Metabolomics as a tool for cardiac research

Metabolomic correlates of coronary atherosclerosis, cardiovascular risk, both or neither. Results of the 2 × 2 phenotypic CAPIRE study

BACKGROUND

Traditional cardiovascular risk factors (RFs) and coronary artery disease (CAD) do not always run parallel. We investigated functional-metabolic correlations of CAD, RFs, or neither in the CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation) 2 × 2 phenotypic observational study.

METHODS

Two hundred and fortyone subjects were included based on RF burden, presence/absence of CAD (assessed by computed tomography angiography), age and sex. Participants displayed one of four phenotypes: CAD with ≥3 RFs, no-CAD with ≥3 RFs, CAD with ≤1 RF and no-CAD with ≤1 RF. Metabolites were identified by gas chromatography-mass spectrometry and pathways by metabolite set enrichment analysis.

RESULTS

Characteristic patterns and specific pathways emerged for each phenotypic group: amino sugars for CAD/high-RF; urea cycle for no-CAD/high-RF; glutathione for CAD/low-RF; glycine and serine for no-CAD/low-RF. Presence of CAD correlated with ammonia recycling; absence of CAD with the transfer of acetyl groups into mitochondria; high-risk profile with alanine metabolism (all p < 0.05). The comparative case-control analyses showed a statistically significant difference for the two pathways of phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism in the CAD/Low-RF vs NoCAD/Low-RF comparison.

CONCLUSIONS

The present 2 × 2 observational study identified specific metabolic pathways for each of the four phenotypes, providing novel functional insights, particularly on CAD with low RF profiles and on the absence of CAD despite high-risk factor profiles.

Detecting early myocardial ischemia in rat heart by MALDI imaging mass spectrometry

Diagnostics of myocardial infarction in human post-mortem hearts can be achieved only if ischemia persisted for at least 6–12 h when certain morphological changes appear in myocardium. The initial 4 h of ischemia is difficult to diagnose due to lack of a standardized method. Developing a panel of molecular tissue markers is a promising approach and can be accelerated by characterization of molecular changes. This study is the first untargeted metabolomic profiling of ischemic myocardium during the initial 4 h directly from tissue section. Ischemic hearts from an ex-vivo Langendorff model were analysed using matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) at 15 min, 30 min, 1 h, 2 h, and 4 h. Region-specific molecular changes were identified even in absence of evident histological lesions and were segregated by unsupervised cluster analysis. Significantly differentially expressed features were detected by multivariate analysis starting at 15 min while their number increased with prolonged ischemia. The biggest significant increase at 15 min was observed for m/z 682.1294 (likely corresponding to S-NADHX—a damage product of nicotinamide adenine dinucleotide (NADH)). Based on the previously reported role of NAD⁺/NADH ratio in regulating localization of the sodium channel (Na_v1.5) at the plasma membrane, Na_v1.5 was evaluated by immunofluorescence. As expected, a fainter signal was observed at the plasma membrane in the predicted ischemic region starting 30 min of ischemia and the change became the most pronounced by 4 h. Metabolomic changes occur early during ischemia, can assist in identifying markers for post-mortem diagnostics and improve understanding of molecular mechanisms.

Characteristics of Blood Metabolic Profile in Coronary Heart Disease, Dilated Cardiomyopathy and Valvular Heart Disease Induced Heart Failure

Purpose: Metabolic impairment is one key contributor to heart failure (HF) pathogenesis and progression. The major causes of HF, coronary heart disease (CHD), dilated cardiomyopathy (DCM), and valvular heart disease (VHD) remains poorly characterized in patients with HF from the view of metabolic profile. We sought to determine metabolic differences in CHD-, VHD-, and DCM-induced HF patients and identify significantly altered metabolites and their correlations.

Procedure: In this study, a total of 96 HF cases and 97 controls were enrolled. The contents of 23 amino acids and 26 carnitines in fasting plasma were measured by a targeted liquid chromatography and mass spectrometry (LC-MS) approach.

Results: Nine metabolites (Histidine, Arginine, Citrulline, Glutamine, Valine, hydroxyhexadecenyl-carnitine, acylcarnitine C22, hydroxytetradecanoyl-carnitine, and carnitine) were found to be related with the occurrence of HF. Arginine, Glutamine and hydroxytetradecanoyl-carnitine could effectively distinguish CHD and DCM patients, and hydroxytetradecanoyl-carnitine and aspartic acid were able to classify CHD and VHD cohorts.

Conclusion: This study indicated that circulating amino acids and long-chain acylcarnitine levels were closely associated with progression of heart failure. Monitoring these metabolic alterations by LC-MS may help the differentiation of CHD, VHD, and DCM in the early stage, and provide new diagnostics targets or therapeutic interventions.

NMR-Based Metabolomics

Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.

The potential of using itaconate as treatment for inflammation-related heart diseases

Intracellular metabolites can cause critical changes in biological functions. Itaconate is perhaps the most fascinating substance in macrophages. Lipopolysaccharide can activate aconitate decarboxylase 1 and induces the generation of itaconate from the tricarboxylic acid cycle by decarboxylation of cis-aconitate. It has been reported that itaconate has beneficial effects on inflammation and oxidation. The mechanisms involved in these effects include the suppression of succinate dehydrogenase, the activation of nuclear factor E2-related factor 2 by alkylation of Kelch-like ECH-associated protein 1, suppression of aerobic glycolysis through regulation of glyceraldehyde-3-phosphate dehydrogenase and fructose-bisphosphate aldolase A, and suppression of IκBζ translation through activating transcription factor 3 activation. All of these findings elucidated the possible therapeutic implications of itaconate in inflammation-related diseases. In this review, we highlight that itaconate is a crucial molecule of the immunomodulatory response in macrophages and can regulate between immune response and cardiovascular metabolism. Furthermore, these discoveries suggest that itaconate is a very novel therapeutic molecule for the treatment of inflammation-related heart diseases.

Plasma Metabolomic Profiles Differentiate Patients With Dilated Cardiomyopathy and Ischemic Cardiomyopathy

Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are common causes of heart failure (HF). Though they share similar clinical characteristics, their differential effects on cardiovascular metabolomics have yet to be elucidated. In this study, we applied a comprehensive metabolomics platform to plasma samples of HF patients with different etiology (38 patients with DCM and 18 patients with ICM) and 20 healthy controls. Significant differences in metabolomics profiling were shown among two cardiomyopathy groups and healthy controls. Two hundred thirty three dysregulated metabolites were identified between DCM vs. healthy controls, and 204 dysregulated metabolites between ICM patients and healthy controls. They have 140 metabolites in common, with fold-changes in the same direction in both groups. Pathway analysis found the commonalities of HF pathways as well as disease-specific metabolic signatures. In addition, we found that a combination panel of 6 metabolites including 1-pyrroline-2-carboxylate, norvaline, lysophosphatidylinositol (16:0/0:0), phosphatidylglycerol (6:0/8:0), fatty acid esters of hydroxy fatty acid (24:1), and phosphatidylcholine (18:0/18:3) may have the potential to differentiate patients with DCM and ICM.

