Metabolomics and ischaemic heart disease. Clin Sci (Lond). 2013;124:289-306. [PMID: 23157406 DOI: 10.1042/cs20120268]

Untargeted metabolomics reveals that declined PE and PC in obesity may be associated with prostate hyperplasia

BACKGROUND

Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood.

METHODS

A prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF).

RESULTS

A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms.

CONCLUSIONS

In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Big Data in Gastroenterology Research

Studying individual data types in isolation provides only limited and incomplete answers to complex biological questions and particularly falls short in revealing sufficient mechanistic and kinetic details. In contrast, multi-omics approaches to studying health and disease permit the generation and integration of multiple data types on a much larger scale, offering a comprehensive picture of biological and disease processes. Gastroenterology and hepatobiliary research are particularly well-suited to such analyses, given the unique position of the luminal gastrointestinal (GI) tract at the nexus between the gut (mucosa and luminal contents), brain, immune and endocrine systems, and GI microbiome. The generation of 'big data' from multi-omic, multi-site studies can enhance investigations into the connections between these organ systems and organisms and more broadly and accurately appraise the effects of dietary, pharmacological, and other therapeutic interventions. In this review, we describe a variety of useful omics approaches and how they can be integrated to provide a holistic depiction of the human and microbial genetic and proteomic changes underlying physiological and pathophysiological phenomena. We highlight the potential pitfalls and alternatives to help avoid the common errors in study design, execution, and analysis. We focus on the application, integration, and analysis of big data in gastroenterology and hepatobiliary research.

Studies on Metabolic Alterations due to Hypobaric Hypoxia in Serum using NMR Spectroscopy

Introduction The main physiological challenge in high altitude environment is hypoxia which affects the aerobic metabolism reducing the energy supply. These changes may further progress towards extreme environment related diseases. Rarely has the high-altitude biology been studied using system sciences and omics high-throughput technologies.Objective In the present study, 1H-NMR-based metabolomics, along with multivariate analysis, were employed in a preclinical rat model to characterize the serum metabolic changes under chronic hypobaric hypoxia (HH) stress.Material & Methods Rats were exposed to simulated hypobaric hypoxia equivalent of 6700 m above the sea level. The serum samples were collected from control and HH-exposure (7, 14, and 21 days) of hypobaric hypoxia.Results & Discussion The 1H-NMR metabolomics of the serum showed alterations in the metabolism of membranes, amino-acids altered cellular bioenergetics and osmoregulation. Multivariate statistical analysis revealed alterations in acetoacetate, choline, glutamine, acetate, betaine, ketone bodies & branched amino acid metabolites.Conclusion Present findings establishes the fingerprint biomarkers for chronic environmental hypoxia which will help in understanding extreme environment related health problems, early detection and developing strategies to clinically address high altitude hypoxia.

Metabolomics of Arterial Stiffness

Arterial stiffness (AS) is one of the earliest detectable signs of structural and functional alterations of the vessel wall and an independent predictor of cardiovascular events and death. The emerging field of metabolomics can be utilized to detect a wide spectrum of intermediates and products of metabolism in body fluids that can be involved in the pathogenesis of AS. Research over the past decade has reinforced this idea by linking AS to circulating acylcarnitines, glycerophospholipids, sphingolipids, and amino acids, among other metabolite species. Some of these metabolites influence AS through traditional cardiovascular risk factors (e.g., high blood pressure, high blood cholesterol, diabetes, smoking), while others seem to act independently through both known and unknown pathophysiological mechanisms. We propose the term 'arteriometabolomics' to indicate the research that applies metabolomics methods to study AS. The 'arteriometabolomics' approach has the potential to allow more personalized cardiovascular risk stratification, disease monitoring, and treatment selection. One of its major goals is to uncover the causal metabolic pathways of AS. Such pathways could represent valuable treatment targets in vascular ageing.

Lipids: biomarkers of healthy aging

Life expectancy, and longevity have been increasing in recent years. However, this is, in most cases, accompanied by age-related diseases. Thus, it became essential to better understand the mechanisms inherent to aging, and to establish biomarkers that characterize this physiological process. Among all biomolecules, lipids appear to be a good target for the study of these biomarkers. In fact, some lipids have already been associated with age-related diseases. With the development of analytical techniques such as Mass Spectrometry, and Nuclear Magnetic Resonance, Lipidomics has been increasingly used to study pathological, and physiological states of an organism. Thus, the study of serum, and plasma lipidome in centenarians, and elderly individuals without age-related diseases can be a useful tool for the identification of aging biomarkers, and to understand physiological aging, and longevity. This review focus on the importance of lipids as biomarkers of aging, and summarize the changes in the lipidome that have been associated with aging, and longevity.

