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

Comprehensive Metabolomic Characterization of Coronary Artery Diseases

BACKGROUND

Pathogenesis and diagnostic biomarkers for diseases can be discovered by metabolomic profiling of human fluids. If the various types of coronary artery disease (CAD) can be accurately characterized by metabolomics, effective treatment may be targeted without using unnecessary therapies and resources.

OBJECTIVES

The authors studied disturbed metabolic pathways to assess the diagnostic value of metabolomics-based biomarkers in different types of CAD.

METHODS

A cohort of 2,324 patients from 4 independent centers was studied. Patients underwent coronary angiography for suspected CAD. Groups were divided as follows: normal coronary artery (NCA), nonobstructive coronary atherosclerosis (NOCA), stable angina (SA), unstable angina (UA), and acute myocardial infarction (AMI). Plasma metabolomic profiles were determined by liquid chromatography-quadrupole time-of-flight mass spectrometry and were analyzed by multivariate statistics.

RESULTS

We made 12 cross-comparisons to and within CAD to characterize metabolic disturbances. We focused on comparisons of NOCA versus NCA, SA versus NOCA, UA versus SA, and AMI versus UA. Other comparisons were made, including SA versus NCA, UA versus NCA, AMI versus NCA, UA versus NOCA, AMI versus NOCA, AMI versus SA, significant CAD (SA/UA/AMI) versus nonsignificant CAD (NCA/NOCA), and acute coronary syndrome (UA/AMI) versus SA. A total of 89 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism, increased amino acid metabolism, increased short-chain acylcarnitines, decrease in tricarboxylic acid cycle, and less biosynthesis of primary bile acid. For differential diagnosis, 12 panels of specific metabolomics-based biomarkers provided areas under the curve of 0.938 to 0.996 in the discovery phase (n = 1,086), predictive values of 89.2% to 96.0% in the test phase (n = 933), and 85.3% to 96.4% in the 3-center external sets (n = 305).

CONCLUSIONS

Plasma metabolomics are powerful for characterizing metabolic disturbances. Differences in small-molecule metabolites may reflect underlying CAD and serve as biomarkers for CAD progression.

Muscle Sympathetic Nerve Activity Is Associated With Elements of the Plasma Lipidomic Profile in Young Asian Adults

BACKGROUND

Asian subjects are at increased cardio-metabolic risk at comparatively lower body mass index (BMI) compared with white subjects. Sympathetic nervous system activation and dyslipidemia, both characteristics of increased adiposity, appear to be related. We therefore analyzed the association of muscle sympathetic nerve activity (MSNA) with the plasma lipidomic profile in young adult Asian and white subjects.

METHODS

Blood samples were collected from 101 participants of either Asian or white background (age, 18 to 30 years; BMI, 28.1 ± 5.9 kg/m2). Lipids were extracted from plasma and analyzed using electrospray ionization-tandem mass spectrometry. MSNA was quantified using microneurography. The association of MSNA and obesity with lipid species was examined using linear regression analysis.

RESULTS

The plasma concentrations of total dihydroceramide, ceramide, GM3 ganglioside, lysoalkylphosphatidylcholine, alkenylphosphatidylethanolamine, and lysophosphatidylinositol were elevated in the Asian subjects relative to the white subjects. After adjustment for confounders, diacylglycerols and triacylglycerols, cholesterol esters, phosphatidylinositols, phosphatidylethanolamines, and phosphatidylglycerols bore significant associations with MSNA but only in the Asian subjects. These associations remained significant after further adjustment for the participants' degree of insulin resistance and appeared not to be related to differences in diet macronutrient content between groups.

CONCLUSIONS

The lipidomic profile differs between Asian and white subjects. There exists a strong relationship between certain lipid species and MSNA. The association is stronger in Asian subjects, despite their lower BMI. This study demonstrates an association between circulating lipids and central sympathetic outflow. Whether the stronger association between the lipid profile and sympathetic activation underpins the apparent greater risk posed by increased adiposity in Asian individuals merits further attention.

Enzymatic lipid oxidation by eosinophils propagates coagulation, hemostasis, and thrombotic disease

Blood coagulation is essential for physiological hemostasis but simultaneously contributes to thrombotic disease. However, molecular and cellular events controlling initiation and propagation of coagulation are still incompletely understood. In this study, we demonstrate an unexpected role of eosinophils during plasmatic coagulation, hemostasis, and thrombosis. Using a large-scale epidemiological approach, we identified eosinophil cationic protein as an independent and predictive risk factor for thrombotic events in humans. Concurrent experiments showed that eosinophils contributed to intravascular thrombosis by exhibiting a strong endogenous thrombin-generation capacity that relied on the enzymatic generation and active provision of a procoagulant phospholipid surface enriched in 12/15-lipoxygenase-derived hydroxyeicosatetraenoic acid-phosphatidylethanolamines. Our findings reveal a previously unrecognized role of eosinophils and enzymatic lipid oxidation as regulatory elements that facilitate both hemostasis and thrombosis in response to vascular injury, thus identifying promising new targets for the treatment of thrombotic disease.

Plasma Ceramides, Mediterranean Diet, and Incident Cardiovascular Disease in the PREDIMED Trial (Prevención con Dieta Mediterránea)

BACKGROUND

Although in vitro studies and investigations in animal models and small clinical populations have suggested that ceramides may represent an intermediate link between overnutrition and certain pathological mechanisms underlying cardiovascular disease (CVD), no prospective studies have investigated the association between plasma ceramides and risk of CVD.

METHODS

The study population consisted of 980 participants from the PREDIMED trial (Prevención con Dieta Mediterránea), including 230 incident cases of CVD and 787 randomly selected participants at baseline (including 37 overlapping cases) followed for ≤7.4 years. Participants were randomized to a Mediterranean diet supplemented with extra virgin olive oil, a Mediterranean diet supplemented with nuts, or a control diet. Plasma ceramide concentrations were measured on a liquid chromatography tandem mass spectrometry metabolomics platform. The primary outcome was a composite of nonfatal acute myocardial infarction, nonfatal stroke, or cardiovascular death. Hazard ratios were estimated with weighted Cox regression models using Barlow weights to account for the case-cohort design.

