A practical guide to metabolomic profiling as a discovery tool for human heart disease

Causal association between blood metabolites and risk of hypertension: a Mendelian randomization study

Background

Previous studies have indicated a strong link between blood metabolites and hypertension, however the causality of metabolites and hypertension is unknown.

Methods

Two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between 486 blood metabolites and essential hypertension (EHT). Blood metabolite GWAS data was utilized as the exposure, with EHT GWAS data as the outcome. To further verify the results, another different source of EHT GWAS data was repeatedly analyzed. The major MR analytic approach used to determine causality was inverse variance weighted (IVW), with MR-Egger, Weighted Median, and MR-PRESSO models serving as supplements. We used the Cochran Q test to examine heterogeneity. Horizontal pleiotropy was examined using MR-Egger intercept and MR-PRESSO global test. The MR Steiger test confirmed the causal relationship between blood metabolites and EHT.

Results

In this study, nine blood metabolites associated with EHT were preliminarily identified by MR analysis, including four known metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid, creatine, hexadecanedioate) and five unknown metabolites. Then another source of EHT GWAS data was repeatedly analyzed for further verification, and two overlapped metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid) were found. There was a negative correlation between N-acetylornithine and EHT (OR = 0.987, 95% CI = 0.980-0.993, P = 1.01 × 10-4), Cochran's Q test suggested there was no heterogeneity (Q = 31.7586, P = 0.1331), MR-Egger intercept and MR-PRESSO global test suggested there was no horizontal pleiotropy (P > 0.05), Leave-one-out analysis indicated that no single single-nucleotide polymorphism (SNP) had a significant effect on the results, and MR Steiger test confirmed that the direction of causality was correct (P < 0.001). There was a negative correlation between X-12510-2-aminooctanoic acid and EHT (OR = 0.982, 95% CI = 0.972-0.993, P = 0.0017), and there was no evidence of heterogeneity or pleiotropy in multiple sensitivity analyses.

Conclusion

The study discovered some blood metabolites causally linked to EHT, which might lead to new understandings of the pathophysiology of hypertension.

MALDI-TOF MS: A Promising Analytical Approach to Cancer Diagnostics and Monitoring

Cancer remains the second most common cause of death after cardiovascular diseases, accounting for nearly 10 million deaths in 2020. Although the incidence of cancer increases considerably with age, the cancer burden can also be reduced and have a high chance of cure through early detection, appropriate treatment, and care of patients. The development of high-throughput analytical approaches, like matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), contributes to identifying a pool of proteins/peptides as putative biomarkers for the early detection, diagnosis, and tumor progression. The purpose of the current review is to present an updated outline of recent proteome/peptidome research to establish putative cancer biomarkers using MALDI-TOF MS and highlight the applicability of statistical analysis in the oncology field. The pros and cons of MALDI-TOF MS application on cancer diagnostics and monitoring will be discussed, as well as compared with tandem mass spectrometry (MS/MS)-based proteomics (e.g., liquid chromatography–tandem mass spectrometry). In addition, pre-analytical (e.g., sample quality control) and analytical (e.g., sample pre-treatment, instrumental analytical conditions) properties that influence the robustness of MALDI-TOF MS data will be also discussed.

Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia

Acute myocardial ischemia (AMI) remains the leading cause of death worldwide, and the post-mortem diagnosis of AMI represents a current challenge for both clinical and forensic pathologists. In the present study, the untargeted metabolomics based on ultra-performance liquid chromatography combined with high-resolution mass spectrometry was applied to analyze serum metabolic signatures from AMI in a rat model (n = 10 per group). A total of 28 endogenous metabolites in serum were significantly altered in AMI group relative to control and sham groups. A set of machine learning algorithms, namely gradient tree boosting (GTB), support vector machine (SVM), random forest (RF), logistic regression (LR), and multilayer perceptron (MLP) models, was used to screen the more valuable metabolites from 28 metabolites to optimize the biomarker panel. The results showed that classification accuracy and performance of MLP model were better than other algorithms when the metabolites consisting of L-threonic acid, N-acetyl-L-cysteine, CMPF, glycocholic acid, L-tyrosine, cholic acid, and glycoursodeoxycholic acid. Finally, 17 blood samples from autopsy cases were applied to validate the classification model's value in human samples. The MLP model constructed based on rat dataset achieved accuracy of 88.23%, and ROC of 0.89 for predicting AMI type II in autopsy cases of sudden cardiac death. The results demonstrated that MLP model based on 7 molecular biomarkers had a good diagnostic performance for both AMI rats and autopsy-based blood samples. Thus, the combination of metabolomics and machine learning algorithms provides a novel strategy for AMI diagnosis.

Metabolomics and NMR

The purpose of this manuscript will be to convince the reader to dive deeper into NMR spectroscopy and prevent the technique from being just another "black-box" in the lab. We will try to concisely highlight interesting topics and supply additional references for further exploration at each stage. The advantages of delving into the technique will be shown. The secondary objective, i.e., avoiding common problems before starting, will hopefully then become clear. Lastly, we will emphasize the spectrometer information needed for manuscript reporting to allow reproduction of results and confirm findings.

Metabolic Profiling and Metabolites Fingerprints in Human Hypertension: Discovery and Potential

Early detection of pathogenesis through biomarkers holds the key to controlling hypertension and preventing cardiovascular complications. Metabolomics profiling acts as a potent and high throughput tool offering new insights on disease pathogenesis and potential in the early diagnosis of clinical hypertension with a tremendous translational promise. This review summarizes the latest progress of metabolomics and metabolites fingerprints and mainly discusses the current trends in the application in clinical hypertension. We also discussed the associated mechanisms and pathways involved in hypertension's pathogenesis and explored related research challenges and future perspectives. The information will improve our understanding of the development of hypertension and inspire the clinical application of metabolomics in hypertension and its associated cardiovascular complications.

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.

Current progress in metabolomics of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.