Comparing Levels of Metabolic Predictors of Coronary Heart Disease between Healthy Lean and Overweight Females

Screening for the metabolomic signature of coronary heart disease (CHD) before disease onset could help in early diagnosis and potentially disease prevention. In this study, the levels of 17 CHD metabolic biomarkers in apparently healthy overweight females were compared to lean counterparts, and their associations with conventional clinical risk factors were determined. Clinical and metabolic data from 200 apparently healthy non-obese Qatari females were collected from Qatar Biobank (discovery cohort). Logistic regression was used to assess the association between body mass index (BMI) groups and 17 CHD metabolic biomarkers, and receiver operating characteristic (ROC) analysis was used to evaluate the prognostic value of CHD metabolic biomarkers in overweight. Stepwise linear regression was performed to identify the classical risk factors associated with CHD metabolites differentiating the two BMI groups. Validation of the association of CHD metabolic biomarkers with BMI groups was performed in 107 subjects (replication cohort). Out of the tested CHD metabolic biomarkers, five were significantly different between lean and overweight females in the discovery cohort (AUC = 0.73). Among these, the association of mannose, asparagine, and linoleate with BMI groups was confirmed in the replication cohort (AUC = 0.97). Significant correlations between predictors of CHD in overweight healthy women and classical risk factors were observed, including serum levels of cholesterol, testosterone, triiodothyronine, thyroxine, creatinine, albumin, bilirubin, glucose, c-peptide, uric acid, calcium and chloride. Apparently, healthy overweight females exhibit significantly different levels of specific CHD metabolites compared to their lean counterparts, offering a prognostic potential with preventative value.

1H NMR serum metabolomic profiling of patients at risk of cardiovascular diseases performing stress test

Cardiovascular diseases are the leading cause of death worldwide. Changes in lifestyle and/or pharmacological treatment are able to reduce the burden of coronary artery diseases (CAD) and early diagnosis is crucial for the timely and optimal management of the disease. Stress testing is a good method to measure the burden of CAD but it is time consuming and pharmacological testing may not fully mimic exercise test. The objectives of the present project were to characterize the metabolic profile of the population undergoing pharmacological and exercise stress testing to evaluate possible differences between them, and to assess the capacity of ¹H NMR spectroscopy to predict positive stress testing. Pattern recognition was applied to ¹H NMR spectra from serum of patients undergoing stress test and metabolites were quantified. The effects of the stress test, confounding variables and the ability to predict ischemia were evaluated using OPLS-DA. There was an increase in lactate and alanine concentrations in post-test samples in patients undergoing exercise test, but not in those submitted to pharmacological testing. However, when considering only pharmacological patients, those with a positive test result, showed increased serum lactate, that was masked by the much larger amount of lactate associated to exercise testing. In conclusion, we have established that pharmacological stress test does not reproduce the dynamic changes observed in exercise stress. Although there is promising evidence suggesting that ¹H NMR based metabolomics could predict stress test results, further studies with much larger populations will be required in order to obtain a definitive answer.

Untargeted metabolomic analysis of coronary artery disease patients with diastolic dysfunction show disturbed oxidative pathway

INTRODUCTION

Left ventricular diastolic dysfunction (LVDD) is common in patients with coronary artery disease (CAD) with prevalence estimates of 34% and constitutes a predictor of all-cause mortality. Although diastolic dysfunction is induced by myocardial ischemia and has been shown to alter the clinical course, the role of coronary artery disease in the diastolic dysfunction and its progression into heart failure has not been completely elucidated.

OBJECTIVE

The present study was conducted to identify possible metabolites in coronary artery disease patients that are differentially regulated in patients with diastolic dysfunction.

METHODS

The serum of CAD (n = 75) patients and young healthy volunteers (n = 43) were analysed by using gas chromatography mass spectrometry (GC-MS) technique. Pre-processing of data results in 1547 features; among them 1064 features were annotated using NIST library.

RESULTS AND CONCLUSION

Fifteen metabolites were found to be statistically different between cases and control. Variation in metabolites were identified and correlated with several clinically important echocardiography parameters i.e. LVDD grades, ejection fraction (EF) and E/e' values. The results suggested that metabolic products of fatty acid oxidation and glucose oxidation pathways such as oleic acid, stearic acid, palmitic acid, linoleic acid, galactose, pyruvic and lactic acids are predominantly up regulated in patients with coronary artery disease and severity of diastolic dysfunction appears to be linked to increase in fatty acid oxidation and inflammation. The metabolic fingerprints of these patients give us an insight into the pathophysiological mechanism of diastolic dysfunction in coronary artery disease patients although it did not identify validated novel markers.

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.