RESULTS

The multivariable hazard ratios (HR) and 95% confidence intervals (CIs) comparing the extreme quartiles of plasma concentrations of C16:0, C22:0, C24:0, and C24:1 ceramides were 2.39 (1.49-3.83, Ptrend<0.001), 1.91 (1.21-3.01, Ptrend=0.003), 1.97 (1.21-3.20, Ptrend=0.004), and 1.73 (1.09-2.74, Ptrend=0.011), respectively. The ceramide score, calculated as a weighted sum of concentrations of four ceramides, was associated with a 2.18-fold higher risk of CVD across extreme quartiles (HR, 2.18; 95% CI, 1.36-3.49; Ptrend<0.001). The association between baseline ceramide score and incident CVD varied significantly by treatment groups (Pinteraction=0.010). Participants with a higher ceramide score and assigned to either of the 2 active intervention arms of the trial showed similar CVD risk to those with a lower ceramide score, whereas participants with a higher ceramide score and assigned to the control arm presented significantly higher CVD risk. Changes in ceramide concentration were not significantly different between Mediterranean diet and control groups during the first year of follow-up.

CONCLUSIONS

Our study documented a novel positive association between baseline plasma ceramide concentrations and incident CVD. In addition, a Mediterranean dietary intervention may mitigate potential deleterious effects of elevated plasma ceramide concentrations on CVD.

CLINICAL TRIAL REGISTRATION

URL: http://www.isrctn.com. Unique identifier: ISRCTN35739639.

Novel Risk Markers and Risk Assessments for Cardiovascular Disease

The use of risk markers has transformed cardiovascular medicine, exemplified by the routine assessment of troponin, for both diagnosis and assessment of prognosis in patients with chest pain. Clinical risk factors form the basis for risk assessment of cardiovascular disease and the addition of biochemical, cellular, and imaging parameters offers further refinement. Identifying novel risk factors may allow greater risk stratification and a steady, but gradual progression toward precision medicine. Indeed, the generation of data in this area of research is explosive and when combined with new technologies and techniques provides the potential for more refined, targeted approaches to cardiovascular medicine. Although discussing the most recent developments in this field, this review article aims to strike a balance between novelty and validity by focusing on recent large sample-size studies that have been validated in a separate cohort in most cases. Risk markers related to atherosclerosis, thrombosis, inflammation, cardiac injury, and fibrosis are introduced in the context of their pathophysiology. Rapidly developing new areas, such as assessment of micro-RNA, are also explored. Subsequently the prognostic ability of these risk markers in coronary artery disease, heart failure, and atrial fibrillation is discussed in detail.

Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine-N-oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine.

Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques

BACKGROUND. The identification of patients with high-risk atherosclerotic plaques prior to the manifestation of clinical events remains challenging. Recent findings question histology- and imaging-based definitions of the “vulnerable plaque,” necessitating an improved approach for predicting onset of symptoms.

METHODS. We performed a proteomics comparison of the vascular extracellular matrix and associated molecules in human carotid endarterectomy specimens from 6 symptomatic versus 6 asymptomatic patients to identify a protein signature for high-risk atherosclerotic plaques. Proteomics data were integrated with gene expression profiling of 121 carotid endarterectomies and an analysis of protein secretion by lipid-loaded human vascular smooth muscle cells. Finally, epidemiological validation of candidate biomarkers was performed in two community-based studies.

RESULTS. Proteomics and at least one of the other two approaches identified a molecular signature of plaques from symptomatic patients that comprised matrix metalloproteinase 9, chitinase 3-like-1, S100 calcium binding protein A8 (S100A8), S100A9, cathepsin B, fibronectin, and galectin-3-binding protein. Biomarker candidates measured in 685 subjects in the Bruneck study were associated with progression to advanced atherosclerosis and incidence of cardiovascular disease over a 10-year follow-up period. A 4-biomarker signature (matrix metalloproteinase 9, S100A8/S100A9, cathepsin D, and galectin-3-binding protein) improved risk prediction and was successfully replicated in an independent cohort, the SAPHIR study.

CONCLUSION. The identified 4-biomarker signature may improve risk prediction and diagnostics for the management of cardiovascular disease. Further, our study highlights the strength of tissue-based proteomics for biomarker discovery.

FUNDING. UK: British Heart Foundation (BHF); King’s BHF Center; and the National Institute for Health Research Biomedical Research Center based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London in partnership with King’s College Hospital. Austria: Federal Ministry for Transport, Innovation and Technology (BMVIT); Federal Ministry of Science, Research and Economy (BMWFW); Wirtschaftsagentur Wien; and Standortagentur Tirol.

Dynamic and temporal assessment of human dried blood spot MS/MSALL shotgun lipidomics analysis

BACKGROUND

Real-time and dynamic assessment of an individual's lipid homeostatic state in blood is complicated due to the need to collect samples in a clinical environment. In the context of precision medicine and population health, tools that facilitate sample collection and empower the individual to participate in the process are necessary to complement advanced bioanalytical analysis. The dried blood spot (DBS) methodology via finger prick or heel prick is a minimally invasive sample collection method that allows the relative ease and low cost of sample collection as well as transport. However, it has yet to be integrated into broad scale personalized lipidomic analysis. Therefore, in this study we report the development of a novel DBS high resolution MS/MSALL lipidomics workflow.

METHODS

In this report we compared lipidomic analysis of four types of blood sample collection methods (DBS, venous whole blood, serum, and plasma) across several parameters, which include lipidomics coverage of each matrix and the effects of temperature and time on the coverage and stability of different lipid classes and molecular species. The novel DBS-MS/MSALL lipidomics platform developed in this report was then applied to examine postprandial effects on the blood lipidome and further to explore the temporal fluctuation of the lipidome across hours and days.