A review of applications of metabolomics in osteoarthritis

Osteoarthritis (OA) represents the most prevalent and disabling arthritis worldwide due to its heterogeneous and progressive articular degradation. However, effective and timely diagnosis and fundamental treatment for this disorder are lacking. Metabolomics, a growing field in life science research in recent years, has the potential to detect many metabolites and thus explains the underlying pathophysiological processes. Hence, new specific metabolic markers and related metabolic pathways can be identified for OA. In this review, we aimed to provide an overview of studies related to the metabolomics of OA in animal models and humans to describe the metabolic changes and related pathways for OA. The present metabolomics studies reveal that the pathogenesis of OA may be significantly related to perturbations of amino acid metabolism. These altered amino acids (e.g., branched-chain amino acids, arginine, and alanine), as well as phospholipids, were identified as potential biomarkers to distinguish patients with OA from healthy individuals.

Cardiac function dependence on carbon monoxide

Nitric oxide, studied to evaluate its role in cardiovascular physiology, has cardioprotective and therapeutic effects in cellular signaling, mitochondrial function, and in regulating inflammatory processes. Heme oxygenase (major role in catabolism of heme into biliverdin, carbon monoxide (CO), and iron) has similar effects as well. CO has been suggested as the molecule that is responsible for many of the above mentioned cytoprotective and therapeutic pathways as CO is a signaling molecule in the control of physiological functions. This is counterintuitive as toxic effects are related to its binding to hemoglobin. However, CO is normally produced in the body. Experimental evidence indicates that this toxic gas, CO, exerts cytoprotective properties related to cellular stress including the heart and is being assessed for its cytoprotective and cytotherapeutic properties. While survival of adult cardiomyocytes depends on oxidative phosphorylation (survival and resulting cardiac function is impaired by mitochondrial damage), mitochondrial biogenesis is modified by the heme oxygenase-1/CO system and can result in promotion of mitochondrial biogenesis by associating mitochondrial redox status to the redox-active transcription factors. It has been suggested that the heme oxygenase-1/CO system is important in differentiation of embryonic stem cells and maturation of cardiomyocytes which is thought to mitigate progression of degenerative cardiovascular diseases. Effects on other cardiac cells are being studied. Acute exposure to air pollution (and, therefore, CO) is associated with cardiovascular mortality, myocardial infarction, and heart failure, but changes in the endogenous heme oxygenase-1 system (and, thereby, CO) positively affect cardiovascular health. We will review the effect of CO on heart health and function in this article.

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

Altered lipid metabolism has been associated with the progression of various cancers, and aberrant expression of enzymes involved in the lipid metabolism has been detected in different stages of cancer. Breast cancer (BC) is one of the cancer types known to be associated with alterations in the lipid metabolism and overexpression of enzymes involved in this metabolism. It has been demonstrated that inhibition of the activity of certain enzymes, such as that of phospholipase A₂ in BC cell lines sensitizes these cells and decreases the IC₅₀ values for forthcoming therapy with traditional drugs, such as doxorubicin and tamoxifen. Moreover, other phospholipases, such as phospholipase C and D, are involved in intracellular signal transduction, which emphasizes their importance in cancer development. Finally, BC is assumed to be dependent on the diet and the composition of lipids in nutrients. Despite their importance, analytical approaches that can associate the activity of phospholipases with changes in the lipid composition and distribution in cancer tissues are not yet standardized. In this review, an overview of various analytical platforms that are applied on the study of lipids and phospholipase activity in BC tissues will be given, as well as their association with cancer diagnosis and tumor progression. The methods that are applied to tissues obtained from the BC patients will be emphasized and critically evaluated, regarding their applicability in oncology.

NMR-Based Metabolomics in Cardiac Research

Proton (¹H) nuclear magnetic resonance (NMR) spectroscopy can measure a range of metabolites in both cardiac tissue and blood plasma for following cardiovascular disease. For solution-state NMR spectroscopy, it is necessary to create a tissue extract, with perchloric acid, acetonitrile/water, and chloroform/methanol being popular extraction media. Alternatively, high-resolution magic angle spinning (HRMAS) ¹H NMR spectroscopy can be used to derive a metabolic profile directly from intact cardiac tissue. This chapter will discuss the practical methods used for ¹H NMR spectroscopy to follow cardiovascular diseases both in terms of metabolic changes in cardiac tissue and changes in blood plasma.

Metabolomics and its application in the treatment of coronary heart disease with traditional Chinese medicine

Traditional Chinese Medicine (TCM) is the treasure of Chinese Nation and gained the gradual acceptance of the international community. However, the methods and theories of TCM understanding of diseases are lack of appropriate modern scientific characterization systems. Moreover, traditional risk factors cannot promote to detection and prevent those patients with coronary artery disease (CAD) who have not developed acute myocardial infarction (MI) in time. To sum up, there is still no objective systematic evaluation system for the therapeutic mechanism of TCM in the prevention and cure of cardiovascular disease. Thus, new ideas and technologies are needed. The development of omics technology, especially metabolomics, can be used to predict the level of metabolites in vivo and diagnose the physiological state of the body in time to guide the corresponding intervention. In particular, metabolomics is also a very powerful tool to promote the modernization of TCM and the development of TCM in personalized medicine. This article summarized the application of metabolomics in the early diagnosis, the discovery of biomarkers and the treatment of TCM in CAD.

Robust effect of metabolic syndrome on major metabolic pathways in the myocardium

Although the high-fat-diet-induced metabolic syndrome (MetS) is a precursor of human cardiac pathology, the myocardial metabolic state in MetS is far from clear. The discrepancies in metabolite handling between human and small animal models and the difficulties inherent in obtaining human tissue complicate the identification of the myocardium-specific metabolic response in patients. Here we use the large animal model of swine that develops the hallmark criteria of human MetS. Our comparative metabolomics together with transcriptomics and computational nonnegative matrix factorization (NMF) interpretation of the data exposes significant decline in metabolites related to the fatty acid oxidation, glycolysis, and pentose phosphate pathway. Behind the reversal lies decreased expression of enzymes that operate in the pathways. We showed that diminished glycogen deposition is a metabolic signature of MetS in the pig myocardium. The depletion of glycogen arises from disbalance in expression of genes that break down and synthesize glycogen. We show robust acetoacetate accumulation and activated expression of key enzymes in ketone body formation, catabolism and transporters, suggesting a shift in fuel utilization in MetS. A contrasting enrichment in O-GlcNAcylated proteins uncovers hexosamine pathway and O-GlcNAcase (OGA) expression involvement in the myocardial response to MetS. Although the hexosamine biosynthetic pathway (HBP) activity and the availability of the UDP-GlcNAc substrate in the MetS myocardium is low, the level of O-GlcNacylated proteins is high as the O-GlcNacase is significantly diminished. Our data support the perception of transcriptionally driven myocardial alterations in expression of standard fatty acids, glucose metabolism, glycogen, and ketone body related enzymes and subsequent paucity of their metabolite products in MetS. This aberrant energy metabolism in the MetS myocardium provide insight into the pathogenesis of CVD in MetS.

