Discovery and Validation of Potential Serum Biomarkers for Pediatric Patients with Congenital Heart Diseases by Metabolomics

Highly sensitive determination of L-glutamic acid in pig serum with an enzyme-free molecularly imprinted polymer on a carbon-nanotube modified electrode

Through electrochemical polymerization using L-glutamic acid (L-Glu) as a template and 4,6-diaminoresorcinol as a functional monomer, an enzyme-free molecularly imprinted polymer (MIP) based L-Glu sensor with multi-walled carbon nanotubes (MWCNTs) decorated on a glassy carbon electrode (GCE), namely G-MIP/MWCNTs/GCE, was developed in this work. The reaction conditions were optimized as follows: electrochemical polymerization of 23 cycles, pH of 3.0, molar ratio of template/monomer of 1 : 4, volume ratio of elution reagents of acetonitrile/formic acid of 1 : 1, and elution time of 2 min. The prepared materials and molecularly imprinted polymer were characterized by using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) as well as electrochemical methods. The electrochemical properties of different electrodes were investigated via differential pulse voltammetry (DPV), showing that the electrode of G-MIP/MWCNTs/GCE exhibited excellent catalytic oxidation activity towards L-Glu. A good linear relationship between peak-currents and L-Glu concentrations in a range from 1.00 × 10-8 to 1.00 × 10-5 mol L-1 was observed, with a detection limit of 5.13 × 10-9 mol L-1 (S/N = 3). The imprinted sensor possesses excellent selectivity, high sensitivity, and good stability, which have been successfully applied for the detection of L-Glu in pig serum samples with a recovery rate of 97.4-105.5%, being comparable to commercial high-performance liquid chromatography, demonstrating a simple, rapid, and accurate way for the determination of L-Glu in the fields of animal nutrition and biomedical engineering.

Plasma metabolic profiling of patients with tetralogy of fallot

BACKGROUND

Tetralogy of Fallot (TOF) is a common congenital heart disease with high mortality. However, the medical imageology and liquidbiopsy techniques present certain limitations. Thus, this study investigated the plasma metabolic profiles to distinguish key metabolites for early diagnosis of TOF.

METHODS

In total, 69 patients with TOF and 43 normal controls were enrolled for targeted metabolomics based on liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Absolute quantification of metabolites was performed using our standard database. The differentially expressed metabolites (DEMs) were screened by fold change (FC), VIP value and pearson correlation coefficient of OPLS-DA model. Receiver operating characteristic curve (ROC) was used to evaluate predictive ability of DEMs.

RESULTS

Different metabolic profiles were presented between TOF and Normal.The pathway analysis showed that significantly changed metabolites were enriched in nicotinamide and purine metabolism. Many intermediatesproductof purine and amido acid were higher in TOF than in Normal group, while energy substrates and electron carriers were lower in TOF than in Normal group. ROC analysis revealed a high diagnostic value of plasma FAD for differentiating TOF from Normal (AUC = 1).

CONCLUSION

Our study quantitatively characterized plasma metabolites in patients with TOF and may help to develop reliable biomarkers that contribute to the early TOF screening.

The value of lipid metabolites 9,10-DOA and 11,12-EET in prenatal diagnosis of fetal heart defects

AIMS

To explore the maternal metabolic changes of fetal congenital heart disease (FCHD), and screen metabolic markers to establish a practical diagnostic model.

METHODS

Maternal peripheral serum from 17 FCHD and 63 non-FCHD pregnant were analyzed by Ultra High-performance Liquid Chromatography-Mass/Mass (UPLC-MS/MS).

RESULTS

In the FCHD and the non-FCHD, 132 metabolites were identified, including 35 differential metabolites enriched in the purine, caffeine, primary bile acid, and arachidonic acid metabolism pathway. Finally, the screened (+/-)9,10-dihydroxy-12Z-octadecenoic acid (AUC = 0.888) and 11,12-epoxy-(5Z,8Z,11Z)-icosatrienoic acid (AUC = 0.995) were incorporated into the logistic regression model. The AUC value of the two-metabolite model was 1.0, superior to proline (AUC = 0.867), uric acid (AUC = 0.789), glutamine (AUC = 0.705), and taurine (AUC = 0.923) previously reported. The clinical decision curve analysis (DCA) showed the highest clinical net benefit of the model, and internal validation by bootstrap shows the robustness of the model (Brier Score = 0.005).

CONCLUSION

For the prenatal diagnosis of CHD, our findings are of great clinical significance. As an additional screening procedure, the identification model might be used to detect.

