Metabolomics as a tool for cardiac research

Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

Plasma Metabolome Predicts Aortic Stiffness and Future Risk of Coronary Artery Disease and Mortality After 23 Years of Follow-Up in the General Population

BACKGROUND

Increased aortic stiffness (arteriosclerosis) is associated with early vascular aging independent of age and sex. The underlying mechanisms of early vascular aging remain largely unexplored in the general population. We aimed to investigate the plasma metabolomic profile in aortic stiffness (vascular aging) and associated risk of incident cardiovascular disease and mortality.

METHODS AND RESULTS

We included 6865 individuals from 2 Swedish population-based cohorts. Untargeted plasma metabolomics was performed by liquid-chromatography mass spectrometry. Aortic stiffness was assessed directly by carotid-femoral pulse wave velocity (PWV) and indirectly by augmentation index (AIx@75). A least absolute shrinkage and selection operator (LASSO) regression model was created on plasma metabolites in order to predict aortic stiffness. Associations between metabolite-predicted aortic stiffness and risk of new-onset cardiovascular disease, cardiovascular mortality, and all-cause mortality were calculated. Metabolite-predicted aortic stiffness (PWV and AIx@75) was positively associated particularly with acylcarnitines, dimethylguanidino valeric acid, glutamate, and cystine. The plasma metabolome predicted aortic stiffness (PWV and AIx@75) with good accuracy (R2=0.27 and R2=0.39, respectively). Metabolite-predicted aortic stiffness (PWV and AIx@75) was significantly correlated with age, sex, systolic blood pressure, body mass index, and low-density lipoprotein. After 23 years of follow-up, metabolite-predicted aortic stiffness (PWV and AIx@75) was significantly associated with increased risk of new-onset coronary artery disease, cardiovascular mortality, and all-cause mortality.

CONCLUSIONS

Aortic stiffness is associated particularly with altered metabolism of acylcarnitines, cystine, and dimethylguanidino valeric acid. These metabolic disturbances predict increased risk of new-onset coronary artery disease, cardiovascular mortality, and all-cause mortality after more than 23 years of follow-up in the general population.

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates, such as fatty acids, carbohydrates, lipids, and amino acids, to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities, which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection: direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF-MS/MS). Using DI-FTICR MS, 9644 metabolic features were detected where 7156 were assigned a molecular formula and 1107 were annotated by accurate mass assignment. Using LC-Q-TOF-MS/MS, 21,428 metabolic features were detected where 285 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 1340 heart metabolites were identified in this study, which span a wide range of polarities including polar (benzenoids, carbohydrates, and nucleosides) as well as nonpolar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results from this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.

Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization

Aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM) are distinct disorders leading to left ventricular hypertrophy (LVH), but whether cardiac metabolism substantially differs between these in humans remains to be elucidated. We undertook an invasive (aortic root, coronary sinus) metabolic profiling in patients with severe AS and HCM in comparison with non-LVH controls to investigate cardiac fuel selection and metabolic remodeling. These patients were assessed under different physiological states (at rest, during stress induced by pacing). The identified changes in the metabolome were further validated by metabolomic and orthogonal transcriptomic analysis, in separately recruited patient cohorts. We identified a highly discriminant metabolomic signature in severe AS in all samples, regardless of sampling site, characterized by striking accumulation of long-chain acylcarnitines, intermediates of fatty acid transport across the inner mitochondrial membrane, and validated this in a separate cohort. Mechanistically, we identify a downregulation in the PPAR-α transcriptional network, including expression of genes regulating fatty acid oxidation (FAO). In silico modeling of β-oxidation demonstrated that flux could be inhibited by both the accumulation of fatty acids as a substrate for mitochondria and the accumulation of medium-chain carnitines which induce competitive inhibition of the acyl-CoA dehydrogenases. We present a comprehensive analysis of changes in the metabolic pathways (transcriptome to metabolome) in severe AS, and its comparison to HCM. Our results demonstrate a progressive impairment of β-oxidation from HCM to AS, particularly for FAO of long-chain fatty acids, and that the PPAR-α signaling network may be a specific metabolic therapeutic target in AS.

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies

BACKGROUND

A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity.

METHODS

In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity.

FINDINGS

The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity.

CONCLUSIONS

This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity.

FUNDING

This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

Blood metabolites mediate the impact of lifestyle factors on the risk of urolithiasis: a multivariate, mediation Mendelian randomization study

Urolithiasis is closely linked to lifestyle factors. However, the causal relationship and underlying mechanisms remain unclear. This study aims to investigate the relationship between lifestyle factors and the onset of urolithiasis and explore potential blood metabolite mediators and their role in mediating this relationship. In this study, we selected single nucleotide polymorphisms (SNPs) as instrumental variables if they exhibited significant associations with our exposures in genome-wide association studies (GWAS) (p < 5.0 × 10-8). Summary data for urolithiasis came from the FinnGen database, including 8597 cases and 333,128 controls. We employed multiple MR analysis methods to assess causal links between genetically predicted lifestyle factors and urolithiasis, as well as the mediating role of blood metabolites. A series of sensitivity and pleiotropy analyses were also conducted. Our results show that cigarettes smoked per day (odds ratio [OR] = 1.159, 95% confidence interval [CI] = 1.004-1.338, p = 0.044) and alcohol intake frequency (OR = 1.286, 95% CI = 1.056-1.565, p = 0.012) were positively associated with increased risk of urolithiasis, while tea intake (OR = 0.473, 95% CI = 0.299-0.784, p = 0.001) was positively associated with reduced risk of urolithiasis. Mediation analysis identifies blood metabolites capable of mediating the causal relationship between cigarettes smoked per day, tea intake and urolithiasis. We have come to the conclusion that blood metabolites serve as potential causal mediators of urolithiasis, underscoring the importance of early lifestyle interventions and metabolite monitoring in the prevention of urolithiasis.

Metabolomics Profiling Predicts Ventricular Arrhythmia in Patients with an Implantable Cardioverter Defibrillator

Implantable cardioverter defibrillators (ICDs) reduce sudden cardiac death (SCD) when patients experience life-threatening ventricular arrhythmias (LTVA). However, current strategies determining ICD patient selection and risk stratification are inefficient. We used metabolomics to assess whether dysregulated metabolites are associated with LTVA and identify potential biomarkers. Baseline plasma samples were collected from 72 patients receiving ICDs. Over a median follow-up of 524.0 days (range 239.0-705.5), LTVA occurred in 23 (31.9%) patients (22 effective ICD treatments and 1 SCD). After confounding risk factors adjustment for age, smoking, secondary prevention, and creatine kinase MB, 23 metabolites were significantly associated with LTVA. Pathway analysis revealed LTVA associations with disrupted metabolism of glycine, serine, threonine, and branched chain amino acids. Pathway enrichment analysis identified a panel of 6 metabolites that potentially predicted LTVA, with an area under the receiver operating characteristic curve of 0.8. Future studies are necessary on biological mechanisms and potential clinical use.