Metabolic remodeling of cardiomyocytes identified in phosphoinositide-dependent kinase 1-deficient mice

Metabolic remodeling plays an essential role in the pathophysiology of heart failure (HF). Many studies have shown that the disruption of phosphoinositide-dependent protein kinase-1 (PDK1) caused severe and lethal HF; however, the metabolic pattern of PDK1 deletion remains ambiguous. ¹H nuclear magnetic resonance-based metabolomics was applied to explore the altered metabolic pattern in Pdk1-deficient mice. Principle component analysis showed significant separation as early as 4 weeks of age, and dysfunction of metabolism precedes a morphological change in Pdk1-deficient mice. A time trajectory plot indicated that disturbed metabolic patterns were related to the pathological process of the HF in Pdk1-deficient mice, rather than the age of mice. Metabolic profiles demonstrated significantly increased levels of acetate, glutamate, glutamine, and O-phosphocholine in Pdk1 deletion mice. Levels of lactate, alanine, glycine, taurine, choline, fumarate, IMP, AMP, and ATP were significantly decreased compared with controls. Furthermore, PDK1 knockdown decreased the oxygen consumption rate in H9C2 cells as determined using a Seahorse XF96 Analyzer. These findings imply that the disruption of metabolism and impaired mitochondrial activity might be involved in the pathogenesis of HF with PDK1 deletion.

Metabolomics and Heart Diseases: From Basic to Clinical Approach

BACKGROUND

The field of metabolomics has been steadily increasing in size for the last 15 years. Advances in analytical and statistical methods have allowed metabolomics to flourish in various areas of medicine. Cardiovascular diseases are some of the main research targets in metabolomics, due to their social and medical relevance, and also to the important role metabolic alterations play in their pathogenesis and evolution. Metabolomics has been applied to the full spectrum of cardiovascular diseases: from patient risk stratification to myocardial infarction and heart failure. However - despite the many proof-ofconcept studies describing the applicability of metabolomics in the diagnosis, prognosis and treatment evaluation in cardiovascular diseases - it is not yet used in routine clinical practice. Recently, large phenome centers have been established in clinical environments, and it is expected that they will provide definitive proof of the applicability of metabolomics in clinical practice. But there is also room for small and medium size centers to work on uncommon pathologies or to resolve specific but relevant clinical questions.

OBJECTIVES

In this review, we will introduce metabolomics, cover the metabolomic work done so far in the area of cardiovascular diseases.

CONCLUSION

The cardiovascular field has been at the forefront of metabolomics application and it should lead the transfer to the clinic in the not so distant future.

Analysis of serum changes in response to a high fat high cholesterol diet challenge reveals metabolic biomarkers of atherosclerosis

Atherosclerotic plaques are characterized by an accumulation of macrophages, lipids, smooth muscle cells, and fibroblasts, and, in advanced stages, necrotic debris within the arterial walls. Dietary habits such as high fat and high cholesterol (HFHC) consumption are known risk factors for atherosclerosis. However, the key metabolic contributors to diet-induced atherosclerosis are far from established. Herein, we investigate the role of a 2-year HFHC diet challenge in the metabolic changes of development and progression of atherosclerosis. We used a non-human primate (NHP) model (baboons, n = 60) fed a HFHC diet for two years and compared metabolomic profiles in serum from animals on baseline chow with serum collected after the challenge diet using two-dimensional gas chromatography time-of-flight mass-spectrometry (2D GC-ToF-MS) for untargeted metabolomic analysis, to quantify metabolites that contribute to atherosclerotic lesion formation. Further, clinical biomarkers associated with atherosclerosis, lipoprotein measures, fat indices, and arterial plaque formation (lesions) were quantified. Using two chemical derivatization (i.e., silylation) approaches, we quantified 321 metabolites belonging to 66 different metabolic pathways, which revealed significantly different metabolic profiles of HFHC diet and chow diet fed baboon sera. We found heritability of two important metabolites, lactic acid and asparagine, in the context of diet-induced metabolic changes. In addition, abundance of cholesterol, lactic acid, and asparagine were sex-dependent. Finally, 35 metabolites correlated (R2, 0.068-0.271, P < 0.05) with total lesion burden assessed in three arteries (aortic arch, common iliac artery, and descending aorta) which could serve as potential biomarkers pending further validation. This study demonstrates the feasibility of detecting sex-specific and heritable metabolites in NHPs with diet-induced atherosclerosis using untargeted metabolomics allowing understanding of atherosclerotic disease progression in humans.

Pilot study of myocardial ischemia-induced metabolomic changes in emergency department patients undergoing stress testing

BACKGROUND

The heart is a metabolically active organ, and plasma acylcarnitines are associated with long-term risk for myocardial infarction. We hypothesized that myocardial ischemia from cardiac stress testing will produce dynamic changes in acylcarnitine and amino acid levels compared to levels seen in matched control patients with normal stress tests.

