Metabolomic distinction and insights into the pathogenesis of human primary dilated cardiomyopathy

Decoding the 'Fifth' Nucleotide: Impact of RNA Pseudouridylation on Gene Expression and Human Disease

Cellular RNAs, both coding and noncoding are adorned by > 100 chemical modifications, which impact various facets of RNA metabolism and gene expression. Very often derailments in these modifications are associated with a plethora of human diseases. One of the most oldest of such modification is pseudouridylation of RNA, wherein uridine is converted to a pseudouridine (Ψ) via an isomerization reaction. When discovered, Ψ was referred to as the 'fifth nucleotide' and is chemically distinct from uridine and any other known nucleotides. Experimental evidence accumulated over the past six decades, coupled together with the recent technological advances in pseudouridine detection, suggest the presence of pseudouridine on messenger RNA, as well as on diverse classes of non-coding RNA in human cells. RNA pseudouridylation has widespread effects on cellular RNA metabolism and gene expression, primarily via stabilizing RNA conformations and destabilizing interactions with RNA-binding proteins. However, much remains to be understood about the RNA targets and their recognition by the pseudouridylation machinery, the regulation of RNA pseudouridylation, and its crosstalk with other RNA modifications and gene regulatory processes. In this review, we summarize the mechanism and molecular machinery involved in depositing pseudouridine on target RNAs, molecular functions of RNA pseudouridylation, tools to detect pseudouridines, the role of RNA pseudouridylation in human diseases like cancer, and finally, the potential of pseudouridine to serve as a biomarker and as an attractive therapeutic target.

The Role of Gut Microbiota and Its Metabolites in Patients with Heart Failure

Heart failure (HF) is a significant health concern; early detection and prevention are crucial. Recent studies suggest that the gut microbiota and its metabolites may influence HF development and risk factors. We explored this relationship by examining changes in gut microbiota composition and metabolite levels in HF patients. HF patients often exhibit decreased alpha and beta diversity compared to controls, suggesting lower bacterial richness and community variation. Changes in specific bacterial phyla were observed, with decreases in Firmicutes (e.g., Ruminococcus) and Bacteroidetes (e.g., Prevotella) and increases in Proteobacteria (e.g., Escherichia, Shigella, and Klebsiella) and Actinobacteria. Gut-microbiota-related metabolites have been identified, potentially affecting various body systems, including the cardiovascular system. Among these are short-chain fatty acids (SCFAs), betaine, trimethylamine N-oxide (TMAO), phenylalanine, tryptophan-kynurenine, and phenylacetylgutamine (PAGIn). Although SCFAs positively affect our organisms, patients with HF have been observed to experience a decline in bacteria responsible for producing these chemical compounds. There have been indications of possible links between betaine, TMAO, phenylalanine, tryptophan-kynurenine, PAGIn, and heart failure. TMAO and phenylalanine, in particular, show promise as potential prognostic factors. However, their clinical significance has not yet been thoroughly evaluated and requires further investigation.

Unlocking the dark matter: noncoding RNAs and RNA modifications in cardiac aging

Cardiac aging is a multifaceted process that encompasses structural and functional alterations culminating in heart failure. As the elderly population continues to expand, there is a growing urgent need for interventions to combat age-related cardiac functional decline. Noncoding RNAs have emerged as critical regulators of cellular and biochemical processes underlying cardiac disease. This review summarizes our current understanding of how noncoding RNAs function in the heart during aging, with particular emphasis on mechanisms of RNA modification that control their activity. Targeting noncoding RNAs as potential novel therapeutics in cardiac aging is also discussed.

Metabolomic Association and Risk Prediction With Heart Failure in Older Adults

BACKGROUND

Older adults have markedly increased risks of heart failure (HF), specifically HF with preserved ejection fraction (HFpEF). Identifying novel biomarkers can help in understanding HF pathogenesis and improve at-risk population identification. This study aimed to identify metabolites associated with incident HF, HFpEF, and HF with reduced ejection fraction and examine risk prediction in older adults.

METHODS

Untargeted metabolomic profiling was performed in Black and White adults from the ARIC study (Atherosclerosis Risk in Communities) visit 5 (n=3719; mean age, 75 years). We applied Cox regressions to identify metabolites associated with incident HF and its subtypes. The metabolite risk score (MRS) was constructed and examined for associations with HF, echocardiographic measures, and HF risk prediction. Independent samples from visit 3 (n=1929; mean age, 58 years) were used for replication.

RESULTS

Sixty metabolites (hazard ratios range, 0.79-1.49; false discovery rate, <0.05) were associated with incident HF after adjusting for clinical risk factors, eGFR, and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Mannonate, a hydroxy acid, was replicated (hazard ratio, 1.36 [95% CI, 1.19-1.56]) with full adjustments. MRS was associated with an 80% increased risk of HF per SD increment, and the highest MRS quartile had 8.7× the risk of developing HFpEF than the lowest quartile. High MRS was also associated with unfavorable values of cardiac structure and function. Adding MRS over clinical risk factors and NT-proBNP improved 5-year HF risk prediction C statistics from 0.817 to 0.850 (∆C, 0.033 [95% CI, 0.017-0.047]). The association between MRS and incident HF was replicated after accounting for clinical risk factors (P<0.05).

CONCLUSIONS

Novel metabolites associated with HF risk were identified, elucidating disease pathways, specifically HFpEF. An MRS was associated with HF risk and improved 5-year risk prediction in older adults, which may assist at at-risk population identification.

Metabolomic profiling reveals key metabolites associated with hypertension progression

Introduction

Pre-hypertension is a prevalent condition among the adult population worldwide. It is characterized by asymptomatic elevations in blood pressure beyond normal levels but not yet reaching the threshold for hypertension. If left uncontrolled, pre-hypertension can progress to hypertension, thereby increasing the risk of serious complications such as heart disease, stroke, kidney damage, and others.

Objective

The precise mechanisms driving the progression of hypertension remain unknown. Thus, identifying the metabolic changes associated with this condition can provide valuable insights into potential markers or pathways implicated in the development of hypertension.

Methods

In this study, we utilized untargeted metabolomics profiling, which examines over 1,000 metabolites to identify novel metabolites contributing to the progression from pre-hypertension to hypertension. Data were collected from 323 participants through Qatar Biobank.

Results

By comparing metabolic profiles between pre-hypertensive, hypertensive and normotensive individuals, six metabolites including stearidonate, hexadecadienoate, N6-carbamoylthreonyladenosine, 9 and 13-S-hydroxyoctadecadienoic acid (HODE), 2,3-dihydroxy-5-methylthio- 4-pentenoate (DMTPA), and linolenate were found to be associated with increased risk of hypertension, in both discovery and validation cohorts. Moreover, these metabolites showed a significant diagnostic performance with area under curve >0.7.

Conclusion

These findings suggest possible biomarkers that can predict the risk of progression from pre-hypertension to hypertension. This will aid in early detection, diagnosis, and management of this disease as well as its associated complications.

Metabolome Profiling in the Plasma of Dogs with Idiopathic Dilated Cardiomyopathy: A Multiplatform Mass-Spectrometry-Based Approach

Dilated cardiomyopathy is one of the important diseases in dogs and humans. The second most common cause of heart failure in dogs is idiopathic dilated cardiomyopathy (iDCM), which results in heart failure or sudden cardiac death due to arrhythmia. This study aimed to determine changes in the plasma metabolome of dogs with iDCM compared to healthy dogs. For that purpose, a multiplatform mass-spectrometry-based approach was used. In this study, we included two groups of dogs: 12 dogs with iDCM and 8 healthy dogs. A total of 272 metabolites were detected in the plasma samples of dogs by combining three approaches but four MS-based platforms (GC-MS, LC-MS (untargeted), LC-MS (targeted), and FIA-MS (targeted) methods). Our findings demonstrated changes in the canine plasma metabolome involved in the development of iDCM, including the different concentrations of amino acids, biogenic amines, acylcarnitines, triglycerides and diglycerides, sphingomyelins, and organic acids. The results of this study will enable the detection and monitoring of pathophysiological mechanisms involved in the development of iDCM in the future.

Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism

Introduction

Cardiomyopathies are complex heart diseases with significant prevalence around the world. Among these, primary forms are the major contributors to heart failure and sudden cardiac death. As a high-energy demanding engine, the heart utilizes fatty acids, glucose, amino acid, lactate and ketone bodies for energy to meet its requirement. However, continuous myocardial stress and cardiomyopathies drive towards metabolic impairment that advances heart failure (HF) pathogenesis. So far, metabolic profile correlation across different cardiomyopathies remains poorly understood.

Methods

In this study, we systematically explore metabolic differences amongst primary cardiomyopathies. By assessing the metabolic gene expression of all primary cardiomyopathies, we highlight the significantly shared and distinct metabolic pathways that may represent specialized adaptations to unique cellular demands. We utilized publicly available RNA-seq datasets to profile global changes in the above diseases (|log2FC| ≥ 0.28 and BH adjusted p-val 0.1) and performed gene set analysis (GSA) using the PAGE statistics on KEGG pathways.

Results

Our analysis demonstrates that genes in arachidonic acid metabolism (AA) are significantly perturbed across cardiomyopathies. In particular, the arachidonic acid metabolism gene PLA2G2A interacts with fibroblast marker genes and can potentially influence fibrosis during cardiomyopathy.

Conclusion

The profound significance of AA metabolism within the cardiovascular system renders it a key player in modulating the phenotypes of cardiomyopathies.

Gut Microbiome-Based Management of Patients With Heart Failure: JACC Review Topic of the Week

Despite therapeutic advances, chronic heart failure (HF) is still associated with significant risk of morbidity and mortality. The course of disease and responses to therapies vary widely among individuals with HF, highlighting the need for precision medicine approaches. Gut microbiome stands to be an important aspect of precision medicine in HF. Exploratory clinical studies have revealed shared patterns of gut microbiome dysregulation in this disease, with mechanistic animal studies providing evidence for active involvement of the gut microbiome in development and pathophysiology of HF. Deeper insights into gut microbiome-host interactions in patients with HF promise to deliver novel disease biomarkers, preventative and therapeutic targets, and improve disease risk stratification. This knowledge may enable a paradigm shift in how we care for patients with HF, and pave the path toward improved clinical outcomes through personalized HF care.

Metabolomic profiling in dogs with dilated cardiomyopathy eating non-traditional or traditional diets and in healthy controls

Dilated cardiomyopathy (DCM), caused by genetic and environmental factors, usually progresses to heart failure, a major cause of death in elderly people. A diet-associated form of DCM was recently identified in pet dogs eating non-traditional (NT) diets. To identify potential dietary causes, we analyzed metabolomic signatures and gene set/pathway enrichment in (1) all dogs based on disease, diet, and their interactions and (2) dogs with DCM based on diet. Metabolomic analysis was performed in 38 dogs with DCM eating NT diets (DCM-NT), 8 dogs with DCM eating traditional diets, 12 healthy controls eating NT diets, and 17 healthy controls eating traditional diets. Overall, 153 and 63 metabolites differed significantly between dogs with DCM versus healthy controls and dogs eating NT versus traditional diets, respectively, with 12 metabolites overlapping both analyses. Protein-protein interaction networks and gene set enrichment analysis identified 105 significant pathways and gene sets including aging-related pathways (e.g., nuclear factor-kappa B, oxidative damage, inflammation). Seventeen metabolites differed significantly in dogs with DCM eating NT versus traditional diets (e.g., fatty acids, amino acids, legume biomarkers), suggesting different mechanisms for primary versus diet-associated DCM. Our multifaceted metabolomic assessment of DCM in dogs highlighted diet's role in some forms of DCM.

Comprehensive analysis of transcriptomics and metabolomics to understand chronic ethanol induced murine cardiotoxicity

Alcohol abuse has attracted public attention and long-term alcohol exposure can lead to alcohol-featured non-ischemic dilated cardiomyopathy. However, the precise underlying mechanisms of alcoholic cardiomyopathy remain to be elucidated. This study aimed to comprehensively characterize alcohol abuse-mediated effects on downstream metabolites and genes transcription using a multi-omics strategy. We established chronic ethanol intoxication model in adult male C57BL/6 mice through 8 weeks of 95% alcohol vapor administration and performed metabolomics analysis, mRNA-seq and microRNA-seq analysis with myocardial tissues. Firstly, ethanol markedly induced ejection fraction reductions, cardiomyocyte hypertrophy, and myocardial fibrosis in mice with myocardial oxidative injury. In addition, the omics analysis identified a total of 166 differentially expressed metabolites (DEMs), 241 differentially expressed genes (DEGs) and 19 differentially expressed microRNAs (DEmiRNAs), respectively. The results highlighted that alcohol abuse mainly interfered with endogenous lipids, amino acids and nucleotides production and the relevant genes transcription in mice hearts. Based on KEGG database, the affected signaling pathways are primarily mapped to the antigen processing and presentation, regulation of actin cytoskeleton, AMPK signaling pathway, tyrosine metabolism and PPAR signaling pathway, etc. Furthermore, 9 hub genes related to oxidative stress from DEGs were selected based on function annotation, and potential alcoholic cardiotoxic oxidative stress biomarkers were determined through establishing PPI network and DEmiRNAs-DEGs cross-talk. Altogether, our data strongly supported the conclusion that ethanol abuse characteristically affected amino acid and energy metabolism, nucleotide metabolism and especially lipids metabolism in mice hearts, and underlined the values of lipids signaling and oxidative stress in the treatment strategies.

RNA modifications in aging-associated cardiovascular diseases

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.

NMR-Based Metabolomic Analysis of Cardiac Tissues Clarifies Molecular Mechanisms of CVB3-Induced Viral Myocarditis and Dilated Cardiomyopathy

Viral myocarditis (VMC), which is defined as inflammation of the myocardium with consequent myocardial injury, may develop chronic disease eventually leading to dilated cardiomyopathy (DCM). Molecular mechanisms underlying the progression from acute VMC (aVMC), to chronic VMC (cVMC) and finally to DCM, are still unclear. Here, we established mouse models of VMC and DCM with Coxsackievirus B3 infection and conducted NMR-based metabolomic analysis of aqueous metabolites extracted from cardiac tissues of three histologically classified groups including aVMC, cVMC and DCM. We showed that these three pathological groups were metabolically distinct from their normal counterparts and identified three impaired metabolic pathways shared by these pathological groups relative to normal controls, including nicotinate and nicotinamide metabolism; alanine, aspartate and glutamate metabolism; and D-glutamine and D-glutamate metabolism. We also identified two extra impaired metabolic pathways in the aVMC group, including glycine, serine and threonine metabolism; and taurine and hypotaurine metabolism Furthermore, we identified potential cardiac biomarkers for metabolically distinguishing these three pathological stages from normal controls. Our results indicate that the metabolomic analysis of cardiac tissues can provide valuable insights into the molecular mechanisms underlying the progression from acute VMC to DCM.

Metabolite Signature in the Carriers of Pathogenic Genetic Variants for Cardiomyopathy: A Population-Based METSIM Study

Hypertrophic (HCM) and dilated (DCM) cardiomyopathies are among the leading causes of sudden cardiac death. We identified 38 pathogenic or likely pathogenic variant carriers for HCM in three sarcomere genes (MYH7, MYBPC3, TPMI) among 9.928 participants of the METSIM Study having whole exome sequencing data available. Eight of them had a clinical diagnosis of HCM. We also identified 20 pathogenic or likely pathogenic variant carriers for DCM in the TTN gene, and six of them had a clinical diagnosis of DCM. The aim of our study was to investigate the metabolite signature in the carriers of the pathogenic or likely pathogenic genetic variants for HCM and DCM, compared to age- and body-mass-index-matched controls. Our novel findings were that the carriers of pathogenic or likely pathogenic variants for HCM had significantly increased concentrations of bradykinin (des-arg 9), vanillactate, and dimethylglycine and decreased concentrations of polysaturated fatty acids (PUFAs) and lysophosphatidylcholines compared with the controls without HCM. Additionally, our novel findings were that the carriers of pathogenic or likely pathogenic variants for DCM had significantly decreased concentrations of 1,5-anhydrogluticol, histidine betaine, N-acetyltryptophan, and methylsuccinate and increased concentrations of trans-4-hydroxyproline compared to the controls without DCM. Our population-based study shows that the metabolite signature of the genetic variants for HCM and DCM includes several novel metabolic pathways not previously described.

