysis of 190 urine and 130 plasma features that could be detected and quantified in the GC-MS spectra, we identified contrasting levels of 22 urine and 21 plasma features between AVS patients and control subjects. Following metabolite assignment, we observed significant changes in the concentration of known metabolites in urine (n = 14) and plasma (n = 15) that distinguish the metabolomic profiles of AVS patients from healthy controls. Associations with AVS were replicated in both plasma and urine for about half of these metabolites. Among these, 2-Oxovaleric acid, elaidic acid, myristic acid, palmitic acid, estrone, myo-inositol showed contrasting trends of regulation in the two biofluids. Only trans-Aconitic acid and 2,4-Di-tert-butylphenol showed consistent patterns of regulation in both plasma and urine. These results illustrate the power of metabolomics in identifying potential disease-associated biomarkers and provide a foundation for further studies towards early diagnostic applications in severe heart conditions that may prevent surgery in the elderly.

Autocrine INSL5 promotes tumor progression and glycolysis via activation of STAT5 signaling

Metabolic reprogramming plays important roles in development and progression of nasopharyngeal carcinoma (NPC), but the underlying mechanism has not been completely defined. In this work, we found INSL5 was elevated in NPC tumor tissue and the plasma of NPC patients. Plasma INSL5 could serve as a novel diagnostic marker for NPC, especially for serum VCA-IgA-negative patients. Moreover, higher plasma INSL5 level was associated with poor disease outcome. Functionally, INSL5 overexpression increased, whereas knockdown of its receptor GPCR142 or inhibition of INSL5 reduced cell proliferation, colony formation, and cell invasion in vitro and tumorigenicity in vivo. Mechanistically, INSL5 enhanced phosphorylation and nuclear translocation of STAT5 and promoted glycolytic gene expression, leading to induced glycolysis in cancer cells. Pharmaceutical inhibition of glycolysis by 2-DG or blockade of INSL5 by a neutralizing antibody reversed INSL5-induced proliferation and invasion, indicating that INSL5 can be a potential therapeutic target in NPC. In conclusion, INSL5 enhances NPC progression by regulating cancer cell metabolic reprogramming and is a potential diagnostic and prognostic marker as well as a therapeutic target for NPC.

Aerobic training prevents cardiometabolic changes triggered by myocardial infarction in ovariectomized rats

This study aimed to evaluate the impact of aerobic training (AT) on autonomic, cardiometabolic, ubiquitin-proteasome activity, and inflammatory changes evoked by myocardial infarction (MI) in ovariectomized rats. Female Wistar rats were ovariectomized and divided into four groups: sedentary + sham (SS), sedentary + MI (SI), AT + sham surgery (TS), AT + MI (TI). AT was performed on a treadmill for 8 weeks before MI. Infarcted rats previously subjected to AT presented improved physical capacity, increased interleukin-10, and decreased pro-inflammatory cytokines. Metabolomic analysis identified and quantified 62 metabolites, 9 were considered significant by the Vip Score. SS, SI, and TS groups presented distinct metabolic profiles; however, TI could not be distinguished from the SS group. MI dramatically increased levels of dimethylamine, and AT prevented this response. Our findings suggest that AT may be useful in preventing the negative changes in functional, inflammatory, and metabolic parameters related to MI in ovariectomized rats.

Difference in Metabolomic Response to Exercise between Patients with and without Hypertrophic Cardiomyopathy

It is unclear how hypertrophic cardiomyopathy (HCM) affects cardiac metabolic pathways at rest and with exercise. This case-control study compared 15 cases with HCM to 2 control groups without HCM. Metabolomic profiling of 210 metabolites was carried out at rest and at peak exercise. The 50 most discriminant metabolites differentially regulated during exercise were selected using partial least squares discriminant analysis. Pathway enrichment analysis was also performed. At rest, no significant difference was observed in metabolomic profiling of HCM cases as compared to controls. By contrast, there were significant differences in metabolomic profiling in response to exercise (p < 0.05) in the following metabolic pathways: the aminoacyl-tRNA biosynthesis pathway; the nitrogen metabolism pathway; the glycine, serine, and threonine metabolism pathway; and the arginine and proline metabolism pathway. The present study demonstrates differential regulation of several metabolic pathways in patients with HCM in the setting of exercise stress.

