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

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.

Mass spectrometry meets the challenge of understanding the complexity of the lipoproteome: recent findings regarding proteins involved in dyslipidemia and cardiovascular disease

Despite the fact that link between dyslipidemia and atherosclerosis was made over 100 years ago, atherosclerosis remains a major cause of morbidity and mortality worldwide. Major efforts focus towards understanding lipid metabolism, particularly by studying its particle compartments in circulation: the lipoproteins. In recent years, mass spectrometry has played an integral role in the deep sequencing of the lipoproteome and in metabolism studies conducted in vivo. This review highlights the path of lipoprotein research towards state-of-the-art mass spectrometry with special emphasis on the method of selected reaction monitoring and its impact on apolipoprotein metabolism studies. Also presented is what is expected for the lipoprotein field with the recent advent of high resolution/accurate mass parallel reaction monitoring mass spectrometry. The benefits of high resolution/accurate mass measurements are demonstrated by example instrument workflows and by detailing a novel method to quantify very low levels of circulating proprotein convertase subtilisin-kexin type 9 in rabbit. It is anticipated that future clinical studies or clinical trials aimed to treat dyslipidemia by manipulating key regulatory proteins will benefit from the new and exciting opportunities afforded by the latest technologies in mass spectrometry.

Postprandial Plasma Phospholipids in Men Are Influenced by the Source of Dietary Fat

BACKGROUND

Postprandial lipemia represents a risk factor for chronic diseases, including type 2 diabetes. Little is known about the effect of dietary fat on the plasma lipidome in the postprandial period.

OBJECTIVE

The objective of this study was to assess the effect of dairy fat and soy oil on circulating postprandial lipids in men.

METHODS

Men (40-60 y old, nonsmokers; n = 16) were randomly assigned in a crossover design to consume 2 breakfast meals of dairy-based or soy oil-based foods. The changes in the plasma lipidome during the 4-h postprandial period were analyzed with electrospray ionization tandem mass spectrometry and included 316 lipid species in 23 classes and subclasses, representing sphingolipids, phospholipids, glycerolipids, and sterols.

RESULTS

Nonparametric Friedman tests showed significant changes in multiple plasma lipid classes, subclasses, and species in the postprandial period after both dairy and soy meals. No difference was found in triglyceridemia after each meal. However, 6 endogenous lipid classes increased after dairy but decreased after soy (P < 0.05), including ether-linked phospholipids and plasmalogens and sphingomyelin (not present in soy), dihexosylceramide, and GM3 ganglioside. Phosphatidylcholine and phosphatidylinositol were not affected by the soy meal but were significantly elevated after the dairy meal (8.3% and 16%, respectively; P < 0.05).

CONCLUSIONS

The changes in postprandial plasma phospholipids in men relate to the diet composition and the relative size of the endogenous phospholipid pools. Despite similar lipemic responses as measured by changes in triglyceride concentrations, the differential responses to dairy and soy meals derived through lipidomic analysis of phospholipids suggest differences in the metabolism of soybean oil and dairy fat. The increased concentrations of plasmalogens, with potential antioxidant capacity, in the postprandial period after dairy but not soy meals may represent a further important difference in the response to these sources of fat. The trial was registered at www.anzctr.org.au as ACTRN12610000562077.

Lipidomics: quest for molecular lipid biomarkers in cardiovascular disease

Lipidomics is the comprehensive analysis of molecular lipid species, including their quantitation and metabolic pathways. The huge diversity of native lipids and their modifications make lipidomic analyses challenging. The method of choice for sensitive detection and quantitation of molecular lipid species is mass spectrometry, either by direct infusion (shotgun lipidomics) or coupled with liquid chromatography. Although shotgun lipidomics allows for high-throughput analysis, low-abundant lipid species are not detected. Previous separation of lipid species by liquid chromatography increases ionization efficiency and is better suited for quantifying low abundant and isomeric lipid species. In this review, we will discuss the potential of lipidomics for cardiovascular research. To date, cardiovascular research predominantly focuses on the role of lipid classes rather than molecular entities. An in-depth knowledge about the molecular lipid species that contribute to the pathophysiology of cardiovascular diseases may provide better biomarkers and novel therapeutic targets for cardiovascular disease.