Metabolic and metabolomics insights into dilated cardiomyopathy (DCM)

BACKGROUND

Dilated cardiomyopathy (DCM) is the most common form of heart muscle disease characterized by progressive dilatation and ventricular dysfunction. Metabolomics is an emerging and powerful discipline that provides a global information on the phenotype of mammalian systems via the study of endogenous and exogenous metabolites in cells, tissues and biofluids. These studies aid in the identification of biomarkers to prevent diseases in later life or help to early detect onset of diseases as well as aiding in the elucidation of disease mechanisms.

SUMMARY

Metabolomics provides a unique opportunity to discover biomarkers for DCM. This review demonstrates evidence of metabolite-based biomarkers useful for predicting, diagnosing and monitoring therapeutic interventions of DCM. Key metabolites identified as potential biomarkers for diagnosing DCM include acyl-carnitines, succinic acid, malate, methylhistidine, aspartate, methionine, phenylalanine. In terms of differentiating DCM from ICM, potential biomarkers including 1-pyrroline-2-carboxylate, norvaline, lysophosphatidylinositol (16:0/0:0), phosphatidylglycerol, fatty acid esters of hydroxy fatty acid, and phosphatidylcholine were identified. Acyl-carnitines, isoleucine and linoleic acid and tryptophan were the main biomarkers to monitor treatment response to DCM. Mapping metabolites to metabolic pathways revealed dysregulation of BCAA, glycolysis, tricarboxylic acid cycle and triacylglycerol and pentose phosphate metabolism which have therapeutic potential for DCM. This review shows several limitations including the use of small sample sizes, lack of interpretation of age and sex differences in most studies and the fact that studies have so far been limited to case-control study designs.

KEY MESSAGES

Metabolites have close proximity to disease phenotype. With recent advancements in metabolomics field, potential biomarkers for DCM have been identified based on studies using different biological and metabolomics technologies. However, multi-center studies with larger populations that will lead to validation of these identified biomarkers to enable their clinical translation and utilization are still needed.

Interplay Between Gut Microbiota and Amino Acid Metabolism in Heart Failure

Heart failure (HF) is a complex clinical syndrome of which the incidence is on the rise worldwide. Cardiometabolic disorders are associated with the deterioration of cardiac function and progression of HF. Recently, there has been renewed interest in gut microbiota (GM) and its metabolites in the cardiovascular disease. HF-caused hypoperfusion could increase intestinal permeability, and a “leaky” bowel leads to bacterial translocation and make its metabolites more easily enter the circulation. Considerable evidence shows that the composition of microbiota and amino acids (AAs) has been altered in HF patients, and AAs could serve as a diagnostic and prognostic biomarker in HF. The findings indicate that the gut–amino acid–HF axis may play a key role in the progression of HF. In this paper, we focus on the interrelationship between the AA metabolism and GM alterations during the development of heart failure. We also discuss the potential prognostic and therapeutic value of the gut–amino acid–HF axis in the cortex of HF.

Investigation of diets associated with dilated cardiomyopathy in dogs using foodomics analysis

Dilated cardiomyopathy (DCM) is a disease of the heart muscle that affects both humans and dogs. Certain canine diets have been associated with DCM, but the diet-disease link is unexplained, and novel methods are needed to elucidate mechanisms. We conducted metabolomic profiling of 9 diets associated with canine DCM, containing ≥ 3 pulses, potatoes, or sweet potatoes as main ingredients, and in the top 16 dog diet brands most frequently associated with canine DCM cases reported to the FDA (3P/FDA diets), and 9 non-3P/FDA diets. We identified 88 named biochemical compounds that were higher in 3P/FDA diets and 23 named compounds that were lower in 3P/FDA diets. Amino acids, amino acid-derived compounds, and xenobiotics/plant compounds were the largest categories of biochemicals that were higher in 3P/FDA diets. Random forest analyses identified the top 30 compounds that distinguished the two diet groups with 100% predictive accuracy. Four diet ingredients distinguished the two diet groups (peas, lentils, chicken/turkey, and rice). Of these ingredients, peas showed the greatest association with higher concentrations of compounds in 3P/FDA diets. Moreover, the current foodomics analyses highlight relationships between diet and DCM in dogs that can identify possible etiologies for understanding diet-disease relationships in dogs and humans.

Glycolysis Metabolites and Risk of Atrial Fibrillation and Heart Failure in the PREDIMED Trial

The increased prevalence of atrial fibrillation (AF) and heart failure (HF) highlights the need to better understand the mechanisms underlying these cardiovascular diseases (CVDs). In the present study, we aimed to evaluate the association between glycolysis-related metabolites and the risk of AF and HF in a Mediterranean population at high risk of CVD. We used two case-control studies nested within the PREDIMED trial. A total of 512 incident AF cases matched to 734 controls, and 334 incident HF cases matched to 508 controls, were included. Plasma metabolites were quantified by using hydrophilic interaction liquid chromatography coupled with high-resolution negative ion mode MS detection. Conditional logistic regression analyses were performed. The results showed no association between baseline plasma glycolysis intermediates and other related metabolites with AF. Only phosphoglycerate was associated with a higher risk of HF (OR _{for 1 SD increase}: 1.28; 95% CI: 1.06, 1.53). The present findings do not support a role of the glycolysis pathway in the pathogenesis of AF. However, the increased risk of HF associated with phosphoglycerate requires further studies.

RNA modifications in cardiovascular diseases, the potential therapeutic targets

More than one hundred RNA modifications decorate the chemical and topological properties of these ribose nucleotides, thereby executing their biological functions through post-transcriptional regulation. In cardiovascular diseases, a wide range of RNA modifications including m⁶A (N6-adenosine methylation), m⁵C (5-methylcytidin), Nm (2'-O-ribose-methylation), Ψ (pseudouridine), m⁷G (N7-methylguanosine), and m¹A (N1-adenosine methylation) have been found in tRNA, rRNA, mRNA and other noncoding RNA, which can function as a novel mechanism in metabolic syndrome, heart failure, coronary heart disease, and hypertension. In this review, we will summarize the current understanding of the regulatory roles and significance of several types of RNA modifications in CVDs (cardiovascular diseases) and the interplay between RNA modifications and noncoding RNA, epigenetics. Finally, we will focus on the potential therapeutic strategies by using RNA modifications.

Narrative review of metabolomics in cardiovascular disease

Cardiovascular diseases are accompanied by disorders in the cardiac metabolism. Furthermore, comorbidities often associated with cardiovascular disease can alter systemic and myocardial metabolism contributing to worsening of cardiac performance and health status. Biomarkers such as natriuretic peptides or troponins already support diagnosis, prognosis and treatment of patients with cardiovascular diseases and are represented in international guidelines. However, as cardiovascular diseases affect various pathophysiological pathways, a single biomarker approach cannot be regarded as ideal to reveal optimal clinical application. Emerging metabolomics technology allows the measurement of hundreds of metabolites in biological fluids or biopsies and thus to characterize each patient by its own metabolic fingerprint, improving our understanding of complex diseases, significantly altering the management of cardiovascular diseases and possibly personalizing medicine. This review outlines current knowledge, perspectives as well as limitations of metabolomics for diagnosis, prognosis and treatment of cardiovascular diseases such as heart failure, atherosclerosis, ischemic and non-ischemic cardiomyopathy. Furthermore, an ongoing research project tackling current inconsistencies as well as clinical applications of metabolomics will be discussed. Taken together, the application of metabolomics will enable us to gain more insights into pathophysiological interactions of metabolites and disease states as well as improving therapies of patients with cardiovascular diseases in the future.