METHODS

We analyzed targeted metabolomic profiles in a pilot study of 20 case patients with inducible ischemia on stress testing from an existing prospectively collected repository of 357 consecutive patients presenting with symptoms of Acute Coronary Syndrome (ACS) in an Emergency Department (ED) observation unit between November 2012 and September 2014. We selected 20 controls matched on age, sex, and body-mass index (BMI). A peripheral blood sample was drawn <1 hour before stress testing and 2 hours after stress testing on each patient. We assayed 60 select acylcarnitines and amino acids by tandem mass spectrometry (MS/MS) using a Quattro Micro instrument (Waters Corporation, Milford, MA). Metabolite values were log transformed for skew. We then performed bivariable analysis for stress test outcome and both individual timepoint metabolite concentrations and stress-delta metabolite ratios (T2/T0). False discovery rates (FDR) were calculated for 60 metabolites while controlling for age, sex, and BMI. We built multivariable regularized linear models to predict stress test outcome from metabolomics data at times 0, 2 hours, and log ratio between these two. We used leave-one-out cross-validation to estimate the performance characteristics of the model.

RESULTS

Nine of our 20 case subjects were male. Cases' average age was 55.8, with an average BMI 29.5. Bivariable analysis identified 5 metabolites associated with positive stress tests (FDR < 0.2): alanine, C14:1-OH, C16:1, C18:2, C20:4. The multivariable regularized linear models built on T0 and T2 had Area Under the ROC Curve (AUC-ROC) between 0.5 and 0.55, however, the log(T2/T0) model yielded 0.625 AUC, with 65% sensitivity and 60% specificity. The top metabolites selected by the model were: Ala, Arg, C12-OH/C10-DC, C14:1-OH, C16:1, C18:2, C18:1, C20:4 and C18:1-DC.

CONCLUSIONS

Stress-delta metabolite analysis of patients undergoing stress testing is feasible. Future studies with a larger sample size are warranted.

Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption

Background

Diet is a major contributor to metabolic disease risk, but there is controversy as to whether increased incidences of diseases such as non-alcoholic fatty liver disease arise from consumption of saturated fats or free sugars. Here, we investigate whether a sub-set of triacylglycerols (TAGs) were associated with hepatic steatosis and whether they arise from de novo lipogenesis (DNL) from the consumption of carbohydrates.

Results

We conduct direct infusion mass spectrometry of lipids in plasma to study the association between specific TAGs and hepatic steatosis assessed by ultrasound and fatty liver index in volunteers from the UK-based Fenland Study and evaluate clustering of TAGs in the National Survey of Health and Development UK cohort. We find that TAGs containing saturated and monounsaturated fatty acids with 16–18 carbons are specifically associated with hepatic steatosis. These TAGs are additionally associated with higher consumption of carbohydrate and saturated fat, hepatic steatosis, and variations in the gene for protein phosphatase 1, regulatory subunit 3b (PPP1R3B), which in part regulates glycogen synthesis. DNL is measured in hyperphagic ob/ob mice, mice on a western diet (high in fat and free sugar) and in healthy humans using stable isotope techniques following high carbohydrate meals, demonstrating the rate of DNL correlates with increased synthesis of this cluster of TAGs. Furthermore, these TAGs are increased in plasma from patients with biopsy-confirmed steatosis.

Conclusion

A subset of TAGs is associated with hepatic steatosis, even when correcting for common confounding factors. We suggest that hepatic steatosis risk in western populations is in part driven by increased DNL following carbohydrate rich meals in addition to the consumption of saturated fat.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1439-8) contains supplementary material, which is available to authorized users.

High Glucose-Induced Cardiomyocyte Death May Be Linked to Unbalanced Branched-Chain Amino Acids and Energy Metabolism

High glucose-induced cardiomyocyte death is a common symptom in advanced-stage diabetic patients, while its metabolic mechanism is still poorly understood. The aim of this study was to explore metabolic changes in high glucose-induced cardiomyocytes and the heart of streptozotocin-induced diabetic rats by ¹H-NMR-based metabolomics. We found that high glucose can promote cardiomyocyte death both in vitro and in vivo studies. Metabolomic results show that several metabolites exhibited inconsistent variations in vitro and in vivo. However, we also identified a series of common metabolic changes, including increases in branched-chain amino acids (BCAAs: leucine, isoleucine and valine) as well as decreases in aspartate and creatine under high glucose condition. Moreover, a reduced energy metabolism could also be a common metabolic characteristic, as indicated by decreases in ATP in vitro as well as AMP, fumarate and succinate in vivo. Therefore, this study reveals that a decrease in energy metabolism and an increase in BCAAs metabolism could be implicated in high glucose-induced cardiomyocyte death.

Novel targets and future strategies for acute cardioprotection: Position Paper of the European Society of Cardiology Working Group on Cellular Biology of the Heart

Ischaemic heart disease and the heart failure that often results, remain the leading causes of death and disability in Europe and worldwide. As such, in order to prevent heart failure and improve clinical outcomes in patients presenting with an acute ST-segment elevation myocardial infarction and patients undergoing coronary artery bypass graft surgery, novel therapies are required to protect the heart against the detrimental effects of acute ischaemia/reperfusion injury (IRI). During the last three decades, a wide variety of ischaemic conditioning strategies and pharmacological treatments have been tested in the clinic-however, their translation from experimental to clinical studies for improving patient outcomes has been both challenging and disappointing. Therefore, in this Position Paper of the European Society of Cardiology Working Group on Cellular Biology of the Heart, we critically analyse the current state of ischaemic conditioning in both the experimental and clinical settings, provide recommendations for improving its translation into the clinical setting, and highlight novel therapeutic targets and new treatment strategies for reducing acute myocardial IRI.

Metabolomics Study for Identification of Potential Biomarkers of Long-term Survival in Kidney Transplantation Recipients

BACKGROUND

The recent progress and appropriate use of immunosuppressive drugs have considerably improved the short-term survival in kidney transplantation recipients (KTRs). The development of new strategies to improve long-term survival outcome after kidney transplantation is also becoming important. Although current diagnosis of allograft dysfunction relies on serum creatinine concentration and biopsy, they are nonspecific indicators of allograft function. Therefore, noninvasive, sensitive, and specific biomarkers for the prediction of long-term survival are needed. The aim of this study was to discover potential biomarkers for long-term survival in KTRs through the use of liquid chromatography-tandem mass spectrometry.

METHODS

We used the metabolic approach to explore the change of metabolites in the serum of KTRs. Twenty-four KTRs with long-term good survival (LGS) and 10 KTRs with chronic antibody-mediated rejection (CAMR) were included in this study. After quantile normalization with chromatographic data, multivariate statistical analysis was performed. We attempted to analyze metabolic profiling with LGS and CAMR groups.