An automated shotgun lipidomics platform for high throughput, comprehensive, and quantitative analysis of blood plasma intact lipids

Blood plasma has gained protagonism in lipidomics studies due to its availability, uncomplicated collection and preparation, and informative readout of physiological status. At the same time, it is also technically challenging to analyze due to its complex lipid composition affected by many factors, which can hamper the throughput and/or lipidomics coverage. To tackle these issues, we developed a comprehensive, high throughput, and quantitative mass spectrometry-based shotgun lipidomics platform for blood plasma lipid analyses. The main hallmarks of this technology are (i) it is comprehensive, covering 22 quantifiable different lipid classes encompassing more than 200 lipid species; (ii) it is amenable to high-throughput, with less than 5 min acquisition time allowing the complete analysis of 200 plasma samples per day; (iii) it achieves absolute quantification, by inclusion of internal standards for every lipid class measured; (iv) it is highly reproducible, achieving an average coefficient of variation of <10% (intra-day), approx. 10% (inter-day), and approx. 15% (inter-site) for most lipid species; (v) it is easily transferable allowing the direct comparison of data acquired in different sites. Moreover, we thoroughly assessed the influence of blood stabilization with different anticoagulants and freeze-thaw cycles to exclude artifacts generated by sample preparation.

Practical applications: This shotgun lipidomics platform can be implemented in different laboratories without compromising reproducibility, allowing multi-site studies and inter-laboratory comparisons. This possibility combined with the high-throughput, broad lipidomic coverage and absolute quantification are important aspects for clinical applications and biomarker research.

Metabolomic signature of arterial stiffness in male patients with peripheral arterial disease

Arterial stiffness is an independent determinant of cardiovascular risk and a marker of subclinical organ damage. Metabolomics may facilitate identification of novel low-molecular cardiovascular risk factors. The aim of the present study was to compare metabolic signatures and functional-biochemical characteristics of patients with peripheral arterial disease (PAD) and clinically healthy subjects. We studied 42 men with symptomatic PAD (aged 66±7 years) and 46 healthy men (aged 66±8 years). Aortic pulse wave velocity (aPWV) was assessed by applanation tonometry using the Sphygmocor device. Metabolic profiling was performed with high-performance liquid chromatography and mass spectrometry. Serum oxidized low-density lipoprotein (oxLDL) level was measured by enzyme-linked immunosorbent assay. The aPWV as well as serum levels of lactate, free carnitine and 11 amino acids including tyrosine were higher among the patients with PAD. In contrast, serum levels of pyruvate, citrate, α-ketoglutarate, aconitate and cysteine were higher in the control group. In multiple regression models, aPWV was independently determined by log-tyrosine and log-oxLDL in the patients (R(2)=0.61; P<0.001) and by age, log-pyruvate and log-oxLDL in the controls (R(2)=0.52; P<0.001). Our study describes for the first time significant differences in metabolomic signature of patients with advanced atherosclerosis compared with clinically healthy controls. The aPWV is independently associated with serum levels of tyrosine and oxLDL in the patients with PAD and is related to pyruvate and oxLDL levels in the control group. The measurement of low-molecular metabolites, which are related to changes in vascular phenotypes, may lead to identification of novel vascular risk markers.

Mechanistic insights revealed by lipid profiling in monogenic insulin resistance syndromes

Background

Evidence from several recent metabolomic studies suggests that increased concentrations of triacylglycerols with shorter (14–16 carbon atoms), saturated fatty acids are associated with insulin resistance and the risk of type 2 diabetes. Although causality cannot be inferred from association studies, patients in whom the primary cause of insulin resistance can be genetically defined offer unique opportunities to address this challenge.