RESULTS

More than 1,200 lipid molecular species from a single DBS sample were identified and quantified. The lipidomics profile of the DBS samples is comparable to whole blood matrix. DBS-MS/MSALL lipidomic analysis in postprandial experiments revealed significant alterations in triacylglyceride species. Temporal analysis of the lipidome at various times in the day and across days identified several lipid species that fluctuate as a function of time, and a subset of lipid species were identified to be significantly altered across hours within a day and within successive days of the week.

CONCLUSIONS

A novel DBS-MS/MSALL lipidomics method has been established for human blood. The feasibility and application of this method demonstrate the potential utility for lipidomics analysis in both healthy and diverse diseases states. This DBS MS-based lipidomics analysis represents a formidable approach for empowering patients and individuals in the era of precision medicine to uncover novel biomarkers and to monitor lipid homeostasis.

Metabolic profiles in heart failure due to non-ischemic cardiomyopathy at rest and under exercise

AIMS

Identification of metabolic signatures in heart failure (HF) patients and evaluation of their diagnostic potential to discriminate HF patients from healthy controls during baseline and exercise conditions.

METHODS

Plasma samples were collected from 22 male HF patients with non-ischemic idiopathic cardiomyopathy and left ventricular systolic dysfunction and 19 healthy controls before (t0), at peak (t1) and 1 h after (t2) symptom-limited cardiopulmonary exercise testing. Two hundred fifty-two metabolites were quantified by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC)-MS/MS-based metabolite profiling.

RESULTS

Plasma metabolite profiles clearly differed between HF patients and controls at t0 (P < 0.05). The metabolic signature of HF was characterized by decreased levels of complex lipids and fatty acids, notably phosphatidylcholines, cholesterol, and sphingolipids. Moreover, reduced glutamine and increased glutamate plasma levels, significantly increased purine degradation products, as well as signs of impaired glucose metabolism were observed. The metabolic differences increased strongly according to New York Heart Association functional class and the addition of three metabolites further improved prediction of exercise capacity (Q² = 0.24 to 0.35). Despite a high number of metabolites changing significantly with exercise (30.2% at t1/t0), the number of significant alterations between HF and controls was almost unchanged at t₁ and t₂ (30.7 and 29.0% vs. 31.3% at t₀) with a similar predictive group separation (Q² = 0.50 for t0, 0.52 for t1, and 0.56 for t2, respectively).

CONCLUSIONS

Our study identified a metabolic signature of non-ischemic HF with prominent changes in complex lipids including phosphatidylcholines, cholesterol, and sphingolipids. The metabolic changes were already evident at rest and largely preserved under exercise.

A Non-Targeted Liquid Chromatographic-Mass Spectrometric Metabolomics Approach for Association with Coronary Artery Disease: An Identification of Biomarkers for Depiction of Underlying Biological Mechanisms

Background

We performed non-targeted metabolomics analysis using liquid chromatography-mass spectrometry coupled technique to explore the biological mechanism of coronary artery disease (CAD) events for improved prediction.

Material/Methods

We studied the association of CAD events in 4092 individuals and observed the replication of sphingomyelin (28:1), lysophosphatidylcholine (18:2), lysophosphatidylcholine (18:1), and monoglyceride (18:2), which were independent of main CAD risk factors.

Results

We found that these 4 metabolites were responsible for traditional risk factors and also contributed to the modifications related to reclassification and discrimination. Monoglycerides (MonoGs) were positively associated with C-reactive proteins and body mass index, while lysophosphatidylcholines (LPPCs), which had less evidence of subclinical CAD in an additional 1010 participants, yielded a reverse pattern. An association between monoGs and CAD independence of triglycerides (triGs) were also observed. On the basis of Mendelian randomization analysis, we observed a positive but weak irregular effect (odds ratio per unit increase in standard deviation in monoG=1.11, P-value=0.05) on CAD.

Conclusions

Our work establishes the relationship of metabolome with coronary artery disease and explains the biological mechanism of CAD events, as we identified the above-mentioned metabolites along with the evidence supporting their clinical use.

Circulating MicroRNA-122 Is Associated With the Risk of New-Onset Metabolic Syndrome and Type 2 Diabetes

MicroRNA-122 (miR-122) is abundant in the liver and involved in lipid homeostasis, but its relevance to the long-term risk of developing metabolic disorders is unknown. We therefore measured circulating miR-122 in the prospective population-based Bruneck Study (n = 810; survey year 1995). Circulating miR-122 was associated with prevalent insulin resistance, obesity, metabolic syndrome, type 2 diabetes, and an adverse lipid profile. Among 92 plasma proteins and 135 lipid subspecies quantified with mass spectrometry, it correlated inversely with zinc-α-2-glycoprotein and positively with afamin, complement factor H, VLDL-associated apolipoproteins, and lipid subspecies containing monounsaturated and saturated fatty acids. Proteomics analysis of livers from antagomiR-122-treated mice revealed novel regulators of hepatic lipid metabolism that are responsive to miR-122 inhibition. In the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT, n = 155), 12-month atorvastatin reduced circulating miR-122. A similar response to atorvastatin was observed in mice and cultured murine hepatocytes. Over up to 15 years of follow-up in the Bruneck Study, multivariable adjusted risk ratios per one-SD higher log miR-122 were 1.60 (95% CI 1.30-1.96; P < 0.001) for metabolic syndrome and 1.37 (1.03-1.82; P = 0.021) for type 2 diabetes. In conclusion, circulating miR-122 is strongly associated with the risk of developing metabolic syndrome and type 2 diabetes in the general population.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis

INTRODUCTION

The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex).

METHODS

We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods.

RESULTS

We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R2 = 0.10, test data set) and brain atrophy (R2 ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines.

DISCUSSION

Blood lipids are promising AD biomarkers that may lead to new treatment strategies.