RESULTS

The orthogonal partial least-squares discriminant analysis score plot showed a separation between 2 groups in the principal component. In the corresponding loading plot, 344 metabolites responsible for the separation observed in the score plot were identified (variable influence on projection ≥1.0). We then selected 54 metabolites to compare mass with charge by searching a web database, and 11 compounds were identified.

CONCLUSIONS

We found metabolites in serum that differ in LGS and CAMR groups. Further studies are needed to figure out potential metabolomic biomarkers to predict long-term survival in KTRs.

Comprehensive Metabolomic Profiling and Incident Cardiovascular Disease: A Systematic Review

BACKGROUND

Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD).

METHODS AND RESULTS

We searched MEDLINE and EMBASE from inception to January 2016. Studies were eligible if they pertained to adult humans; followed an agnostic and/or comprehensive approach; used serum or plasma (not urine or other biospecimens); conducted metabolite profiling at baseline in the context of examining prospective disease; and included myocardial infarction, stroke, and/or CVD death in the CVD outcome definition. We identified 12 original articles (9 cohort and 3 nested case-control studies); participant numbers ranged from 67 to 7256. Mass spectrometry was the predominant analytical method. The number and chemical diversity of metabolites were very heterogeneous, ranging from 31 to >10 000 features. Four studies used untargeted profiling. Different types of metabolites were associated with CVD risk: acylcarnitines, dicarboxylacylcarnitines, and several amino acids and lipid classes. Only tiny improvements in CVD prediction beyond traditional risk factors were observed using these metabolites (C index improvement ranged from 0.006 to 0.05).

CONCLUSIONS

There are a limited number of longitudinal studies assessing associations between comprehensive metabolomic profiles and CVD risk. Quantitatively synthesizing the literature is challenging because of the widely varying analytical tools and the diversity of methodological and statistical approaches. Although some results are promising, more research is needed, notably standardization of metabolomic techniques and statistical approaches. Replication and combinations of novel and holistic methodological approaches would move the field toward the realization of its promise.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling

¹H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum ¹H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

Exploring the human microbiome from multiple perspectives: factors altering its composition and function

Our microbiota presents peculiarities and characteristics that may be altered by multiple factors. The degree and consequences of these alterations depend on the nature, strength and duration of the perturbations as well as the structure and stability of each microbiota. The aim of this review is to sketch a very broad picture of the factors commonly influencing different body sites, and which have been associated with alterations in the human microbiota in terms of composition and function. To do so, first, a graphical representation of bacterial, fungal and archaeal genera reveals possible associations among genera affected by different factors. Then, the revision of sequence-based predictions provides associations with functions that become part of the active metabolism. Finally, examination of microbial metabolite contents and fluxes reveals whether metabolic alterations are a reflection of the differences observed at the level of population structure, and in the last step, link microorganisms to functions under perturbations that differ in nature and aetiology. The utilisation of complementary technologies and methods, with a special focus on metabolomics research, is thoroughly discussed to obtain a global picture of microbiota composition and microbiome function and to convey the urgent need for the standardisation of protocols.

Changes in the mitochondrial function and in the efficiency of energy transfer pathways during cardiomyocyte aging

The role of mitochondria in alterations that take place in the muscle cell during healthy aging is a matter of debate during recent years. Most of the studies in bioenergetics have a focus on the model of isolated mitochondria, while changes in the crosstalk between working myofibrils and mitochondria in senescent cardiomyocytes have been less studied. The aim of our research was to investigate the modifications in the highly regulated ATP production and energy transfer systems in heart cells in old rat cardiomyocytes. The results of our work demonstrated alterations in the diffusion restrictions of energy metabolites, manifested by changes in the apparent Michaelis-Menten constant of mitochondria to exogenous ADP. The creatine kinase (CK) phosphotransfer pathway efficiency declines significantly in senescence. The ability of creatine to stimulate OXPHOS as well as to increase the affinity of mitochondria for ADP is falling and the most critical decline is already in the 1-year group (middle-age model in rats). Also, a moderate decrease in the adenylate kinase phosphotransfer system was detected. The importance of glycolysis increases in senescence, while the hexokinase activity does not change during healthy aging. The main result of our study is that the decline in the heart muscle performance is not caused by the changes in the respiratory chain complexes activity but mainly by the decrease in the energy transfer efficiency, especially by the CK pathway.

Plasma Metabolic Profile Determination in Young ST-segment Elevation Myocardial Infarction Patients with Ischemia and Reperfusion: Ultra-performance Liquid Chromatography and Mass Spectrometry for Pathway Analysis

Background:

This study was to establish a disease differentiation model for ST-segment elevation myocardial infarction (STEMI) youth patients experiencing ischemia and reperfusion via ultra-performance liquid chromatography and mass spectrometry (UPLC/MS) platform, which searches for closely related characteristic metabolites and metabolic pathways to evaluate their predictive value in the prognosis after discharge.

Methods:

Forty-seven consecutive STEMI patients (23 patients under 45 years of age, referred to here as “youth,” and 24 “elderly” patients) and 48 healthy control group members (24 youth, 24 elderly) were registered prospectively. The youth patients were required to provide a second blood draw during a follow-up visit one year after morbidity (n = 22, one lost). Characteristic metabolites and relative metabolic pathways were screened via UPLC/MS platform base on the Kyoto encyclopedia of genes and genomes (KEGG) and Human Metabolome Database. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of characteristic metabolites in the prognosis after discharge.

Results:

We successfully established an orthogonal partial least squares discriminated analysis model (R₂X = 71.2%, R₂Y = 79.6%, and Q₂ = 55.9%) and screened out 24 ions; the sphingolipid metabolism pathway showed the most drastic change. The ROC curve analysis showed that ceramide [Cer(d18:0/16:0), Cer(t18:0/12:0)] and sphinganine in the sphingolipid pathway have high sensitivity and specificity on the prognosis related to major adverse cardiovascular events after youth patients were discharged. The area under curve (AUC) was 0.671, 0.750, and 0.711, respectively. A follow-up validation one year after morbidity showed corresponding AUC of 0.778, 0.833, and 0.806.

