Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis

Large-scale, comprehensive plasma metabolomic analyses reveal potential biomarkers for the diagnosis of early-stage coronary atherosclerosis

BACKGROUND

Coronary atherosclerosis (CAS) is a prevalent and chronic life-threatening disease. However, the detection of CAS at an early stage is difficult because of the lack of effective noninvasive diagnostic methods. The present study aimed to characterize the plasma metabolome of early-stage CAS patients to discover metabolomic biomarkers, develop a novel metabolite-based model for accurate noninvasive diagnosis of early-stage CAS, and explore the underlying metabolic mechanisms involved.

METHODS

A total of 100 patients with early-stage CAS and 120 age- and sex-matched control subjects were recruited from the Chinese Han population and further randomly divided into training (n = 120) and test sets (n = 100). The metabolomic profiles of the plasma samples were analyzed by an integrated untargeted liquid chromatography-mass spectrometry approach, including two separation modes and two ionization modes. Univariate and multivariate statistical analyses were employed to identify potential biomarkers and construct an early-stage CAS diagnostic model.

RESULTS

The integrated analytical method established herein improved metabolite coverage compared with single chromatographic separation and MS ionization mode. A total of 80 metabolites were identified as potential biomarkers of early-stage CAS, and these metabolites were mainly involved in glycerophospholipid, fatty acid, sphingolipid, and amino acid metabolism. An effective diagnostic model for early-stage CAS was established, incorporating 11 metabolites and achieving areas under the receiver operating characteristic curve (AUCs) of 0.984 and 0.908 in the training and test sets, respectively.

CONCLUSIONS

Our study not only successfully developed an effective noninvasive diagnostic model for identifying early-stage CAS but also provided novel insights into the pathogenesis of CAS.

Identification of Novel Biomarkers for Early Diagnosis of Atherosclerosis Using High-Resolution Metabolomics

Atherosclerosis (AS) is a metabolic disorder and the pre-stage of several cardiovascular diseases, including myocardial infarction, stroke, and angina pectoris. Early detection of AS can provide the opportunity for effective management and better clinical results, along with the prevention of further progression of the disease. In the current study, an untargeted and targeted metabolomic approach was used to identify possible metabolic signatures that have altered levels in AS patients. A total of 200 serum samples from individuals with AS and normal were analyzed via liquid chromatography-high-resolution mass spectrometry. Univariate and multivariate analysis approaches were used to identify differential metabolites. A group of metabolites associated with bile acids, amino acids, steroid hormones, and purine metabolism were identified that are capable of distinguishing AS-risk sera from normal. Further, the targeted metabolomics approach confirmed that six metabolites, namely taurocholic acid, cholic acid, cortisol, hypoxanthine, trimethylamine N-oxide (TMAO), and isoleucine, were found to be significantly upregulated, while the concentrations of glycoursodeoxycholic acid, glycocholic acid, testosterone, leucine, methionine, phenylalanine, tyrosine, and valine were found to be significantly downregulated in the AS-risk sera. The receiver operating characteristic curves of three metabolites, including cortisol, hypoxanthine, and isoleucine, showed high sensitivity and specificity. Taken together, these findings suggest cortisol, hypoxanthine, and isoleucine as novel biomarkers for the early and non-invasive detection of AS. Thus, this study provides new insights for further investigations into the prevention and management of AS.

Combining metabolomics and OCT to reveal plasma metabolic profiling and biomarkers of plaque erosion and plaque rupture in STEMI patients

OBJECTIVE

Plaque erosion (PE) and plaque rupture (PR) are the main subtypes of ST-segment elevation myocardial infarction (STEMI), the differences of metabolic patterns between PE and PR remain largely unknown.

METHODS

132 STEMI patients were divided into training set (PR, n = 36; PE, n = 36) and test set (PR, n = 30; PE, n = 30), the plasma from patients were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry.

RESULTS

We identified 56 and 28 differences in training and test set, respectively. Among these metabolites, it was found that docosahexaenoic acid (DHA), salicylic acid and proline were recognized in both tests. Receiver Operating Characteristic (ROC) analysis showed that the area under curve of docosahexaenoic acid (DHA) was 0.81 and 0.75 in training and test samples, respectively; proline was 0.67 and 0.74 in training and test samples, respectively; salicylic acid was 0.70 and 0.73 in training and test samples, respectively.