Core functional nodes and sex-specific pathways in human ischaemic and dilated cardiomyopathy

Poor access to human left ventricular myocardium is a significant limitation in the study of heart failure (HF). Here, we utilise a carefully procured large human heart biobank of cryopreserved left ventricular myocardium to obtain direct molecular insights into ischaemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM), the most common causes of HF worldwide. We perform unbiased, deep proteomic and metabolomic analyses of 51 left ventricular (LV) samples from 44 cryopreserved human ICM and DCM hearts, compared to age-, gender-, and BMI-matched, histopathologically normal, donor controls. We report a dramatic reduction in serum amyloid A1 protein in ICM hearts, perturbed thyroid hormone signalling pathways and significant reductions in oxidoreductase co-factor riboflavin-5-monophosphate and glycolytic intermediate fructose-6-phosphate in both; unveil gender-specific changes in HF, including nitric oxide-related arginine metabolism, mitochondrial substrates, and X chromosome-linked protein and metabolite changes; and provide an interactive online application as a publicly-available resource.

LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma

Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography—mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.

Serum lipids profiling perturbances in patients with ischemic heart disease and ischemic cardiomyopathy

Background

Ischemic heart disease (IHD) is a common cardiovascular disorder associated with inadequate blood supply to the myocardium. Chronic coronary ischemia leads to ischemic cardiomyopathy (ICM). Despite their rising prevalence and morbidity, few studies have discussed the lipids alterations in these patients.

Methods

In this cross-sectional study, we analyzed serum lipids profile in IHD and ICM patients using a lipidomics approach. Consecutive consenting patients admitted to the hospital for IHD and ICM were enrolled. Serum samples were obtained after overnight fasting. Non-targeted metabolomics was applied to demonstrate lipids metabolic profile in control, IHD and ICM patients.

Results

A total of 63 and 62 lipids were detected in negative and positive ion mode respectively. Among them, 16:0 Lyso PI, 18:1 Lyso PI in negative ion mode, and 19:0 Lyso PC, 12:0 SM d18:1/12:0, 15:0 Lyso PC, 17:0 PC, 18:1–18:0 PC in positive ion mode were significantly altered both in IHD and ICM as compared to control. 13:0 Lyso PI, 18:0 Lyso PI, 16:0 PE, 14:0 PC DMPC, 16:0 ceramide, 18:0 ceramide in negative ion mode, and 17:0 PE, 19:0 PC, 14:0 Lyso PC, 20:0 Lyso PC, 18:0 PC DSPC, 18:0–22:6 PC in positive ion mode were significantly altered only in ICM as compared to IHD and control.

Conclusion

Using non-targeted lipidomics profiling, we have successfully identified a group of circulating lipids that were significantly altered in IHD and ICM. The lipids metabolic signatures shed light on potential new biomarkers and therapeutics for preventing and treating ICM.

Glycerol-3-phosphate is an FGF23 regulator derived from the injured kidney

Fibroblast growth factor 23 (FGF23) is a bone-derived hormone that controls blood phosphate levels by increasing renal phosphate excretion and reducing 1,25-dihydroxyvitamin D3 [1,25(OH)2D] production. Disorders of FGF23 homeostasis are associated with significant morbidity and mortality, but a fundamental understanding of what regulates FGF23 production is lacking. Because the kidney is the major end organ of FGF23 action, we hypothesized that it releases a factor that regulates FGF23 synthesis. Using aptamer-based proteomics and liquid chromatography-mass spectrometry-based (LC-MS-based) metabolomics, we profiled more than 1600 molecules in renal venous plasma obtained from human subjects. Renal vein glycerol-3-phosphate (G-3-P) had the strongest correlation with circulating FGF23. In mice, exogenous G-3-P stimulated bone and bone marrow FGF23 production through local G-3-P acyltransferase-mediated (GPAT-mediated) lysophosphatidic acid (LPA) synthesis. Further, the stimulatory effect of G-3-P and LPA on FGF23 required LPA receptor 1 (LPAR1). Acute kidney injury (AKI), which increases FGF23 levels, rapidly increased circulating G-3-P in humans and mice, and the effect of AKI on FGF23 was abrogated by GPAT inhibition or Lpar1 deletion. Together, our findings establish a role for kidney-derived G-3-P in mineral metabolism and outline potential targets to modulate FGF23 production during kidney injury.

Oleic Acid Attenuates Ang II (Angiotensin II)-Induced Cardiac Remodeling by Inhibiting FGF23 (Fibroblast Growth Factor 23) Expression in Mice