Plasma metabolomics supports the use of long-duration cardiac arrest rodent model to study human disease by demonstrating similar metabolic alterations

Cardiac arrest (CA) is a leading cause of death and there is a necessity for animal models that accurately represent human injury severity. We evaluated a rat model of severe CA injury by comparing plasma metabolic alterations to human patients. Plasma was obtained from adult human control and CA patients post-resuscitation, and from male Sprague–Dawley rats at baseline and after 20 min CA followed by 30 min cardiopulmonary bypass resuscitation. An untargeted metabolomics evaluation using UPLC-QTOF-MS/MS was performed for plasma metabolome comparison. Here we show the metabolic commonality between humans and our severe injury rat model, highlighting significant metabolic dysfunction as seen by similar alterations in (1) TCA cycle metabolites, (2) tryptophan and kynurenic acid metabolites, and (3) acylcarnitine, fatty acid, and phospholipid metabolites. With substantial interspecies metabolic similarity in post-resuscitation plasma, our long duration CA rat model metabolically replicates human disease and is a suitable model for translational CA research.

Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

2,2',4,4'-tetrabromodiphenyl ether (BDE-47) induces wide metabolic changes including attenuated mitochondrial function and enhanced glycolysis in PC12 cells

Polybrominated diphenyl ethers (PBDEs) are extensively used as brominated flame retardants in various factory products. As environmental pollutants, the adverse effects of PBDEs on human health have been receiving considerable attention. However, the precise fundamental mechanisms of toxicity induced by PBDEs are still not fully understood. In this study, the mechanism of cytotoxicity induced by 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) was investigated by combining Seahorse XFp analysis and mass spectrometry-based metabolomics and flux approaches in PC12 cells, one of the most widely used neuron-like cell lines for investigating cytotoxic effects. The Seahorse results suggest that BDE-47 significantly attenuated mitochondrial respiration and enhanced glycolysis in PC12 cells. Additionally, metabolomics results revealed the reduction of TCA metabolites such as citrate, succinate, aconitate, malate, fumarate, and glutamate after BDE-47 exposure. Metabolic flux analysis showed that BDE-47 exposure reduced the oxidative metabolic capacity of mitochondria in PC12 cells. Furthermore, various altered metabolites were found in multiple metabolic pathways, especially in glycine-serine-threonine metabolism and glutathione metabolism. A total of 17 metabolic features were determined in order to distinguish potentially disturbed metabolite markers of BDE-47 exposure. Our findings provide possible biomarkers of cytotoxic effects induced by BDE-47 exposure, and elicit a deeper understanding of the intramolecular mechanisms that could be used in further studies to validate the potential neurotoxicity of PBDEs in vivo. Based on our results, therapeutic approaches targeting mitochondrial function and the glycolysis pathway may be a promising direction against PBDE exposure.

The synergistic mechanism of total saponins and flavonoids in Notoginseng-Safflower pair against myocardial ischemia uncovered by an integrated metabolomics strategy

The Notoginseng-Safflower pair composed of Panax notoginseng (Burk.) F. H. Chen and Carthamus tinctorius L. has remarkable clinical efficacy for preventing and treating cardiovascular diseases in China. Notoginseng total saponins (NS) and Safflower total flavonoids (SF) are the major effective ingredients in Notoginseng and Safflower, respectively. Though our previous study showed that the combination of NS and SF (NS-SF) exhibits significant cardioprotective effects for myocardial ischemia (MI), there might be difference in their action mechanisms. However, the anti-MI characteristics of individual NS and SF remains unclear. Herein, an integrated metabolomics strategy coupled with multiple biological methods were employed to investigate the cardioprotective effects of NS and SF alone or in combination against isoproterenol (ISO)-induced MI and to further explore the synergistic relationship between NS and SF. Our results demonstrated that pretreatments with NS, SF, and NS-SF all showed cardioprotective effects against MI injury and NS-SF exhibited to be the best. Interestingly, the results demonstrated that NS and SF exhibited differentiated metabolic targets and mediators in the glycerophospholipid metabolism. Furthermore, administration of NS alone exhibited greater effects on reversing the elevated the proinflammatory metabolites and mediators in MI rats compared to SF alone. However, individual SF showed greater amelioration of MI-disturbed antioxidant and prooxidative metabolites and better inhibition of the oxidative stress than NS alone. Collectively, our study demonstrated that the capability of NS-SF to regulate both metabolic targets of NS and SF might be the basis of NS-SF to produce a cooperative effect greater than their individual effects that enhance the anti-MI efficacy and provided valuable information for the clinical application of Notoginseng-Safflower pair.

The Potential of Metabolomics in the Diagnosis of Thyroid Cancer

Thyroid cancer is the most common endocrine system malignancy. However, there is still a lack of reliable and specific markers for the detection and staging of this disease. Fine needle aspiration biopsy is the current gold standard for diagnosis of thyroid cancer, but drawbacks to this technique include indeterminate results or an inability to discriminate different carcinomas, thereby requiring additional surgical procedures to obtain a final diagnosis. It is, therefore, necessary to seek more reliable markers to complement and improve current methods. "Omics" approaches have gained much attention in the last decade in the field of biomarker discovery for diagnostic and prognostic characterisation of various pathophysiological conditions. Metabolomics, in particular, has the potential to identify molecular markers of thyroid cancer and identify novel metabolic profiles of the disease, which can, in turn, help in the classification of pathological conditions and lead to a more personalised therapy, assisting in the diagnosis and in the prediction of cancer behaviour. This review considers the current results in thyroid cancer biomarker research with a focus on metabolomics.

Potential of food intake biomarkers in nutrition research

The influence of dietary habits on health/disease is well-established. Accurate dietary assessment is essential to understand metabolic pathways/processes involved in this relationship. In recent years, biomarker discovery has become a major area of interest for improving dietary assessment. Well-established nutrient intake biomarkers exist; however, there is growing interest in identifying and using biomarkers for more accurate and objective measurements of food intake. Metabolomics has emerged as a key tool used for biomarker discovery, employing techniques such as NMR spectroscopy, or MS. To date, a number of putatively identified biomarkers were discovered for foods including meat, cruciferous vegetables and legumes. However, many of the results are associations only and lack the desired validation including dose-response studies. Food intake biomarkers can be employed to classify individuals into consumers/non-consumers of specific foods, or into dietary patterns. Food intake biomarkers can also play a role in correcting self-reported measurement error, thus improving dietary intake estimates. Quantification of food intake was previously performed for citrus (proline betaine), chicken (guanidoacetate) and grape (tartaric acid) intake. However, this area still requires more investigation and expansion to a range of foods. The present review will assess the current literature of identified specific food intake biomarkers, their validation and the variety of biomarker uses. Addressing the utility of biomarkers and highlighting gaps in this area is important to advance the field in the context of nutrition research.