Monitoring live mitochondrial metabolism in real-time using NMR spectroscopy

Investigation of mitochondrial metabolism is gaining increased interest owing to the growing recognition of the role of mitochondria in health and numerous diseases. Studies of isolated mitochondria promise novel insights into the metabolism devoid of confounding effects from other cellular organelles such as cytoplasm. This study describes the isolation of mitochondria from mouse skeletal myoblast cells (C2C12) and the investigation of live mitochondrial metabolism in real-time using isotope tracer-based NMR spectroscopy. [3-13 C1 ]pyruvate was used as the substrate to monitor the dynamic changes of the downstream metabolites in mitochondria. The results demonstrate an intriguing phenomenon, in which lactate is produced from pyruvate inside the mitochondria and the results were confirmed by treating mitochondria with an inhibitor of mitochondrial pyruvate carrier (UK5099). Lactate is associated with health and numerous diseases including cancer and, to date, it is known to occur only in the cytoplasm. The insight that lactate is also produced inside mitochondria opens avenues for exploring new pathways of lactate metabolism. Further, experiments performed using inhibitors of the mitochondrial respiratory chain, FCCP and rotenone, show that [2-13 C1 ]acetyl coenzyme A, which is produced from [3-13 C1 ]pyruvate and acts as a primary substrate for the tricarboxylic acid cycle in mitochondria, exhibits a remarkable sensitivity to the inhibitors. These results offer a direct approach to visualize mitochondrial respiration through altered levels of the associated metabolites.

Metabolomics Assessment of Volume Overload-Induced Heart Failure and Oxidative Stress in the Kidney

The incidence of heart failure (HF) is increasing and is associated with a poor prognosis. Moreover, HF often coexists with renal dysfunction and is associated with a worsened outcome. In many experimental studies on cardiac dysfunction, the function of other organs was either not addressed or did not show any decline. Until now, the exact mechanisms for initiating and sustaining this interaction are still unknown. The objective of this study is to use volume overload to induce cardiac hypertrophy and HF in aortocaval fistula (ACF) rat models, and to elucidate how volume overload affects metabolic changes in the kidney, even with normal renal function, in HF. The results showed the metabolic changes between control and ACF rats, including taurine metabolism; purine metabolism; glycine, serine, and threonine metabolism; glycerophospholipid metabolism; and histidine metabolism. Increasing the downstream purine metabolism from inosine to uric acid in the kidneys of ACF rats induced oxidative stress through xanthine oxidase. This result was consistent with HK-2 cells treated with xanthine and xanthine oxidase. Under oxidative stress, taurine accumulation was observed in ACF rats, indicating increased activity of the hypotaurine-taurine pathway as a defense mechanism against oxidative stress in the kidney. Another antioxidant, ascorbic acid 2-sulfate, showed lower levels in ACF rats, indicating that the kidneys experience elevated oxidative stress due to volume overload and HF. In summary, metabolic profiles are more sensitive than clinical parameters in reacting to damage to the kidney in HF.

Causal effects of genetically determined blood metabolites on multiple myeloma: a Mendelian randomization study

Previous studies have shown that metabolites play an important role in phenotypic regulation. However, the causal relationship between metabolites and multiple myeloma has not been adequately investigated. Here, we attempt to explore the causal effects of genetically determined blood metabolites on multiple myeloma. The large-scale public blood metabolites and multiple myeloma datasets from independently published genome-wide association studies (GWAS) were used to explore the causal relationship between each genetically determined blood metabolite and multiple myeloma through inverse variance weighted (IVW), weighted median, MR-Egger and mode-based estimation methods. Sensitivity tests were performed to evaluate the stability and reliability of the results by MR-Egger regression and leave-one-out methods. Metabolic pathway analysis was further explored using filtered data. Statistical analyses were all performed in R. Among 452 metabolites, ten known metabolites and three unknown metabolites had significant causal relationship with multiple myeloma (P < 0.05). Four known metabolites, 3-methyl-2-oxovalenate, oxidized bilirubin, isovalerylcarnitine and glutamine carnitine, reached statistical significance in IVW models. Metabolic pathways analysis identified four significant pathways. The occurrence of multiple myeloma may have a causal relationship with these four metabolites, and there are four metabolic pathways that are also related to the occurrence of multiple myeloma. This can provide new ideas for exploring early screening and treatment of multiple myeloma.

Significant dysregulation of lipid metabolism in patients with papillary thyroid carcinoma after thyroidectomy

Introduction

Thyroidectomy and thyrotropin suppressive therapy is the widely used surgical treatment for papillary thyroid carcinoma (PTC) patients. However, systematic metabolic changes of post-operative PTC patients were rarely reported.

Methods

Here, untargeted metabolomic detection of cohorts from PTC before (t0) and 1-month-after (t1) thyroidectomy, were performed to characterize circulating metabolic signatures after surgical treatment.

Results

Our results showed PTC patients exhibited lower thyroid stimulating hormone degree, higher total thyroxine, and significant lipid-related metabolic alternations after thyroidectomy, which included 97 upregulations (including 93 lipids) and 5 downregulations (including 2 lipids and 3 nucleotides). Enrichment of metabolic pathways mainly included biosynthesis of fatty acids, purine metabolism, and linoleic acid metabolism. We also demonstrated that differential surgical approaches (hemi- and total thyroidectomy) and post-operative complication phenotypes (insomnia, fatigue), might lead to characteristic metabolic signatures.

Discussion

This study revealed dynamic changes of metabolite characteristics of PTC patients after surgical treatment, which were associated with clinical thyroid function parameters, surgical approaches, and complication occurrence. It enlightened us to pay more attention on the post-operative metabolic dysregulation of PTC patients and their long-term qualities of life, so as to provide cautious clinical decisions on surgical choices, treatments, and follow-up details.

Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post-traumatic stress disorder

Metabolomics, proteomics and DNA methylome assays, when done in tandem from the same blood sample and analyzed together, offer an opportunity to evaluate the molecular basis of post-traumatic stress disorder (PTSD) course and pathogenesis. We performed separate metabolomics, proteomics, and DNA methylome assays on blood samples from two well-characterized cohorts of 159 active duty male participants with relatively recent onset PTSD (<1.5 years) and 300 male veterans with chronic PTSD (>7 years). Analyses of the multi-omics datasets from these two independent cohorts were used to identify convergent and distinct molecular profiles that might constitute potential signatures of severity and progression of PTSD and its comorbid conditions. Molecular signatures indicative of homeostatic processes such as signaling and metabolic pathways involved in cellular remodeling, neurogenesis, molecular safeguards against oxidative stress, metabolism of polyunsaturated fatty acids, regulation of normal immune response, post-transcriptional regulation, cellular maintenance and markers of longevity were significantly activated in the active duty participants with recent PTSD. In contrast, we observed significantly altered multimodal molecular signatures associated with chronic inflammation, neurodegeneration, cardiovascular and metabolic disorders, and cellular attritions in the veterans with chronic PTSD. Activation status of signaling and metabolic pathways at the early and late timepoints of PTSD demonstrated the differential molecular changes related to homeostatic processes at its recent and multi-system syndromes at its chronic phase. Molecular alterations in the recent PTSD seem to indicate some sort of recalibration or compensatory response, possibly directed in mitigating the pathological trajectory of the disorder.