CONCLUSIONS

DHA, salicylic acid, and proline could be used as non-invasive biomarkers to differentiate PE and PR.

The Dark Side of Sphingolipids: Searching for Potential Cardiovascular Biomarkers

Cardiovascular diseases (CVDs) are the leading cause of death and illness in Europe and worldwide, responsible for a staggering 47% of deaths in Europe. Over the past few years, there has been increasing evidence pointing to bioactive sphingolipids as drivers of CVDs. Among them, most studies place emphasis on the cardiovascular effect of ceramides and sphingosine-1-phosphate (S1P), reporting correlation between their aberrant expression and CVD risk factors. In experimental in vivo models, pharmacological inhibition of de novo ceramide synthesis averts the development of diabetes, atherosclerosis, hypertension and heart failure. In humans, levels of circulating sphingolipids have been suggested as prognostic indicators for a broad spectrum of diseases. This article provides a comprehensive review of sphingolipids' contribution to cardiovascular, cerebrovascular and metabolic diseases, focusing on the latest experimental and clinical findings. Cumulatively, these studies indicate that monitoring sphingolipid level alterations could allow for better assessment of cardiovascular disease progression and/or severity, and also suggest them as a potential target for future therapeutic intervention. Some approaches may include the down-regulation of specific sphingolipid species levels in the circulation, by inhibiting critical enzymes that catalyze ceramide metabolism, such as ceramidases, sphingomyelinases and sphingosine kinases. Therefore, manipulation of the sphingolipid pathway may be a promising strategy for the treatment of cardio- and cerebrovascular diseases.

Serum metabolomic profiles associated with subclinical and clinical cardiovascular phenotypes in people with type 2 diabetes

BACKGROUND

Atherosclerotic cardiovascular diseases (CVD) is the leading cause of death in diabetes, but the full range of biomarkers reflecting atherosclerotic burden and CVD risk in people with diabetes is unknown. Metabolomics may help identify novel biomarkers potentially involved in development of atherosclerosis. We investigated the serum metabolomic profile of subclinical atherosclerosis, measured using ankle brachial index (ABI), in people with type 2 diabetes, compared with the profile for symptomatic CVD in the same population.

METHODS

The Edinburgh Type 2 Diabetes Study is a cohort of 1,066 individuals with type 2 diabetes. ABI was measured at baseline, years 4 and 10, with cardiovascular events assessed at baseline and during 10 years of follow-up. A panel of 228 metabolites was measured at baseline using nuclear magnetic resonance spectrometry, and their association with both ABI and prevalent CVD was explored using univariate regression models and least absolute shrinkage and selection operator (LASSO). Metabolites associated with baseline ABI were further explored for association with follow-up ABI and incident CVD.

RESULTS

Mean (standard deviation, SD) ABI at baseline was 0.97 (0.18, N = 1025), and prevalence of CVD was 35.0%. During 10-year follow-up, mean (SD) change in ABI was + 0.006 (0.178, n = 436), and 257 CVD events occurred. Lactate, glycerol, creatinine and glycoprotein acetyls levels were associated with baseline ABI in both univariate regression [βs (95% confidence interval, CI) ranged from - 0.025 (- 0.036, - 0.015) to - 0.023 (- 0.034, - 0.013), all p < 0.0002] and LASSO analysis. The associations remained nominally significant after adjustment for major vascular risk factors. In prospective analyses, lactate was nominally associated with ABI measured at years 4 and 10 after adjustment for baseline ABI. The four ABI-associated metabolites were all positively associated with prevalent CVD [odds ratios (ORs) ranged from 1.29 (1.13, 1.47) to 1.49 (1.29, 1.74), all p < 0.0002], and they were also positively associated with incident CVD [ORs (95% CI) ranged from 1.19 (1.02, 1.39) to 1.35 (1.17, 1.56), all p < 0.05].

CONCLUSIONS

Serum metabolites relating to glycolysis, fluid balance and inflammation were independently associated with both a marker of subclinical atherosclerosis and with symptomatic CVD in people with type 2 diabetes. Additional investigation is warranted to determine their roles as possible etiological and/or predictive biomarkers for atherosclerotic CVD.