Plasma metabolic profiles were compared between patients with hypertension with and without left ventricular hypertrophy and significantly decreased oleic acid (OA) levels were observed in the peripheral blood of patients with hypertension with left ventricular hypertrophy. We sought to determine the effect and underlying mechanisms of OA on cardiac remodeling. In vitro studies with isolated neonatal mouse cardiomyocytes and cardiac fibroblasts revealed that OA significantly attenuated Ang II (angiotensin II)-induced cardiomyocyte growth and cardiac fibroblast collagen expression. In vivo, cardiac function, hypertrophic growth of cardiomyocytes, and fibrosis were analyzed after an Ang II (1000 ng/kg/minute) pump was implanted for 14 days. We found that OA could significantly prevent Ang II-induced cardiac remodeling in mice. RNA sequencing served as a gene expression roadmap highlighting gene expression changes in the hearts of Ang II-induced mice and OA-treated mice. The results revealed that FGF23 (fibroblast growth factor 23) expression was significantly upregulated in mouse hearts in response to Ang II infusion, which was significantly suppressed in the hearts of OA-treated mice. Furthermore, overexpression of FGF23 in the heart by injection of an AAV-9 vector aggravated Ang II-induced cardiac remodeling and impaired the protective effect of OA on cardiac remodeling. Further study found that OA could suppress Ang II-induced FGF23 expression by inhibiting the translocation of Nurr1 (nuclear receptor–related 1 protein) from the cytoplasm to the nucleus. Our findings suggest a novel role of OA in preventing Ang II-induced cardiac remodeling via suppression of FGF23 expression.

Application of Metabolomics to Renal and Cardiometabolic Diseases

Metabolomics has been increasingly applied to study renal and related cardiometabolic diseases, including diabetes and cardiovascular diseases. These studies span cross-sectional studies correlating metabolites with specific phenotypes, longitudinal studies to identify metabolite predictors of future disease, and physiologic/interventional studies to probe underlying causal relationships. This chapter provides a description of how metabolomic profiling is being used in these contexts, with an emphasis on study design considerations as a practical guide for investigators who are new to this area. Research in kidney diseases is underlined to illustrate key principles. The chapter concludes by discussing the future potential of metabolomics in the study of renal and cardiometabolic diseases.

Twenty years of metabonomics: so what has metabonomics done for toxicology?

In 1999 the journal Xenobiotica published a perspective article detailing the new concept of metabonomics and its application to toxicology. The approach was to apply analytical chemistry techniques, and in particular ¹H NMR spectroscopy, to profile biofluids and tissues to assess the metabolic effects of xenobiotics. Metabonomics has been shown to be sensitive not only to organ specific toxicity but also provides information on the cells, tissues and mechanisms involved, as well as their interactions with the host's sex, age, diet and environment. This review assesses the impact of metabonomics on drug toxicology over the past twenty years and its future prospects. These applications include:Pharmacometabonomics - the prediction of drug effects through the analysis of predose, biofluid metabolite profiles, which reflect both genetic and environmental influences on physiology.The microbiomes role in toxicology - understanding how xenobiotics can be modified by the microbiome dramatically changing their impact on the host.Development of expert systems for toxicity prediction.Data fusion of different omics to better understand the underlying mechanisms of drug toxicity.Metabonomics and exposome - understanding how multiple environmental toxicants might interact with the host organism to produce their overall phenotype. While there has been huge growth in the use of metabonomics within toxicology these applications are set to increase as the tools become more sensitive and robust, as well as the increased use of both experimental and in silico databases to aid prediction of toxicology.

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Background

To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC.

Methods

In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways.

Results

The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N′-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria.

Conclusions

UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

High-throughput metabolite profiling: identification of plasma taurine as a potential biomarker of functional outcome after aneurysmal subarachnoid hemorrhage

OBJECTIVE

Metabolite profiling (or metabolomics) can identify candidate biomarkers for disease and potentially uncover new pathways for intervention. The goal of this study was to identify potential biomarkers of functional outcome after subarachnoid hemorrhage (SAH).

METHODS

The authors performed high-throughput metabolite profiling across a broad spectrum of chemical classes (163 metabolites) on plasma samples taken from 191 patients with SAH who presented to Massachusetts General Hospital between May 2011 and October 2016. Samples were drawn at 3 time points following ictus: 0-5, 6-10, and 11-14 days. Elastic net (EN) and LASSO (least absolute shrinkage and selection operator) machine learning analyses were performed to identify metabolites associated with 90-day functional outcomes as assessed by the modified Rankin Scale (mRS). Additional univariate and multivariate analyses were then conducted to further examine the relationship between metabolites and clinical variables and 90-day functional outcomes.

RESULTS

One hundred thirty-seven (71.7%) patients with aneurysmal SAH met the criteria for inclusion. A good functional outcome (mRS score 0-2) at 90 days was found in 79 (57.7%) patients. Patients with good outcomes were younger (p = 0.002), had lower admission Hunt and Hess grades (p < 0.0001) and modified Fisher grades (p < 0.0001), and did not develop hydrocephalus (p < 0.0001) or delayed cerebral ischemia (DCI) (p = 0.049). EN and LASSO machine learning methods identified taurine as the leading metabolite associated with 90-day functional outcome (p < 0.0001). Plasma concentrations of the amino acid taurine from samples collected between days 0 and 5 after aneurysmal SAH were 21.9% (p = 0.002) higher in patients with good versus poor outcomes. Logistic regression demonstrated that taurine remained a significant predictor of functional outcome (p = 0.013; OR 3.41, 95% CI 1.28-11.4), after adjusting for age, Hunt and Hess grade, modified Fisher grade, hydrocephalus, and DCI.