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates such as fatty acids, carbohydrates, lipids, and amino acids to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic extractions) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection - direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF MS/MS). Using DI-FTICR MS, 9,521 metabolic features were detected where 7,699 were assigned a chemical formula and 1,756 were assigned an annotated by accurate mass assignment. Using LC-Q-TOF MS/MS, 21,428 metabolic features were detected where 626 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 2276 heart metabolites were identified in this study which span a wide range of polarities including polar (benzenoids, alkaloids and derivatives and nucleosides) as well as non-polar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results of this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites.

Association of Baseline Metabolomic Profiles With Incident Stroke and Dementia and With Imaging Markers of Cerebral Small Vessel Disease

BACKGROUND AND OBJECTIVES

Cerebral small vessel disease is a major cause of stroke and dementia. Metabolomics can help identify novel risk factors to better understand pathogenesis and predict disease progression and severity.

METHODS

We analyzed baseline metabolomic profiles from 118,021 UK Biobank participants. We examined cross-sectional associations of 325 metabolites with MRI markers of small vessel disease, evaluated longitudinal associations with incident stroke and dementia, and ascertained causal relationships using Mendelian randomization.

RESULTS

In cross-sectional analyses, lower levels of apolipoproteins, free cholesterol, cholesteryl esters, fatty acids, lipoprotein particle concentrations, phospholipids, and triglycerides were associated with increased white matter microstructural damage on diffusion tensor MRI. In longitudinal analyses, lipoprotein subclasses of very large high-density lipoprotein cholesterol (HDL) were associated with an increased risk of stroke, and acetate and 3-hydroxybutyrate were associated with an increased risk of dementia. Mendelian randomization analyses identified strong evidence supporting causal relationships for many findings. A few metabolites had consistent associations across multiple analysis types. Increased total lipids in very large HDL and increased HDL particle size were associated with increased white matter damage (lower fractional anisotropy: OR: 1.44, 95% CI 1.07-1.95, and OR: 1.19, 95% CI 1.06-1.34, respectively; mean diffusivity: OR: 1.49, 95% CI 1.11-2.01, and OR: 1.24, 95% CI 1.11-1.40, respectively) and an increased risk of incident all stroke (HR: 4.04, 95% CI 2.13-7.64, and HR: 1.54, 95% CI 1.20-1.98, respectively) and ischemic stroke (HR: 3.12, 95% CI 1.53-6.38; HR: 1.37, 95% CI 1.04-1.81). Valine was associated with decreased mean diffusivity (OR: 0.51, 95% CI 0.30-0.88) and had a protective association with all-cause dementia (HR: 0.008, 95% CI 0.002-0.035). Increased levels of cholesterol in small HDL were associated with a decreased risk of incident all stroke (HR: 0.17, 95% CI 0.08-0.39) and ischemic stroke (HR: 0.19, 95% CI 0.08-0.46) and were supported by evidence of a causal association with MRI-confirmed lacunar stroke (OR: 0.96, 95% CI 0.93-0.99).

DISCUSSION

In this large-scale metabolomics study, we found multiple metabolites associated with stroke, dementia, and MRI markers of small vessel disease. Further studies may help inform the development of personalized prediction models and provide insights into mechanistic pathways and future treatment approaches.

Metabolomic profiling of cardiac allografts after controlled circulatory death

BACKGROUND

Assessment of myocardial viability during ex situ heart perfusion (ESHP) is based on the measurement of lactate concentrations. As this provides with limited information, we sought to investigate the metabolic signature associated with donation after circulatory death (DCD) and the impact of ESHP on the myocardial metabolome.

METHODS

Porcine hearts were retrieved either after warm ischemia (DCD group, N = 6); after brain-stem death (BSD group, N = 6); or without DCD nor BSD (Control group, N = 6). Hearts were perfused using normothermic oxygenated blood for 240 minutes. Plasma and myocardial samples were collected respectively every 30 and 60 minutes, and analyzed by an untargeted metabolomic approach using liquid chromatography coupled to high-resolution mass spectrometry.

RESULTS

Median duration of warm ischemia was 23 minutes [19-29] in DCD animals. Lactate level within myocardial biopsies was not significantly different between groups at T0 (p = 0.281), and remained stable over the 4-hour period of ESHP. More than 300 metabolites were detected in plasma and heart biopsy samples. Compared to BSD animals, metabolomics changes involving energy and nucleotide metabolisms were observed in plasma samples of DCD animals before initiation of ESHP, whereas 2 metabolites (inosine monophosphate and methylbutyrate) exhibited concentration changes in biopsy samples. Normalization of DCD metabolic profile was remarkable after 4 hours of ESHP.

CONCLUSION

A specific metabolic profile was observed in DCD hearts, mainly characterized by an increased nucleotide catabolism. DCD and BSD metabolomes proved normalized during ESHP. Complementary investigations are needed to correlate these findings to cardiac performances.

Assessment of Cardiac Energy Metabolism, Function, and Physiology in Patients With Heart Failure Taking Empagliflozin: The Randomized, Controlled EMPA-VISION Trial

BACKGROUND

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have emerged as a paramount treatment for patients with heart failure (HF), irrespective of underlying reduced or preserved ejection fraction. However, a definite cardiac mechanism of action remains elusive. Derangements in myocardial energy metabolism are detectable in all HF phenotypes, and it was proposed that SGLT2i may improve energy production. The authors aimed to investigate whether treatment with empagliflozin leads to changes in myocardial energetics, serum metabolomics, and cardiorespiratory fitness.

METHODS

EMPA-VISION (Assessment of Cardiac Energy Metabolism, Function and Physiology in Patients With Heart Failure Taking Empagliflozin) is a prospective, randomized, double-blind, placebo-controlled, mechanistic trial that enrolled 72 symptomatic patients with chronic HF with reduced ejection fraction (HFrEF; n=36; left ventricular ejection fraction ≤40%; New York Heart Association class ≥II; NT-proBNP [N-terminal pro-B-type natriuretic peptide] ≥125 pg/mL) and HF with preserved ejection fraction (HFpEF; n=36; left ventricular ejection fraction ≥50%; New York Heart Association class ≥II; NT-proBNP ≥125 pg/mL). Patients were stratified into respective cohorts (HFrEF versus HFpEF) and randomly assigned to empagliflozin (10 mg; n=35: 17 HFrEF and 18 HFpEF) or placebo (n=37: 19 HFrEF and 18 HFpEF) once daily for 12 weeks. The primary end point was a change in the cardiac phosphocreatine:ATP ratio (PCr/ATP) from baseline to week 12, determined by phosphorus magnetic resonance spectroscopy at rest and during peak dobutamine stress (65% of age-maximum heart rate). Mass spectrometry on a targeted set of 19 metabolites was performed at baseline and after treatment. Other exploratory end points were investigated.