Austrian Lipid Consensus on the management of metabolic lipid disorders to prevent vascular complications: A joint position statement issued by eight medical societies. 2016 update

In 2010, eight Austrian medical societies proposed a joint position statement on the management of metabolic lipid disorders for the prevention of vascular complications. An updated and extended version of these recommendations according to the current literature is presented, referring to the primary and secondary prevention of vascular complications in adults, taking into consideration the guidelines of other societies. The "Austrian Lipid Consensus - 2016 update" provides guidance for individualized risk stratification and respective therapeutic targets, and discusses the evidence for reducing vascular endpoints with available lipid-lowering therapies. Furthermore, specific management in key patient groups is outlined, including subjects presenting with coronary, cerebrovascular, and/or peripheral atherosclerosis; diabetes mellitus and/or metabolic syndrome; nephropathy; and familial hypercholesterolemia.

Metabolomic Signature of Coronary Artery Disease in Type 2 Diabetes Mellitus

Coronary artery disease (CAD) is a common complication of type 2 diabetes mellitus (T2D). This case-control study was done to identify metabolites with different concentrations between T2D patients with and without CAD and to characterise implicated metabolic mechanisms relating to CAD. Fasting serum samples of 57 T2D subjects, 26 with (cases) and 31 without CAD (controls), were targeted for metabolite profiling of 163 metabolites. To assess the association between metabolite levels and CAD, partial least squares (PLS) analysis and multivariate logistic regression analysis with adjustment for CAD risk factors and medications were performed. We observed a separation of cases and controls with two classes of metabolites being significantly associated with CAD, including phosphatidylcholines, and serine. Four metabolites being independent from the common CAD risk factors displaying best separation between cases and controls were further selected. Addition of the metabolite concentrations to risk factor analysis raised the area under the receiver-operating-characteristic curve from 0.72 to 0.88 (p = 0.020), providing improved sensitivity and specificity for CAD classification. Serum phospholipid and serine levels independently discriminate T2D patients with and without CAD. Oxidative stress and reduced antioxidative capacity lead to lower metabolite concentrations probably due to changes in membrane composition and accelerated phospholipid degradation.

Blood triacylglycerols: a lipidomic window on diet and disease

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

Identifying new Risk Markers and Potential Targets for Coronary Artery Disease: The Value of the Lipidome and Metabolome

PURPOSE

This systematic review was performed to summarize published data on lipidomic and metabolomic risk markers of coronary artery disease.

METHODS

Studies were identified from a literature search of PubMed.

RESULTS

Published data shows that analysis of metabolites and lipids offers an opportunity to increase our knowledge of the biological processes related to development and progression of atherosclerotic coronary disease. It is evident that advanced analytical technologies are able to detect and identify a large number of molecules that may have important structural and functional roles over and above currently used biomarkers in the cardiovascular field. It is suggested in a number of reports that the novel biomarkers can be used to improve risk stratification and patient selection for different treatments. Also, monitoring treatment efficacy and safety as well as lifestyle changes should be facilitated by such novel markers.

CONCLUSION

Until now a plethora of biomarker candidates associated with cardiovascular event risk have been identified, but very few have passed through clinical and analytical validation and found their way into clinical use. Consequently, the appetite of physicians to use these novel tests in daily clinical routine has not yet been truly tested.

Inflammatory processes in cardiovascular disease: a route to targeted therapies

Inflammatory processes are firmly established as central to the development and complications of cardiovascular diseases. Elevated levels of inflammatory markers have been shown to be predictive of future cardiovascular events. The specific targeting of these processes in experimental models has been shown to attenuate myocardial and arterial injury, reduce disease progression, and promote healing. However, the translation of these observations and the demonstration of clear efficacy in clinical practice have been disappointing. A major limitation might be that tools currently used to measure 'inflammation' are insufficiently precise and do not provide information about disease site and activity, or discriminate between functionally important activation pathways. The challenge, therefore, is to make measures of inflammation that are more meaningful, and which can guide specific targeted therapies. In this Review, we consider the roles of inflammatory processes in the related pathologies of atherosclerosis and acute myocardial infarction, by providing an evaluation of the known and emerging inflammatory pathways. We highlight contemporary techniques to characterize and quantify inflammation, and consider how they might be used to guide specific treatments. Finally, we discuss emerging opportunities in the field, including their current limitations and challenges that are the focus of ongoing study.

Markers of sympathetic nervous system activity associate with complex plasma lipids in metabolic syndrome subjects

BACKGROUND AND AIMS

Plasma sphingolipids including ceramides, and gangliosides are associated with insulin resistance (IR) through effects on insulin signalling and glucose metabolism. Our studies of subjects with metabolic syndrome (MetS) showed close relationships between IR and sympathetic nervous system (SNS) activity including arterial norepinephrine (NE). We have therefore investigated possible associations of IR and SNS activity with complex lipids that are involved in both insulin sensitivity and neurotransmission.

METHODS

We performed a cross-sectional assessment of 23 lipid classes/subclasses (total 339 lipid species) by tandem mass spectrometry in 94 overweight untreated subjects with IR (quantified by HOMA-IR, Matsuda index and plasma insulin).

RESULTS

Independently of IR parameters, several circulating complex lipids associated significantly with arterial NE and NEFA (non-esterified fatty acids) and marginally with heart rate (HR). After accounting for BMI, HOMA-IR, systolic BP, age, gender, and correction for multiple comparisons, these associations were significant (p < 0.05): NE with ceramide, phosphatidylcholine, alkyl- and alkenylphosphatidylcholine and free cholesterol; NEFA with mono- di- and trihexosylceramide, G_M3 ganglioside, sphingomyelin, phosphatidylcholine, alkyl- and alkenylphosphatidylcholine, phosphatidylinositol and free cholesterol; HR marginally (p = or <0.1>0.05) with ceramide, G_M3 ganglioside, sphingomyelin, lysophosphatidylcholine, phosphatidylinositol, lysophosphatidylinositol and free cholesterol. Multiple subspecies of these lipids significantly associated with NE and NEFA. None of the IR biomarkers associated significantly with lipid classes/subclasses after correction for multiple comparisons.