Methods

We compared metabolite profiles in patients with congenital lipodystrophy or loss-of-function insulin resistance (INSR gene) mutations with healthy controls.

Results

The absence of significant differences in triacylglycerol species in the INSR group suggest that changes previously observed in epidemiological studies are not purely a consequence of insulin resistance. The presence of triacylglycerols with lower carbon numbers and high saturation in patients with lipodystrophy suggests that these metabolite changes may be associated with primary adipose tissue dysfunction. The observed pattern of triacylglycerol species is indicative of increased de novo lipogenesis in the liver. To test this we investigated the distribution of these triacylglycerols in lipoprotein fractions using size exclusion chromatography prior to mass spectrometry. This associated these triacylglycerols with very low-density lipoprotein particles, and hence release of triacylglycerols into the blood from the liver. To test further the hepatic origin of these triacylglycerols we induced de novo lipogenesis in the mouse, comparing ob/ob and wild-type mice on a chow or high fat diet, confirming that de novo lipogenesis induced an increase in relatively shorter, more saturated fatty acids.

Conclusions

Overall, these studies highlight hepatic de novo lipogenesis in the pathogenesis of metabolic dyslipidaemia in states where energy intake exceeds the capacity of adipose tissue.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0179-6) contains supplementary material, which is available to authorized users.

Effects of choline on health across the life course: a systematic review

CONTEXT

Choline is a precursor of both betaine and acetylcholine and might, therefore, influence cardiovascular and cognitive outcomes. There has been concern, however, that it may influence blood lipid levels because it is an essential component of very-low-density lipoproteins.

OBJECTIVE

The aim was to systematically review, using PRISMA guidelines, the literature pertaining to the effects of choline on body composition and on metabolic, cardiovascular, respiratory, and neurological outcomes in different life stages.

DATA SOURCES

The MEDLINE, Embase, Cochrane Central, Web of Science, PubMed, and Google Scholar databases were searched up to July 2014.

DATA EXTRACTION

Fifty relevant articles were identified. These comprised trials and cohort, case-control, and cross-sectional studies that assessed blood levels of choline, dietary intake of choline, and supplementation with choline in a population free of diseases at baseline.

DATA SYNTHESIS

There is some observational evidence that choline during pregnancy may be beneficial for the neurological health of the child. In adults, choline may have beneficial effects on cognition, but high-quality (intervention) studies are lacking. Results on the effects of choline on body composition, blood lipids, and cardiovascular health were inconsistent.

CONCLUSIONS

Evidence to confirm the suggested effects of choline on health in different stages of life is scarce. Potential effects of choline need to be confirmed by intervention studies. Possible harmful effects on cardiometabolic health need careful evaluation.

Lipidomic profiling at the interface of metabolic surgery and cardiovascular disease

Bariatric surgery has helped patients attain not only significant and sustained weight loss but has also proved to be an effective means of mitigating or reversing various obesity-related comorbidities. The impressive rates of remission or resolution of type 2 diabetes mellitus (T2D) following bariatric surgery are well documented and have rightly received great attention. Less understood are the effects of bariatric surgery on cardiovascular disease (CVD) and its underlying risk factors. Thanks to the availability of increasingly sensitive laboratory tools, the emerging science of lipidomics and metagenomics is poised to offer significant contributions to our understanding of metabolically induced vascular diseases. They are set to identify novel mechanisms explaining how the varied approaches of bariatric surgery produce the remarkable improvements in multiple organs observed during patient follow-up. This article reviews recent and novel findings in patients through the lens of lipidomics with an emphasis on CVD.