RESULTS

Empagliflozin treatment did not change cardiac energetics (ie, PCr/ATP) at rest in HFrEF (adjusted mean treatment difference [empagliflozin - placebo], -0.25 [95% CI, -0.58 to 0.09]; P=0.14) or HFpEF (adjusted mean treatment difference, -0.16 [95% CI, -0.60 to 0.29]; P=0.47]. Likewise, there were no changes in PCr/ATP during dobutamine stress in HFrEF (adjusted mean treatment difference, -0.13 [95% CI, -0.35 to 0.09]; P=0.23) or HFpEF (adjusted mean treatment difference, -0.22 [95% CI, -0.66 to 0.23]; P=0.32). No changes in serum metabolomics or levels of circulating ketone bodies were observed.

CONCLUSIONS

In patients with either HFrEF or HFpEF, treatment with 10 mg of empagliflozin once daily for 12 weeks did not improve cardiac energetics or change circulating serum metabolites associated with energy metabolism when compared with placebo. Based on our results, it is unlikely that enhancing cardiac energy metabolism mediates the beneficial effects of SGLT2i in HF.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03332212.

Serum lipidomics reveals phosphatidylethanolamine and phosphatidylcholine disorders in patients with myocardial infarction and post-myocardial infarction-heart failure

BACKGROUND

Myocardial infarction (MI) and post-MI-heart failure (pMIHF) are a major cause of death worldwide, however, the underlying mechanisms of pMIHF from MI are not well understood. This study sought to characterize early lipid biomarkers for the development of pMIHF disease.

METHODS

Serum samples from 18 MI and 24 pMIHF patients were collected from the Affiliated Hospital of Zunyi Medical University and analyzed using lipidomics with Ultra High Performance Liquid Chromatography and Q-Exactive High Resolution Mass Spectrometer. The serum samples were tested by the official partial least squares discriminant analysis (OPLS-DA) to find the differential expression of metabolites between the two groups. Furthermore, the metabolic biomarkers of pMIHF were screened using the subject operating characteristic (ROC) curve and correlation analysis.

RESULTS

The average age of the 18 MI and 24 pMIHF participants was 57.83 ± 9.28 and 64.38 ± 10.89 years, respectively. The B-type natriuretic peptide (BNP) level was 328.5 ± 299.842 and 3535.96 ± 3025 pg/mL, total cholesterol(TC) was 5.59 ± 1.51 and 4.69 ± 1.13 mmol/L, and blood urea nitrogen (BUN) was 5.24 ± 2.15 and 7.20 ± 3.49 mmol/L, respectively. In addition, 88 lipids, including 76 (86.36%) down-regulated lipids, were identified between the patients with MI and pMIHF. ROC analysis showed that phosphatidylethanolamine (PE) (12:1e_22:0) (area under the curve [AUC] = 0.9306) and phosphatidylcholine (PC) (22:4_14:1) (AUC = 0.8380) could be potential biomarkers for the development of pMIHF. Correlation analysis showed that PE (12:1e_22:0) was inversely correlated with BNP and BUN, but positively correlated with TC. In contrast, PC (22:4_14:1) was positively associated with both BNP and BUN, and was negatively associated with TC.

CONCLUSIONS

Several lipid biomarkers were identified that could potentially be used to predict and diagnose patients with pMIHF. PE (12:1e_22:0) and PC (22:4_14:1) could sufficiently differentiate between patients with MI and pMIHF.

Molecular signatures of post-traumatic stress disorder in war-zone-exposed veteran and active-duty soldiers

Post-traumatic stress disorder (PTSD) is a multisystem syndrome. Integration of systems-level multi-modal datasets can provide a molecular understanding of PTSD. Proteomic, metabolomic, and epigenomic assays are conducted on blood samples of two cohorts of well-characterized PTSD cases and controls: 340 veterans and 180 active-duty soldiers. All participants had been deployed to Iraq and/or Afghanistan and exposed to military-service-related criterion A trauma. Molecular signatures are identified from a discovery cohort of 218 veterans (109/109 PTSD+/-). Identified molecular signatures are tested in 122 separate veterans (62/60 PTSD+/-) and in 180 active-duty soldiers (PTSD+/-). Molecular profiles are computationally integrated with upstream regulators (genetic/methylation/microRNAs) and functional units (mRNAs/proteins/metabolites). Reproducible molecular features of PTSD are identified, including activated inflammation, oxidative stress, metabolic dysregulation, and impaired angiogenesis. These processes may play a role in psychiatric and physical comorbidities, including impaired repair/wound healing mechanisms and cardiovascular, metabolic, and psychiatric diseases.

Hyperkalemic or Low Potassium Cardioplegia Protects against Reduction of Energy Metabolism by Oxidative Stress

Open-heart surgery is often an unavoidable option for the treatment of cardiovascular disease and prevention of cardiomyopathy. Cardiopulmonary bypass surgery requires manipulating cardiac contractile function via the perfusion of a cardioplegic solution. Procedure-associated ischemia and reperfusion (I/R) injury, a major source of oxidative stress, affects postoperative cardiac performance and long-term outcomes. Using large-scale liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics, we addressed whether cardioplegic solutions affect the baseline cellular metabolism and prevent metabolic reprogramming by oxidative stress. AC16 cardiomyocytes in culture were treated with commonly used cardioplegic solutions, High K+ (HK), Low K+ (LK), Del Nido (DN), histidine-tryptophan-ketoglutarate (HTK), or Celsior (CS). The overall metabolic profile shown by the principal component analysis (PCA) and heatmap revealed that HK or LK had a minimal impact on the baseline 78 metabolites, whereas HTK or CS significantly repressed the levels of multiple amino acids and sugars. H2O2-induced sublethal mild oxidative stress causes decreases in NAD, nicotinamide, or acetylcarnitine, but increases in glucose derivatives, including glucose 6-P, glucose 1-P, fructose, mannose, and mannose 6-P. Additional increases include metabolites of the pentose phosphate pathway, D-ribose-5-P, L-arabitol, adonitol, and xylitol. Pretreatment with HK or LK cardioplegic solution prevented most metabolic changes and increases of reactive oxygen species (ROS) elicited by H2O2. Our data indicate that HK and LK cardioplegic solutions preserve baseline metabolism and protect against metabolic reprogramming by oxidative stress.