Palmitic Acid, A Critical Metabolite, Aggravates Cellular Senescence Through Reactive Oxygen Species Generation in Kawasaki Disease

Coronary artery lesions (CALs) are severe complications of Kawasaki disease (KD), resulting in stenosis and thrombogenesis. Metabolomic profiling of patients’ plasma could assist in elucidating the pathogenesis of CALs and identifying diagnostic biomarkers, which are imperative for clinical treatment. The metabolic profiles between KD patients with CALs and without CALs (non-coronary artery lesion, or NCAL, group) indicated the most significantly differentially expressed metabolite, palmitic acid (PA), showed the most massive fold change at 9.879. Furthermore, PA was proven to aggravate endothelial cellular senescence by increasing the generation of reactive oxygen species (ROS) in KD, and those two phenotypes were confirmed to be enriched among the differentially expressed genes between KD and normal samples from GEO datasets. Collectively, our findings indicate that cellular senescence may be one of the mechanisms of vascular endothelial damage in KD. PA may be a biomarker and potential therapeutic target for predicting the occurrence of CALs in KD patients. All things considered, our findings confirm that plasma metabolomics was able to identify promising biomarkers and potential pathogenesis mechanisms in KD. To conclude, Palmitic acid could be a novel target in future studies of CALs in patients with KD.

Intestinal Flora: A Potential New Regulator of Cardiovascular Disease

Although substantial progress has been made in reducing the burden of the disease by preventing the risk factors of cardiovascular disease (CVD), potential risk factors still exist and lead to its progression. In recent years, numerous studies have revealed that intestinal flora can interfere with the physiological processes of the host through changes in composition and function or related metabolites. Intestinal flora thus affects the occurrence and development of a variety of CVDs, including atherosclerosis, ischemic heart disease, and heart failure. Moreover, studies have found that interventions for intestinal flora and its metabolites provide new opportunities for CVD treatment. This article mainly discusses the interaction between the human intestinal flora and its metabolites, the occurrence and development of CVD, and the potential of intestinal flora as a new target for the diagnosis and treatment of CVD.

COVID-19 In-Hospital Mortality in People with Diabetes Is Driven by Comorbidities and Age-Propensity Score-Matched Analysis of Austrian National Public Health Institute Data

BACKGROUND

It is a matter of debate whether diabetes alone or its associated comorbidities are responsible for severe COVID-19 outcomes. This study assessed the impact of diabetes on intensive care unit (ICU) admission and in-hospital mortality in hospitalized COVID-19 patients.

METHODS

A retrospective analysis was performed on a countrywide cohort of 40,632 COVID-19 patients hospitalized between March 2020 and March 2021. Data were provided by the Austrian data platform. The association of diabetes with outcomes was assessed using unmatched and propensity-score matched (PSM) logistic regression.

RESULTS

12.2% of patients had diabetes, 14.5% were admitted to the ICU, and 16.2% died in the hospital. Unmatched logistic regression analysis showed a significant association of diabetes (odds ratio [OR]: 1.24, 95% confidence interval [CI]: 1.15-1.34, p < 0.001) with in-hospital mortality, whereas PSM analysis showed no significant association of diabetes with in-hospital mortality (OR: 1.08, 95%CI: 0.97-1.19, p = 0.146). Diabetes was associated with higher odds of ICU admissions in both unmatched (OR: 1.36, 95%CI: 1.25-1.47, p < 0.001) and PSM analysis (OR: 1.15, 95%CI: 1.04-1.28, p = 0.009).

CONCLUSIONS

People with diabetes were more likely to be admitted to ICU compared to those without diabetes. However, advanced age and comorbidities rather than diabetes itself were associated with increased in-hospital mortality in COVID-19 patients.

Musk Tongxin Dripping Pills for treating Ticagrelor in Patients After Percutaneous Coronary Intervention: Echocardiography Combined with Untargeted Metabolomics

Objectives: As current clinical practice guidelines, ticagrelor is the suggested therapeutic scheme to prevent adverse cardiovascular events in acute myocardial infarction (AMI) patients undergoing percutaneous coronary intervention (PCI) treatment. However, this therapeutic strategy still fails, and around 30% patients display inadequate antiplatelet responses. Musk Tongxin Dripping Pill (MTDP) in Chinese hospital was usually considered as the combination with ticagrelor to improve the treatment effect. Unfortunately, the mechanism has not been elucidated.