CONCLUSIONS

This is the first demonstration that arterial norepinephrine and NEFA, that reflect both SNS activity and IR, associate significantly with circulating complex lipids independently of IR, suggesting a role for such lipids in neural mechanisms operating in MetS.

Identification of Shared and Unique Serum Lipid Profiles in Diabetes Mellitus and Myocardial Infarction

Background

Diabetes mellitus (DM) and cardiovascular disease are associated with dyslipidemia, but the detailed lipid molecular pattern in both diseases remains unknown.

Methods and Results

We used shotgun mass spectrometry to determine serum levels of 255 molecular lipids in 316 controls, 171 DM, and 99 myocardial infarction (MI) events from a cohort derived from the Malmö Diet and Cancer study. Orthogonal projections to latent structures analyses were conducted between the lipids and clinical parameters describing DM or MI. Fatty acid desaturases (FADS) and elongation of very long chain fatty acid protein 5 (ELOVL5) activities were estimated by calculating product to precursor ratios of polyunsaturated fatty acids in complex lipids. FADS genotypes encoding these desaturases were then tested for association with lipid levels and ratios. Differences in the levels of lipids belonging to the phosphatidylcholine and triacylglyceride (TAG) classes contributed the most to separating DM from controls. TAGs also played a dominating role in discriminating MI from controls. Levels of C18:2 fatty acids in complex lipids were lower both in DM and MI versus controls (DM, P=0.004; MI, P=6.0E‐06) at least due to an acceleration in the metabolic flux from C18:2 to C20:4 (eg, increased estimated ELOVL5: DM, P=0.02; MI, P=0.04, and combined elongase‐desaturase activities: DM, P=3.0E‐06; MI, P=2.0E‐06). Minor allele carriers of FADS genotypes were associated with increased levels of C18:2 (P≤0.007) and lower desaturase activity (P≤0.002).

Conclusions

We demonstrate a possible relationship between decreased levels of C18:2 in complex lipids and DM or MI. We thereby highlight the importance of molecular lipids in the pathogenesis of both diseases.

Liver microRNAs: potential mediators and biomarkers for metabolic and cardiovascular disease?

Recent discoveries have revealed that microRNAs (miRNAs) play a key role in the regulation of gene expression. In this review, we summarize the rapidly evolving knowledge about liver miRNAs (including miR-33, -33*, miR-223, -30c, -144, -148a, -24, -29, and -122) and their link to hepatic lipid metabolism, atherosclerosis and cardiovascular disease, non-alcoholic fatty liver disease, metabolic syndrome, and type-2 diabetes. With regards to its biomarker potential, the main focus is on miR-122 as the most abundant liver miRNA with exquisite tissue specificity. MiR-122 has been proposed to play a central role in the maintenance of lipid and glucose homeostasis and is consistently detectable in serum and plasma. This miRNA may therefore constitute a novel biomarker for cardiovascular and metabolic diseases.

Cardioprotection and lifespan extension by the natural polyamine spermidine

Aging is associated with an increased risk of cardiovascular disease and death. Here we show that oral supplementation of the natural polyamine spermidine extends the lifespan of mice and exerts cardioprotective effects, reducing cardiac hypertrophy and preserving diastolic function in old mice. Spermidine feeding enhanced cardiac autophagy, mitophagy and mitochondrial respiration, and it also improved the mechano-elastical properties of cardiomyocytes in vivo, coinciding with increased titin phosphorylation and suppressed subclinical inflammation. Spermidine feeding failed to provide cardioprotection in mice that lack the autophagy-related protein Atg5 in cardiomyocytes. In Dahl salt-sensitive rats that were fed a high-salt diet, a model for hypertension-induced congestive heart failure, spermidine feeding reduced systemic blood pressure, increased titin phosphorylation and prevented cardiac hypertrophy and a decline in diastolic function, thus delaying the progression to heart failure. In humans, high levels of dietary spermidine, as assessed from food questionnaires, correlated with reduced blood pressure and a lower incidence of cardiovascular disease. Our results suggest a new and feasible strategy for protection against cardiovascular disease.

A Novel Lipid Biomarker Panel for the Detection of Heart Failure with Reduced Ejection Fraction

OBJECTIVES

In this study we aimed to identify novel metabolomic biomarkers suitable for improved diagnosis of heart failure with reduced ejection fraction (HFrEF).

METHODS

We prospectively recruited 887 individuals consisting of HFrEF patients with either ischemic (ICMP, n = 257) or nonischemic cardiomyopathy (NICMP, n = 269), healthy controls (n = 327), and patients with pulmonary diseases (n = 34). A single-center identification (n = 238) was followed by a multicenter confirmation study (n = 649). Plasma samples from the single-center study were subjected to metabolite profiling analysis to identify metabolomic features with potential as HFrEF biomarkers. A dedicated analytical protocol was developed for the routine analysis of selected metabolic features in the multicenter cohort.

RESULTS

In the single-center study, 92 of 181 metabolomic features with known chemical identity (51%) were significantly changed in HFrEF patients compared to healthy controls (P <0.05). Three specific metabolomic features belonging to the lipid classes of sphingomyelins, triglycerides, and phosphatidylcholines were selected as the cardiac lipid panel (CLP) and analyzed in the multicenter study using the dedicated analytical protocol. The combination of the CLP with N-terminal pro-B-type natriuretic peptide (NT-proBNP) distinguished HFrEF patients from healthy controls with an area under the curve (AUC) of 0.97 (sensitivity 80.2%, specificity 97.6%) and was significantly superior compared to NT-proBNP alone (AUC = 0.93, sensitivity 81.7%, specificity 88.1%, P <0.001), even in the subgroups with mildly reduced left ventricular EF (0.94 vs 0.87; P <0.001) and asymptomatic patients (0.95 vs 0.91; P <0.05).

CONCLUSIONS

The new metabolomic biomarker panel has the potential to improve HFrEF detection, even in mild and asymptomatic stages. The observed changes further indicate lipid alterations in the setting of HFrEF.