Identification of a Pharmacological Biomarker for the Bioassay-Based Quality Control of a Thirteen-Component TCM Formula (Lianhua Qingwen) Used in Treating Influenza A Virus (H1N1) Infection

As chemical analysis for quality control (QC) of traditional Chinese medicine (TCM) formula is difficult to guarantee the effectiveness, a bioassay method that combines QC with evaluation of therapeutic effects has been developed to assess the TCM quality. Here, we chose a thirteen-component TCM formula, Lianhua Qingwen capsule (LHQW), as a representative sample, to explore the pivotal biomarkers for a bioassay and to investigate close association between QC and pharmacological actions. Initially, our results showed that chemical fingerprinting could not effectively distinguish batches of LHQW. Pharmacological experiments indicated that LHQW could treat influenza A virus (H1N1) infection in the H1N1 mouse model, as claimed in clinical trials, by improving pathologic alterations and bodyweight loss, and decreasing virus replication, lung lesions and inflammation. Furthermore, by using serum metabolomics analysis, we identified two important metabolites, prostaglandin F_2α and arachidonic acid, and their metabolic pathway, arachidonic acid metabolism, as vital indicators of LHQW in treatment of influenza. Subsequently, macrophages transcriptomics highlighted the prominent role of cyclooxygenase-2 (COX-2) as the major rate-limiting enzyme in the arachidonic acid metabolism pathway. Finally, COX-2 was validated by in vivo gene expression and in vitro enzymatic activity with 43 batches of LHQW as a viable pharmacological biomarker for the establishment of bioassay-based QC. Our study provides systematic methodology in the pharmacological biomarker exploration for establishing the bioassay-based QC of LHQW or other TCM formulas relating to their pharmacological activities and mechanism.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

NMR assignment of the in vivo daphnia magna metabolome

Daphnia (freshwater fleas) are among the most widely used organisms in regulatory aquatic toxicology/ecology, while their recent listing as an NIH model organism is stimulating research for understanding human diseases and processes.

Metabolomic Perspectives in Antiblastic Cardiotoxicity and Cardioprotection

Despite advances in supportive and protective therapy for myocardial function, cardiovascular diseases due to antineoplastic therapy-primarily cardiomyopathy associated with contractile dysfunction-remain a major cause of morbidity and mortality. Because of the limitations associated with current therapies, investigators are searching for alternative strategies that can timely recognise cardiovascular damage-thus permitting a quick therapeutic approach-or prevent the development of the disease. Damage to the heart can result from both traditional chemotherapeutic agents, such as anthracyclines, and new targeted therapies, such as tyrosine kinase inhibitors. In recent years, metabolomics has proved to be a practical tool to highlight fundamental changes in the metabolic state in several pathological conditions. In this article, we present the state-of-the-art technology with regard to the metabolic mechanisms underlying cardiotoxicity and cardioprotection.

Myocardial Energy Stress, Autophagy Induction, and Cardiomyocyte Functional Responses

Significance: Energy stress in the myocardium occurs in a variety of acute and chronic pathophysiological contexts, including ischemia, nutrient deprivation, and diabetic disease settings of substrate disturbance. Although the heart is highly adaptive and flexible in relation to fuel utilization and routes of adenosine-5'-triphosphate (ATP) generation, maladaptations in energy stress situations confer functional deficit. An understanding of the mechanisms that link energy stress to impaired myocardial performance is crucial. Recent Advances: Emerging evidence suggests that, in parallel with regulated enzymatic pathways that control intracellular substrate supply, other processes of "bulk" autophagic macromolecular breakdown may be important in energy stress conditions. Recent findings indicate that cargo-specific autophagic activity may be important in different stress states. In particular, induction of glycophagy, a glycogen-specific autophagy, has been described in acute and chronic energy stress situations. The impact of elevated cardiomyocyte glucose flux relating to glycophagy dysregulation on contractile function is unknown. Critical Issues: Ischemia- and diabetes-related cardiac adverse events comprise the majority of cardiovascular disease morbidity and mortality. Current therapies involve management of systemic comorbidities. Cardiac-specific adjunct treatments targeted to manage myocardial energy stress responses are lacking. Future Directions: New knowledge is required to understand the mechanisms involved in selective recruitment of autophagic responses in the cardiomyocyte energy stress response. In particular, exploration of the links between cell substrate flux, calcium ion (Ca²⁺) flux, and phagosomal cargo flux is required. Strategies to target specific fuel "bulk" management defects in cardiac energy stress states may be of therapeutic value.

Application of Metabolomics to Epidemiological Studies of Atherosclerosis and Cardiovascular Disease

Metabolomics has developed as a powerful tool for investigating the complex pathophysiology underlying atherosclerosis and cardiovascular disease. Many epidemiological studies have applied this technique to accurately and comprehensively assess the effects of environmental factors on health outcomes, which used to be a perpetual challenge. Metabolites are defined as small molecules which are intermediate products of metabolic reactions catalyzed by numerous enzymes occurring within cells. Consequent to both genetic variation and environment, they allow us to explore the gene–environment interactions and to gain a better understanding of multifactorial diseases like cardiovascular disease. This review article highlights the findings of well-known prospective cohort studies around the world that have utilized metabolomics for a wide range of purposes, including biomarker discovery, improving cardiovascular risk prediction and early disease diagnosis, and exploring detailed mechanisms of disease onset and progression. However, technical challenges still exist in applying them clinically. One limitation is due to various analytical platforms that are used based on the judgment of each study; comparative assessments among different platforms need to be conducted in order to correctly interpret and validate each data externally. Secondly, metabolite levels obtained in most high-throughput metabolomics profiling studies are often semiquantitative rather than fully quantitative concentrations, which makes it difficult to compare and combine results among different studies and to determine the levels for practical use. In 2014, the Consortium of Metabolomics Studies was developed, which is expected to take the lead in overcoming these issues.

Nuclear magnetic resonance-based metabolomics and metabolic pathway networks from patient-matched esophageal carcinoma, adjacent noncancerous tissues and urine

BACKGROUND

Several studies have demonstrated a correlation between esophageal cancer (EC) and perturbed urinary metabolomic profiles, but none has described the correlation between urine metabolite profiles and those of the tumor and adjacent esophageal mucosa in the same patient.