Methods: The untargeted metabolomic method was introduced based on liquid chromatography–high-resolution mass spectrometry (HPLC-HRMS) coupled with STI for the research of the drug combination mechanism between ticagrelor and MTDP. 28 patients with a confirmed diagnosis of AMI were selectively collected, who were then divided into two different dosage regimen groups, and the serum samples were collected for the untargeted metabolomics assay. Then the differential metabolites were associated with blood biochemical indicators.

Results: The GLS values in both groups increased after treatment and those in the ticagrelor and MTDP combination group after treatment were higher than those in the ticagrelor group (p < 0.05), suggesting that the combination medication has better therapeutic effect on patients with myocardial infarction. From metabolomics analysis, the species of metabolites changed in two groups before and after treatment. Moreover, 93 differential metabolites changed in the drug combination group compared with the ticagrelor group after treatment (p < 0.05), which mainly related to changes in fatty acid metabolism pathways. Then the differential metabolites were found to be related with blood biochemical indicators, such as lipid, high-density lipoprotein (HDL), and low-density lipoprotein (LDL).

Conclusion: This work will provide a possible mechanism of the drug combination interaction between ticagrelor and MTDP from two angles of echocardiography and metabonomics. Several potential metabolic pathways were also found to have a relationship with MTDP, which will provide a new perspective in clinical medication.

Lipidomic Profiling Identifies Signatures of Poor Cardiovascular Health

Ideal cardiovascular health (CVH) is defined for the presence of ideal behavioral and health metrics known to prevent cardiovascular disease (CVD). The association of circulatory phospho- and sphingo-lipids to primary reduction in cardiovascular risk is unclear. Our aim was to determine the association of CVH metrics with the circulating lipid profile of a population-based cohort. Serum sphingolipid and phospholipid species were extracted from 461 patients of the randomly selected prospective Kardiovize study based on Brno, Czech Republic. Lipids species were measured by a hyphenated mass spectrometry technique, and were associated with poor CVH scores, as defined by the American Heart Association. Phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE) species were significantly lower in ideal and intermediate scores of health dietary metric, blood pressure, total cholesterol and blood fasting glucose compared to poor scores. Current smokers presented higher levels of PC, PE and LPE individual species compared to non-smokers. Ceramide (Cer) d18:1/14:0 was altered in poor blood pressure, total cholesterol and fasting blood glucose metrics. Poor cardiovascular health metric is associated with a specific phospho- and sphingolipid pattern. Circulatory lipid profiling is a potential biomarker to refine cardiovascular health status in primary prevention strategies.

Lipid Metabolite Biomarkers in Cardiovascular Disease: Discovery and Biomechanism Translation from Human Studies

Lipids represent a valuable target for metabolomic studies since altered lipid metabolism is known to drive the pathological changes in cardiovascular disease (CVD). Metabolomic technologies give us the ability to measure thousands of metabolites providing us with a metabolic fingerprint of individual patients. Metabolomic studies in humans have supported previous findings into the pathomechanisms of CVD, namely atherosclerosis, apoptosis, inflammation, oxidative stress, and insulin resistance. The most widely studied classes of lipid metabolite biomarkers in CVD are phospholipids, sphingolipids/ceramides, glycolipids, cholesterol esters, fatty acids, and acylcarnitines. Technological advancements have enabled novel strategies to discover individual biomarkers or panels that may aid in the diagnosis and prognosis of CVD, with sphingolipids/ceramides as the most promising class of biomarkers thus far. In this review, application of metabolomic profiling for biomarker discovery to aid in the diagnosis and prognosis of CVD as well as metabolic abnormalities in CVD will be discussed with particular emphasis on lipid metabolites.