Phosphatidylcholine and phosphatidylethanolamine plasmalogens in lipid loaded human macrophages

Background

Plasmalogens are either phosphatidylcholine (PC P) or phosphatidylethanolamine (PE P) glycerophospholipids containing a vinyl ether moiety in sn-1-position and an esterified fatty acid in sn-2 position. Multiple functions have been proposed, including reservoir of precursors for inflammatory mediators, modulation of membrane fluidity, and anti-oxidative properties. They could therefore play a role under conditions of metabolic stress. Especially enzymatically modified LDL (eLDL) and oxidatively modified LDL (oxLDL) represent modifications of LDL that are taken up by macrophages in atherosclerotic plaques. The aim of this study was to analyze plasmalogen related effects of eLDL and oxLDL in human monocyte derived macrophages, as well as the effects of HDL₃ mediated deloading.

Methods

Elutriated monocytes from nine healthy donors were differentiated in vitro for four days. Macrophages were then loaded with native LDL, eLDL and oxLDL for 24h and subsequently deloaded with HDL₃ for another 24h. Lipidomic and transcriptomic profiles were obtained.

Results

Loading of macrophages with eLDL and oxLDL led to a transient but strong elevation of lysophosphatidylcholine (LPC) most likely through direct uptake. Only eLDL induced increased levels of total PC, presumably through an induction of PC synthesis. On the other hand treatment with oxLDL led to a significant increase in PC P. Analysis of individual lipid species showed lipoprotein and saturation specific effects for LPC, PC P and PE P species. Membrane fluidity was decreased by the large amount of FC contained in the lipoproteins, as indicated by a lower PC to FC ratio after lipoprotein loading. In contrast the observed changes in the saturated to mono-unsaturated fatty acid (SFA to MUFA) and saturated to poly-unsaturated fatty acid (SFA to PUFA) ratios in PE P could represent a cellular reaction to counteract this effect by producing more fluid membranes. Transcriptomic analysis showed considerable differences between eLDL and oxLDL treated macrophages. As a common feature of both lipoproteins we detected a strong downregulation of pathways for endogenous lipid synthesis as well as for exogenous lipid uptake. Deloading with HDL₃ had only minor effects on total lipid class as well as on individual lipid species levels, most of the time not reaching significance. Interestingly treatment with HDL₃ had no effect on membrane fluidity under these conditions, although incubation with HDL₃ was partially able to counteract the oxLDL induced transcriptomic effects. To investigate the functional effect of lipoprotein treatment on macrophage polarization we performed surface marker flow cytometry. Under our experimental conditions oxLDL was able to partially shift the surface marker pattern towards a pro-inflammatory M1-like phenotype. This is consistent with the consumption of arachidonic acid containing PE P species in oxLDL treated cells, presumably for the synthesis of inflammatory mediators.

Summary

Our findings provide novel data on the lipoprotein induced, lipidomic and transcriptomic changes in macrophages. This can help us better understand the development of metabolic, inflammatory diseases as well as improve our background knowledge on lipid biomarkers in serum.

Lipidomics Reveals Changes in Metabolism, Indicative of Anesthetic-Induced Neurotoxicity in Developing Brains

Numerous studies have demonstrated that treatment with high dose anesthetics for a prolonged duration induces brain injury in infants. However, whether anesthetic treatment leading to neurotoxicity is associated with alterations in lipid metabolism and homeostasis is still unclear. This review first outlines the lipidomics tools for analysis of lipid molecular species that can inform alterations in lipid species after anesthetic exposure. Then the available data indicating anesthetics cause changes in lipid profiles in the brain and serum of infant monkeys in preclinical studies are summarized, and the potential mechanisms leading to the altered lipid metabolism and their association with anesthetic-induced brain injury are also discussed. Finally, whether lipid changes identified in serum of infant monkeys can serve as indicators for the early detection of anesthetic-induced brain injury is described. We believe extensive studies on alterations in lipids after exposure to anesthetics will allow us to better understand anesthetic-induced neurotoxicity, unravel its underlying biochemical mechanisms, and develop powerful biomarkers for early detection/monitoring of the toxicity.

Omega-3 fatty acids modulate the lipid profile, membrane architecture, and gene expression of leiomyoma cells