Iron Deficiency and Deranged Myocardial Energetics in Heart Failure

Among different pathomechanisms involved in the development of heart failure, adverse metabolic myocardial remodeling closely related to ineffective energy production, constitutes the fundamental feature of the disease and translates into further progression of both cardiac dysfunction and maladaptations occurring within other organs. Being the component of key enzymatic machineries, iron plays a vital role in energy generation and utilization, hence the interest in whether, by correcting systemic and/or cellular deficiency of this micronutrient, we can influence the energetic efficiency of tissues, including the heart. In this review we summarize current knowledge on disturbed energy metabolism in failing hearts as well as we analyze experimental evidence linking iron deficiency with deranged myocardial energetics.

Pediatric Population with Down Syndrome: Obesity and the Risk of Cardiovascular Disease and Their Assessment Using Omics Techniques-Review

People with Down syndrome (PWDS) are more at risk for developing obesity, oxidative stress disorders, metabolic disorders, and lipid and carbohydrate profile disorders than the general population. The presence of an additional copy of genes on chromosome 21 (i.e., the superoxide dismutase 1 gene (SOD1) and gene coding for the cystathionine β-synthase (CBS) enzyme) raises the risk for cardiovascular disease (CVD). As a result of disorders in metabolic processes and biochemical pathways, theoretically protective factors (low homocysteine level, high SOD1 level) do not fulfil their original functions. Overexpression of the CBS gene leads to the accumulation of homocysteine-a CVD risk factor. An excessive amount of protective SOD1, in the case of a lack of compensatory increase in the activity of catalase and peroxidase, leads to intensifying free radical processes. The occurrence of metabolic disorders and the amplified effect of oxidative stress carries higher risk of exposure of people with DS to CVD. At present, classic predispositions are known, but it is necessary to identify early risk factors in order to be able to employ CVD and obesity prophylaxis. Detailed determination of the metabolic and lipid profile may provide insight into the molecular mechanisms underlying CVD.

Integration of metabolomics and transcriptomics to reveal anti-chronic myocardial ischemia mechanism of Gualou Xiebai decoction

ETHNOPHARMACOLOGICAL RELEVANCE

Gualou Xiebai decoction (GLXB), a well-known classic traditional Chinese medicine formula, is a recorded and proven therapy for the management of cardiac diseases. However, its pharmacological characteristics and mechanism of action are unclear.

MATERIALS AND METHODS

The effects of GLXB and its mechanism of action in an isoprenaline-induced rat model of chronic myocardial ischemia (CMI) were investigated by incorporating metabonomics and transcriptomics. Meanwhile, the echocardiographic evaluation, histopathological analysis, serum biochemistry assay, TUNEL assay and western blot analysis were detected to revealed the protective effects of GLXB on CMI.

RESULTS

The results of echocardiographic evaluation, histopathological analysis and serum biochemistry assay revealed that GLXB had a significantly cardioprotective performance by reversing echocardiographic abnormalities, restoring pathological disorders and converting the serum biochemistry perturbations. Further, the omics analysis indicated that many genes and metabolites were regulated after modeling and GLXB administration, and maintained the marked "high-low" or "low-high" trends. Meanwhile, the results from integrated bioinformatics analysis suggested that the interaction network mainly consisted of amino acid and organic acid metabolism. The results of TUNEL assay and western blot analysis complemented the findings of integrated analysis of metabolomics and transcriptomics.

CONCLUSION

These findings suggested that GLXB has a curative effect in isoproterenol-induced CMI in rats. Integrated analysis based on transcriptomics and metabolomics studies revealed that the mechanism of GLXB in alleviating CMI was principally by the regulation of energy homeostasis and apoptosis, which was through a multi-component and multi-target treatment modality.

Amino acid profiling to predict prognosis in patients with heart failure: an expert review

Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; however, the evidence has not yet been sufficiently evaluated. We describe the utilization of amino acids in the healthy heart and in heart failure before reviewing the literature on amino acid profiling for prognostic prediction. We expertly interpret the findings and provide suggestions for future research to advance the understanding of the prognostic potential of amino acid profiling in heart failure. Our analysis revealed correlations between amino acid biomarkers and traditional prognostic factors, the additional prognostic value of amino acid biomarkers over traditional prognostic factors, and the successful use of amino acid biomarkers to distinguish heart failure aetiology. Although certain amino acid biomarkers have demonstrated additional prognostic value over traditional measures, such as New York Heart Association functional class, these measures are deeply rooted in clinical practice; thus, amino acid biomarkers may be best placed as additional prognostic tools to improve current risk stratification rather than as surrogate tools. Once the metabolic profiles of different heart failure aetiologies have been clearly delineated, the amino acid biomarkers with the most value in prognostic prediction should be determined. Amino acid profiling could be useful to evaluate the pathophysiology and metabolic status of different heart failure cohorts, distinguish heart failure aetiologies, and improve risk stratification and prognostic prediction.

Insights into the development of pentylenetetrazole-induced epileptic seizures from dynamic metabolomic changes

Epilepsy is often considered to be a progressive neurological disease, and the nature of this progression remains unclear. Understanding the overall and common metabolic changes of epileptic seizures can provide novel clues for their control and prevention. Herein, a chronic kindling animal model was established to obtain generalized tonic-clonic seizures via the repeated injections of pentylenetetrazole (PTZ) at subconvulsive dose. Dynamic metabolomic changes in plasma and urine from PTZ-kindled rats at the different kindling phases were explored using NMR-based metabolomics, in combination with behavioral assessment, brain neurotransmitter measurement, electroencephalography and histopathology. The increased levels of glucose, lactate, glutamate, creatine and creatinine, together with the decreased levels of pyruvate, citrate and succinate, ketone bodies, asparagine, alanine, leucine, valine and isoleucine in plasma and/or urine were involved in the development and progression of seizures. These altered metabolites reflected the pathophysiological processes including the compromised energy metabolism, the disturbed amino acid metabolism, the peripheral inflammation and changes in gut microbiota functions. NMR-based metabolomics could provide brain disease information by the dynamic plasma and urinary metabolic changes during chronic epileptic seizures, yielding classification of seizure stages and profound insights into controlling epilepsy via targeting deficient energy metabolism.

Machine Learning Algorithm to Predict Obstructive Coronary Artery Disease: Insights from the CorLipid Trial

Developing risk assessment tools for CAD prediction remains challenging nowadays. We developed an ML predictive algorithm based on metabolic and clinical data for determining the severity of CAD, as assessed via the SYNTAX score. Analytical methods were developed to determine serum blood levels of specific ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and APOB/APOA1 ratio. Patients were grouped into: obstructive CAD (SS > 0) and non-obstructive CAD (SS = 0). A risk prediction algorithm (boosted ensemble algorithm XGBoost) was developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD. The study population comprised 958 patients (CorLipid trial (NCT04580173)), with no prior CAD, who underwent coronary angiography. Of them, 533 (55.6%) suffered ACS, 170 (17.7%) presented with NSTEMI, 222 (23.2%) with STEMI, and 141 (14.7%) with unstable angina. Of the total sample, 681 (71%) had obstructive CAD. The algorithm dataset was 73 biochemical parameters and metabolic biomarkers as well as anthropometric and medical history variables. The performance of the XGBoost algorithm had an AUC value of 0.725 (95% CI: 0.691−0.759). Thus, a ML model incorporating clinical features in addition to certain metabolic features can estimate the pre-test likelihood of obstructive CAD.