Metabolic Signature of Arrhythmogenic Cardiomyopathy

Arrhythmogenic cardiomyopathy (ACM) is a genetic-based cardiac disease accompanied by severe ventricular arrhythmias and a progressive substitution of the myocardium with fibro-fatty tissue. ACM is often associated with sudden cardiac death. Due to the reduced penetrance and variable expressivity, the presence of a genetic defect is not conclusive, thus complicating the diagnosis of ACM. Recent studies on human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs) obtained from ACM individuals showed a dysregulated metabolic status, leading to the hypothesis that ACM pathology is characterized by an impairment in the energy metabolism. However, despite efforts having been made for the identification of ACM specific biomarkers, there is still a substantial lack of information regarding the whole metabolomic profile of ACM patients. The aim of the present study was to investigate the metabolic profiles of ACM patients compared to healthy controls (CTRLs). The targeted Biocrates AbsoluteIDQ^® p180 assay was used on plasma samples. Our analysis showed that ACM patients have a different metabolome compared to CTRLs, and that the pathways mainly affected include tryptophan metabolism, arginine and proline metabolism and beta oxidation of fatty acids. Altogether, our data indicated that the plasma metabolomes of arrhythmogenic cardiomyopathy patients show signs of endothelium damage and impaired nitric oxide (NO), fat, and energy metabolism.

Plasma Metabolomics Reveals Metabolic Profiling For Diabetic Retinopathy and Disease Progression

BACKGROUNDS

Diabetic retinopathy (DR), the main retinal vascular complication of DM, is the leading cause of visual impairment and blindness among working-age people worldwide. The aim of this study was to investigate the difference of plasma metabolic profiles in patients with DR to better understand the mechanism of this disease and disease progression.

METHODS

We used ultrahigh-performance liquid Q-Exactive mass spectrometry and multivariate statistical analyses to conduct a comprehensive analysis of plasma metabolites in a population with DR and proliferative DR (PDR). A risk score based on the level of the selected metabolite was established and evaluated using the least absolute shrinkage and selection operator regularization logistic regression (LASSO-LR) based machine learning model.

RESULTS

22 differentially expressed metabolites which belonged to different metabolic pathway were identified and confirmed to be associated with the occurrence of DR. A risk score based on the level of the selected metabolite pseudouridine was established and evaluated to strongly associated with the occurrence of DR. Four circulating plasma metabolites (pseudouridine, glutamate, leucylleucine and N-acetyltryptophan) were identified to be differentially expressed between patients with PDR and other patients, and a risk score formula based on these plasma metabolites was developed and assessed to be significantly related to PDR.

CONCLUSIONS

Our work highlights the possible use of the risk score assessment based on the plasma metabolites not only reveal in the early diagnosis of DR and PDR but also assist in enhancing current therapeutic strategies in the clinic.

Method comparison of HPLC-ninhydrin-photometry and UHPLC-PITC-tandem mass spectrometry for serum amino acid analyses in patients with complex congenital heart disease and controls

INTRODUCTION

Metabolomics studies are not routine when quantifying amino acids (AA) in congenital heart disease (CHD).

OBJECTIVES

Comparative analysis of 24 AA in serum by traditional high-performance liquid chromatography (HPLC) based on ion exchange and ninhydrin derivatisation followed by photometry (PM) with ultra-high-performance liquid chromatography and phenylisothiocyanate derivatisation followed by tandem mass spectrometry (TMS); interpretation of findings in CHD patients and controls.

METHODS

PM: Sample analysis as above (total run time, ~ 119 min). TMS: Sample analysis by AbsoluteIDQ® p180 kit assay (BIOCRATES Life Sciences AG, Innsbruck, Austria), which employs PITC derivatisation; separation of analytes on a Waters Acquity UHPLC BEH18 C18 reversed-phase column, using water and acetonitrile with 0.1% formic acid as the mobile phases; and quantification on a Triple-Stage Quadrupole tandem mass spectrometer (Thermo Fisher Scientific, Waltham, MA) with electrospray ionisation in the presence of internal standards (total run time, ~ 8 min). Calculation of coefficients of variation (CV) (for precision), intra- and interday accuracies, limits of detection (LOD), limits of quantification (LOQ), and mean concentrations.

RESULTS

Both methods yielded acceptable results with regard to precision (CV < 10% PM, < 20% TMS), accuracies (< 10% PM, < 34% TMS), LOD, and LOQ. For both Fontan patients and controls AA concentrations differed significantly between methods, but patterns yielded overall were parallel.

CONCLUSION

Serum AA concentrations differ with analytical methods but both methods are suitable for AA pattern recognition. TMS is a time-saving alternative to traditional PM under physiological conditions as well as in patients with CHD.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier NCT03886935, date of registration March 27th, 2019 (retrospectively registered).

Gut microbiome - A potential mediator of pathogenesis in heart failure and its comorbidities: State-of-the-art review

Gut microbiome (GMB) has been increasingly recognized as a contributor to development and progression of heart failure (HF), immune-mediated subtypes of cardiomyopathy (myocarditis and anthracycline-induced cardiotoxicity), response to certain cardiovascular drugs, and HF-related comorbidities, such as chronic kidney disease, cardiorenal syndrome, insulin resistance, malnutrition, and cardiac cachexia. Gut microbiome is also responsible for the "gut hypothesis" of HF, which explains the adverse effects of gut barrier dysfunction and translocation of GMB on the progression of HF. Furthermore, accumulating evidence has suggested that gut microbial metabolites, including short chain fatty acids, trimethylamine N-oxide (TMAO), amino acid metabolites, and bile acids, are mechanistically linked to pathogenesis of HF, and could, therefore, serve as potential therapeutic targets for HF. Even though there are a variety of proposed therapeutic approaches, such as dietary modifications, prebiotics, probiotics, TMAO synthesis inhibitors, and fecal microbial transplant, targeting GMB in HF is still in its infancy and, indeed, requires further preclinical and clinical evidence. In this review, we aim to highlight the role gut microbiome plays in HF pathophysiology and its potential as a novel therapeutic target in HF.

Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels

Aortic valve stenosis (AVS) is a prevalent condition among the elderly population that eventually requires aortic valve replacement. The lack of reliable biomarkers for AVS poses a challenge for its early diagnosis and the application of preventive measures. Untargeted gas chromatography mass spectrometry (GC-MS) metabolomics was applied in 46 AVS cases and 46 controls to identify plasma and urine metabolites underlying AVS risk. Multivariate data analyses were performed on pre-processed data (e.g. spectral peak alignment), in order to detect changes in metabolite levels in AVS patients and to evaluate their performance in group separation and sensitivity of AVS prediction, followed by regression analyses to test for their association with AVS. Through untargeted analysis of 190 urine and 130 plasma features that could be detected and quantified in the GC-MS spectra, we identified contrasting levels of 22 urine and 21 plasma features between AVS patients and control subjects. Following metabolite assignment, we observed significant changes in the concentration of known metabolites in urine (n = 14) and plasma (n = 15) that distinguish the metabolomic profiles of AVS patients from healthy controls. Associations with AVS were replicated in both plasma and urine for about half of these metabolites. Among these, 2-Oxovaleric acid, elaidic acid, myristic acid, palmitic acid, estrone, myo-inositol showed contrasting trends of regulation in the two biofluids. Only trans-Aconitic acid and 2,4-Di-tert-butylphenol showed consistent patterns of regulation in both plasma and urine. These results illustrate the power of metabolomics in identifying potential disease-associated biomarkers and provide a foundation for further studies towards early diagnostic applications in severe heart conditions that may prevent surgery in the elderly.