AIM

To investigate how urinary metabolic phenotypes were linked to the changes in the biochemical landscape of esophageal tumors.

METHODS

Nuclear magnetic resonance-based metabolomics were applied to esophageal tumor tissues and adjacent normal mucosal tissues alongside patient-matched urine samples.

RESULTS

Analysis revealed that specific metabolite changes overlapped across both metrics, including glucose, glutamate, citrate, glycine, creatinine and taurine, indicating that the networks for metabolic pathway perturbations in EC, potentially involved in but not limited to disruption of fatty acid metabolism, glucose and glycolytic metabolism, tricarboxylic acid cycle and glutaminolysis. Additionally, changes in most urinary biomarkers correlated with changes in biomarker candidates in EC tissues, implying enhanced energy production for rapid cell proliferation.

CONCLUSION

Overall, these associations provide evidence for distinct metabolic signatures and pathway disturbances between the tumor tissues and urine of EC patients, and changes in urinary metabolic signature could reflect reprogramming of the aforementioned metabolic pathways in EC tissues. Further investigation is needed to validate these initial findings using larger samples and to establish the underlying mechanism of EC progression.

An Unbiased Lipid Phenotyping Approach To Study the Genetic Determinants of Lipids and Their Association with Coronary Heart Disease Risk Factors

Direct infusion high-resolution mass spectrometry (DIHRMS) is a novel, high-throughput approach to rapidly and accurately profile hundreds of lipids in human serum without prior chromatography, facilitating in-depth lipid phenotyping for large epidemiological studies to reveal the detailed associations of individual lipids with coronary heart disease (CHD) risk factors. Intact lipid profiling by DIHRMS was performed on 5662 serum samples from healthy participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS). We developed a novel semi-targeted peak-picking algorithm to detect mass-to-charge ratios in positive and negative ionization modes. We analyzed lipid partial correlations, assessed the association of lipid principal components with established CHD risk factors and genetic variants, and examined differences between lipids for a common genetic polymorphism. The DIHRMS method provided information on 360 lipids (including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids), with a median coefficient of variation of 11.6% (range: 5.4-51.9). The lipids were highly correlated and exhibited a range of associations with clinical chemistry biomarkers and lifestyle factors. This platform can provide many novel insights into the effects of physiology and lifestyle on lipid metabolism, genetic determinants of lipids, and the relationship between individual lipids and CHD risk factors.

Metabolomic Investigation of β-Thalassemia in Chorionic Villi Samples

BACKGROUND

Beta-thalassemias are blood disorders characterized by poorly understood clinical phenotypes ranging from asymptomatic to severe anemia. Metabolic composition of the human placenta could be affected by the presence of pathological states such as β-thalassemia. The aim of our study was to describe metabolic changes in chorionic villi samples of fetuses affected by β-thalassemia compared to a control group by applying a metabolomics approach.

METHODS

Chorionic villi samples were differentiated according to the genetic diagnosis of β-thalassemia: control (Group 1, n = 27); heterozygous (Group 2, n = 7); homozygous (Group 3, n = 7). Gas chromatography-mass spectrometry was used to detect the metabolic composition of the samples. Subsequently, multivariate and univariate statistical analysis was performed. The discriminant metabolites were used to identify the altered pathways.

RESULTS

Supervised multivariate models were devised to compare the groups. The model resulting from the comparison between Group 1 and Group 3 was the most significant. Discriminant metabolites were identified, and the most altered pathways were as follows: pentose phosphate pathway (PPP), arachidonic acid metabolism, glycolysis, and gluconeogenesis, suggesting the presence of an energetic shift toward the PPP and the presence of oxidative stress in β-thalassemia chorionic villi samples.

CONCLUSIONS

The metabolomics approach identified a specific metabolic fingerprint in chorionic villi of fetuses affected by β-thalassemia.

Metabolic Profiling of the Diabetic Heart: Toward a Richer Picture

The increasing global prevalence of diabetes has been accompanied by a rise in diabetes-related conditions. This includes diabetic cardiomyopathy (DbCM), a progressive form of heart disease that occurs with both insulin-dependent (type-1) and insulin-independent (type-2) diabetes and arises in the absence of hypertension or coronary artery disease. Over time, DbCM can develop into overt heart failure. Like other forms of cardiomyopathy, DbCM is accompanied by alterations in metabolism which could lead to further progression of the pathology, with metabolic derangement postulated to precede functional changes in the diabetic heart. Moreover in the case of type-2 diabetes, underlying insulin resistance is likely to prevent the canonical substrate switch of the failing heart away from fatty acid oxidation toward increased use of glycolysis. Analytical chemistry techniques, collectively known as metabolomics, are useful tools for investigating the condition. In this article, we provide a comprehensive review of those studies that have employed metabolomic techniques, namely chromatography, mass spectrometry and nuclear magnetic resonance spectroscopy, to profile metabolic remodeling in the diabetic heart of human patients and animal models. These studies collectively demonstrate that glycolysis and glucose oxidation are suppressed in the diabetic myocardium and highlight a complex picture regarding lipid metabolism. The diabetic heart typically shows an increased reliance on fatty acid oxidation, yet triacylglycerols and other lipids accumulate in the diabetic myocardium indicating probable lipotoxicity. The application of lipidomic techniques to the diabetic heart has identified specific lipid species that become enriched and which may in turn act as plasma-borne biomarkers for the condition. Metabolomics is proving to be a powerful approach, allowing a much richer analysis of the metabolic alterations that occur in the diabetic heart. Careful physiological interpretation of metabolomic results will now be key in order to establish which aspects of the metabolic derangement are causal to the progression of DbCM and might form the basis for novel therapeutic intervention.

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.

Metabolomics in early detection and prognosis of acute coronary syndrome

Acute coronary syndrome (ACS) is one of the most dangerous types of coronary heart disease (CHD) and contributes to significant mortality and morbidity worldwide. Outcomes in these patients remain a challenge despite improvements in diagnosis and treatment. Risk stratification continues to be problematic and the identification of novel predictors is crucial for improved outcomes. As such, there is a strong need for the development of novel analytical methods as well as the characterization of better predictive and prognostic biomarkers to enable more personalized treatment. Metabolite profile analysis may greatly assist in interpreting altered pathway dynamics, especially when combined with other 'omics' technologies such as transcriptomics and proteomics. In this review, we describe ACS pathophysiology and recent advances in the role of metabolomics in the diagnosis and the molecular pathogenesis of ACS. We briefly describe key technologies used in metabolomics research and statistical approaches for data reduction and pathway analysis and discuss their application to CHD.