Uterine leiomyomas (fibroids or myomas) are the most common benign tumors of premenopausal women and new medical treatments are needed. This study aimed to determine the effects of omega-3 fatty acids on the lipid profile, membrane architecture and gene expression patterns of extracellular matrix components (collagen1A1, fibronectin, versican, or activin A), mechanical signaling (integrin β1, FAK, and AKAP13), sterol regulatory molecules (ABCG1, ABCA1, CAV1, and SREBF2), and mitochondrial enzyme (CYP11A1) in myometrial and leiomyoma cells. Myometrial tissues had a higher amount of arachidonic acid than leiomyoma tissues while leiomyoma tissues had a higher level of linoleic acid than myometrial tissues. Treatment of primary myometrial and leiomyoma cells with eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA) reduced the monounsaturated fatty acid (MUFA) content and increased the polyunsaturated fatty acid (PUFA) content in both cell types. Myometrial and leiomyoma cell membranes were in the liquid-crystalline phase, but EPA- and DHA-treated cells had decreased membrane fluidity. While we found no changes in the mRNA expression of ECM components, EPA and DHA treatment reduced levels of ABCG1, ABCA1, and AKAP13 in both cell types. EPA and DHA also reduced FAK and CYP11A1 expression in myometrial cells. The ability of omega-3 fatty acids to remodel membrane architecture and downregulate the expression of genes involved in mechanical signaling and lipid accumulation in leiomyoma cells offers to further investigate this compound as preventive and/or therapeutic option.

Metabolomics and Lipidomics of Ischemic Stroke

Ischemic stroke is a sudden loss of brain function due to the reduction of blood flow. Brain tissues cease to function with subsequent activation of the ischemic cascade. Metabolomics and lipidomics are modern disciplines that characterize the metabolites and lipid components of a biological system, respectively. Because the pathogenesis of ischemic stroke is heterogeneous and multifactorial, it is crucial to establish comprehensive metabolomic and lipidomic approaches to elucidate these alterations in this disease. Fortunately, metabolomic and lipidomic studies have the distinct advantages of identifying tissue/mechanism-specific biomarkers, predicting treatment and clinical outcome, and improving our understanding of the pathophysiologic basis of disease states. Therefore, recent applications of these analytical approaches in the early diagnosis of ischemic stroke were discussed. In addition, the emerging roles of metabolomics and lipidomics on ischemic stroke were summarized, in order to gain new insights into the mechanisms underlying ischemic stroke and in the search for novel metabolite biomarkers and their related pathways.

21st century toolkit for optimizing population health through precision nutrition

Scientific, technological, and economic progress over the last 100 years all but eradicated problems of widespread food shortage and nutrient deficiency in developed nations. But now society is faced with a new set of nutrition problems related to energy imbalance and metabolic disease, which require new kinds of solutions. Recent developments in the area of new analytical tools enable us to systematically study large quantities of detailed and multidimensional metabolic and health data, providing the opportunity to address current nutrition problems through an approach called Precision Nutrition. This approach integrates different kinds of "big data" to expand our understanding of the complexity and diversity of human metabolism in response to diet. With these tools, we can more fully elucidate each individual's unique phenotype, or the current state of health, as determined by the interactions among biology, environment, and behavior. The tools of precision nutrition include genomics, metabolomics, microbiomics, phenotyping, high-throughput analytical chemistry techniques, longitudinal tracking with body sensors, informatics, data science, and sophisticated educational and behavioral interventions. These tools are enabling the development of more personalized and predictive dietary guidance and interventions that have the potential to transform how the public makes food choices and greatly improve population health.

Metabolomics through the lens of precision cardiovascular medicine

Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.

Nuclear Magnetic Resonance Metabolomic Profiling of Mouse Kidney, Urine and Serum Following Renal Ischemia/Reperfusion Injury

Background

Ischemia/reperfusion (I/R) is the most common cause of acute kidney injury (AKI). Its pathophysiology remains unclear. Metabolomics is dedicated to identify metabolites involved in (patho)physiological changes of integrated living systems. Here, we performed ¹H-Nuclear Magnetic Resonance metabolomics using urine, serum and kidney samples from a mouse model of renal I/R.

Methods

Renal 30-min ischemia was induced in 12-week-old C57BL/6J male mice by bilaterally clamping vascular pedicles, and was followed by 6, 24 or 48-hour reperfusion (n = 12/group). Sham-operated mice were used as controls. Statistical discriminant analyses, i.e. principal component analysis and orthogonal projections to latent structures (OPLS-DA), were performed on urine, serum and kidney lysates at each time-point. Multivariate receiver operating characteristic (ROC) curves were drawn, and sensitivity and specificity were calculated from ROC confusion matrix (with averaged class probabilities across 100 cross-validations).

Results

Urine OPLS-DA analysis showed a net separation between I/R and sham groups, with significant variations in levels of taurine, di- and tri-methylamine, creatine and lactate. Such changes were observed as early as 6 hours post reperfusion. Major metabolome modifications occurred at 24h post reperfusion. At this time-point, correlation coefficients between urine spectra and conventional AKI biomarkers, i.e. serum creatinine and urea levels, reached 0.94 and 0.95, respectively. The area under ROC curve at 6h, 24h and 48h post surgery were 0.73, 0.98 and 0.97, respectively. Similar discriminations were found in kidney samples, with changes in levels of lactate, fatty acids, choline and taurine. By contrast, serum OPLS-DA analysis could not discriminate sham-operated from I/R-exposed animals.