Multi-omics approaches for revealing the complexity of cardiovascular disease

The development and progression of cardiovascular disease (CVD) can mainly be attributed to the narrowing of blood vessels caused by atherosclerosis and thrombosis, which induces organ damage that will result in end-organ dysfunction characterized by events such as myocardial infarction or stroke. It is also essential to consider other contributory factors to CVD, including cardiac remodelling caused by cardiomyopathies and co-morbidities with other diseases such as chronic kidney disease. Besides, there is a growing amount of evidence linking the gut microbiota to CVD through several metabolic pathways. Hence, it is of utmost importance to decipher the underlying molecular mechanisms associated with these disease states to elucidate the development and progression of CVD. A wide array of systems biology approaches incorporating multi-omics data have emerged as an invaluable tool in establishing alterations in specific cell types and identifying modifications in signalling events that promote disease development. Here, we review recent studies that apply multi-omics approaches to further understand the underlying causes of CVD and provide possible treatment strategies by identifying novel drug targets and biomarkers. We also discuss very recent advances in gut microbiota research with an emphasis on how diet and microbial composition can impact the development of CVD. Finally, we present various biological network analyses and other independent studies that have been employed for providing mechanistic explanation and developing treatment strategies for end-stage CVD, namely myocardial infarction and stroke.

Multi-omic signatures of atherogenic dyslipidaemia: pre-clinical target identification and validation in humans

BACKGROUND

Dyslipidaemia is a major risk factor for atherosclerosis and cardiovascular diseases. The molecular mechanisms that translate dyslipidaemia into atherogenesis and reliable markers of its progression are yet to be fully elucidated. To address this issue, we conducted a comprehensive metabolomic and proteomic analysis in an experimental model of dyslipidaemia and in patients with familial hypercholesterolemia (FH).

METHODS

Liquid chromatography/mass spectrometry (LC/MS) and immunoassays were used to find out blood alterations at metabolite and protein levels in dyslipidaemic ApoE^-/-/LDLR^-/- mice and in FH patients to evaluate their human relevance.

RESULTS

We identified 15 metabolites (inhibitors and substrates of nitric oxide synthase (NOS), low-molecular-weight antioxidants (glutamine, taurine), homocysteine, methionine, 1-methylnicotinamide, alanine and hydroxyproline) and 9 proteins (C-reactive protein, proprotein convertase subtilisin/kexin type 9, apolipoprotein C-III, soluble intercellular adhesion molecule-1, angiotensinogen, paraoxonase-1, fetuin-B, vitamin K-dependent protein S and biglycan) that differentiated FH patients from healthy controls. Most of these changes were consistently found in dyslipidaemic mice and were further amplified if mice were fed an atherogenic (Western or low-carbohydrate, high-protein) diet.

CONCLUSIONS

The alterations highlighted the involvement of an immune-inflammatory response system, oxidative stress, hyper-coagulation and impairment in the vascular function/regenerative capacity in response to dyslipidaemia that may also be directly engaged in development of atherosclerosis. Our study further identified potential biomarkers for an increased risk of atherosclerosis that may aid in clinical diagnosis or in the personalized treatment.

Association of Lipidomic Profiles With Progression of Carotid Artery Atherosclerosis in HIV Infection

Importance

Lipid metabolism disruption and excess risk of cardiovascular disease (CVD) have been observed in HIV-infected individuals, but the associations among HIV infection, plasma lipidome, and CVD risk have not been well understood.

Objective

To evaluate plasma lipidomic profiles and their associations with carotid artery atherosclerosis in individuals with HIV and individuals without HIV.

Design, Setting, and Participants

Prospective analysis in the Women's Interagency HIV Study and Multicenter AIDS Cohort Study during a 7-year follow-up (from 2004-2006 to 2011-2013) at multicenter HIV cohorts in the United States. The study included 737 participants aged 35 to 55 years (520 with HIV and 217 without HIV) without CVD or carotid artery plaque at baseline. Data were analyzed between April 2017 and July 2019.

Exposures

Two hundred eleven plasma lipid species.

Main Outcomes and Measures

Poisson regression was used to examine the associations of baseline lipid species with risk of plaque measured by repeated B-mode carotid artery ultrasonography imaging.