Identification of potential serum biomarkers for congenital heart disease children with pulmonary arterial hypertension by metabonomics

BACKGROUND

Pulmonary arterial hypertension is a common complication in patients with congenital heart disease. In the absence of early diagnosis and treatment, pediatric patients with PAH has a poor survival rate. Here, we explore serum biomarkers for distinguishing children with pulmonary arterial hypertension associated with congenital heart disease (PAH-CHD) from CHD.

METHODS

Samples were analyzed by nuclear magnetic resonance spectroscopy-based metabolomics and 22 metabolites were further quantified by ultra-high-performance liquid chromatography-tandem mass spectroscopy.

RESULTS

Serum levels of betaine, choline, S-Adenosyl methionine (SAM), acetylcholine, xanthosine, guanosine, inosine and guanine were significantly altered between CHD and PAH-CHD. Logistic regression analysis showed that combination of serum SAM, guanine and N-terminal pro-brain natriuretic peptide (NT-proBNP), yielded the predictive accuracy of 157 cases was 92.70% with area under the curve of the receiver operating characteristic curve value of 0.9455.

CONCLUSION

We demonstrated that a panel of serum SAM, guanine and NT-proBNP is potential serum biomarkers for screening PAH-CHD from CHD.

Early postnatal metabolic profile in neonates with critical CHDs

BACKGROUND

Cyanotic CHD is a life-threatening condition that presents with low oxygen saturation in the newborn period. Hypoxemia might cause alterations in the metabolic pathways. In the present study, we aimed to evaluate the early postnatal amino acid and carnitine/acylcarnitine profiles of newborn infants with cyanotic CHD.

METHODS

A single centre case-control study was conducted. Twenty-seven patients with cyanotic CHD and 54 healthy newborn controls were enrolled. As part of the neonatal screening programme, results of amino acid and carnitine/acylcarnitine were recorded and compared between groups.

RESULTS

Twenty-seven neonates with cyanotic CHD and 54 healthy newborns as controls were enrolled in the study. Cyanotic CHD neonates had higher levels of alanine, phenylalanine, leucine/isoleucine, citrulline, ornithine, C5, C5-OH; but lower levels of C3, C10, C12, C14, C14:1, C16, C16.1, C18, C5-DC, C6-DC, C16-OH, C16:1-OH when compared with the healthy controls.

CONCLUSION

This study showed that there are differences between patients with cyanotic CHD and healthy controls in terms of postnatal amino acid and carnitine/acylcarnitine profiles.

Metabolomics: A New Tool in Our Understanding of Congenital Heart Disease

Although the genetic origins underpinning congenital heart disease (CHD) have been extensively studied, genes, by themselves, do not entirely predict phenotypes, which result from the complex interplay between genes and the environment. Consequently, genes merely suggest the potential occurrence of a specific phenotype, but they cannot predict what will happen in reality. This task can be revealed by metabolomics, the most promising of the "omics sciences". Though metabolomics applied to CHD is still in its infant phase, it has already been applied to CHD prenatal diagnosis, as well as to predict outcomes after cardiac surgery. Particular metabolomic fingerprints have been identified for some of the specific CHD subtypes. The hallmarks of CHD-related pulmonary arterial hypertension have also been discovered. This review, which is presented in a narrative format, due to the heterogeneity of the selected papers, aims to provide the readers with a synopsis of the literature on metabolomics in the CHD setting.

Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis

INTRODUCTION

Congenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a biomarker during pregnancy.

METHODS

Sixty-five amniotic fluid samples (28 cases and 37 controls) during the second and third trimesters were utilized in this study. The metabolomics of CHD and normal fetuses were analyzed by untargeted metabolomics technology. Differential comparison and randomForest were used to screen metabolic biomarkers.

RESULTS

A total of 2472 metabolites were detected, and they were distributed differentially between the cases and controls. Setting the selection criteria of fold change (FC) ≥ 2, P value < 0.01 and variable importance for the projection (VIP) ≥ 1.5, we screened 118 differential metabolites. Within the prediction model by random forest, PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin and 2,6-di-tert-butylbenzoquinone showed good prediction effects. Differential metabolites were mainly concentrated in aldosterone synthesis and secretion, drug metabolism, nicotinate and nicotinamide metabolism pathways, which may be related to the occurrence and development of CHD.

CONCLUSION

This study provides a new database of CHD metabolic biomarkers and mechanistic research. These results need to be further verified in larger samples.

Comprehensive metabolomic characterization of atrial fibrillation

Background

Using human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.

Objectives

By investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.

Methods

A cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.