Conclusions:

By analyzing the plasma metabolism of myocardial infarction patients, we successfully established a model that can distinguish two different factors simultaneously: pathological conditions and age. Sphingolipid metabolism is the top most altered pathway in young STEMI patients and as such may represent a valuable prognostic factor and potential therapeutic target.

Urine Metabolomics in Hypertension Research

Functional genomics requires an understanding of the complete network of changes within an organism by extensive measurements of moieties from mRNA, proteins, and metabolites. Metabolomics utilizes analytic chemistry tools to profile the complete spectrum of metabolites found in a tissue, cells, or biofluids using a wide range of tools from infrared spectroscopy, fluorescence spectroscopy, NMR spectroscopy, and mass spectrometry. In this protocol, we outline a procedure for performing metabolomic analysis of urine samples using liquid chromatography-mass spectrometry (LC-MS). We outline the advantages of using this approach and summarize some of the early promising studies in cardiovascular diseases using this approach.

Blood triacylglycerols: a lipidomic window on diet and disease

Although the measurement of triacylglycerols (TAGs) by clinical chemistry has been used in the diagnosis of a range of metabolic diseases, such approaches ignore the different species of TAGs that contribute to the total concentration. With the advent of LC and direct infusion forms of MS it is now possible to profile the individual TAGs in blood plasma or tissue extracts. This mini review surveys the information that is obtainable from the lipidomic profiling of TAGs in following metabolic diseases such as type 2 diabetes (T2DM), cardiovascular disease (CVD) and non-alcoholic fatty liver disease, as well as the development of insulin resistance and obesity.

Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems

Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as "statistically significant" in the study. Such metabolic "dark matter" means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function.

Pomegranate-Derived Polyphenols Reduce Reactive Oxygen Species Production via SIRT3-Mediated SOD2 Activation

Pomegranate-derived polyphenols are expected to prevent life-style related diseases. In this study, we evaluated the ability of 8 pomegranate-derived polyphenols, along with other polyphenols, to augment SIRT3, a mammalian SIR2 homolog localized in mitochondria. We established a system for screening foods/food ingredients that augment the SIRT3 promoter in Caco-2 cells and identified 3 SIRT3-augmenting pomegranate-derived polyphenols (eucalbanin B, pomegraniin A, and eucarpanin T₁). Among them, pomegraniin A activated superoxide dismutase 2 (SOD2) through SIRT3-mediated deacetylation, thereby reducing intracellular reactive oxygen species. The other SIRT3-augmenting polyphenols tested also activated SOD2, suggesting antioxidant activity. Our findings clarify the underlying mechanisms involved in the antioxidant activity of pomegraniin A.

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future

Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact.

Cardiac Metabolism in Perspective

The heart is a biological pump that converts chemical to mechanical energy. This process of energy conversion is highly regulated to the extent that energy substrate metabolism matches energy use for contraction on a beat-to-beat basis. The biochemistry of cardiac metabolism includes the biochemistry of energy transfer, metabolic regulation, and transcriptional, translational as well as posttranslational control of enzymatic activities. Pathways of energy substrate metabolism in the heart are complex and dynamic, but all of them conform to the First Law of Thermodynamics. The perspectives expand on the overall idea that cardiac metabolism is inextricably linked to both physiology and molecular biology of the heart. The article ends with an outlook on emerging concepts of cardiac metabolism based on new molecular models and new analytical tools. © 2016 American Physiological Society. Compr Physiol 6:1675-1699, 2016.

Proteomics and metabolomics in biomarker discovery for cardiovascular diseases: progress and potential

INTRODUCTION

The process of discovering novel biomarkers and potential therapeutic targets may be shortened using proteomic and metabolomic approaches.

AREAS COVERED

Several complementary strategies, each one presenting different advantages and limitations, may be used with these novel approaches. In vitro studies show how cells involved in cardiovascular disease react, although the phenotype of cultured cells differs to that occurring in vivo. Tissue analysis either in human specimens or animal models may show the proteins that are expressed in the pathological process, although the presence of structural proteins may be confounding. To identify circulating biomarkers, analyzing the secretome of cultured atherosclerotic tissue, analysis of blood cells and/or plasma may be more straightforward. However, in the latter approach, high-abundant proteins may mask small molecules that could be potential biomarkers. The study of sub-proteomes such as high-density lipoproteins may be useful to circumvent this limitation. Regarding metabolomics, most studies have been performed in small populations, and we need to perform studies in large populations in order to discover robust biomarkers. Expert commentary: It is necessary to involve the clinicians in these areas to improve the design of clinical studies, including larger populations, in order to obtain consistent novel biomarkers.

Urinary metabolic profile predicts high-fat diet sensitivity in the C57Bl6/J mouse

To prevent the development of adiposity-associated metabolic diseases, early biomarkers are needed. Such markers could bring insight to understand the complexity of susceptibility to obesity. Urine and plasma metabolomics fingerprints have been successfully associated with metabolic dysfunctions. Fat resistance (FR) was found to be associated with higher urinary levels of acylglycines and leucine. However, no differences were observed before the diet switch. In this context, we aimed at characterizing metabolic signatures predictive of resistance or sensitivity to fat in the C57Bl6/J mouse model. Urinary metabolic profiles of FR (n=15) and fat sensitivity (FS) mice (n=14) were performed on liquid chromatography-mass spectrometry. Urinary and plasma metabolic profiles were first collected at baseline (during low-fat diet), then after 10weeks of high-fat (HF) feeding. Mice were sorted a posteriori into FS and FR based on their final adiposity. After HF feeding for 10weeks, FS mice tended to have lower plasma levels of β-hydroxybutyrate than FR ones. Urinary metabolic profiles showed that baseline levels of octanoylglycine, leucine and valine were significantly lower in FS mice. Moreover, expressions in the adipose tissue of Baat and Glyat mRNA were lower in FS than in FR mice. In muscle, mRNA encoding CaD and UbE2b tended to be lower in FS mice than in FR mice (P=.056 and P=.071, respectively). The data show that lower levels of urinary octanoylglycine, leucine and valine are potential predictive biomarkers of FS and could be related to a lower stimulation in adipose acyl-coenzyme A conjugation to glycine and to muscle protein breakdown.