Broad spectrum metabolomics for detection of abnormal metabolic pathways in a mouse model for retinitis pigmentosa

Retinitis pigmentosa (RP) is a degenerative disease of the retina that affects approximately 1 million people worldwide. There are multiple genetic causes of this disease, for which, at present, there are no effective therapeutic strategies. In the present report, we utilized broad spectrum metabolomics to identify perturbations in the metabolism of the rd10 mouse, a genetic model for RP that contains a mutation in Pde6β. These data provide novel insights into mechanisms that are potentially critical for retinal degeneration. C57BL/6J and rd10 mice were raised in cyclic light followed by either light or dark adaptation at postnatal day (P) 18, an early stage in the degeneration process. Mice raised entirely in the dark until P18 were also evaluated. After euthanasia, retinas were removed and extracted for analysis by ultra-performance liquid chromatography-time of flight-mass spectrometry (UPLC-QTOF-MS). Compared to wild type mice, rd10 mice raised in cyclic light or in complete darkness demonstrate significant alterations in retinal pyrimidine and purine nucleotide metabolism, potentially disrupting deoxynucleotide pools necessary for mitochondrial DNA replication. Other metabolites that demonstrate significant increases are the Coenzyme A intermediate, 4'-phosphopantothenate, and acylcarnitines. The changes in these metabolites, identified for the first time in a model of RP, are highly likely to disrupt normal energy metabolism. High levels of nitrosoproline were also detected in rd10 retinas relative to those from wild type mice. These results suggest that nitrosative stress may be involved in retinal degeneration in this mouse model.

Identification of Key circRNAs/lncRNAs/miRNAs/mRNAs and Pathways in Preeclampsia Using Bioinformatics Analysis

BACKGROUND This study aimed to identify significantly altered circRNAs/lncRNAs/miRNAs/mRNAs pathways in preeclampsia (PE), investigate their target relationships, and determine their biological functions. MATERIAL AND METHODS Base on RNA-seq technique and the GEO database, expression profiles of circRNAs/lncRNAs/miRNAs/mRNAs related to PE were obtained. Differentially expressed RNAs were determined using the Limma package in R. Gene set enrichment analysis (GSEA) was performed using GSEA software (v. 3.0) and illustrated by ClusterProfiler and ggplot2 package in R. DAVID database (v. 6.8) was implemented to analyze functional categories and the association between genes and the corresponding Gene Ontology (GO) classification. The R visualization package GOPlot was used to get a better visualization of the relationships between genes and the selected functional categories. CeRNA networks which visualized the correlations between circRNA/lncRNA-miRNA-mRNA were constructed using Cytoscape software (v. 3.6.0). Targetscan and miRanda database were used to predict target relationships between circRNA/lncRNA-miRNA-mRNA. QRT-PCR and luciferase reporter assay were used to verify the expression and target relationship of has_circ_0088196/LINC01492/miR-100-5p/LIF (leukemia inhibitory factor). RESULTS The jak-stat signaling pathway was activated and miR-100-5p was downregulated in PE compared with normal tissues both in collected placental tissue samples and GEO database. Upregulated LIF, LINC01492, and hsa_circ_0088196 were negatively correlated with miR-100-5p expression and had a targeted relationship with miR-100-5p. CONCLUSIONS miR-100-5p may suppress PE development, while LIF, LINC01492, and hsa_circ_0088196 may promote it though inhibiting miR-100-5p. The jak-stat signaling pathway was activated and involved in PE progression.

Oxidative Stress and Bronchopulmonary Dysplasia: Evidences From Microbiomics, Metabolomics, and Proteomics

Bronchopulmonary dysplasia is a major issue affecting morbidity and mortality of surviving premature babies. Preterm newborns are particularly susceptible to oxidative stress and infants with bronchopulmonary dysplasia have a typical oxidation pattern in the early stages of this disease, suggesting the important role of oxidative stress in its pathogenesis. Bronchopulmonary dysplasia is a complex disease where knowledge advances as new investigative tools become available. The explosion of the "omics" disciplines has recently affected BPD research. This review focuses on the new evidence coming from microbiomics, metabolomics and proteomics in relation to oxidative stress and pathogenesis of bronchopulmonary dysplasia. Since the pathogenesis is not yet completely understood, information gained in this regard would be important for planning an efficacious prevention and treatment strategy for the future.

Familial resemblances in human plasma metabolites are attributable to both genetic and common environmental effects

Metabolites are of great importance for understanding the pathogenesis of several diseases. Understanding the genetic contribution to metabolite concentrations may provide insights into mechanisms of complex diseases. Several studies have investigated heritability of metabolites but none investigated potential influences of genetic and environmental factors on the relationship between metabolites and cardiometabolic (CM) risk factors. Thus, we tested the hypothesis that both genetic and common environmental effects contribute to the variance of plasma metabolite concentrations and that shared genetic and environmental effects explain their phenotypic correlations with CM risk factors. To test this hypothesis, variance component method and bivariate genetic analysis were performed in a family-based sample of 48 French Canadians from 16 families. Familial resemblances were computed for all 147 detected metabolites and 9 (acetylornithine, acylcarnitine C9, arginine, phosphatidylcholine acyl-alkyl C36:4, serotonin, lysophosphatidylcholine acyl C20:4, citrulline, asymmetric dimethylarginine, phosphatidylcholine acyl-alkyl C36:5) showed a significant familial effect (55.7%, 18.7%, and 37.0% for maximal heritability, genetic heritability, and common environmental effect, respectively). Citrulline, phosphatidylcholine acyl-alkyl C36:4, phosphatidylcholine acyl-alkyl C36:5, and serotonin had significant phenotypic correlations with CM risk factors. Citrulline had a positive genetic correlation with apolipoprotein B100, while phosphatidylcholine acyl-alkyl C36:5 had a positive environmental correlation with total cholesterol. In conclusion, familial resemblances in metabolite concentrations were mainly attributable to common environmental effect when considering metabolites with a significant familial effect. Common genetic and environmental factors may also influence the relationship between metabolites and CM risk factors.

Diastolic left ventricular function in relation to circulating metabolic biomarkers in a population study

Aims

We studied the association of circulating metabolic biomarkers with asymptomatic left ventricular diastolic dysfunction, a risk-carrying condition that affects 25% of the population.