Results

The metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8–90.2%.

Conclusions

Serum metabolomics is a powerful way to identify metabolic disturbances. Differences in small–molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis.

Identification of metabolomic profile related to adult Fontan pathophysiology

Background

Metabolic disorders are important pathophysiologies that can cause multiple organ dysfunction and worsen prognosis in Fontan patients. This study aimed to comprehensively evaluate the metabolomic profile of adult Fontan patients and characterize its pathophysiology in relation to 2 control groups.

Methods and Results

We performed metabolomic analysis of 31 plasma samples using capillary electrophoresis time-of-flight mass spectrometry. This observational cross-sectional study compared plasma metabolites of 14 heterogeneous adult Fontan patients with those of control groups, including 9 patients with congenital heart disease after biventricular repair and 8 normal healthy controls. Fontan patients exhibited significant differences in intermediate metabolite concentrations related to glycolysis, the tricarboxylic acid (TCA) cycle, and the urea cycle. The plasma concentrations of lactic acid, 2-oxoglutarate, isocitric acid, malic acid, cis-aconitic acid, arginine, citrulline, and the ratio of ornithine/citrulline showed significantly differences among the groups. Multiple logistic regression analysis with a stepwise selection-elimination method identified 2-oxoglutaric acid (odds ratio [OR] 1.98, 95% confidence interval [CI] 1.05–3.76) and cis-aconitic acid (OR 2.69, 95% CI 1.04–6.99) as independently associated with Fontan patients. After adjustment for the covariates of age and gender, 2-oxoglutaric acid (OR 1.97, 95% CI 0.98–3.93) and cis-aconitic acid (OR 3.88, 95% CI 0.99–15.2) showed remarkable relationships with Fontan patients.

Conclusions

The present findings suggest that abnormalities in the TCA cycle and amino acid metabolism are distinguishing features in the pathophysiology of Fontan patients. Future metabolomic studies will assist in developing biomarkers for the early prediction of “silent” Fontan pathophysiologies.

Urine metabolomic biomarkers for prediction of isolated fetal congenital heart defect

OBJECTIVE

To identify maternal second and third trimester urine metabolomic biomarkers for the detection of fetal congenital heart defects (CHDs).

STUDY DESIGN

This was a prospective study. Metabolomic analysis of randomly collected maternal urine was performed, comparing pregnancies with isolated, non-syndromic CHDs versus unaffected controls. Mass spectrometry (liquid chromatography and direct injection and tandem mass spectrometry, LC-MS-MS) as well as nuclear magnetic resonance spectrometry, ¹H NMR, were used to perform the analyses between 14 0/7 and 37 0/7 weeks gestation. A total of 36 CHD cases and 41 controls were compared. Predictive algorithms using urine markers alone or combined with, clinical and ultrasound (US) (four-chamber view) predictors were developed and compared.

RESULTS

A total of 222 metabolites were identified, of which 16 were overlapping between the two platforms. Twenty-three metabolite concentrations were found in significantly altered in CHD gestations on univariate analysis. The concentration of methionine was most significantly altered. A predictive algorithm combining metabolites (histamine, choline, glucose, formate, methionine, and carnitine) plus US four-chamber view achieved an AUC = 0.894; 95% CI, 0814-0.973 with a sensitivity of 83.8% and specificity of 87.8%. Enrichment pathway analysis identified several lipid related pathways that are dysregulated in CHD, including phospholipid biosynthesis, phosphatidylcholine biosynthesis, phosphatidylethanolamine biosynthesis, and fatty acid metabolism. This could be consistent with the increased risk of CHD in diabetic pregnancies.

CONCLUSIONS

We report a novel, noninvasive approach, based on the analysis of maternal urine for isolated CHD detection. Further, the dysregulation of lipid- and folate metabolism appears to support prior data on the mechanism of CHD.

Identification of potential serum biomarkers for simultaneously classifying lung adenocarcinoma, squamous cell carcinoma and small cell carcinoma

BACKGROUND

Histological subtypes of lung cancer are crucial for making treatment decisions. However, multi-subtype classifications including adenocarcinoma (AC), squamous cell carcinoma (SqCC) and small cell carcinoma (SCLC) were rare in the previous studies. This study aimed at identifying and screening potential serum biomarkers for the simultaneous classification of AC, SqCC and SCLC.

PATIENTS AND METHODS

A total of 143 serum samples of AC, SqCC and SCLC were analyzed by 1HNMR and UPLC-MS/MS. The stepwise discriminant analysis (DA) and multilayer perceptron (MLP) were employed to screen the most efficient combinations of markers for classification.