Glycerophosphocholine Metabolites and Cardiovascular Disease Risk Factors in Adolescents: A Cohort Study

BACKGROUND

Glycerophosphocholine (GPC) metabolites modulate atherosclerosis and thus risk for cardiovascular disease (CVD). Preclinical CVD may start during adolescence. Here, we used targeted serum lipidomics to identify a new panel of GPCs, and tested whether any of these GPCs are associated, in adolescence, with classical risk factors of CVD, namely excess visceral fat (VF), elevated blood pressure, insulin resistance, and atherogenic dyslipidemia.

METHODS

We studied a population-based sample of 990 adolescents (12-18 years, 48% male), as part of the Saguenay Youth Study. Using liquid chromatography-electrospray ionization-mass spectrometry, we identified 69 serum GPCs within the 450 to 680 m/z range. We measured VF with MRI.

RESULTS

We identified several novel GPCs that were associated with multiple CVD risk factors. Most significantly, PC16:0/2:0 was negatively associated with VF (P=1.4×10^-19), blood pressure (P=7.7×10^-5), and fasting triacylglycerols (P=9.0×10^-5), and PC14:1/0:0 was positively associated with VF (P=3.0×10^-7), fasting insulin (P=5.4×10^-32), and triacylglycerols (P=1.4×10^-29). The Sobel test of mediation revealed that both GPCs mediated their respective relations between VF (as a potential primary exposure) and CVD risk factors (as outcomes, P values<1.3×10^-3). Furthermore, a GPC shown recently to predict incident coronary heart disease in older adults, PC18:2/0:0, was associated with several CVD risk factors in adolescents; these associations were less strong than those with the newly identified GPCs.

CONCLUSIONS

We identified novel GPCs strongly associated with multiple CVD risk factors in adolescents. These GPCs may be sensitive indicators of obesity-related risk for CVD outcomes in adults, and may improve biological understanding of CVD risk.

Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus

BACKGROUND

Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk.

METHODS

Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework.

RESULTS

Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species into the base model, showing an increase in the C statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762; P<0.0001) and a continuous net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease).

CONCLUSIONS

The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes mellitus.

CLINICAL TRIAL REGISTRATION

URL: https://clinicaltrials.gov. Unique identifier: NCT00145925.

Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology

Objective

Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.

Methods

The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.

Results

After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI).

Conclusion

Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring.

Lipidomic analyses in epidemiology

Clinical lipid measurements have been the mainstay of risk assessment for chronic disease since the Framingham study commenced over 60 years ago. Thousands of subsequent epidemiological studies have provided much insight into the relationship between plasma lipid profiles, health and disease. However, the human lipidome consists of thousands of individual lipid species, and current lipidomic technology presents us with an unprecedented opportunity to measure lipid phenotypes, representing genomic, metabolic, diet and lifestyle-related exposures, in large epidemiological studies. The number of epidemiological studies using lipidomic profiling is increasing and has the potential to provide improved biological and clinical insight into human disease. In this review, we discuss current lipidomic technologies, epidemiological studies using these technologies and the statistical approaches used in the analysis of the resulting data. We highlight the potential of integrating genomic and lipidomic datasets and discuss the future opportunities and challenges in this emerging field.

Vascular proteomics in metabolic and cardiovascular diseases

The vasculature is essential for proper organ function. Many pathologies are directly and indirectly related to vascular dysfunction, which causes significant morbidity and mortality. A common pathophysiological feature of diseased vessels is extracellular matrix (ECM) remodelling. Analysing the protein composition of the ECM by conventional antibody-based techniques is challenging; alternative splicing or post-translational modifications, such as glycosylation, can mask epitopes required for antibody recognition. By contrast, proteomic analysis by mass spectrometry enables the study of proteins without the constraints of antibodies. Recent advances in proteomic techniques make it feasible to characterize the composition of the vascular ECM and its remodelling in disease. These developments may lead to the discovery of novel prognostic and diagnostic markers. Thus, proteomics holds potential for identifying ECM signatures to monitor vascular disease processes. Furthermore, a better understanding of the ECM remodelling processes in the vasculature might make ECM-associated proteins more attractive targets for drug discovery efforts. In this review, we will summarize the role of the ECM in the vasculature. Then, we will describe the challenges associated with studying the intricate network of ECM proteins and the current proteomic strategies to analyse the vascular ECM in metabolic and cardiovascular diseases.

Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers

Aim: Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events. Results: A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC–MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed. Conclusion: Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.

Evidence from randomised controlled trials does not support current dietary fat guidelines: a systematic review and meta-analysis

OBJECTIVES

National dietary guidelines were introduced in 1977 and 1983, by the USA and UK governments, respectively, with the ambition of reducing coronary heart disease (CHD) mortality by reducing dietary fat intake. A recent systematic review and meta-analysis by the present authors, examining the randomised controlled trial (RCT) evidence available to the dietary committees during those time periods, found no support for the recommendations to restrict dietary fat. The present investigation extends our work by re-examining the totality of RCT evidence relating to the current dietary fat guidelines.

METHODS

A systematic review and meta-analysis of RCTs currently available, which examined the relationship between dietary fat, serum cholesterol and the development of CHD, was undertaken.

RESULTS

The systematic review included 62 421 participants in 10 dietary trials: 7 secondary prevention studies, 1 primary prevention and 2 combined. The death rates for all-cause mortality were 6.45% and 6.06% in the intervention and control groups, respectively. The risk ratio (RR) from meta-analysis was 0.991 (95% CI 0.935 to 1.051). The death rates for CHD mortality were 2.16% and 1.80% in the intervention and control groups, respectively. The RR was 0.976 (95% CI 0.878 to 1.084). Mean serum cholesterol levels decreased in all intervention groups and all but one control group. The reductions in mean serum cholesterol levels were significantly greater in the intervention groups; this did not result in significant differences in CHD or all-cause mortality.