Methods and results

In 570 randomly recruited people, we assessed in 2005–2010 and in 2009–2013 the multivariable-adjusted correlations of e’ (early left ventricular relaxation) and E/e’ (left ventricular filling pressure) measured by Doppler echocardiography with 43 serum metabolites, quantified by magnetic resonance spectroscopy. In 2009–2013, e’ cross-sectionally increased (Bonferroni corrected p ≤ 0.016) with the branched-chain amino acid valine (per one standard deviation increment, +0.274 cm/s (95% confidence interval, 0.057–0.491)) and glucose+the amino acid (AA) taurine (+0.258 cm/s (0.067–0.481)), while E/e’ decreased ( p ≤ 0.017) with valine (–0.264 (–0.496– –0.031)). The risk of developing left ventricular diastolic dysfunction over follow-up (9.4%) was inversely associated ( p ≤ 0.0059) with baseline glucose+amino acid taurine (odds ratio, 0.64 (0.44–0.94). In partial least squares analyses of all the baseline and follow-up data, markers consistently associated with better diastolic left ventricular function included the amino acids 2-aminobutyrate and 4-hydroxybutyrate and the branched-chain amino acids leucine and valine, and those consistently associated with worse diastolic left ventricular function glucose+amino acid glutamine and fatty acid pentanoate. Branched-chain amino acid metabolism (–log10 p = 12.6) and aminoacyl-tRNA biosynthesis (9.9) were among the top metabolic pathways associated with left ventricular diastolic dysfunction.

Conclusion

The associations of left ventricular diastolic dysfunction with circulating amino acids and branched-chain amino acids were consistent over a five-year interval and suggested a key role of branched-chain amino acid metabolism and aminoacyl-tRNA biosynthesis in maintaining diastolic left ventricular function.

Simplified plasma essential amino acid-based profiling provides metabolic information and prognostic value additive to traditional risk factors in heart failure

In heart failure (HF), metabolic disturbances represent functional perturbations in peripheral tissues and also predict patient outcomes. This study developed a simplified essential amino acid-based profile and tested whether it could improve prognostication. Plasma essential amino acids and lipidomics were measured on 1084 participants. The initial cohort included 94 normal controls and 599 patients hospitalized due to acute/decompensated HF. The validation cohort included 391 HF patients. Patients were followed for composite events (death/HF related re-hospitalization) and were categorized into three groups: high risk type 1 (leucine ≥145 μM and phenylalanine ≥ 88.9 μM), high risk type 2 (leucine < 81.2 μM), and low risk (other). Types 1 and 2 were associated with higher event rates [hazard ratio (95% confidence intervals) = 1.88 (1.27-2.79) and 7.71 (4.97-11.9), respectively, p < 0.001]. Compared to the low-risk group, both types of high-risk patients were older and had lower blood pressure and estimated glomerular filtration rates, but higher B-type natriuretic peptides (BNP). In addition, type 1 was associated with more incompletely metabolized lipids in the blood; type 2 patients had lower body mass indexes, rates of using guideline-based medications, and levels of cholesterol, hemoglobin, and albumin. The prognostic value of types 1 and 2 remained significant after adjusting for age, BNP and other risk factors. The value of using high-risk types for prognosis was confirmed in the validation cohort. In conclusion, simplified essential amino acid-based profiling identified two high-risk populations and provided metabolic information and prognostic value additive to traditional risk factors.

An integrated portable system for single chip simultaneous measurement of multiple disease associated metabolites

Metabolites, the small molecules that underpin life, can act as indicators of the physiological state of the body when their abundance varies, offering routes to diagnosis of many diseases. The ability to assay for multiple metabolites simultaneously will underpin a new generation of precision diagnostic tools. Here, we report the development of a handheld device based on complementary metal oxide semiconductor (CMOS) technology with multiple isolated micro-well reaction zones and integrated optical sensing allowing simultaneous enzyme-based assays of multiple metabolites (choline, xanthine, sarcosine and cholesterol) associated with multiple diseases. These metabolites were measured in clinically relevant concentration range with minimum concentrations measured: 25 μM for choline, 100 μM for xanthine, 1.25 μM for sarcosine and 50 μM for cholesterol. Linking the device to an Android-based user interface allows for quantification of metabolites in serum and urine within 2 min of applying samples to the device. The quantitative performance of the device was validated by comparison to accredited tests for cholesterol and glucose.

Human Plasma Metabolomics Implicates Modified 9-cis-Retinoic Acid in the Phenotype of Left Main Artery Lesions in Acute ST-Segment Elevated Myocardial Infarction

The detection of left main coronary artery disease (LMCAD) is crucial before ST-segment elevated myocardial infarction (STEMI) or sudden cardiac death. The aim of this study was to identify characteristic metabolite modifications in the LMCAD phenotype, using the metabolomics technique. Metabolic profiles were generated based on ultra-performance liquid chromatography and mass spectrometry, combined with multivariate statistical analysis. Plasma samples were collected prospectively from a propensity-score matched cohort including 44 STEMI patients (22 consecutive LMCAD and 22 non-LMCAD), and 22 healthy controls. A comprehensive metabolomics data analysis was performed with Metaboanalyst 3.0 version. The retinol metabolism pathway was shown to have the strongest discriminative power for the LMCAD phenotype. According to biomarker analysis through receiver-operating characteristic curves, 9-cis-retinoic acid (9cRA) dominated the first page of biomarkers, with area under the curve (AUC) value 0.888. Next highest were a biomarker panel consisting of 9cRA, dehydrophytosphingosine, 1H-Indole-3-carboxaldehyde, and another seven variants of lysophosphatidylcholines, exhibiting the highest AUC (0.933). These novel data propose that the retinol metabolism pathway was the strongest differential pathway for the LMCAD phenotype. 9cRA was the most critical biomarker of LMCAD, and a ten-metabolite plasma biomarker panel, in which 9cRA remained the weightiest, may help develop a potent predictive model for LMCAD in clinic.

From lipid locus to drug target through human genomics

In the last decade, over 175 genetic loci have robustly been associated to levels of major circulating blood lipids. Most loci are specific to one or two lipids, whereas some (SUGP1, ZPR1, TRIB1, HERPUD1, and FADS1) are associated to all. While exposing the polygenic architecture of circulating lipids and the underpinnings of dyslipidaemia, these genome-wide association studies (GWAS) have provided further evidence of the critical role that lipids play in coronary heart disease (CHD) risk, as indicated by the 2.7-fold enrichment for macrophage gene expression in atherosclerotic plaques and the association of 25 loci (such as PCSK9, APOB, ABCG5-G8, KCNK5, LPL, HMGCR, NPC1L1, CETP, TRIB1, ABO, PMAIP1-MC4R, and LDLR) with CHD. These GWAS also confirmed known and commonly used therapeutic targets, including HMGCR (statins), PCSK9 (antibodies), and NPC1L1 (ezetimibe). As we head into the post-GWAS era, we offer suggestions for how to move forward beyond genetic risk loci, towards refining the biology behind the associations and identifying causal genes and therapeutic targets. Deep phenotyping through lipidomics and metabolomics will refine and increase the resolution to find causal and druggable targets, and studies aimed at demonstrating gene transcriptional and regulatory effects of lipid associated loci will further aid in identifying these targets. Thus, we argue the need for deeply phenotyped, large genetic association studies to reduce costs and failures and increase the efficiency of the drug discovery pipeline. We conjecture that in the next decade a paradigm shift will tip the balance towards a data-driven approach to therapeutic target development and the application of precision medicine where human genomics takes centre stage.