Conclusions

Our study demonstrates that renal I/R in mouse causes early and sustained metabolomic changes in urine and kidney composition. The most implicated pathways at 6h and 24h post reperfusion include gluconeogenesis, taurine and hypotaurine metabolism, whereas protein biosynthesis, glycolysis, and galactose and arginine metabolism are key at 48h post reperfusion.

Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences

Lipidomics is a newly emerged discipline that studies cellular lipids on a large scale based on analytical chemistry principles and technological tools, particularly mass spectrometry. Recently, techniques have greatly advanced and novel applications of lipidomics in the biomedical sciences have emerged. This review provides a timely update on these aspects. After briefly introducing the lipidomics discipline, we compare mass spectrometry-based techniques for analysis of lipids and summarize very recent applications of lipidomics in health and disease. Finally, we discuss the status of the field, future directions, and advantages and limitations of the field.

Targeted metabolomic profiling of cardioprotective effect of Ginkgo biloba L. extract on myocardial ischemia in rats

BACKGROUND

Myocardial ischemia (MI) is one of the highest mortality diseases in the world. It is closely associated with metabolism disorders of endogenous substances. Ginkgo biloba L. extract (GBE) is a popular herbal medicine used for prevention and therapy of MI. But its regulation effect on the metabolism disorders caused by MI remains currently unknown.

PURPOSE

Our metabolomic profiling study provided insight into endogenous metabolic disorders of MI and cardioprotective mechanisms of GBE.

STUDY DESIGN

The rats were preventive administrated of GBE (200mg/kg, i.g.) for 4 weeks and then subcutaneous injected of isoproterenol to establish MI model. Heart marker enzymes and histopathological examination were adopted to evaluate MI model and effect of GBE. On this base, endogenous metabolites in rat plasma and heart were well profiled using the developed targeted metabolomic profiling platform to comprehensively analyze metabolic pathways and find biomarkers.

METHODS

A targeted metabolomic profiling platform was developed and only 100μl biological sample was used to quantify 808 metabolites covering the core network of lipid, energy, amino acid and nucleotide metabolism. Then using this platform, endogenous metabolites of rats undergoing MI model and GBE pre-treatment were well profiled. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to discriminate between groups and find biomarkers.

RESULTS

The metabolomic profiles of MI model rats pre-protected by GBE were significantly different from those of unprotected. 47 metabolites were found as potential biomarkers and indicated MI would lead to disturbed metabolism due to inflammation, oxidative stress and structural damage; while GBE could effectively restore fatty acid, sphingolipid, phosphoglyceride, glyceride, amino acid and energy metabolism, closely related to its antioxidant, PAF antagonist and hypolipidemic properties.

CONCLUSION

The cardioprotective effect of GBE can be achieved through the comprehensive regulation of multiple metabolic pathways.

Metabolomic patterns associated to QTc interval in shiftworkers: an explorative analysis

OBJECTIVES

(1)H NMR-metabolomic approach was used to investigate QTc interval correlation with plasma metabolic profiles in shiftworkers.

METHODS

Socio-demographic data, electrocardiographic QTc interval and plasma metabolic profiles from 32 male shiftworkers, were correlated by multivariate regression analysis.

RESULTS

We found a positive correlation between QTc interval values, body mass index, glycemia and lactate level and a negative correlation between QTc interval and both pyroglutamate and 3-hydroxybutyrate plasma level.

CONCLUSIONS

Our analysis provides evidence of the association between clinical, metabolic profiles and QTc interval values. This could be used to identify markers of early effects and/or susceptibility in shiftworkers.

Three plasma metabolite signatures for diagnosing high altitude pulmonary edema

High-altitude pulmonary edema (HAPE) is a potentially fatal condition, occurring at altitudes greater than 3,000 m and affecting rapidly ascending, non-acclimatized healthy individuals. However, the lack of biomarkers for this disease still constitutes a bottleneck in the clinical diagnosis. Here, ultra-high performance liquid chromatography coupled with Q-TOF mass spectrometry was applied to study plasma metabolite profiling from 57 HAPE and 57 control subjects. 14 differential plasma metabolites responsible for the discrimination between the two groups from discovery set (35 HAPE subjects and 35 healthy controls) were identified. Furthermore, 3 of the 14 metabolites (C8-ceramide, sphingosine and glutamine) were selected as candidate diagnostic biomarkers for HAPE using metabolic pathway impact analysis. The feasibility of using the combination of these three biomarkers for HAPE was evaluated, where the area under the receiver operating characteristic curve (AUC) was 0.981 and 0.942 in the discovery set and the validation set (22 HAPE subjects and 22 healthy controls), respectively. Taken together, these results suggested that this composite plasma metabolite signature may be used in HAPE diagnosis, especially after further investigation and verification with larger samples.