Results

Of the 737 included participants, 398 (54%) were women, 351 (48%) were African American (non-Hispanic), 156 of 737 (21%) were nonwhite Hispanic, and the mean (SD) age was 45 (6) years. After adjusting for demographic and behavioral factors, we identified 12 lipid species, representing independent signals for 10 lipid classes, associated with risk of plaque. Nine lipid species remained significant after further adjusting for conventional CVD risk factors, although many of them showed moderate to high association with conventional blood lipids (eg, total and low-density lipoprotein cholesterols and triglycerides). Cholesteryl ester (16:1) (risk ratio [RR] per standard deviation, 1.28; 95% CI, 1.08-1.52), ceramide (16:0) (RR, 1.29; 95% CI, 1.02-1.63), lysophosphatidylcholine (20:4) (RR, 1.28; 95% CI, 1.05-1.58), lysophosphatidylethanolamine (16:0) (RR, 1.28; 95% CI, 1.05-1.57), phosphatidylethanolamine (38:6) (RR, 1.33; 95% CI, 1.08-1.64), phosphatidylethanolamine-plasmalogen (36:2) (RR, 1.25; 95% CI, 1.04-1.52), phosphatidylserine-plasmalogen (36:3) (RR, 1.19; 95% CI, 1.00-1.43), and triacylglycerol (54:6) (RR, 1.26; 95% CI, 1.04-1.54) were associated with increased risk of plaque, while phosphatidylcholine (36:4) (RR, 0.65; 95% CI, 0.54-0.77) was associated with decreased risk of plaque. Most of these plaque-increased lipid species showed higher levels in individuals with HIV, particularly among individuals with HIV using antiretroviral therapy compared with individuals without HIV. Network analysis identified 9 lipid modules, and 2 modules composed of triacylglycerols and phosphatidylcholines with long and unsaturated acyl chains, respectively, showed the strongest associations with increased risk of plaque.

Conclusions and Relevance

This study identified multiple plasma lipid species associated with carotid artery atherosclerosis, and alterations in these lipid species might be associated with HIV infection and antiretroviral therapy. Our data suggest unfavorable associations of long-chain and unsaturated triacylglycerols and phosphatidylcholines with carotid artery plaque formation.

Serum lipids profiling perturbances in patients with ischemic heart disease and ischemic cardiomyopathy

Background

Ischemic heart disease (IHD) is a common cardiovascular disorder associated with inadequate blood supply to the myocardium. Chronic coronary ischemia leads to ischemic cardiomyopathy (ICM). Despite their rising prevalence and morbidity, few studies have discussed the lipids alterations in these patients.

Methods

In this cross-sectional study, we analyzed serum lipids profile in IHD and ICM patients using a lipidomics approach. Consecutive consenting patients admitted to the hospital for IHD and ICM were enrolled. Serum samples were obtained after overnight fasting. Non-targeted metabolomics was applied to demonstrate lipids metabolic profile in control, IHD and ICM patients.

Results

A total of 63 and 62 lipids were detected in negative and positive ion mode respectively. Among them, 16:0 Lyso PI, 18:1 Lyso PI in negative ion mode, and 19:0 Lyso PC, 12:0 SM d18:1/12:0, 15:0 Lyso PC, 17:0 PC, 18:1–18:0 PC in positive ion mode were significantly altered both in IHD and ICM as compared to control. 13:0 Lyso PI, 18:0 Lyso PI, 16:0 PE, 14:0 PC DMPC, 16:0 ceramide, 18:0 ceramide in negative ion mode, and 17:0 PE, 19:0 PC, 14:0 Lyso PC, 20:0 Lyso PC, 18:0 PC DSPC, 18:0–22:6 PC in positive ion mode were significantly altered only in ICM as compared to IHD and control.

Conclusion

Using non-targeted lipidomics profiling, we have successfully identified a group of circulating lipids that were significantly altered in IHD and ICM. The lipids metabolic signatures shed light on potential new biomarkers and therapeutics for preventing and treating ICM.

Lipid-based biomarkers for CVD, COPD, and aging - A translational perspective

For many diseases, there is an unmet need for new or better biomarkers for improved disease risk assessment and monitoring, as available markers lack sufficient specificity. Lipids are drawing major interest as potential candidates for filling these gaps. This has recently been demonstrated by the identification of selective ceramides for prediction of cardiovascular mortality, enabling improved risk assessment of cardiovascular disease compared with conventional clinical markers. In this review, we discuss current lipid biomarker findings and the possible connection between cardiovascular disease, chronic obstructive pulmonary disease, and aging. Moreover, we discuss how to overcome the current roadblocks facing lipid biomarker research. We stress the need for improved quantification, standardization of methodologies, and establishment of initial reference values to allow for an efficient transfer path of research findings into the clinical landscape, and, ultimately, to put newly identified biomarkers into practical use.