RESULTS

The results of non-targeted metabolomics analysis showed that the changes of metabolites of choline, lipid or amino acid might contribute to the classification of lung cancer subtypes. 17 metabolites in those pathways were further quantified by UPLC-MS/MS. DA screened out that serum xanthine, S-adenosyl methionine (SAM), carcinoembryonic antigen (CEA), neuron-specific enolase (NSE) and squamous cell carcinoma antigen (SCC) contributed significantly to the classification of AC, SqCC and SCLC. The average accuracy of 92.3% and the area under the receiver operating characteristic curve of 0.97 would be achieved by MLP model when a combination of those five variables as input parameters.

CONCLUSION

Our findings suggested that metabolomics was helpful in screening potential serum markers for lung cancer classification. The MLP model established can be used for the simultaneous diagnosis of AC, SqCC and SCLC with high accuracy, which is worthy of further study.

Metabolomics analysis reveals the protective effect of quercetin-3-O-galactoside (Hyperoside) on liver injury in mice induced by acetaminophen

We investigated the protective effect of Hyperoside (HPS) on liver injury induced by acetaminophen (APAP) in C57 mice. HPS was administered orally for 7 days and APAP was administered orally on the 7th day. Serum and liver samples were then collected for biochemical analyses, histopathology assessments, and metabolomics studies. Metabolites were assessed using a UHPLC-MS system. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to process the data. Pathway analyses were performed using Metaboanalyst 4.0. Western blot and qRT-PCR were used to determine the protein and mRNA levels, respectively. HPS interacted with active sites in CYP2E1 and caused protein degradation. In conclusion, our results suggested that HPS prevented the oxidative stress-induced liver injury caused by APAP. PRACTICAL APPLICATIONS: Hyperoside was shown to have potential protective and therapeutic effects against liver diseases. Male C57 mice were used to perform pharmacodynamic, pharmacology, and metabolomics evaluations. At a dose of 60 mg/kg, HPS prevented oxidative stress-induced liver injury caused by APAP by regulating the glutathione-related metabolites and enzymes through the inhibition of CYP2E1.

5,7,3',4'-flavan-on-ol (taxifolin) protects against acetaminophen-induced liver injury by regulating the glutathione pathway

Taxifolin (TAX) reportedly exerts protective and therapeutic effects in liver. Herein, the effects of TAX against acetaminophen (APAP)-induced hepatotoxicity were investigated. Pharmacodynamics, pharmacology and metabolomics analyses of TAX were assessed on C57 mice and L-02 cells. TAX was administered for 7 days, and APAP was given on the last day to establish an acute liver injury model. ALT and AST levels were determined, and liver ROS, MDA, GST, GSH and GPX1 were analysed. The expression and protein abundance of GPX1, GPS-Pi, GCLC and GCLM were assessed by PCR and western blotting, and metabolic changes in cells and serum were investigated by UPLC-Q-Orbitrap-MS. Serum ALT and AST, and liver ROS, MDA, GST, GSH and GPX1 levels confirmed the protective effects of TAX. Besides, we found Only treating with TAX decreased the expression of CYP2E1 in mice liver tissue. TAX reversed the APAP-induced decrease in cell viability in L-02 cells, and reduced cellular ROS levels. Furthermore, TAX reversed the APAP-induced decrease in antioxidant enzymes at both mRNA and protein levels. Metabolomics analysis identified metabolites mainly related to glutathione metabolism (36 in vivo and 23 in vitro). The concentration of glutathione, oxidized glutathione, carnitine, succinic acid, pyroglutamic acid, citrulline, taurine, palmitoleic acid, phytoshingosine-1-P and sphingosine-1-P were close to normal levels after treating with TAX. These results indicate that TAX prevents APAP-induced liver injury by inhibiting APAP metabolic activation mediated by CYP450 enzymes, modulating glutathione metabolism, and expression of related antioxidative signals. These properties could be harnessed to prevent or treat hepatotoxicity.

Hypoplastic left heart syndrome: From bedside to bench and back

Hypoplastic Left Heart Syndrome (HLHS) is a complex Congenital Heart Disease (CHD) that was almost universally fatal until the advent of the Norwood operation in 1981. Children with HLHS who largely succumbed to the disease within the first year of life, are now surviving to adulthood. However, this survival is associated with multiple comorbidities and HLHS infants have a higher mortality rate as compared to other non-HLHS single ventricle patients. In this review we (a) discuss current clinical challenges associated in the care of HLHS patients, (b) explore the use of systems biology in understanding the molecular framework of this disease, (c) evaluate induced pluripotent stem cells as a translational model to understand molecular mechanisms and manipulate them to improve outcomes, and (d) investigate cell therapy, gene therapy, and tissue engineering as a potential tool to regenerate hypoplastic cardiac structures and improve outcomes.