CONCLUSIONS

Elevated plasma taurine levels following aneurysmal SAH predict a good 90-day functional outcome. While experimental evidence in animals suggests that this effect may be mediated through downregulation of pro-inflammatory cytokines, additional studies are required to validate this hypothesis in humans.

Application of metabolomics for unveiling the therapeutic role of traditional Chinese medicine in metabolic diseases

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional medicine has been practiced for thousands of years in China and some Asian countries. Traditional Chinese Medicine (TCM) is characterized as multi-component and multiple targets in disease therapy, and it is a great challenge for elucidating the mechanisms of TCM.

AIM OF THE REVIEW

Comprehensively summarize the application of metabolomics in biomarker discovery, stratification of TCM syndromes, and mechanism underlying TCM therapy on metabolic diseases.

METHODS

This review systemically searched the publications with key words such as metabolomics, traditional Chinese medicine, metabolic diseases, obesity, cardiovascular disease, diabetes mellitus in "Title OR Abstract" in major databases including PubMed, the Web of Science, Google Scholar, Science Direct, CNKI from 2010 to 2019.

RESULTS

A total of 135 papers was searched and included in this review. An overview of articles indicated that metabolic characteristics may be a hallmark of different syndromes/models of metabolic diseases, which provides a new perspective for disease diagnosis and therapeutic optimization. Moreover, TCM treatment has significantly altered the metabolic perturbations associated with metabolic diseases, which may be an important mechanism for the therapeutic effect of TCM.

CONCLUSIONS

Until now, many metabolites and differential biomarkers related to the pathogenesis of metabolic diseases and TCM therapy have been discovered through metabolomics research. Unfortunately, the biological role and mechanism of disease-related metabolites were largely unclarified so far, which warrants further investigation.

Profiling thiol metabolites in myocardial infarction human serum by stable isotope labeling assisted liquid chromatography-mass spectrometry

Myocardial Infarction (MI) is one of the most common causes of deaths worldwide. Thiols have been reported to play a key role in physiological and pathological processes of MI. Comprehensive analysis of thiols would be conducive to fully elucidate the relation between thiols and MI. In the current study, we analyze the metabolomic differences of thiols in serum between MI patients (n = 30) and healthy controls (HCs, n = 30) by stable isotope labeling-dispersive solid phase extraction-liquid chromatography-full scan-Orbitrap-mass spectrometry analysis (IL-DSPE-LC-full scan-Orbitrap MS) method. We detected 300 potential thiols in serum of MI patients and HCs, among which, 67 thiols were positively or putatively identified. Furthermore, we found that the levels of 71 thiols in serum exhibited significant difference between MI patients and HCs. In the transsulfuration pathway, we observed that Cys and Hcys were upregulated, while GSH were downregulated. Our results provide a comprehensive understanding of thiols metabolome in human serum between MI patients and HCs.

Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics

BACKGROUND

Many genome-wide association studies have detected genomic regions associated with traits, yet understanding the functional causes of association often remains elusive. Utilizing systems approaches and focusing on intermediate molecular phenotypes might facilitate biologic understanding.

RESULTS

The availability of exome sequencing of two populations of African-Americans and European-Americans from the Atherosclerosis Risk in Communities study allowed us to investigate the effects of annotated loss-of-function (LoF) mutations on 122 serum metabolites. To assess the findings, we built metabolomic causal networks for each population separately and utilized structural equation modeling. We then validated our findings with a set of independent samples. By use of methods based on concepts of Mendelian randomization of genetic variants, we showed that some of the affected metabolites are risk predictors in the causal pathway of disease. For example, LoF mutations in the gene KIAA1755 were identified to elevate the levels of eicosapentaenoate (p-value = 5E-14), an essential fatty acid clinically identified to increase essential hypertension. We showed that this gene is in the pathway to triglycerides, where both triglycerides and essential hypertension are risk factors of metabolomic disorder and heart attack. We also identified that the gene CLDN17, harboring loss-of-function mutations, had pleiotropic actions on metabolites from amino acid and lipid pathways.

CONCLUSION

Using systems biology approaches for the analysis of metabolomics and genetic data, we integrated several biological processes, which lead to findings that may functionally connect genetic variants with complex diseases.