CONCLUSIONS

The current available evidence found no significant difference in all-cause mortality or CHD mortality, resulting from the dietary fat interventions. RCT evidence currently available does not support the current dietary fat guidelines. The evidence per se lacks generalisability for population-wide guidelines.

Nutrigenomics, the Microbiome, and Gene-Environment Interactions: New Directions in Cardiovascular Disease Research, Prevention, and Treatment: A Scientific Statement From the American Heart Association

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention.

Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches

INTRODUCTION

Cardiovascular (CVD) risk assessment with traditional risk factors (age, sex, blood pressure, lipids, smoking and diabetes) has remained relatively invariant over the past decades despite some inaccuracies associated with this approach. However, the search for novel, robust and cost-effective risk markers of CVD risk is ongoing.

AREAS COVERED

A large share of the major developments in CVD risk prediction during the past five years has been made in large-scale biomarker discovery and the so called 'omics' - the rapidly growing fields of genomics, transcriptomics, epigenetics and metabolomics. This review focuses on how these new technologies are helping drive primary CVD risk estimation forward in recent years, and speculates on how they could be utilized more effectively for discovering novel risk factors in the future. Expert commentary: The search for new CVD risk factors is currently undergoing a significant revolution as the simple relationship between single risk factors and disease will have to be replaced by models that strive to integrate the whole field of omics into medicine.

Metabolomic Profiles of Body Mass Index in the Framingham Heart Study Reveal Distinct Cardiometabolic Phenotypes

Background

Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling.

Methods and Results

We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI) was associated with 69 of 217 metabolites (P<0.00023 for all), including aromatic (tyrosine, phenylalanine) and branched chain amino acids (valine, isoleucine, leucine). Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate), the tryptophan pathway (kynurenine, kynurenic acid), and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance [IR] and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine) were distinct from those associated with baseline glucose or other traits. Obesity status appeared to “modify” the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals.

Conclusions

In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance, and dyslipidemia, but not with fasting glucose or blood pressure traits.

Bioanalytical techniques in nontargeted clinical lipidomics

Lipidomic analysis aims at comprehensive characterization of molecular lipids in biological systems. Due to the central role of lipid metabolism in many devastating diseases, lipidomics is being increasingly applied in biomedical research. Over the past years, advances in analytical techniques and bioinformatics enabled increasingly comprehensive and accurate coverage of lipids both in tissues and biofluids, yet many challenges remain. This review highlights recent progress in the domain of analytical lipidomics, with main emphasis on non-targeted methodologies for large scale clinical applications, as well as discusses some of the key challenges and opportunities in this field.

Personalized Cardiovascular Disease Prediction and Treatment-A Review of Existing Strategies and Novel Systems Medicine Tools

Cardiovascular disease (CVD) continues to constitute the leading cause of death globally. CVD risk stratification is an essential tool to sort through heterogeneous populations and identify individuals at risk of developing CVD. However, applications of current risk scores have recently been shown to result in considerable misclassification of high-risk subjects. In addition, despite long standing beneficial effects in secondary prevention, current CVD medications have in a primary prevention setting shown modest benefit in terms of increasing life expectancy. A systems biology approach to CVD risk stratification may be employed for improving risk-estimating algorithms through addition of high-throughput derived omics biomarkers. In addition, modeling of personalized benefit-of-treatment may help in guiding choice of intervention. In the area of medicine, realizing that CVD involves perturbations of large complex biological networks, future directions in drug development may involve moving away from a reductionist approach toward a system level approach. Here, we review current CVD risk scores and explore how novel algorithms could help to improve the identification of risk and maximize personalized treatment benefit. We also discuss possible future directions in the development of effective treatment strategies for CVD through the use of genome-scale metabolic models (GEMs) as well as other biological network-based approaches.

Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX): A Combinatorial Multimolecular Omics Approach for Systems Biology

Interconnected molecular networks are at the heart of signaling pathways that mediate adaptive plasticity of eukaryotic cells. To gain deeper insights into the underlying molecular mechanisms, a comprehensive and representative analysis demands a deep and parallel coverage of a broad spectrum of molecular species. Therefore, we introduce a simultaneous metabolite, protein, lipid extraction (SIMPLEX) procedure, a novel strategy for the quantitative investigation of lipids, metabolites, and proteins. Compared with unimolecular workflows, SIMPLEX offers a fundamental turn in study design since multiple molecular classes can be accessed in parallel from one sample with equal efficiency and reproducibility. Application of this method in mass-spectrometry-based workflows allowed the simultaneous quantification of 360 lipids, 75 metabolites, and 3327 proteins from 10(6)cells. The versatility of this method is shown in a model system for adipogenesis- peroxisomal proliferator-activated receptor gamma (PPARG) signaling in mesenchymal stem cells-where we utilized SIMPLEX to explore cross-talk within and between all three molecular classes and identified novel potential molecular entry points for interventions, indicating that SIMPLEX provides a superior strategy compared with conventional workflows.

Meeting report from the 2nd International Symposium on New Frontiers in Cardiovascular Research. Protecting the cardiovascular system from ischemia: between bench and bedside

Recent advances in basic cardiovascular research as well as their translation into the clinical situation were the focus at the last "New Frontiers in Cardiovascular Research meeting". Major topics included the characterization of new targets and procedures in cardioprotection, deciphering new players and inflammatory mechanisms in ischemic heart disease as well as uncovering microRNAs and other biomarkers as versatile and possibly causal factors in cardiovascular pathogenesis. Although a number of pathological situations such as ischemia-reperfusion injury or atherosclerosis can be simulated and manipulated in diverse animal models, also to challenge new drugs for intervention, patient studies are the ultimate litmus test to obtain unequivocal information about the validity of biomedical concepts and their application in the clinics. Thus, the open and bidirectional exchange between bench and bedside is crucial to advance the field of ischemic heart disease with a particular emphasis of understanding long-lasting approaches in cardioprotection.