Metabolic basis of neuronal vulnerability to ischemia; an in vivo untargeted metabolomics approach

Understanding the root causes of neuronal vulnerability to ischemia is paramount to the development of new therapies for stroke. Transient global cerebral ischemia (tGCI) leads to selective neuronal cell death in the CA1 sub-region of the hippocampus, while the neighboring CA3 sub-region is left largely intact. By studying factors pertaining to such selective vulnerability, we can develop therapies to enhance outcome after stroke. Using untargeted liquid chromatography-mass spectrometry, we analyzed temporal metabolomic changes in CA1 and CA3 hippocampal areas following tGCI in rats till the setting of neuronal apoptosis. 64 compounds in CA1 and 74 in CA3 were found to be enriched and statistically significant following tGCI. Pathway analysis showed that pyrimidine and purine metabolism pathways amongst several others to be enriched after tGCI in CA1 and CA3. Metabolomics analysis was able to capture very early changes following ischemia. We detected 6 metabolites to be upregulated and 6 to be downregulated 1 hour after tGCI in CA1 versus CA3. Several metabolites related to apoptosis and inflammation were differentially expressed in both regions after tGCI. We offer a new insight into the process of neuronal apoptosis, guided by metabolomic profiling that was not performed to such an extent previously.

Clinical and lifestyle related factors influencing whole blood metabolite levels - A comparative analysis of three large cohorts

Objective

Human blood metabolites are influenced by a number of lifestyle and environmental factors. Identification of these factors and the proper quantification of their relevance provides insights into human biological and metabolic disease processes, is key for standardized translation of metabolite biomarkers into clinical applications, and is a prerequisite for comparability of data between studies. However, so far only limited data exist from large and well-phenotyped human cohorts and current methods for analysis do not fully account for the characteristics of these data. The primary aim of this study was to identify, quantify and compare the impact of a comprehensive set of clinical and lifestyle related factors on metabolite levels in three large human cohorts. To achieve this goal, we improve current methodology by developing a principled analysis approach, which could be translated to other cohorts and metabolite panels.

Methods

63 Metabolites (amino acids, acylcarnitines) were quantified by liquid chromatography tandem mass spectrometry in three cohorts (total N = 16,222). Supported by a simulation study evaluating various analytical approaches, we developed an analysis pipeline including preprocessing, identification, and quantification of factors affecting metabolite levels. We comprehensively identified uni- and multivariable metabolite associations considering 29 environmental and clinical factors and performed metabolic pathway enrichment and network analyses.

Results

Inverse normal transformation of batch corrected and outlier removed metabolite levels accompanied by linear regression analysis proved to be the best suited method to deal with the metabolite data. Association analyses revealed numerous uni- and multivariable significant associations. 15 of the analyzed 29 factors explained >1% of variance for at least one of the metabolites. Strongest factors are application of steroid hormones, reticulocytes, waist-to-hip ratio, sex, haematocrit, and age. Effect sizes of factors are comparable across studies.

Conclusions

We introduced a principled approach for the analysis of MS data allowing identification, and quantification of effects of clinical and lifestyle factors with metabolite levels. We detected a number of known and novel associations broadening our understanding of the regulation of the human metabolome. The large heterogeneity observed between cohorts could almost completely be explained by differences in the distribution of influencing factors emphasizing the necessity of a proper confounder analysis when interpreting metabolite associations.

•

Amino-acids and acylcarnitines analyzed in three studies with >16,000 individuals.

•

Develop a generic and adaptable bioinformatics workflow.

•

Analysis of the impact of 29 clinical and life-style factors on blood metabolites.

•

Analysis of network between factors and metabolites.

•

Comparison of results between studies.