Lipidomics in vascular health: current perspectives

Identifying the mechanisms that convert a healthy vascular wall to an atherosclerotic wall is of major importance since the consequences may lead to a shortened lifespan. Classical risk factors (age, smoking, obesity, diabetes mellitus, hypertension, and dyslipidemia) may result in the progression of atherosclerotic lesions by processes including inflammation and lipid accumulation. Thus, the evaluation of blood lipids and the full lipid complement produced by cells, organisms, or tissues (lipidomics) is an issue of importance. In this review, we shall describe the recent progress in vascular health research using lipidomic advances. We will begin with an overview of vascular wall biology and lipids, followed by a short analysis of lipidomics. Finally, we shall focus on the clinical implications of lipidomics and studies that have examined lipidomic approaches and vascular health.

A preliminary study on postmortem interval estimation of suffocated rats by GC-MS/MS-based plasma metabolic profiling

Estimation of postmortem interval (PMI) is an important goal in judicial autopsy. Although many approaches can estimate PMI through physical findings and biochemical tests, accurate PMI calculation by these conventional methods remains difficult because PMI is readily affected by surrounding conditions, such as ambient temperature and humidity. In this study, Sprague-Dawley (SD) rats (10 weeks) were sacrificed by suffocation, and blood was collected by dissection at various time intervals (0, 3, 6, 12, 24, and 48 h; n = 6) after death. A total of 70 endogenous metabolites were detected in plasma by gas chromatography-tandem mass spectrometry (GC-MS/MS). Each time group was separated from each other on the principal component analysis (PCA) score plot, suggesting that the various endogenous metabolites changed with time after death. To prepare a prediction model of a PMI, a partial least squares (or projection to latent structure, PLS) regression model was constructed using the levels of significantly different metabolites determined by variable importance in the projection (VIP) score and the Kruskal-Wallis test (P < 0.05). Because the constructed PLS regression model could successfully predict each PMI, this model was validated with another validation set (n = 3). In conclusion, plasma metabolic profiling demonstrated its ability to successfully estimate PMI under a certain condition. This result can be considered to be the first step for using the metabolomics method in future forensic casework.

Human plasma lipidome is pleiotropically associated with cardiovascular risk factors and death

BACKGROUND

Cardiovascular disease (CVD) is the most common cause of death in the United States and is associated with a high economic burden. Prevention of CVD focuses on controlling or improving the lipid profile of patients at risk. The human lipidome is made up of thousands of ubiquitous lipid species. By studying biologically simple canonical lipid species, we investigated whether the lipidome is genetically redundant and whether its genetic influences can provide clinically relevant clues of CVD risk.

METHODS AND RESULTS

We performed a genetic study of the human lipidome in 1212 individuals from 42 extended Mexican American families. High-throughput mass spectrometry enabled rapid capture of precise lipidomic profiles, providing 319 unique species. Using variance component-based heritability analyses and bivariate trait analyses, we detected significant genetic influences on each lipid assayed. Median heritability of the plasma lipid species was 0.37. Hierarchical clustering based on complex genetic correlation patterns identified 12 genetic clusters that characterized the plasma lipidome. These genetic clusters were differentially but consistently associated with risk factors of CVD, including central obesity, obesity, type 2 diabetes mellitus, raised serum triglycerides, and metabolic syndrome. Also, these clusters consistently predicted occurrence of cardiovascular deaths during follow-up.

CONCLUSIONS

The human plasma lipidome is heritable. Shared genetic influences reduce the dimensionality of the human lipidome into clusters that are associated with risk factors of CVD.

Laboratory evaluation and metabolomics in inflammatory bowel disease

Diagnosis and prognosis of inflammatory bowel disease (IBD) remain a challenge for physicians, and they are often based on history, clinical symptoms and endoscopic, histological, radiological and laboratory findings. Studies have shown that metabolomics may have important value in the diagnosis and prognosis of IBD. This paper will review the latest progress in laboratory evaluation and metabolomics in IBD.

Personalized nutrition and obesity

The past few decades have witnessed a rapid rise in nutrition-related disorders such as obesity in the United States and over the world. Traditional nutrition research has associated various foods and nutrients with obesity. Recent advances in genomics have led to identification of the genetic variants determining body weight and related dietary factors such as intakes of energy and macronutrients. In addition, compelling evidence has lent support to interactions between genetic variations and dietary factors in relation to obesity and weight change. Moreover, recently emerging data from other 'omics' studies such as epigenomics and metabolomics suggest that more complex interplays between the global features of human body and dietary factors may exist at multiple tiers in affecting individuals' susceptibility to obesity; and a concept of 'personalized nutrition' has been proposed to integrate this novel knowledge with traditional nutrition research, with the hope ultimately to endorse person-centric diet intervention to mitigate obesity and related disorders.