Urinary 1H-NMR Metabolomics in the First Week of Life Can Anticipate BPD Diagnosis

Despite the advancements in medical knowledge and technology, the etiopathogenesis of bronchopulmonary dysplasia (BPD) is not yet fully understood although oxidative stress seems to play a role, leading to a very demanding management of these patients by the neonatologist. In this context, metabolomics can be useful in understanding, diagnosing, and treating this illness since it is one of the newest omics science that analyzes the metabolome of an individual through the investigation of biological fluids such as urine and blood. In this study, 18 patients admitted to the Neonatal Intensive Care Unit of the Cagliari University Hospital were enrolled. Among them, 11 patients represented the control group and 7 patients subsequently developed BPD. A sample of urine was collected from each patient at 7 days of life and analyzed through ¹H-NMR coupled with multivariate statistical analysis. The discriminant metabolites between the 2 groups noted were alanine, betaine, trimethylamine-N-oxide, lactate, and glycine. Utilizing metabolomics, it was possible to detect the urinary metabolomics fingerprint of neonates in the first week of life who subsequently developed BPD. Future studies are needed to confirm these promising results suggesting a possible role of microbiota and oxidative stress, and to apply this technology in clinical practice.

Metabolomic Approach to Redox and Nitrosative Reactions in Cardiovascular Diseases

Metabolomics, also referred to as metabonomics, is one of the most recent innovative technologies in medicine. It offers a direct functional read-out of phenotypes by the detection, identification, and quantification of a large number of metabolites within a biological sample such as urine and blood. Metabolites (<1500 Da) represent the output of cellular metabolism, accounting for expression and activity of genes, transcripts, and proteins, and offering unique insights into small molecule regulation, which may uncover new biochemical patterns. Metabolomics research has considerable potential for translating the metabolic fingerprint into personalized therapeutic strategies. Within the field of interest, cardiovascular disease (CVD) is one of the most developed areas. However, CVD remains the leading cause of death worldwide with a marked increase in mortality rates over the past six decades. In this scenario, recent findings indicate the important role of redox and nitrosative (RN) reactions in CVD development and progression. RN reactions are generally involved in the homeostatic modulation of a wide number of cellular and organ functions. Conversely, the imbalance of these reactions may lead to a condition of allostasis that in turn can cause CVD. The aim of this review is to highlight how the use of metabolomics may be useful for the study of RN reactions related to CVD, providing a tool to understand the mechanisms underlying reactions that could lead to impaired ROS or RNS formation.

Cardiac applications of hyperpolarised magnetic resonance

Cardiovascular disease is the leading cause of death world-wide. It is increasingly recognised that cardiac pathologies show, or may even be caused by, changes in metabolism, leading to impaired cardiac energetics. The heart turns over 15 times its own weight in ATP every day and thus relies heavily on the availability of substrates and on efficient oxidation to generate this ATP. A number of old and emerging drugs that target different aspects of metabolism are showing promising results with regard to improved cardiac outcomes in patients. A non-invasive imaging technique that could assess the role of different aspects of metabolism in heart disease, as well as measure changes in cardiac energetics due to treatment, would be valuable in the routine clinical care of cardiac patients. Hyperpolarised magnetic resonance spectroscopy and imaging have revolutionised metabolic imaging, allowing real-time metabolic flux assessment in vivo for the first time. In this review we summarise metabolism in the healthy and diseased heart, give an introduction to the hyperpolarisation technique, 'dynamic nuclear polarisation' (DNP), and review the preclinical studies that have thus far explored healthy cardiac metabolism and different models of human heart disease. We furthermore show what advances have been made to translate this technique into the clinic, what technical challenges still remain and what unmet clinical needs and unexplored metabolic substrates still need to be assessed by researchers in this exciting and fast-moving field.

Integration of Metabonomics and Transcriptomics Reveals the Therapeutic Effects and Mechanisms of Baoyuan Decoction for Myocardial Ischemia

Myocardial ischemia (MI) is an escalating public health care burden worldwide. Baoyuan decoction (BYD) is a traditional Chinese medicine formula with cardioprotective activity; however, its pharmacological characteristics and mechanisms are obscured. Herein, a multi-omics strategy via incorporating the metabonomics, transcriptomics, and pharmacodynamics was adopted to investigate the effects and molecular mechanisms of BYD for treating MI in a rat model of left anterior descending coronary artery (LADCA) ligation. The results indicated that BYD has a significantly cardioprotective role against MI by decreasing the infarct size, converting the echocardiographic abnormalities and myocardial enzyme markers, and reversing the serum metabolic disorders and myocardial transcriptional perturbations resulting from MI. Integrated bioinformatics analysis and literature reports constructed the interaction network based on the changes of the key MI targeted-metabolites and transcripts after BYD treatment and disclosed that the cardioprotection of BYD is mainly involved in the regulation of energy homeostasis, oxidative stress, apoptosis, inflammation, cardiac contractile dysfunction, and extracellular matrix remodeling. The results of histopathological examination, quantitative RT-PCR assay, cardiac energy synthesis, and serum antioxidant assessment complemented the multi-omics findings, and indicated the multi-pathway modulation mechanisms of BYD. Our investigation demonstrated that the multi-omics approach could achieve a complementary and verified view for the comprehensive evaluation of therapeutic effects and complex mechanisms of TCMF like BYD.

Metabolic Biomarkers in Heart Failure

Metabolomics is the study of small, organic molecules within biochemical pathways. With advancement of technology, nuclear magnetic resonance, gas chromatography, and mass spectrometry have allowed for the discovery and analysis of large databases of metabolites implicated in heart failure. Metabolomics also explores the patient and environment interactions and unlocks the link between environmental exposures and the development of cardiovascular disease. Although a relatively new field, metabolomics is poised to become a clinically impactful field that develops novel biomarkers and explores new therapeutic interventions in heart failure.