Serum metabolites reflecting gut microbiome alpha diversity predict type 2 diabetes

Type 2 diabetes (T2D) is associated with reduced gut microbiome diversity, although the cause is unclear. Metabolites generated by gut microbes also appear to be causative factors in T2D. We therefore searched for serum metabolites predictive of gut microbiome diversity in 1018 females from TwinsUK with concurrent metabolomic profiling and microbiome composition. We generated a Microbial Metabolites Diversity (MMD) score of six circulating metabolites that explained over 18% of the variance in microbiome alpha diversity. Moreover, the MMD score was associated with a significantly lower odds of prevalent (OR[95%CI] = 0.22[0.07;0.70], P = .01) and incident T2D (HR[95%CI] = 0.31[0.11,0.90], P = .03). We replicated our results in 1522 individuals from the ARIC study (prevalent T2D: OR[95%CI] = 0.79[0.64,0.96], P = .02, incident T2D: HR[95%CI] = 0.87[0.79,0.95], P = .003). The MMD score mediated 28%[15%,94%] of the total effect of gut microbiome on T2D after adjusting for confounders. Metabolites predicting higher microbiome diversity included 3-phenylpropionate(hydrocinnamate), indolepropionate, cinnamoylglycine and 5-alpha-pregnan-3beta,20 alpha-diol monosulfate(2) of which indolepropionate and phenylpropionate have already been linked to lower incidence of T2D. Metabolites correlating with lower microbial diversity included glutarate and imidazole propionate, of which the latter has been implicated in insulin resistance. Our results suggest that the effect of gut microbiome diversity on T2D is largely mediated by microbial metabolites, which might be modifiable by diet.

Elevated plasma phenylalanine predicts mortality in critical patients with heart failure

Aims

Previous studies found a relationship between elevated phenylalanine levels and poor cardiovascular outcomes. Potential strategies are available to manipulate phenylalanine metabolism. This study investigated whether increased phenylalanine predicted mortality in critical patients with either acute heart failure (HF) or acute on chronic HF, and its correlation with inflammation and immune cytokines.

Methods and results

This study recruited 152 subjects, including 115 patients with HF admitted for critical conditions and 37 normal controls. We measured left ventricular ejection fraction (LVEF), plasma concentrations of phenylalanine, C‐reactive protein, albumin, pre‐albumin, transferrin, and pro‐inflammatory and immune cytokines. Acute Physiology and Chronic Health Evaluation (APACHE II), Sequential Organ Failure Assessment (SOFA), and maximal vasoactive–inotropic scores (VIS_max) were calculated. Patients were followed up until death or a maximum of 1 year. The primary endpoint was all‐cause death. Of the 115 patients, 37 (32.2%) were admitted owing to acute HF, and 78 (67.8%) were admitted owing to acute on chronic HF; 64 (55.7%) had ST elevation/non‐ST elevation myocardial infarction. An LVEF measured during the hospitalization of <40%, 40–50%, and ≥50% was noted in 51 (44.3%), 15 (13.1%), and 49 (42.6%) patients, respectively. During 1 year follow‐up, 51 (44.3%) patients died. Death was associated with higher APACHE II, SOFA, and VIS_max scores; higher levels of C‐reactive protein and phenylalanine; higher incidence of atrial fibrillation and use of inotropic agents; lower cholesterol, albumin, pre‐albumin, and transferrin levels; and significant changes in pro‐inflammatory and immune cytokines. Phenylalanine levels demonstrated an area under the receiver operating characteristic curve of 0.80 for mortality, with an optimal cut‐off value set at 112 μM. Phenylalanine ≥ 112 μM was associated with a higher mortality rate than was phenylalanine < 112 μM (80.5% vs. 24.3%, P < 0.001) [hazard ratio = 5.07 (2.83–9.05), P < 0.001]. The Kaplan–Meier curves revealed that phenylalanine ≥ 112 μM was associated with a lower accumulative survival rate (log rank = 36.9, P < 0.001). Higher phenylalanine levels were correlated with higher APACHE II and SOFA scores, higher C‐reactive protein levels and incidence of using inotropic agents, and changes in cytokines suggestive of immunosuppression, but lower levels of pre‐albumin and transferrin. Further multivariable analysis showed that phenylalanine ≥ 112 μM predicted death over 1 year independently of age, APACHE II and SOFA scores, atrial fibrillation, C‐reactive protein, cholesterol, pre‐albumin, transferrin, and interleukin‐8 and interleukin‐10.

Conclusions

Elevated phenylalanine levels predicted mortality in critical patients, phenotypically predominantly presenting with HF, independently of traditional prognostic factors and cytokines associated with inflammation and immunity.

Metabolic Regulation of Human Pluripotent Stem Cell-Derived Cardiomyocyte Maturation

PURPOSE OF REVIEW

This review summarizes the important role that metabolism plays in driving maturation of human pluripotent stem cell-derived cardiomyocytes.

RECENT FINDINGS

Human pluripotent stem cell-derived cardiomyocytes provide a model system for human cardiac biology. However, these models have been unable to fully recapitulate the maturity observed in the adult heart. By simulating the glucose to fatty acid transition observed in neonatal mammals, human pluripotent stem cell-derived cardiomyocytes undergo structural and functional maturation also accompanied by transcriptional changes and cell cycle arrest. The role of metabolism in energy production, signaling, and epigenetic modifications illustrates that metabolism and cellular phenotype are intimately linked. Further understanding of key metabolic factors driving cardiac maturation will facilitate the generation of more mature human pluripotent stem cell-derived cardiomyocyte models. This will increase our understanding of cardiac biology and potentially lead to novel therapeutics to enhance heart function.

Circulating metabolite profiles to predict response to cardiac resynchronization therapy

Background

Heart failure is associated with ventricular dyssynchrony and energetic inefficiency, which can be alleviated by cardiac resynchronization therapy (CRT) with approximately one-third of non-response rate. Thus far, there is no specific biomarker to predict the response to CRT in patients with heart failure. In this study, we assessed the role of the blood metabolomic profile in predicting the response to CRT.

Methods

A total of 105 dilated cardiomyopathy patients with severe heart failure who received CRT were included in our two-stage study. Baseline blood samples were collected prior to CRT implantation. The response to CRT was defined according to echocardiographic criteria. Metabolomic profiling of serum samples was carried out using ultrahigh performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry.

Results

Seventeen metabolites showed significant differences in their levels between responders and non-responders, and these metabolites were primarily involved in six pathways, including linoleic acid metabolism, Valine, leucine and isoleucine biosynthesis, phenylalanine metabolism, citrate cycle, tryptophan metabolism, and sphingolipid metabolism. A combination of isoleucine, tryptophan, and linoleic acid was identified as an ideal metabolite panel to distinguish responders from non-responders in the discovery set (n = 51 with an AUC of 0.981), and it was confirmed in the validation set (n = 54 with an AUC of 0.929).

Conclusions

Mass spectrometry based serum metabolomics approach provided larger coverage of metabolome which can help distinguish CRT responders from non-responders. A combination of isoleucine, tryptophan, and linoleic acid may associate with significant prognostic values for CRT.

A review of pharmacological and pharmacokinetic properties of stachydrine

Stachydrine is extracted from the leaves of Leonurus japonicus Houtt (or Motherwort, "Yi Mu Cao" in Traditional Chinese Medicine) and is the major bioactive ingredient. So far, stachydrine has demonstrated various bioactivities for the treatment of fibrosis, cardiovascular diseases, cancers, uterine diseases, brain injuries, and inflammation. The pharmacological and pharmacokinetic properties of stachydrine up to 2019 have been comprehensively searched and summarized. This review provides an updated summary of recent studies on the pharmacological activities of stachydrine. Many studies have demonstrated that stachydrine has strong anti-fibrotic properties (on various types of fibrosis) by inhibiting ECM deposition and decreasing inflammatory and oxidative stress through multiple molecular mechanisms (including TGF-β, ERS-mediated apoptosis, MMPs/TIMPs, NF-κB, and JAK/STAT). The cardioprotective and vasoprotective activities of stachydrine are related to its inhibition of β-MHC, excessive autophagy, SIRT1, eNOS uncoupling and TF, promotion of SERCA, and angiogenesis. In addition to its anticancer action, regulation of the uterus, neuroprotective effects, etc. the pharmacokinetic properties of stachydrine are also discussed.

Pseudouridine and N-formylmethionine associate with left ventricular mass index: Metabolome-wide association analysis of cardiac remodeling

BACKGROUND

Heart failure (HF) is the fastest growing form of cardiovascular disease both nationally and globally, underlining a need to phenotype subclinical HF intermediaries to improve primary prevention.