Assessing Cardiac Metabolism: A Scientific Statement From the American Heart Association

In a complex system of interrelated reactions, the heart converts chemical energy to mechanical energy. Energy transfer is achieved through coordinated activation of enzymes, ion channels, and contractile elements, as well as structural and membrane proteins. The heart's needs for energy are difficult to overestimate. At a time when the cardiovascular research community is discovering a plethora of new molecular methods to assess cardiac metabolism, the methods remain scattered in the literature. The present statement on "Assessing Cardiac Metabolism" seeks to provide a collective and curated resource on methods and models used to investigate established and emerging aspects of cardiac metabolism. Some of those methods are refinements of classic biochemical tools, whereas most others are recent additions from the powerful tools of molecular biology. The aim of this statement is to be useful to many and to do justice to a dynamic field of great complexity.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

A targeted metabolomics assay for cardiac metabolism and demonstration using a mouse model of dilated cardiomyopathy

Metabolomics can be performed either as an 'open profiling' tool where the aim is to measure, usually in a semi-quantitative manner, as many metabolites as possible or perform 'closed' or 'targeted' analyses where instead a pre-defined set of metabolites are measured. Targeted methods can be designed to be more sensitive and quantitative and so are particularly appropriate to systems biology for quantitative models of systems or when metabolomics is performed in a hypothesis driven manner to test whether a particular pathway is perturbed. We describe a targeted metabolomics assay that quantifies a broad range of over 130 metabolites relevant to cardiac metabolism including the pathways of the citric acid cycle, fatty acid oxidation, glycolysis, the pentose phosphate pathway, amino acid metabolism, the urea cycle, nucleotides and reactive oxygen species using tandem mass spectrometry to produce quantitative, sensitive and robust data. This assay is illustrated by profiling cardiac metabolism in a lamin A/C (Lmna) mouse model of dilated cardiomyopathy (DCM). The model of DCM was characterised by increases in concentrations of proline and methyl-histidine suggestive of increased myofibrillar and collagen degradation, as well as decreases in a number of citric acid cycle intermediates and carnitine derivatives indicating reduced energy metabolism in the dilated heart. These assays could be used for any other cardiac or cardiovascular disease in that they cover central core metabolism and key pathways involved in cardiac metabolism, and may provide a general start for many mammalian systems.

Magnetic Resonance Spectroscopy: Principles and Techniques: Lessons for Clinicians

Magnetic resonance spectroscopy (MRS) provides a non-invasive 'window' on biochemical processes within the body. Its use is no longer restricted to the field of research, with applications in clinical practice increasingly common. MRS can be conducted at high magnetic field strengths (typically 11-14 T) on body fluids, cell extracts and tissue samples, with new developments in whole-body magnetic resonance imaging (MRI) allowing clinical MRS at the end of a standard MRI examination, obtaining functional information in addition to anatomical information. We discuss the background physics the busy clinician needs to know before considering using the technique as an investigative tool. Some potential applications of hepatic and cerebral MRS in chronic liver disease are also discussed.

Metabonomics and systems biology

Systems biology represents an integrative research strategy that studies the interactions between DNA, mRNA, protein, and metabolite level in an organism, thereby including the interactions with the physical environment and other organisms. The application of metabonomics, or the quantitative study of metabolites in biological systems, in systems biology is currently an emerging area of research, which can contribute to the discovery of (disease) signatures, drug targeting and design, and the further elucidation of basic and more complex biochemical principles. This chapter covers the contribution of metabonomics in advancing our understanding in systems biology.

NMR-Based Metabolomics Separates the Distinct Stages of Disease in a Chronic Relapsing Model of Multiple Sclerosis

Relapsing experimental allergic encephalomyelitis (Cr-EAE) is commonly used to explore the pathogenesis and efficacy of new therapies for MS, but it is unclear whether the metabolome of Cr-EAE is comparable to human multiple sclerosis (MS). For MS, the diagnosis and staging can be achieved by metabolomics on blood using a combination of magnetic resonance spectroscopy and partial least squares discriminant analysis (PLS-DA). Here, we sought to discover whether this approach could be used to differentiate between sequential disease states in Cr-EAE and whether the same metabolites would be discriminatory. Urine and plasma samples were obtained at different time-points from a clinically relevant model of MS. Using PLS-DA modelling for the urine samples furnished some predictive models, but could not discriminate between all disease states. However, PLS-DA modelling of the plasma samples was able to distinguish between animals with clinically silent disease (day 10, 28) and animals with active disease (day 14, 38). We were also able to distinguish Cr-EAE mice from naive mice at all-time points and control mice, treated with complete Freund's adjuvant alone, at day 14 and 38. Key metabolites that underpin these models included fatty acids, glucose and taurine. Two of these metabolites, fatty acids and glucose, were also key metabolites in separating relapsing-remitting MS from secondary-progressive MS in the human study. These results demonstrate the sensitivity of this metabolomics approach for distinguishing between different disease states. Furthermore, some, but not all, of the changes in metabolites were conserved in humans and the mouse model, which could be useful for future drug development.

Comprehensive Metabolic Profiling of Age-Related Mitochondrial Dysfunction in the High-Fat-Fed ob/ob Mouse Heart

The ectopic deposition of fat is thought to lead to lipotoxicity and has been associated with mitochondrial dysfunction and diabetic cardiomyopathy. We have measured mitochondrial respiratory capacities in the hearts of ob/ob and wild-type mice on either a regular chow (RCD) or high-fat (HFD) diet across four age groups to investigate the impact of diet and age on mitochondrial function alongside a comprehensive strategy for metabolic profiling of the tissue. Myocardial mitochondrial dysfunction was only evident in ob/ob mice on RCD at 14 months, but it was detectable at 3 months on the HFD. Liquid chromatography-mass spectrometry (LC-MS) was used to study the profiles of acylcarnitines and the accumulation of triglycerides, but neither class of lipid was associated with mitochondrial dysfunction. However, a targeted LC-MS/MS analysis of markers of oxidative stress demonstrated increases in GSSG/GSH and 8-oxoguanine, in addition to the accumulation of diacylglycerols, which are lipid species linked to lipotoxicity. Our results demonstrate that myocardial mitochondria in ob/ob mice on RCD maintained a similar respiratory capacity to that of wild type until a late stage in aging. However, on a HFD, unlike wild-type mice, ob/ob mice failed to increase mitochondrial respiration, which may be associated with a complex I defect following increased oxidative damage.