Pretreatment Glasgow Prognostic Score Correlated with Serum Histidine Level and Three-Year Mortality of Patients with Locally Advanced Head and Neck Squamous Cell Carcinoma and Optimal Performance Status

Few prospective cohort trials have investigted the effect of pretreatment nutritional and inflammatory status on the clinical outcome of patients with cancer and optimal performance status and assessed the interplay between nutrition, inflammation, body composition, and circulating metabolites before treatment. Here, 50 patients with locally advanced head and neck squamous cell carcinoma (LAHNSCC) and Eastern Cooperative Oncology Group performance status (ECOG PS) ≤ 2 were prospectively recruited along with 43 healthy participants. Before concurrent chemoradiotherapy, compared with healthy controls, the cancer group showed lower levels of histidine, leucine, and phenylalanine and had low values in anthropometric and body composition measurements; however, the group displayed higher ornithine levels, more malnutrition, and severe inflammation. Pretreatment advanced Glasgow prognostic score (1 and 2) status was the sole prognostic factor for 3-year mortality rate and was associated with age and serum histidine levels in patients with cancer. Thus, even at the same tumor stage and ECOG PS, patients with LAHNSCC, poor nutrition, and high inflammation severity at baseline may have inferior survival outcomes than those with adequate nutrition and low inflammation severity. Assessment of pretreatment nutritional and inflammatory status should be included in the enrollment criteria in future studies.

Quantification of Gut Microbiota Dysbiosis-Related Organic Acids in Human Urine Using LC-MS/MS

Urine organic acid contains water-soluble metabolites and/or metabolites—derived from sugars, amino acids, lipids, vitamins, and drugs—which can reveal a human’s physiological condition. These urine organic acids—hippuric acid, benzoic acid, phenylacetic acid, phenylpropionic acid, 4-hydroxybenzoic acid, 4-hydroxyphenyl acetic acid, 3-hydroxyphenylpropionic acid, 3,4-dihydroxyphenyl propionic acid, and 3-indoleacetic acid—were the eligible candidates for the dysbiosis of gut microbiota. The aim of this proposal was to develop and to validate a liquid chromatography−tandem mass spectrometry (LC-MS/MS) bioanalysis method for the nine organic acids in human urine. Stable-labeled isotope standard (creatinine-d3) and acetonitrile were added to the urine sample. The supernatant was diluted with deionized water and injected into LC-MS/MS. This method was validated with high selectivity for the urine sample, a low limit of quantification (10−40 ng/mL), good linearity (r > 0.995), high accuracy (85.8−109.7%), and high precision (1.4−13.3%). This method simultaneously analyzed creatinine in urine, which calibrates metabolic rate between different individuals. Validation has been completed for this method; as such, it could possibly be applied to the study of gut microbiota clinically.

Metabolomic profiling in small vessel disease identifies multiple associations with disease severity

Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches.

Metabolomics of Arterial Stiffness

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

Obesity-Related Insulin Resistance: The Central Role of Adipose Tissue Dysfunction

Obesity is a key player in the onset and progression of insulin resistance (IR), a state by which insulin-sensitive cells fail to adequately respond to insulin action. IR is a reversible condition, but if untreated leads to type 2 diabetes alongside increasing cardiovascular risk. The link between obesity and IR has been widely investigated; however, some aspects are still not fully characterized.In this chapter, we introduce key aspects of the pathophysiology of IR and its intimate connection with obesity. Specifically, we focus on the role of adipose tissue dysfunction (quantity, quality, and distribution) as a driver of whole-body IR. Furthermore, we discuss the obesity-related lipidomic remodeling occurring in adipose tissue, liver, and skeletal muscle. Key mechanisms linking lipotoxicity to IR in different tissues and metabolic alterations (i.e., fatty liver and diabetes) and the effect of weight loss on IR are also reported while highlighting knowledge gaps.

Revealing the Antiepileptic Effect of α-Asaronol on Pentylenetetrazole-Induced Seizure Rats Using NMR-Based Metabolomics

α-Asaronol from Acorus tatarinowii (known as "Shichangpu" in Traditional Chinese medicine) has been proved to possess more efficient antiepileptic activity and lower toxicity than α-asarone (namely "Xixinnaojiaonang" as an antiepileptic drug in China) in our previous study. However, the molecular mechanism of α-asaronol against epilepsy needs to be known if to become a novel antiepileptic medicine. Nuclear magnetic resonance (NMR)-based metabolomics was applied to investigate the metabolic patterns of plasma and the brain tissue extract from pentylenetetrazole (PTZ)-induced seizure rats when treated with α-asaronol or α-asarone. The results showed that α-asaronol can regulate the metabolomic level of epileptic rats to normal to some extent, and four metabolic pathways were associated with the antiepileptic effect of α-asaronol, including alanine, aspartate, and glutamate metabolism; synthesis and degradation of ketone bodies; glutamine and glutamate metabolism; and glycine, serine, and threonine metabolism. It was concluded that α-asaronol plays a vital role in enhancing energy metabolism, regulating the balance of excitatory and inhibitory neurotransmitters, and inhibiting cell membrane damage to prevent the occurrence of epilepsy. These findings are of great significance in developing α-asaronol into a promising antiepileptic drug derived from Traditional Chinese medicine.

Metabolomics of oxidative stress: Nrf2 independent depletion of NAD or increases of sugar alcohols

Nrf2 encodes a transcription factor best known for regulating the expression of antioxidant and detoxification genes. Recent evidence suggested that Nrf2 mediates metabolic reprogramming in cancer cells. However, the role of Nrf2 in the biochemical metabolism of cardiac cells has not been studied. Using LC-MS/MS-based metabolomics, we addressed whether knocking out the Nrf2 gene in AC16 human cardiomyocytes affects metabolic reprogramming by oxidative stress. Profiling the basal level metabolites showed an elevated pentose phosphate pathway and increased levels of sugar alcohols, sorbitol, L-arabitol, xylitol and xylonic acid, in Nrf2 KO cells. With sublethal levels of oxidative stress, depletion of NAD, an increase of GDP and elevation of sugar alcohols, sorbitol and dulcitol, were detected in parent wild type (WT) cells. Knocking out Nrf2 did not affect these changes. Biochemical assays confirmed depletion of NAD in WT and Nrf2 KO cells due to H₂O₂ treatment. These data support that although Nrf2 deficiency caused baseline activation of the pentose phosphate pathway and sugar alcohol synthesis, a brief exposure to none-lethal doses of H₂O₂ caused NAD depletion in an Nrf2 independent manner. Loss of NAD may contribute to oxidative stress associated cell degeneration as observed with aging, diabetes and heart failure.