OBJECTIVES

We aimed to identify novel metabolite associations with left ventricular (LV) remodeling, one upstream HF intermediary, among a community-based cohort of individuals.

METHODS

We examined 1052 Bogalusa Heart Study participants (34.98% African American, 57.41% female, aged 33.6-57.5 years). Measures of LV mass and relative wall thickness (RWT) were obtained using two-dimensional-guided echocardiographic measurements via validated eqs. LV mass was indexed to height^2.7 to calculate left ventricular mass index (LVMI). Untargeted metabolomic analysis of fasting serum samples was conducted. In combined and ethnicity-stratified analyses, multivariable linear and multinomial logistic regression models tested the associations of metabolites with the continuous LVMI and RWT and categorical LV geometry phenotypes, respectively, after adjusting for demographic and traditional cardiovascular disease risk factors.

RESULTS

Pseudouridine (B = 1.38; p = 3.20 × 10^-5) and N-formylmethionine (B = 1.65; 3.30 × 10^-6) were significantly associated with LVMI in the overall sample as well significant in Caucasians, with consistent effect direction and nominal significance (p < .05) in African Americans. Upon exclusion of individuals with self-report myocardial infarction or congestive HF, we similarly observed a 1.33 g/m^2.7 and 1.52 g/m^2.7 higher LVMI for each standard deviation increase in pseudouridine and N-formylmethionine, respectively. No significant associations were observed for metabolites with RWT or categorical LV remodeling outcomes.

CONCLUSIONS

The current analysis identified novel associations of pseudouridine and N-formylmethionine with LVMI, suggesting that mitochondrial-derived metabolites may serve as early biomarkers for LV remodeling and subclinical HF.

Metabolic Profiling Associates with Disease Severity in Nonischemic Dilated Cardiomyopathy

BACKGROUND

Metabolomic profiling may have diagnostic and prognostic value in heart failure. This study investigated whether targeted blood and urine metabolomics reflects disease severity in patients with nonischemic dilated cardiomyopathy (DCM) and compared its incremental value on top of N-terminal prohormone of brain natriuretic peptide (NT-proBNP).

METHODS AND RESULTS

A total of 149 metabolites were measured in plasma and urine samples of 273 patients with DCM and with varying stages of disease (patients with DCM and normal left ventricular reverse remodeling, n = 70; asymptomatic DCM, n = 72; and symptomatic DCM, n = 131). Acylcarnitines, sialic acid and glutamic acid are the most distinctive metabolites associated with disease severity, as repeatedly revealed by unibiomarker linear regression, sparse partial least squares discriminant analysis, random forest, and conditional random forest analyses. However, the absolute difference in the metabolic profile among groups was marginal. A decision-tree model based on the top metabolites did not surpass NT-proBNP in classifying stages. However, a combination of NT-proBNP and the top metabolites improved the decision tree to distinguish patients with DCM and left ventricular reverse remodeling from symptomatic DCM (area under the curve 0.813 ± 0.138 vs 0.739 ± 0.114; P = 0.02).

CONCLUSION

Functional cardiac recovery is reflected in metabolomics. These alterations reveal potential alternative treatment targets in advanced symptomatic DCM. The metabolic profile can complement NT-proBNP in determining disease severity in nonischemic DCM.

Amino Acid-Based Metabolic Profile Provides Functional Assessment and Prognostic Value for Heart Failure Outpatients

Functional capacity is a crucial parameter correlated with outcomes. The currently used New York Heart Association functional classification (NYHA Fc) system has substantial limitations, leading to inaccurate classification. This study investigated whether amino acid-based assessment on metabolic status provides an objective way to assess functional capacity and prognosis in heart failure (HF) outpatients. Plasma concentrations of histidine, ornithine, and phenylalanine (HOP) were measured on 890 HF outpatients to assess metabolic status by calculating the HOP score. Cardiopulmonary exercise testing (CPET) was performed in 387 patients to measure metabolic equivalents (MET) in order to define the functional class based on MET (MET Fc). Patients were followed for composite events (death/HF-related rehospitalization) up to one year. We found only 47% concordance between the MET Fc and NYHA Fc. HOP scores worked better than NYHA Fc for discriminating patients with MET Fc II and III from those with MET Fc I, with the optimal cutoff value set at 8.8. HOP scores ≥ 8.8 were associated with risk factors for composite events in different kinds of HF populations and were a powerful predictor of composite events in univariate analysis. In multivariable analysis, HOP scores ≥ 8.8 remained a powerful event predictor, independent of other risk factors. Kaplan-Meier curves revealed that HOP scores of ≥8.8 stratified patients at higher risk of composite events in a variety of HF populations. In conclusion, amino acid-based assessment of metabolic status correlates with functional capacity in HF outpatients and provides prognostic value for a variety of HF populations.

Phenylalanine- and leucine-defined metabolic types identify high mortality risk in patients with severe infection

OBJECTIVE

To investigate the prognostic value of phenylalanine and leucine in patients with severe infection.

METHODS

Ninety-three patients with infection who had a quick Sequential Organ Failure Assessment (qSOFA) score ≥2 were enrolled. Plasma phenylalanine, leucine, albumin, C-reactive protein, pre-albumin, and transferrin were measured and the SOFA score at enrollment was calculated after hospitalization.

RESULTS

During the 3-month follow-up, 30 (32.3%) patients died. Death was associated with higher SOFA scores, a higher incidence of bacteremia and admission to the intensive care unit, higher C-reactive protein and phenylalanine levels, worse kidney function, and lower pre-albumin and transferrin levels. Patients were categorized into three groups: high-risk type 1 (phenylalanine ≥84μM), high-risk type 2 (phenylalanine <84μM and leucine <93μM), and low-risk (other). Compared to the low-risk type patients, high-risk type 1 and 2 patients had higher mortality rates (hazard ratio 10.1 (95% CI 2.33-43.5) and hazard ratio 5.56 (95% CI 1.22-25.4), respectively). Type 1 patients had higher SOFA scores, a higher incidence of admission to the intensive care unit, and higher C-reactive protein and leucine levels. Type 2 patients had lower albumin and hemoglobin levels. Multivariable analysis showed that both high-risk types were independent predictors of death.

CONCLUSIONS

Phenylalanine- and leucine-defined risk classifications provide metabolic information with prognostic value for patients with severe infection.

Serum Concentrations of Citrate, Tyrosine, 2- and 3- Hydroxybutyrate are Associated with Increased 3-Month Mortality in Acute Heart Failure Patients

Considering the already established relationship between the extent of the metabolic dysfunction and the severity of heart failure (HF), it is conceivable that the metabolomic profile of the serum may have a prognostic capacity for 3-month mortality in acute heart failure (AHF). Out of 152 recruited patients, 130 serum samples were subjected to the metabolomic analyses. The 3-month mortality rate was 24.6% (32 patients). Metabolomic profiling by nuclear magnetic resonance spectroscopy found that the serum levels of 2-hydroxybutyrate (2-HB), 3-hydoxybutyrate (3-HB), lactate, citrate, and tyrosine, were higher in patients who died within 3 months compared to those who were alive 3 months after onset of AHF, which was confirmed by univariable logistic regression analyses (p = 0.009, p = 0.005, p = 0.008, p<0.001, and p<0.001, respectively). These associations still remained significant for all tested metabolites except for lactate after adjusting for established prognostic parameters in HF. In conclusion, serum levels of 2-HB, 3-HB, tyrosine, and citrate measured at admission are associated with an increased 3-month mortality rate in AHF patients and might thus be of prognostic value in AHF.