Metabolomic profiling suggests systemic signatures of premature aging induced by Hutchinson-Gilford progeria syndrome

INTRODUCTION

Hutchinson-Gilford Progeria Syndrome (HGPS) is an extremely rare genetic disorder. HGPS children present a high incidence of cardiovascular complications along with altered metabolic processes and an accelerated aging process. No metabolic biomarker is known and the mechanisms underlying premature aging are not fully understood.

OBJECTIVES

The present work aims to evaluate the metabolic alterations in HGPS using high resolution mass spectrometry.

METHODS

The present study analyzed plasma from six HGPS patients of both sexes (7.7 ± 1.4 years old; mean ± SD) and eight controls (8.6 ± 2.3 years old) by LC-MS/MS in high-resolution non-targeted metabolomics (Q-Exactive Plus). Targeted metabolomics was used to validate some of the metabolites identified by the non-targeted method in a triple quadrupole (TSQ-Quantiva).

RESULTS

We found several endogenous metabolites with statistical differences between control and HGPS children. Multivariate statistical analysis showed a clear separation between groups. Potential novel metabolic biomarkers were identified using the multivariate area under ROC curve (AUROC) based analysis, showing an AUC value higher than 0.80 using only two metabolites, and tending to 1.00 when increasing the number of metabolites in the AUROC model. Taken together, changed metabolic pathways involve sphingolipids, amino acids, and oxidation of fatty acids, among others.

CONCLUSION

Our data show significant alterations in cellular energy use and availability, in signal transduction, and lipid metabolites, adding new insights on metabolic alterations associated with premature aging and suggesting novel putative biomarkers.

Protective effect of 7,3',4'-flavon-3-ol (fisetin) on acetaminophen-induced hepatotoxicity in vitro and in vivo

BACKGROUND

Acetaminophen (APAP) overdose is a leading cause of drug-induced acute liver failure in clinic. Fisetin (FST) is a phenolic compound that has been isolated from many natural products.

PURPOSE

Our aim is to study the protection effect and mechanisms of FST on APAP-induced hepatotoxicity in endogenous metabolism and metabolomics in vitro and in vivo.

METHODS

FST was i.g. administered to mice at 10, 20 and 40 mg/kg for 7 days and a single dose of APAP (400 mg/kg) was given on the last day. Serum and tissue were collected for biochemical analysis. L-02 cells were used to assess cell viability. LC-MS was used to study the metabolic fingerprinting in vivo and vitro. PCA and OPLS-DA were used to search the potential biomarkers (VIP > 1, p < 0.05). The pathway analysis was conducted on Metaboanalyst 4.0. Then liver oxidative stress indices and glutathione markers were examined using PCR and kits.

RESULTS

ALT, AST, liver histological observation and cell viability results showed that FST could reverse APAP induced toxicology in mice and L-02 cells. In metabolomics study, 26 metabolites in vitro and 60 metabolites in vivo were identified by searching in the library and most of them decreased to normal level in FST treatment. It is observed in pathway analysis that the most significant pathway was glutathione metabolism. Furthermore, the results of mRNA and immunofluorescence showed that FST suppressed ROS formation in liver tissue and L-02 cells, as well as restored the expression of GPX1, GST and other antioxidative enzymes genes.

CONCLUSION

Our results indicate that FST prevented APAP-induced hepatotoxicity by regulating glutathione metabolism and the expression of related antioxidative signals.

The metabolome identity: basis for discovery of biomarkers in neurodegeneration

Neurodegenerative disorders are often associated with cellular dysfunction caused by underlying protein-misfolding signalling. Numerous neuropathologies are diagnosed at late stage symptomatic changes which occur in response to these molecular malfunctions and treatment is often too late or restricted only to the slowing of further cell death. Important new strategies to identify early biomarkers with predictive value to intervene with disease progression at stages where cell dysfunction has not progressed irreversibly is of paramount importance. Thus, the identification of these markers presents an essential opportunity to identify and target disease pathways. This review highlights some important metabolic alterations detected in neurodegeneration caused by misfolded prion protein and discusses common toxicity pathways identified across different neurodegenerative diseases. Thus, having established some commonalities between various degenerative conditions, detectable metabolic changes may be of extreme value as an early diagnostic biomarker in disease.