Hypercoagulation and elevation of blood triglycerides are characteristics of Kawasaki disease

Background

Cardiovascular damages poses risks to children with Kawasaki disease (KD). Although hypertriglyceridemia and hypercholesteremia are risk factors of cardiovascular damages, studies on the blood lipid metabolism in KD are still limited. This study aims to analyze the blood lipids and coagulation in KD.

Methods

Triglyceride (TG) and cholesterol levels in the plasma and serum from 20 children with KD were examined in comparison with 10 healthy children (HC) as well as 10 children with high fever from identified bacterial infections (BT). Using electrospray ionization mass spectrometry, we profiled the lipid species. Blood coagulation was analyzed. Statistics was analyzed by one-way ANOVA using SigmaStat.

Results

We found that in KD, plasma TG level was significantly increased, but not serum TG. A total of 19 molecular species of TG were identified, and they were all increased in KD and BT patients, and more pronounced in KD. On the other hand, major molecular species of plasma phosphotidylcholine and lyso-phosphotidylcholine were decreased in KD and BT. Pronounced hypercoagulation was found in KD blood.

Conclusion

Our data indicate hyperlipidemia in KD, especially for TG, which contributes to the hypercoagulation and the potential risk of cardiovascular damages. Evaluation of blood lipid levels in severe KD patients could provide valuable information for treatment and prognosis, thus would be worthy of consideration.

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-015-0167-2) contains supplementary material, which is available to authorized users.

Metabolic profiles of male meat eaters, fish eaters, vegetarians, and vegans from the EPIC-Oxford cohort

BACKGROUND

Human metabolism is influenced by dietary factors and lifestyle, environmental, and genetic factors; thus, men who exclude some or all animal products from their diet might have different metabolic profiles than meat eaters.

OBJECTIVE

We aimed to investigate differences in concentrations of 118 circulating metabolites, including acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, and sphingolipids related to lipid, protein, and carbohydrate metabolism between male meat eaters, fish eaters, vegetarians, and vegans from the Oxford arm of the European Prospective Investigation into Cancer and Nutrition.

DESIGN

In this cross-sectional study, concentrations of metabolites were measured by mass spectrometry in plasma from 379 men categorized according to their diet group. Differences in mean metabolite concentrations across diet groups were tested by using ANOVA, and a false discovery rate-controlling procedure was used to account for multiple testing. Principal component analysis was used to investigate patterns in metabolic profiles.

RESULTS

Concentrations of 79% of metabolites differed significantly by diet group. In the vast majority of these cases, vegans had the lowest concentration, whereas meat eaters most often had the highest concentrations of the acylcarnitines, glycerophospholipids, and sphingolipids, and fish eaters or vegetarians most often had the highest concentrations of the amino acids and a biogenic amine. A clear separation between patterns in the metabolic profiles of the 4 diet groups was seen, with vegans being noticeably different from the other groups because of lower concentrations of some glycerophospholipids and sphingolipids.

CONCLUSIONS

Metabolic profiles in plasma could effectively differentiate between men from different habitual diet groups, especially vegan men compared with men who consume animal products. The difference in metabolic profiles was mainly explained by the lower concentrations of glycerophospholipids and sphingolipids in vegans.

Utility of mass spectrometry for the diagnosis of the unstable coronary plaque

Mass spectrometry is a powerful technique that is used to identify unknown compounds, to quantify known materials, and to elucidate the structure and chemical properties of molecules. Recent advances in the accuracy and speed of the technology have allowed data acquisition for the global analysis of lipids from complex samples such as blood plasma or serum. Here, mass spectrometry as a tool is described, its limitations explained and its application to biomarker discovery in coronary artery disease is considered. In particular an application of mass spectrometry for the discovery of lipid biomarkers that may indicate plaque morphology that could lead to myocardial infarction is elucidated.

New and emerging biomarkers in cardiovascular disease

Cardiovascular disease (CVD) is the most common cause of death and disability worldwide. Therefore, great importance has been placed on the discovery of novel risk factors and metabolic pathways relevant in the prevention and management of CVD. Such research is ongoing and may continue to lead to better risk stratification of individuals and/or the development of new intervention targets and treatment options. This review highlights emerging biomarkers related to lipid metabolism, glycemia, inflammation, and cardiac damage, some of which show promising associations with CVD risk and provide further understanding of the underlying pathophysiology. However, their measurement methodology and assays will require validation and standardization, and it will take time to accumulate evidence of their role in CVD in various population settings in order to fully assess their clinical utility. Several of the novel biomarkers represent intriguing, potentially game-changing targets for therapy.

Recent advances in lipidomics for disease research

Lipidomics is an important branch of metabolomics, which aims at the detailed analysis of lipid species and their multiple roles in the living system. In recent years, the development of various analytical methods for effective identification and characterization of lipids has greatly promoted the process of lipidomics. Meanwhile, as many diseases demonstrate a remarkable alteration in lipid profiles compared with that of healthy people, lipidomics has been extensively introduced to disease research. The comprehensive lipid profiling provides a chance to discover novel biomarkers for specific disease. In addition, it plays a crucial role in the study of lipid metabolism, which could illuminate the pathogenesis of diseases. In this review, after brief discussion of analytical methods for lipidomics in clinical research, we focus on the recent advances of lipidomics related to four types of diseases, including cancer, atherosclerosis, diabetes mellitus, and Alzheimer's disease.

Lipidomics to Assess Omega 3 Bioactivity

How can we resolve the conflict between the strong epidemiological evidence pointing to the usefulness of fish—and, thus, omega 3—consumption with the debacle of supplementation trials? One potential explanation is that the null results obtained thus far are the consequences of ill-contrived investigations that do not allow us to conclude on the effects (or lack thereof) of omega 3 fatty acid supplementation. One potential solution is through the use of lipidomics, which should prove very useful to screen suitable patients and to correlate plasma (or red blood cells, or whole blood, or phospholipid) fatty acid profile with outcomes. This has never been done in omega 3 trials. The wise use of lipidomics should be essential part of future omega 3 trials and would help in untangling this current riddle.