Metabolomics and Heart Diseases: From Basic to Clinical Approach

BACKGROUND

The field of metabolomics has been steadily increasing in size for the last 15 years. Advances in analytical and statistical methods have allowed metabolomics to flourish in various areas of medicine. Cardiovascular diseases are some of the main research targets in metabolomics, due to their social and medical relevance, and also to the important role metabolic alterations play in their pathogenesis and evolution. Metabolomics has been applied to the full spectrum of cardiovascular diseases: from patient risk stratification to myocardial infarction and heart failure. However - despite the many proof-ofconcept studies describing the applicability of metabolomics in the diagnosis, prognosis and treatment evaluation in cardiovascular diseases - it is not yet used in routine clinical practice. Recently, large phenome centers have been established in clinical environments, and it is expected that they will provide definitive proof of the applicability of metabolomics in clinical practice. But there is also room for small and medium size centers to work on uncommon pathologies or to resolve specific but relevant clinical questions.

OBJECTIVES

In this review, we will introduce metabolomics, cover the metabolomic work done so far in the area of cardiovascular diseases.

CONCLUSION

The cardiovascular field has been at the forefront of metabolomics application and it should lead the transfer to the clinic in the not so distant future.

Metabolomic analysis of serum and myocardium in compensated heart failure after myocardial infarction

AIMS

To determine the metabolic adaptations to compensated heart failure using a reproducible model of myocardial infarction and an unbiased metabolic screen. To address the limitations in sample availability and model variability observed in preclinical and clinical metabolic investigations of heart failure.

MAIN METHODS

Metabolomic analysis was performed on serum and myocardial tissue from rabbits after myocardial infarction (MI) was induced by cryo-injury of the left ventricular free wall. Rabbits followed for 12 weeks after MI exhibited left ventricular dilation and depressed systolic function as determined by echocardiography. Serum and tissue from the viable left ventricular free wall, interventricular septum and right ventricle were analyzed using a gas chromatography time of flight mass spectrometry-based untargeted metabolomics assay for primary metabolites.

KEY FINDINGS

Unique results included: a two- three-fold increase in taurine levels in all three ventricular regions of MI rabbits and similarly, the three regions had increased inosine levels compared to sham controls. Reduced myocardial levels of myo-inositol in the myocardium of MI animals point to altered phospholipid metabolism and membrane receptor function in heart failure. Metabolite profiles also provide evidence for responses to oxidative stress and an impairment in TCA cycle energy production in the failing heart.

SIGNIFICANCE

Our results revealed metabolic changes during compensated cardiac dysfunction and suggest potential targets for altering the progression of heart failure.

Succinate links atrial dysfunction and cardioembolic stroke

OBJECTIVE

To determine whether altered metabolic profiles represent a link between atrial dysfunction and cardioembolic (CE) stroke, and thus whether underlying dysfunctional atrial substrate may contribute to thromboembolism risk in CE stroke.

METHODS

A total of 144 metabolites were measured using liquid chromatography-tandem mass spectrometry in plasma samples collected within 9 hours of stroke onset in 367 acute stroke patients. Stroke subtype was assigned using the Causative Classification of Stroke System, and CE stroke (n = 181) was compared to non-CE stroke (n = 186). Markers of left atrial dysfunction included abnormal atrial function (P-wave terminal force in lead V1, PTFV₁ >4,000 μV·ms), left atrial enlargement on echocardiography, and frank atrial fibrillation on ECG. Stroke recurrence risk was assessed using CHADS₂ and CHA₂DS₂-VASc scores. Associations between metabolites and CE stroke, atrial dysfunction, and stroke recurrence risk were evaluated using logistic regression models.

RESULTS

Three tricarboxylic acid metabolites-succinate (odds ratio [OR] 1.71, 95% confidence interval [CI] 1.36-2.15, p = 1.37 × 10^-6), α-ketoglutarate (OR 1.62, 95% CI 1.29-2.04, p = 1.62 × 10^-5), and malate (OR 1.58, 95% CI 1.26-1.97, p = 2.57 × 10^-5)-were associated with CE stroke. Succinate (OR 1.36, 95% CI 1.31-1.98, p = 1.22 × 10^-6), α-ketoglutarate (OR 2.14, 95% CI 1.60-2.87, p = 2.08 × 10^-8), and malate (OR 2.02, 95% CI 1.53-2.66, p = 1.60 × 10^-7) were among metabolites also associated with subclinical atrial dysfunction. Of these, succinate was also associated with left atrial enlargement (OR 1.54, 95% CI 1.23-1.94, p = 1.06 × 10^-4) and stroke recurrence based on dichotomized CHADS₂ (OR 2.63, 95% CI 1.68-4.13, p = 3.00 × 10^-6) and CHA₂DS₂-VASc (OR 2.43, 95% CI 1.60-3.68, p = 4.25 × 10^-6) scores.

CONCLUSIONS

Metabolite profiling identified changes in succinate associated with CE stroke, atrial dysfunction, and stroke recurrence, revealing a putative underlying link between CE stroke and energy metabolism.

Genetic and non-genetic determinants of clinical phenotypes in cardiomyopathy

Cardiomyopathy, a leading cause of death worldwide, is etiologically and phenotypically heterogeneous and is caused by a combination of genetic and non-genetic factors. Major genomic determinants of dilated cardiomyopathy (DCM) are titin truncating mutations and lamin A/C mutations. Patients with these two genotypes show critically different phenotypes, including penetrance, coexistence with a conduction system abnormality, cardiac prognosis, and treatment response. The transcriptomic and epigenomic characteristics of DCM include activation of the DNA damage response, metabolic reprogramming, and dedifferentiation. The proteomic and metabolomic signatures of the DCM heart include a rigorous dependency for free fatty acids, activation of the stress response, and metabolic reprogramming. Proteomic and metabolomic analyses of blood show a distinct immune response and an unexpected link with pathology-specific microbiota in DCM. The direct integration of multi-omics data will not only elucidate inter-omics associations but also enable omics-based patient stratification, which will lead to a deeper understanding of cardiomyopathy and the development of precision medicine in cardiology.

Amino Acid-Based Metabolic Panel Provides Robust Prognostic Value Additive to B-Natriuretic Peptide and Traditional Risk Factors in Heart Failure

Metabolic disturbances represent functional perturbation in peripheral tissues and predict outcomes in patients with heart failure (HF). This study developed an amino acid-based metabolic panel and sought to see whether this panel could add diagnostic and prognostic value to currently used B-type natriuretic peptide (BNP) measurements. Mass spectrometry and ultra-performance liquid chromatography were performed on 1288 participants, including 129 normal controls and 712 patients at HF stages A to D in the initial cohort and 447 stage C patients in the validation cohort. Patients were followed up for composite events (death/HF-related rehospitalization). Histidine, ornithine, and phenylalanine were 3 metabolites found strongly significant to identify patients at stage C and were adopted to develop the HOP panel. Compared to BNP, HOP had better value in discriminating the patients at different stages, especially in elderly patients and those with atrial fibrillation, high body mass index, or kidney dysfunction. HOP was correlated with the distance of 6 min walking distance better than BNP. For prognosis, HOP predicted composite events in patients at stages C and D, independent of log (BNP), age, sex, left ventricular ejection fraction, New York Heart Association functional class, HF stage, diabetes mellitus, chronic kidney disease, hypertension, hemoglobin, and albumin. Higher BNP (≥750 pg/mL) along with higher HOP (≥14) robustly predicted lower event-free survival compared to all others [hazard ratio = 3.15 (2.23-4.46), p < 0.001]. The prognostic value of HOP was confirmed in the validation cohort. In conclusion, aiming for clinical applications, this study proved that the HOP panel provides diagnostic and prognostic value additive to BNP and traditional risk factors.

Circulating microRNA signature for the diagnosis of childhood dilated cardiomyopathy

Circulating miRNAs are proposed as a biomarker of heart disease. This study evaluated whether circulating miRNAs could be used as a biomarker for childhood dilated cardiomyopathy (CDCM). A total of 28 participants were enrolled in a discovery set, including patients with CDCM (n = 16) and healthy children (n = 12). The cardiac function of patients with CDCM was characterized by echocardiography and serum miRNA profiles of all participants were assessed by miRNA sequencing. After miRNA profiling, we quantitatively confirmed 148 regulated miRNAs in patients with CDCM compared with healthy subjects, and none were downregulated. Validation of candidate miRNAs was assessed by quantitative real-time polymerase chain reaction in other patients with CDCM (n = 30) and healthy controls (n = 16). A unique signature comprising mir-142-5p, mir-143-3p, mir-27b-3p, and mir-126-3p differentiated patients with CDCM from healthy subjects. Importantly, we observed an increase in mir-126-3p or let-7g in parallel with a robust decrease in the ejection fraction in patients with CDCM, which could differentiate heart failure patients from non-heart failure patients with CDCM. Moreover, mir-126-3p and let-7g were significantly negatively associated with the left ventricular ejection fraction. This study shows that a signature of four serum miRNAs may be a potential biomarker for diagnosing CDCM and assessing heart failure.