Identification of metabolic markers in coronary artery disease using an untargeted LC-MS based metabolomic approach

Coronary artery disease (CAD), a complex metabolic disorder, is one of the largest causes of death worldwide. Both environmental and genetic factors contribute to the etiology of this metabolic disease. The gene-environment interaction could lead to modulation of various metabolic pathways resulting in altered levels of various metabolites. Thus, identifying metabolites could aid in deciphering pathways that could be involved in the pathophysiology of the disease. With the advent of high resolution mass spectrometry based methodologies, it is now possible to screen thousands of metabolites in a single snapshot thus, allowing the identification of potential disease metabolite markers. In this work, using an untargeted metabolomic approach, we attempted to identify metabolites that have altered levels in CAD patients. Using reverse phase and HILIC based chromatography followed by mass spectrometry we identified a total of 32 metabolites (2 fold; p<0.05) in plasma whose levels were significantly altered in CAD samples. Further, we have validated the discriminative ability of these metabolites in an independent set of CAD and control samples using multivariate PLS-DA analysis. Interestingly, Lyso PC (18:0), Cortisol, Lyso PC (P-17:0), and glycerophosphocholine were among the top discriminators for CAD which implies involvement of phosphatidylcholine pathway in the pathogenesis of atherosclerosis.

BIOLOGICAL SIGNIFICANCE

Herein, we report that an unbiased metabolomic study has the potential to identify newer markers which are involved in several important biological pathways like lipid metabolism, phosphatidylcholine pathway etc. which in turn are implicated in CAD. These markers could be of potential clinical importance for screening subjects at risk of CAD. This article is part of a Special Issue entitled: Proteomics in India.

Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts

BACKGROUND

High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.

METHODS AND RESULTS

We applied quantitative nuclear magnetic resonance metabolomics to identify the biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the National Finnish FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the Southall and Brent Revisited (SABRE) study (n=2622; 573 events) and British Women's Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes mellitus, and medication. When further adjusting for routine lipids, 4 metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation, 1.18; 95% confidence interval, 1.12-1.24; P=4×10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P=1×10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P=6×10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P=5×10(-5)) were associated with lower risk. A risk score incorporating these 4 biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the 2 validation cohorts (relative integrated discrimination improvement, 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5% to 10% risk range (net reclassification, 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).

CONCLUSIONS

Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated fatty acids, and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.

Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease

Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 (hazard ratio [HR] per standard deviation [SD] increment = 0.77, P-value<0.001), lysophosphatidylcholine 18∶2 (HR = 0.81, P-value<0.001), monoglyceride 18∶2 (MG 18∶2; HR = 1.18, P-value = 0.011) and sphingomyelin 28∶1 (HR = 0.85, P-value = 0.015)]. Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors (C-statistic: 0.76 vs. 0.75; NRI: 9.2%). MG 18∶2 was associated with CHD independently of triglycerides. Lysophosphatidylcholines were negatively associated with body mass index, C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2. MG 18∶2 showed an enrichment (P-value = 0.002) of significant associations with CHD-associated SNPs (P-value = 1.2×10⁻⁷ for association with rs964184 in the ZNF259/APOA5 region) and a weak, but positive causal effect (odds ratio = 1.05 per SD increment in MG 18∶2, P-value = 0.05) on CHD, as suggested by Mendelian randomization analysis. In conclusion, we identified four lipid-related metabolites with evidence for clinical utility, as well as a causal role in CHD development.

Non-targeted metabolomic profiling of large population-based studies has become feasible only in the past 1–2 years and this hypothesis-free exploration of the metabolome holds a great potential to fuel the discovery of novel biomarkers for coronary heart disease (CHD). Such biomarkers are not only important for risk stratification and treatment decisions, but can also improve understanding of cardiovascular disease pathophysiology to identify new drug targets. In this study, we investigated the metabolic profiles of more than 3,600 individuals from three population-based studies, and discovered four metabolites that are consistently associated with incident CHD. We integrate genetic and metabolomic analysis to delineate the underlying biological mechanisms and evaluate potential causal effects of the novel biomarkers. Specifically, we found one metabolite to be strongly associated with single nucleotides polymorphisms previously reported for association with CHD, and consistent with a potential causal role in CHD development, as suggested by Mendelian randomization analysis.