Plasma metabonomics study on Chinese medicine syndrome evolution of heart failure rats caused by LAD ligation

BACKGROUND

Chinese medicine syndromes (Zheng) in many disease models are not clearly characterized or validated, and the concepts of Chinese medicine syndromes are confounding and controversial. Metabonomics has been applied to the evaluation and classification of the Chinese medicine syndromes both in clinical and nonclinical studies. In this study, we aim to investigate the evolution of the Chinese medicine syndrome in myocardial infarction induced heart failure and to confirm the feasibility of the Zheng classification by plasma metabonomics in a syndrome and disease combination animal model.

METHODS

The heart failure (HF) model was induced by ligation of the left anterior descending coronary artery (LAD) in Sprague-Dawley rats. The rats were divided into the following two groups: the HF model group (LAD ligation) and the sham operated group. GC-MS was used with pattern recognition technology and principal component analysis (PCA) to analyze the plasma samples at 4, 21 and 45 day after operation.

RESULTS

It was determined that the period from 7 to 28 days was the stable time window of ischemic heart failure with qi deficiency and blood stasis syndrome (QDBS), and the qi deficiency syndrome occurred at 1 to 4 days and 45 to 60 days after operation. The results exhibited 5 plasma metabolite changes in the same trend at 4 and 21 day after the LAD operation, 7 at 21 and 45 day, and 2 at 4 and 45 day. No metabolite showed the same change at all of the 3 time points. At day 21 (the QDBS syndrome time point) after operation, 4 plasma metabolites showed the same trends with the results of our previous study on patients with the blood stasis syndrome.

CONCLUSIONS

The syndrome diagnosis is reliable in the HF rat model in this study. Plasma metabolites can provide a basis for the evaluation of Chinese medicine syndrome animal models.

Aliphatic chain length by isotropic mixing (ALCHIM): determining composition of complex lipid samples by ¹H NMR spectroscopy

Quantifying the amounts and types of lipids present in mixtures is important in fields as diverse as medicine, food science, and biochemistry. Nuclear magnetic resonance (NMR) spectroscopy can quantify the total amounts of saturated and unsaturated fatty acids in mixtures, but identifying the length of saturated fatty acid or the position of unsaturation by NMR is a daunting challenge. We have developed an NMR technique, aliphatic chain length by isotropic mixing, to address this problem. Using a selective total correlation spectroscopy technique to excite and transfer magnetization from a resolved resonance, we demonstrate that the time dependence of this transfer to another resolved site depends linearly on the number of aliphatic carbons separating the two sites. This technique is applied to complex natural mixtures allowing the identification and quantification of the constituent fatty acids. The method has been applied to whole adipocytes demonstrating that it will be of great use in studies of whole tissues.

Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Study

Background—

The bulk of cardiovascular disease risk is not explained by traditional risk factors. Recent advances in mass spectrometry allow the identification and quantification of hundreds of lipid species. Molecular lipid profiling by mass spectrometry may improve cardiovascular risk prediction.

Methods and Results—

Lipids were extracted from 685 plasma samples of the prospective population-based Bruneck Study (baseline evaluation in 2000). One hundred thirty-five lipid species from 8 different lipid classes were profiled by shotgun lipidomics with the use of a triple-quadrupole mass spectrometer. Levels of individual species of cholesterol esters (CEs), lysophosphatidylcholines, phosphatidylcholines, phosphatidylethanolamines (PEs), sphingomyelins, and triacylglycerols (TAGs) were associated with cardiovascular disease over a 10-year observation period (2000–2010, 90 incident events). Among the lipid species with the strongest predictive value were TAGs and CEs with a low carbon number and double-bond content, including TAG(54:2) and CE(16:1), as well as PE(36:5) ( P =5.1×10 −7 , 2.2×10 −4 , and 2.5×10 −3 , respectively). Consideration of these 3 lipid species on top of traditional risk factors resulted in improved risk discrimination and classification for cardiovascular disease (cross-validated ΔC index, 0.0210 [95% confidence interval, 0.0010-0.0422]; integrated discrimination improvement, 0.0212 [95% confidence interval, 0.0031-0.0406]; and continuous net reclassification index, 0.398 [95% confidence interval, 0.175-0.619]). A similar shift in the plasma fatty acid composition was associated with cardiovascular disease in the UK Twin Registry (n=1453, 45 cases).

Conclusions—

This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease. Molecular lipid species constitute promising new biomarkers that outperform the conventional biochemical measurements of lipid classes currently used in clinics.