Determination of up to twenty carboxylic acid containing compounds in clinically relevant matrices by o-benzylhydroxylamine derivatization and liquid chromatography-tandem mass spectrometry

Carboxylic acid containing compounds (R-COOH) are involved in a large number of biological processes and they are relevant for several pathological processes such as neurodegeneration or cancer. Comprehensive methodologies for the quantitative determination of R-COOH in biological samples are required. In this study we have developed a LC-MS/MS method for the quantification of 20 endogenous R-COOH belonging to different pathways such as kynurenine metabolism, serotoninergic pathway, glycolysis, tricarboxylic acid cycle, dopaminergic pathway, short chain fatty acids and glycine metabolism. The approach included derivatization with o-benzylhydroxylamine (reaction time 1 h), liquid-liquid extraction with ethyl acetate and LC-MS/MS detection (run time 10 min). The method was optimized and validated in 5 different matrices (urine, plasma, saliva, brain and liver) following two different approaches: (i) using surrogate matrices and (ii) using actual human samples by standard additions. A suitable linearity was obtained in the endogenous range of the analytes. Adequate intra and inter-assay accuracies (80-120%) and intra- and inter-assay precisions (<20%) were achieved for almost all analytes in all studied matrices. The method was applied in several scenarios to confirm (i) human urinary changes produced in glycolysis after exercise, (ii) metabolic changes produced in rat brain and plasma by methamphetamine administration and (iii) metabolic alterations in human plasma caused by vitamin B6 deficiency. Additionally, the application of the method allowed for establishing previously unreported alterations in R-COOH metabolites under these conditions. Due to the comprehensive analyte and matrix coverage and the wide applicability of the developed methodology, it can be considered as a suitable tool for the study of R-COOH status in health and disease by targeted metabolomics.

Metabolomics Work Flow and Analytics in Systems Biology

Metabolomics is an omics approach of systems biology that involves the development and assessment of large-scale, comprehensive biochemical analysis tools for metabolites in biological systems. This review describes the metabolomics workflow and provides an overview of current analytic tools used for the quantification of metabolic profiles. We explain analytic tools such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, ionization techniques, and approaches for data extraction and analysis.

Predictive serum biomarkers of patients with cerebral infarction

OBJECTIVES

Stroke is the third most common cause of death and also causes seizures and disability. Biomarkers are abnormal signal indicators at the biological level that are present before the organism is seriously affected and are more sensitive to early diagnosis than are traditional imaging methods. Early diagnosis of stroke can prevent the progression of the disease. However, there are currently no widely accepted biomarkers for stroke that have been applied clinically.

METHODS

A serum metabonomics method based on ultra-high-performance liquid chromatography-quadrupole-time of flight tandem mass spectrometry (UPLC-Q-TOF/MS) was used to identify potential biomarkers and metabolic pathways of cerebral infarction. The receiver-operating characteristic (ROC) curve was used to verify the diagnostic and classification abilities of the biomarkers, and a support vector machine (SVM) model was developed for the prediction of cerebral infarction.

RESULTS

Principal component analysis revealed a clear separation between the normal and cerebral infarction groups. A total of 13 potential serum biomarkers were identified, which were mainly involved in linoleic acid metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; tyrosine metabolism; arachidonic acid metabolism; and fatty acid biosynthesis. The ROC curve analysis showed that the potential biomarkers had high specificity and sensitivity for the diagnosis of cerebral infarction. The SVM model had good diagnostic ability and could accurately distinguish the control group from the cerebral infarction group.

DISCUSSION

The metabonomics approach may be a useful bioanalytical method for understanding the pathophysiology of cerebral infarction and may provide an experimental basis for the development of clinical biomarkers for stroke.

Metabolomics as a potential tool for the diagnosis of growth hormone deficiency (GHD): a review

Metabolomics uses several analytical tools to identify the chemical diversity of metabolites present in organisms. These metabolites are low molecular weight molecules (<1500 Da) classified as a final or intermediary product of metabolic processes. The application of this omics technology has become prominent in inferring physiological conditions through reporting on the phenotypic state; therefore, the introduction of metabolomics into clinical studies has been growing in recent years due to its efficiency in discriminating pathophysiological states. Regarding endocrine diseases, there is a great interest in verifying comprehensive and individualized physiological scenarios, in particular for growth hormone deficiency (GHD). The current GHD diagnostic tests are laborious and invasive and there is no exam with ideal reproducibility and sensitivity for diagnosis neither standard GH cut-off point. Therefore, this review was focussed on articles that applied metabolomics in the search for new biomarkers for GHD. The present work shows that the applications of metabolomics in GHD are still limited, since the little complementarily of analytical techniques, a low number of samples, GHD combined to other deficiencies, and idiopathic diagnosis shows a lack of progress. The results of the research are relevant and similar; however, their results do not provide an application for clinical practice due to the lack of multidisciplinary actions that would be needed to mediate the translation of the knowledge produced in the laboratory, if transferred to the medical setting.

LC-MS Based Metabolomics Study of the Effects of EGCG on A549 Cells

(−)-Epigallocatechin-3-gallate (EGCG) is the main bioactive catechin in green tea. The antitumor activity of EGCG has been confirmed in various types of cancer, including lung cancer. However, the precise underlying mechanisms are still largely unclear. In the present study, we investigated the metabolite changes in A549 cells induced by EGCG in vitro utilizing liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. The result revealed 33 differentially expressed metabolites between untreated and 80 μM EGCG-treated A549 cells. The altered metabolites were involved in the metabolism of glucose, amino acid, nucleotide, glutathione, and vitamin. Two markedly altered pathways, including glycine, serine and threonine metabolism and alanine, aspartate and glutamate metabolism, were identified by MetaboAnalyst 5.0 metabolic pathway analysis. These results may provide potential clues for the intramolecular mechanisms of EGCG’s effect on A549 cells. Our study may contribute to future molecular mechanistic studies of EGCG and the therapeutic application of EGCG in cancer management.

Metabolic Profiling and Metabolites Fingerprints in Human Hypertension: Discovery and Potential

Early detection of pathogenesis through biomarkers holds the key to controlling hypertension and preventing cardiovascular complications. Metabolomics profiling acts as a potent and high throughput tool offering new insights on disease pathogenesis and potential in the early diagnosis of clinical hypertension with a tremendous translational promise. This review summarizes the latest progress of metabolomics and metabolites fingerprints and mainly discusses the current trends in the application in clinical hypertension. We also discussed the associated mechanisms and pathways involved in hypertension's pathogenesis and explored related research challenges and future perspectives. The information will improve our understanding of the development of hypertension and inspire the clinical application of metabolomics in hypertension and its associated cardiovascular complications.

Defining Acute Coronary Syndrome through Metabolomics

As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.