Metabolic Disturbances Identified in Plasma Samples from ST-Segment Elevation Myocardial Infarction Patients

ST-segment elevation myocardial infarction (STEMI) is the most severe form of myocardial infarction (MI) and the main contributor to morbidity and mortality caused by MI worldwide. Frequently, STEMI is caused by complete and persistent occlusion of a coronary artery by a blood clot, which promotes heart damage. STEMI impairment triggers changes in gene transcription, protein expression, and metabolite concentrations, which grants a biosignature to the heart dysfunction. There is a major interest in identifying novel biomarkers that could improve the diagnosis of STEMI. In this study, the phenotypic characterization of STEMI patients (n = 15) and healthy individuals (n = 19) was performed, using a target metabolomics approach. Plasma samples were analyzed by UPLC-MS/MS (ultra-high-performance liquid chromatography-tandem mass spectrometry) and FIA-MS (MS-based flow injection analysis). The goal was to identify novel plasma biomarkers and metabolic signatures underlying STEMI. Concentrations of phosphatidylcholines, lysophosphatidylcholines, sphingomyelins, and biogenic amines were altered in STEMI patients in relation to healthy subjects. Also, after multivariate analysis, it was possible to identify alterations in the glycerophospholipids, alpha-linolenic acid, and sphingolipid metabolisms in STEMI patients.

Interaction of clopidogrel and fufang danshen dripping pills assay in coronary heart disease based on non-target metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Clopidogrel is the recommended treatment by current clinical practice guidelines to prevent adverse cardiovascular events in patients with coronary heart disease (CHD), but this treatment regimen still fails and 5-40% patients display inadequate antiplatelet responses. Fufang Danshen Dripping Pill (FDDP), a Chinese patient drug, was used as the combination with clopidogrel to improve the therapeutic effect. However, the mechanism of the interaction between clopidogrel and FDDP has not been elucidated.

MATERIALS AND METHODS

We have used non-targeted metabolism method based on GC-MS and LC-MS for the investigation of drug interactions between clopidogrel and FDDP. 63 patients were divided into four groups with different dosage regimen and the serum samples were collected for the analysis.

RESULTS

We have found 5 and 55 differential metabolites between health volunteer group and CHD patients group, respectively. The contents of these differential metabolites had diverse changes in clopidogrel group, FDDP group, and drug combination group, indicating that the clopidogrel and FDDP combination can adjust the glycometabolism, lipid metabolism, and phospholipid metabolism, sequentially made the content of downstream related metabolites towards to the health volunteer group.

CONCLUSION

This work has explained the mechanism of the interaction between clopidogrel and FDDP from the point of view of metabolic product change, and revealed the potential metabolic pathways it affects, which provided the new ideas for clinical medication.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The anti-inflammatory effect of microRNA-383-3p interacting with IL1R2 against homocysteine-induced endothelial injury in rat coronary arteries

MicroRNAs (miRs) are widely reported to be novel biomarkers involved in the process of coronary atherosclerosis (CAS). Hence, this study aims to explore the function of miR-383-3p targeting IL1R2 on inflammatory injury of coronary artery endothelial cells (CAECs) in CAS. The underlying regulatory mechanisms of miR-383-3p were analyzed in concert with the treatment of miR-383-3p mimics, miR-383-3p inhibitors, and the combination of miR-383-3p inhibitors and siRNA against IL1R2 in homocysteine (HCY)-induced CAECs. MTT, Hoechst 33258 staining, and tube formation assay were employed in order to measure cell viability, apoptosis, and tube formation, respectively. The levels of IL-1β, IL-6, IL-10, and IL-18 were determined by ELISA. IL1R2 was verified as the target gene of miR-383-3p by dual-luciferase reporter gene assay. MiR-383-3p was down-regulated in myocardial tissues of AS rats while IL1R2 was the reciprocal. The up-regulation of miR-383-3p decreased the levels of IL1R2, caspase-1, IL-1β, IL-6, and IL-18 expressions, as well as cell apoptosis rate in the HCY-induced CAECs, while IL-10 expression, cell viability, and tube formation ability were increased. These results were contraindicated in the HCY-induced CAECs treated by miR-383-3p inhibitors. In conclusion, miR-383-3p mediating IL1R2 prevents HCY-induced apoptosis and inflammation injury in CAECs through the inhibition of the activation of inflammasome signaling pathway. These findings highly indicate that miR-383-3p may be beneficial in the prevention of CAS and other cardiovascular diseases.

New tools and resources in metabolomics: 2016-2017

Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time.