Metabolic Dysfunction in Heart Failure: Diagnostic, Prognostic, and Pathophysiologic Insights From Metabolomic Profiling

Metabolic impairment is an intrinsic component of heart failure (HF) pathophysiology. Although initially conceived as a myocardial defect, metabolic dysfunction is now recognized as a systemic process with complex interplay between the myocardium and peripheral tissues and organs. Specifically, HF-associated metabolic dysfunction includes alterations in substrate utilization, insulin resistance, defects in energy production, and imbalanced anabolic-catabolic signaling leading to cachexia. Each of these metabolic abnormalities is associated with significant morbidity and mortality in patients with HF; however, their detection and therapeutic management remains challenging. Given the difficulty in obtaining human cardiac tissue for research purposes, peripheral blood metabolomic profiling, a well-established approach for characterizing small-molecule metabolite intermediates from canonical biochemical pathways, may be a useful technology for dissecting biomarkers and mechanisms of metabolic impairment in HF. In this review, metabolic abnormalities in HF will be discussed with particular emphasis on the application of metabolomic profiling to detecting, risk stratifying, and identifying novel targets for metabolic therapy in this heterogeneous population.

Nuclear magnetic resonance-based metabolomics identifies phenylalanine as a novel predictor of incident heart failure hospitalisation: results from PROSPER and FINRISK 1997

Aims

We investigated the association between quantified metabolite, lipid and lipoprotein measures and incident heart failure hospitalisation (HFH) in the elderly, and examined whether circulating metabolic measures improve HFH prediction.

Methods and results

Overall, 80 metabolic measures from the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial were measured by proton nuclear magnetic resonance spectroscopy (n = 5341; 182 HFH events during 2.7‐year follow‐up). We repeated the work in FINRISK 1997 (n = 7330; 133 HFH events during 5‐year follow‐up). In PROSPER, the circulating concentrations of 13 metabolic measures were found to be significantly different in those who were later hospitalised for heart failure after correction for multiple comparisons. These included creatinine, phenylalanine, glycoprotein acetyls, 3‐hydroxybutyrate, and various high‐density lipoprotein measures. In Cox models, two metabolites were associated with risk of HFH after adjustment for clinical risk factors and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP): phenylalanine [hazard ratio (HR) 1.29, 95% confidence interval (CI) 1.10–1.53; P = 0.002] and acetate (HR 0.81, 95% CI 0.68–0.98; P = 0.026). Both were retained in the final model after backward elimination. Compared to a model with established risk factors and NT‐proBNP, this model did not improve the C‐index but did improve the overall continuous net reclassification index (NRI 0.21; 95% CI 0.06–0.35; P = 0.007) due to improvement in classification of non‐cases (NRI 0.14; 95% CI 0.12–0.17; P < 0.001). Phenylalanine was replicated as a predictor of HFH in FINRISK 1997 (HR 1.23, 95% CI 1.03–1.48; P = 0.023).

Conclusion

Our findings identify phenylalanine as a novel predictor of incident HFH, although prediction gains are low. Further mechanistic studies appear warranted.

Circulating acylcarnitine profile in human heart failure: a surrogate of fatty acid metabolic dysregulation in mitochondria and beyond

Heart failure (HF) is associated with metabolic perturbations, particularly of fatty acids (FAs), which remain to be better understood in humans. This study aimed at testing the hypothesis that HF patients with reduced ejection fraction display systemic perturbations in levels of energy-related metabolites, especially those reflecting dysregulation of FA metabolism, namely, acylcarnitines (ACs). Circulating metabolites were assessed using mass spectrometry (MS)-based methods in two cohorts. The main cohort consisted of 72 control subjects and 68 HF patients exhibiting depressed left ventricular ejection fraction (25.9 ± 6.9%) and mostly of ischemic etiology with ≥2 comorbidities. HF patients displayed marginal changes in plasma levels of tricarboxylic acid cycle-related metabolites or indexes of mitochondrial or cytosolic redox status. They had, however, 22-79% higher circulating ACs, irrespective of chain length (P < 0.0001, adjusted for sex, age, renal function, and insulin resistance, determined by shotgun MS/MS), which reflects defective mitochondrial β-oxidation, and were significantly associated with levels of NH₂-terminal pro-B-type natriuretic peptide levels, a disease severity marker. Subsequent extended liquid chromatography-tandem MS analysis of 53 plasma ACs in a subset group from the primary cohort confirmed and further substantiated with a comprehensive lipidomic analysis in a validation cohort revealed in HF patients a more complex circulating AC profile. The latter included dicarboxylic-ACs and dihydroxy-ACs as well as very long chain (VLC) ACs or sphingolipids with VLCFAs (>20 carbons), which are proxies of dysregulated FA metabolism in peroxisomes. Our study identified alterations in circulating ACs in HF patients that are independent of biological traits and associated with disease severity markers. These alterations reflect dysfunctional FA metabolism in mitochondria but also beyond, namely, in peroxisomes, suggesting a novel mechanism contributing to global lipid perturbations in human HF.NEW & NOTEWORTHY Mass spectrometry-based profiling of circulating energy metabolites, including acylcarnitines, in two cohorts of heart failure versus control subjects revealed multiple alterations in fatty acid metabolism in peroxisomes in addition to mitochondria, thereby highlighting a novel mechanism contributing to global lipid perturbations in heart failure.Listen to this article's corresponding podcast at http://ajpheart.podbean.com/e/acylcarnitines-in-human-heart-failure/.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Metabolomics through the lens of precision cardiovascular medicine

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

Metabolomic Profiling Identifies Novel Circulating Biomarkers of Mitochondrial Dysfunction Differentially Elevated in Heart Failure With Preserved Versus Reduced Ejection Fraction: Evidence for Shared Metabolic Impairments in Clinical Heart Failure

BACKGROUND

Metabolic impairment is an important contributor to heart failure (HF) pathogenesis and progression. Dysregulated metabolic pathways remain poorly characterized in patients with HF and preserved ejection fraction (HFpEF). We sought to determine metabolic abnormalities in HFpEF and identify pathways differentially altered in HFpEF versus HF with reduced ejection fraction (HFrEF).

METHODS AND RESULTS

We identified HFpEF cases, HFrEF controls, and no-HF controls from the CATHGEN study of sequential patients undergoing cardiac catheterization. HFpEF cases (N=282) were defined by left ventricular ejection fraction (LVEF) ≥45%, diastolic dysfunction grade ≥1, and history of HF; HFrEF controls (N=279) were defined similarly, except for having LVEF <45%. No-HF controls (N=191) had LVEF ≥45%, normal diastolic function, and no HF diagnosis. Targeted mass spectrometry and enzymatic assays were used to quantify 63 metabolites in fasting plasma. Principal components analysis reduced the 63 metabolites to uncorrelated factors, which were compared across groups using ANCOVA. In basic and fully adjusted models, long-chain acylcarnitine factor levels differed significantly across groups (P<0.0001) and were greater in HFrEF than HFpEF (P=0.0004), both of which were greater than no-HF controls. We confirmed these findings in sensitivity analyses using stricter inclusion criteria, alternative LVEF thresholds, and adjustment for insulin resistance.

CONCLUSIONS

We identified novel circulating metabolites reflecting impaired or dysregulated fatty acid oxidation that are independently associated with HF and differentially elevated in HFpEF and HFrEF. These results elucidate a specific metabolic pathway in HF and suggest a shared metabolic mechanism in HF along the LVEF spectrum.