Overview of mass spectrometry-based metabolomics: opportunities and challenges

The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.

Entometabolomics: applications of modern analytical techniques to insect studies

Metabolomic analyses can reveal associations between an organism's metabolome and further aspects of its phenotypic state, an attractive prospect for many life-sciences researchers. The metabolomic approach has been employed in some, but not many, insect study systems, starting in 1990 with the evaluation of the metabolic effects of parasitism on moth larvae. Metabolomics has now been applied to a variety of aspects of insect biology, including behaviour, infection, temperature stress responses, CO 2 sedation, and bacteria-insect symbiosis. From a technical and reporting standpoint, these studies have adopted a range of approaches utilising established experimental methodologies. Here, we review current literature and evaluate the metabolomic approaches typically utilised by entomologists. We suggest that improvements can be made in several areas, including sampling procedures, the reduction in sampling and equipment variation, the use of sample extracts, statistical analyses, confirmation, and metabolite identification. Overall, it is clear that metabolomics can identify correlations between phenotypic states and underlying cellular metabolism that previous, more targeted, approaches are incapable of measuring. The unique combination of untargeted global analyses with high-resolution quantitative analyses results in a tool with great potential for future entomological investigations.

Cardiac energy dependence on glucose increases metabolites related to glutathione and activates metabolic genes controlled by mechanistic target of rapamycin

Background

Long chain acyl‐CoA synthetases (ACSL) catalyze long‐chain fatty acids (FA) conversion to acyl‐CoAs. Temporal ACSL1 inactivation in mouse hearts (Acsl1^H−/−) impaired FA oxidation and dramatically increased glucose uptake, glucose oxidation, and mTOR activation, resulting in cardiac hypertrophy. We used unbiased metabolomics and gene expression analyses to elucidate the cardiac cellular response to increased glucose use in a genetic model of inactivated FA oxidation.

Methods and Results

Metabolomics analysis identified 60 metabolites altered in Acsl1^H−/− hearts, including 6 related to glucose metabolism and 11 to cysteine and glutathione pathways. Concurrently, global cardiac transcriptional analysis revealed differential expression of 568 genes in Acsl1^H−/− hearts, a subset of which we hypothesized were targets of mTOR; subsequently, we measured the transcriptional response of several genes after chronic mTOR inhibition via rapamycin treatment during the period in which cardiac hypertrophy develops. Hearts from Acsl1^H−/− mice increased expression of several Hif1α‐responsive glycolytic genes regulated by mTOR; additionally, expression of Scl7a5, Gsta1/2, Gdf15, and amino acid‐responsive genes, Fgf21, Asns, Trib3, Mthfd2, were strikingly increased by mTOR activation.

Conclusions

The switch from FA to glucose use causes mTOR‐dependent alterations in cardiac metabolism. We identified cardiac mTOR‐regulated genes not previously identified in other cellular models, suggesting heart‐specific mTOR signaling. Increased glucose use also changed glutathione‐related pathways and compensation by mTOR. The hypertrophy, oxidative stress, and metabolic changes that occur within the heart when glucose supplants FA as a major energy source suggest that substrate switching to glucose is not entirely benign.

Metabonomic profiling of bladder cancer

Early diagnosis and life-long surveillance are clinically important to improve the long-term survival of bladder cancer patients. Currently, a noninvasive biomarker that is as sensitive and specific as cystoscopy in detecting bladder tumors is lacking. Metabonomics is a complementary approach for identifying perturbed metabolic pathways in bladder cancer. Significant progress has been made using modern metabonomic techniques to characterize and distinguish bladder cancer patients from control subjects, identify marker metabolites, and shed insights on the disease biology and potential therapeutic targets. With its rapid development, metabonomics has the potential to impact the clinical management of bladder cancer patients in the future by revolutionizing the diagnosis and life-long surveillance strategies and stratifying patients for diagnostic, surgical, and therapeutic clinical trials. An introduction to metabonomics, typical metabonomic workflow, and critical evaluation of metabonomic investigations in identifying biomarkers for the diagnosis of bladder cancer are presented.

UHPLC-LTQ-Orbitrap MS combined with spike-in method for plasma metabonomics analysis of acute myocardial ischemia rats and pretreatment effect of Danqi Tongmai tablet

Undoubtedly, metabonomics can reveal the comprehensive efficacies of traditional Chinese medicine (TCM) formulae and its complex mechanism at the molecular biological level. In this study, an attempt was made to address the pretreatment effect of a TCM formula. In this case, as a critical point, we should first know how to really reflect the various endogenous metabolites in a disease status before a TCM formula is employed in a therapeutic procedure. Here, we explored an approach that combined high resolution LTQ-Orbitrap mass spectrometry with a spike-in method to characterize endogenous metabolites in acute myocardial ischemia (AMI) rats. As a result, 19 potential biomarkers in rat plasma were identified and 10 related disturbed pathways were perturbed in the early stages of AMI development. Subsequently, the metabonomics method was applied to investigate the pretreatment effect of the TCM formula named the Danqi Tongmai tablet (DQTM). The results revealed that the DQTM pretreatment could reduce the AMI injury and partially regulate the perturbed TCA cycle and amino and nucleotide metabolism, which were presumable related to energy metabolism and myocardial cells apoptosis/necrosis. In conclusion, UHPLC-LTQ-Orbitrap MS combined with a spike-in method were successfully applied to the metabonomics analysis of DQTM, which demonstrated that not only a comprehensive metabolic profile in the early stages of AMI development was achieved, but also that the underlying holistic efficacies were assessed and it was helpful to understand the possible mechanism of pretreatment with DQTM.