Cardiovascular Metabolomics

Disturbances in cardiac metabolism underlie most cardiovascular diseases. Metabolomics, one of the newer omics technologies, has emerged as a powerful tool for defining changes in both global and cardiac-specific metabolism that occur across a spectrum of cardiovascular disease states. Findings from metabolomics studies have contributed to better understanding of the metabolic changes that occur in heart failure and ischemic heart disease and have identified new cardiovascular disease biomarkers. As technologies advance, the metabolomics field continues to evolve rapidly. In this review, we will discuss the current state of metabolomics technologies, including consideration of various metabolomics platforms and elements of study design; the emerging utility of stable isotopes for metabolic flux studies; and the use of metabolomics to better understand specific cardiovascular diseases, with an emphasis on recent advances in the field.

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 profiling in plasma samples from glioma patients correlates with tumor phenotypes

Background

Tumor-based molecular biomarkers have redefined in the classification gliomas. However, the association of systemic metabolomics with glioma phenotype has not been explored yet.

Methods

In this study, we conducted two-step (discovery and validation) metabolomic profiling in plasma samples from 87 glioma patients. The metabolomics data were tested for correlation with glioma grade (high vs low), glioblastoma (GBM) versus malignant gliomas, and IDH mutation status.

Results

Five metabolites, namely uracil, arginine, lactate, cystamine, and ornithine, significantly differed between high- and low-grade glioma patients in both the discovery and validation cohorts. When the discovery and validation cohorts were combined, we identified 29 significant metabolites with 18 remaining significant after adjusting for multiple comparisons. Those 18 significant metabolites separated high- from low-grade glioma patients with 91.1% accuracy. In the pathway analysis, a total of 18 significantly metabolic pathways were identified. Similarly, we identified 2 and 6 metabolites that significantly differed between GBM and non-GBM, and IDH mutation positive and negative patients after multiple comparison adjusting. Those 6 significant metabolites separated IDH1 mutation positive from negative glioma patients with 94.4% accuracy. Three pathways were identified to be associated with IDH mutation status. Within arginine and proline metabolism, levels of intermediate metabolites in creatine pathway were all significantly lower in IDH mutation positive than in negative patients, suggesting an increased activity of creatine pathway in IDH mutation positive tumors.

Conclusion

Our findings identified metabolites and metabolic pathways that differentiated tumor phenotypes. These may be useful as host biomarker candidates to further help glioma molecular classification.

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.

Metabolomics As a Tool for the Characterization of Drug-Resistant Epilepsy

Purpose

Drug resistance is a critical issue in the treatment of epilepsy, contributing to clinical emergencies and increasing both serious social and economic burdens on the health system. The wide variety of potential drug combinations followed by often failed consecutive attempts to match drugs to an individual patient may mean that this treatment stage may last for years with suboptimal benefit to the patient. Given these challenges, it is valuable to explore the availability of new methodologies able to shorten the period of determining a rationale pharmacologic treatment. Metabolomics could provide such a tool to investigate possible markers of drug resistance in subjects with epilepsy.

Methods

Blood samples were collected from (1) controls (C) (n = 35), (2) patients with epilepsy “responder” (R) (n = 18), and (3) patients with epilepsy “non-responder” (NR) (n = 17) to the drug therapy. The samples were analyzed using nuclear magnetic resonance spectroscopy, followed by multivariate statistical analysis.

Key findings

A different metabolic profile based on metabolomics analysis of the serum was observed between C and patients with epilepsy and also between R and NR patients. It was possible to identify the discriminant metabolites for the three classes under investigation. Serum from patients with epilepsy were characterized by increased levels of 3-OH-butyrate, 2-OH-valerate, 2-OH-butyrate, acetoacetate, acetone, acetate, choline, alanine, glutamate, scyllo-inositol (C < R < NR), and decreased concentration of glucose, lactate, and citrate compared to C (C > R > NR).

Significance

In conclusion, metabolomics may represent an important tool for discovery of differences between subjects affected by epilepsy responding or resistant to therapies and for the study of its pathophysiology, optimizing the therapeutic resources and the quality of life of patients.

Metabolomics and Cardiology: Toward the Path of Perinatal Programming and Personalized Medicine

Heart diseases are one of the leading causes of death in Western Countries and tend to become chronic, lowering the quality of life of the patients and ending up in a massive cost for the Health Systems and the society. Thus, there is a growing interest in finding new technologies that would allow the physician to effectively treat and prevent cardiac illnesses. Metabolomics is one of the new "omics" sciences enabling creation of a photograph of the metabolic state of an individual exposed to different environmental factors and pathologies. This review analyzed the most recent literature about this technology and its application in cardiology in order to understand the metabolic shifts that occur even before the manifestation of these pathologies to find possible early predictive biomarkers. In this way, it could be possible to find better treatments, ameliorate the patient's quality of life, and lower the death rate. This technology seems to be so promising that several industries are trying to set up kits to immediately assess the metabolites variations in order to provide a faster diagnosis and the best treatment specific for that patient, offering a further step toward the path of the development of a tailored medicine.

Metabolomics in nutrition research-a powerful window into nutritional metabolism

Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.

Blood metabolomic fingerprint is distinct in healthy coronary and in stenosing or microvascular ischemic heart disease

BACKGROUND

The endothelium is a key variable in the pathogenesis of atherosclerosis and its complications, particularly coronary artery disease (CAD). Current evidence suggests that the endothelial status can be regarded as an integrated index of individual atherogenic and anti-atherogenic properties, and that the interaction between circulating factors and the arterial wall might be critical for atherogenesis. In organism-level investigations, a functional view is provided by metabolomics, the study of the metabolic profile of small molecules. We sought to verify whether metabolomic analysis can reveal the presence of coronary microenvironment peculiarities associated with distinct manifestations of CAD.

METHODS

Thirty-two coronary blood samples were analyzed using ¹H-NMR-based metabolomics. Samples collected from patients with evidence of myocardial ischemia formed the case group, and were further divided into the stenotic-disease (SD) group (N = 13) and absence of stenosis (microvascular disease; "Micro") group (N = 8); specimens of patients presenting no evidence of ischemic heart disease (dilated cardiomyopathy, valvular diseases) constituted the control group (N = 11).

RESULTS

Application of an orthogonal partial least squares discriminant analysis (OPLS-DA) model to the entire dataset clearly separated the samples into 3 groups, indicating 3 distinct metabolic fingerprints. Relative to control-group members, Micro patients showed a higher content of 2-hydroxybutirate, alanine, leucine, isoleucine, and N-acetyl groups and lower levels of creatine/phosphocreatine, creatinine, and glucose, whereas SD patients showed higher levels of 3-hydroxybutirate and acetate and a lower content of 2-hydroxybutirate. Moreover, relative to SD patients, Micro patients showed higher levels of 2-hydroxybutirate, alanine, leucine, and N-acetyl groups and lower levels of 3-hydroxybutirate and acetate.

CONCLUSIONS

Specific coronary microenvironments are likely associated with distinct development and pathological expression of CAD.