Prevalence of dyslipidemia and gene polymorphisms of ABCB1 and SLCO1B1 in Han, Uygur, Kazak, Hui, Tatar, Kirgiz, and Sibe populations with coronary heart disease in Xinjiang, China

Background

Dyslipidemia is a predisposing factor for coronary heart disease (CHD). High-intensity statin therapy is recommended as secondary prevention. ABCB1 and SLCO1B1 genes influence the efficacy and safety of statins. Xinjiang is a multi-ethnic area; however, little is known about the prevalence of dyslipidemia and gene polymorphisms of ABCB1 and SLCO1B1 in minority groups with CHD.

Objective

To measure levels of lipid and apolipoprotein and the prevalence of dyslipidemia and gene polymorphisms of ABCB1, SLCO1B1 in Han, Uygur, Kazak, Hui, Tatar, Kirgiz, and Sibe populations with CHD in Xinjiang.

Methods

This descriptive retrospective study compares lipid levels in ethnic groups using Kruskal-Wallis test or analysis of variance. The study compared gene polymorphisms and the prevalence of dyslipidemia among different ethnic groups using the chi-square test. The lipid profiles in plasma were measured before lipid-lowering therapy using commercially available kits. Genotyping of SLCO1B1 and ABCB1 variants was performed using sequencing by hybridization.

Results

A total of 2218 patients were successfully screened, including 1044 Han, 828 Uygur, 113 Kazak, 138 Hui, 39 Tatar, 36 Kirgiz, and 20 Sibe patients. The overall mean age was 61.8 ± 10.8 years, and 72.5% of participants were male. Dyslipidemia prevalence in these ethnic groups was 42.1, 49.8, 52.2, 40.6, 48.7, 41.7, and 45.0%, respectively. The prevalence of dyslipidemia, high total cholesterol (TC), high triglycerides (TG), and high low density lipoprotein cholesterol (LDL-C) differed significantly among the groups (P = 0.024; P < 0.001; P < 0.001; P < 0.001, respectively). For the Han group, high LDL-C, high TC, and high TG prevalence differed significantly by gender (P = 0.001, P = 0.022, P = 0.037, respectively). The prevalence of high TC, high TG, and low high density lipoprotein cholesterol (HDL-C) differed significantly by gender in the Uygur group (P = 0.006, P = 0.004, P < 0.001, respectively). The prevalence of high TC in Hui patients significantly differed by gender (P = 0.043). These findings suggest that polymorphisms in ABCB1 and C3435T differ significantly across ethnicities (P < 0.001).

Conclusions

The prevalences of dyslipidemia, high TC, high TG, and high LDL-C in Han, Uygur, Kazak, Hui, Tatar, Kirgiz, and Sibe CHD patients in Xinjiang differed concerning ethnicity. Ethnic, gender, and lifestyle were the key factors that affected the lipid levels of the population. The prevalence of polymorphisms of ABCB1 and C3435T significantly differed across ethnicities. These findings will aid the selection of precision lipid-lowering medications and prevention and treatment of CHD according to ethnicity in Xinjiang.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01544-3.

Genome-wide analysis of blood lipid metabolites in over 5000 South Asians reveals biological insights at cardiometabolic disease loci

BACKGROUND

Genetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies.

METHODS

We characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci.

RESULTS

We identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci.

CONCLUSIONS

Our findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci.

Role of metabolomics in identifying cardiac hypertrophy: an overview of the past 20 years of development and future perspective

Cardiac hypertrophy (CH) is an augmentation of either the right ventricular or the left ventricular mass in order to compensate for the increase of work load on the heart. Metabolic abnormalities lead to histological changes of cardiac myocytes and turn into CH. The molecular mechanisms that lead to initiate CH have been of widespread concern, hence the development of the new field of research, metabolomics: one 'omics' approach that can reveal comprehensive information of the paradigm shift of metabolic pathways network in contrast to individual enzymatic reaction-based metabolites, have attempted and until now only 19 studies have been conducted using experimental animal and human specimens. Nuclear magnetic resonance spectroscopy and mass spectrometry-based metabolomics studies have found that CH is a metabolic disease and is mainly linked to the harmonic imbalance of glycolysis, citric acid cycle, amino acids and lipid metabolism. The current review will summarise the main outcomes of the above mentioned 19 studies that have expanded our understanding of the molecular mechanisms that may lead to CH and eventually to heart failure.

Pharmacodynamic substances in Salvia miltiorrhiza for prevention and treatment of hyperlipidemia and coronary heart disease based on lipidomics technology and network pharmacology analysis

In this study, untargeted lipidomics based on UPLC-Q/TOF-MS, network pharmacology and atomic force microscopy were used to explore the common biomarkers of hyperlipidemia and coronary heart disease, the therapeutic mechanism of the main components of Salvia miltiorrhiza as well as the action mechanism of key lipids. Firstly, the serum samples of 30 healthy people, 30 patients with coronary heart disease and 30 patients with hyperlipidemia were analyzed by using lipidomics technology to obtain biomarkers which can be used to link hyperlipidemia and coronary heart disease and to find potential targets; then, the key components and core targets of Salvia miltiorrhiza intervention in hyperlipidemia and coronary heart disease were analyzed by network pharmacology, the results were verified by atomic force microscopy. It showed that SMS2 might be the key target. And through network pharmacology and atomic force microscope analysis, it can be inferred that salvianolic acid A can combine with SMS2 to play a therapeutic role.

Serum Metabolomic Analysis Suggests Impairment of Myocardial Energy Production in Takotsubo Syndrome

INTRODUCTION

Takotsubo syndrome is a complex entity that, although it usually has a good prognosis, can be life threatening. While recent advances have improved the knowledge of takotsubo syndrome, many aspects of its etiology still remain uncertain. Metabolomics, a hypothesis generating approach, could provide novel pathophysiology information about this disease.

METHODS AND RESULTS

Serum samples were obtained from takotsubo (n = 19) and acute myocardial infarction patients (n = 8) at the cath lab and, in the case of takotsubo, again once the patient had recovered, 3 months after the main event. ¹H NMR spectra of the serum were acquired at 9.4T using a CPMG pulse sequence (32 ms effective delay). Supervised and unsupervised pattern recognition approaches where applied to the data. Pattern recognition was able to differentiate between takotsubo and acute myocardial infarction during the acute phase with 95% accuracy. Myocardial infarction patients showed an increase in lipid signals, a known risk factor for the disease while takotsubo patients showed a relative increase in acetate that could suggest a reduced turnover of the Krebs cycle. When comparing acute and recovered phases, we could detect an increase in alanine and creatine once patients recovered.

CONCLUSIONS

Our results demonstrate that takotsubo syndrome is metabolically different than AMI, showing limited myocardial energy production capacity during the acute phase. We achieved high classification success against AMI; however, this study should be considered as a proof of concept regarding clinical application of metabolic profiling in takotsubo cardiomyopathy.

The Effect of Blood Contained in the Samples on the Metabolomic Profile of Mouse Brain Tissue: A Study by NMR Spectroscopy

(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1^® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency ¹H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student's test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

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

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

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

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

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