Plasma lipidome is independently associated with variability in metabolic syndrome in Mexican American families

Plasma lipidome is now increasingly recognized as a potentially important marker of chronic diseases, but the exact extent of its contribution to the interindividual phenotypic variability in family studies is unknown. Here, we used the rich data from the ongoing San Antonio Family Heart Study (SAFHS) and developed a novel statistical approach to quantify the independent and additive value of the plasma lipidome in explaining metabolic syndrome (MS) variability in Mexican American families recruited in the SAFHS. Our analytical approach included two preprocessing steps: principal components analysis of the high-resolution plasma lipidomics data and construction of a subject-subject lipidomic similarity matrix. We then used the Sequential Oligogenic Linkage Analysis Routines software to model the complex family relationships, lipidomic similarities, and other important covariates in a variance components framework. Our results suggested that even after accounting for the shared genetic influences, indicators of lipemic status (total serum cholesterol, TGs, and HDL cholesterol), and obesity, the plasma lipidome independently explained 22% of variability in the homeostatic model of assessment-insulin resistance trait and 16% to 22% variability in glucose, insulin, and waist circumference. Our results demonstrate that plasma lipidomic studies can additively contribute to an understanding of the interindividual variability in MS.

Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery

Metabolism represents the 'sharp end' of systems biology, because changes in metabolite concentrations are necessarily amplified relative to changes in the transcriptome, proteome and enzyme activities, which can be modulated by drugs. To understand such behaviour, we therefore need (and increasingly have) reliable consensus (community) models of the human metabolic network that include the important transporters. Small molecule 'drug' transporters are in fact metabolite transporters, because drugs bear structural similarities to metabolites known from the network reconstructions and from measurements of the metabolome. Recon2 represents the present state-of-the-art human metabolic network reconstruction; it can predict inter alia: (i) the effects of inborn errors of metabolism; (ii) which metabolites are exometabolites, and (iii) how metabolism varies between tissues and cellular compartments. However, even these qualitative network models are not yet complete. As our understanding improves so do we recognise more clearly the need for a systems (poly)pharmacology.

Serum and urine metabolomic fingerprinting in diagnostics of inflammatory bowel diseases

AIM: To evaluate the utility of serum and urine metabolomic analysis in diagnosing and monitoring of inflammatory bowel diseases (IBD).

METHODS: Serum and urine samples were collected from 24 patients with ulcerative colitis (UC), 19 patients with the Crohn’s disease (CD) and 17 healthy controls. The activity of UC was assessed with the Simple Clinical Colitis Activity Index, while the activity of CD was determined using the Harvey-Bradshaw Index. The analysis of serum and urine samples was performed using proton nuclear magnetic resonance (NMR) spectroscopy. All spectra were exported to Matlab for preprocessing which resulted in two data matrixes for serum and urine. Prior to the chemometric analysis, both data sets were unit variance scaled. The differences in metabolite fingerprints were assessed using partial least-squares-discriminant analysis (PLS-DA). Receiver operating characteristic curves and area under curves were used to evaluate the quality and prediction performance of the obtained PLS-DA models. Metabolites responsible for separation in models were tested using STATISTICA 10 with the Mann-Whitney-Wilcoxon test and the Student’s t test (α = 0.05).

RESULTS: The comparison between the group of patients with active IBD and the group with IBD in remission provided good PLS-DA models (P value 0.002 for serum and 0.003 for urine). The metabolites that allowed to distinguish these groups were: N-acetylated compounds and phenylalanine (up-regulated in serum), low-density lipoproteins and very low-density lipoproteins (decreased in serum) as well as glycine (increased in urine) and acetoacetate (decreased in urine). The significant differences in metabolomic profiles were also found between the group of patients with active IBD and healthy control subjects providing the PLS-DA models with a very good separation (P value < 0.001 for serum and 0.003 for urine). The metabolites that were found to be the strongest biomarkers included in this case: leucine, isoleucine, 3-hydroxybutyric acid, N-acetylated compounds, acetoacetate, glycine, phenylalanine and lactate (increased in serum), creatine, dimethyl sulfone, histidine, choline and its derivatives (decreased in serum), as well as citrate, hippurate, trigonelline, taurine, succinate and 2-hydroxyisobutyrate (decreased in urine). No clear separation in PLS-DA models was found between CD and UC patients based on the analysis of serum and urine samples, although one metabolite (formate) in univariate statistical analysis was significantly lower in serum of patients with active CD, and two metabolites (alanine and N-acetylated compounds) were significantly higher in serum of patients with CD when comparing jointly patients in the remission and active phase of the diseases. Contrary to the results obtained from the serum samples, the analysis of urine samples allowed to distinguish patients with IBD in remission from healthy control subjects. The metabolites of importance included in this case up-regulated acetoacetate and down-regulated citrate, hippurate, taurine, succinate, glycine, alanine and formate.

CONCLUSION: NMR-based metabolomic fingerprinting of serum and urine has the potential to be a useful tool in distinguishing patients with active IBD from those in remission.