Urinary metabolomics reveals kynurenine pathway perturbation in newborns with transposition of great arteries after surgical repair

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detection of cyanotic CHD (CCHD) can have disastrous consequences. We therefore sought to use a Precision Fetal Cardiology based approach combining metabolomic profiling of maternal saliva and machine learning, a major branch of artificial intelligence (AI), for the prenatal detection of isolated, non-syndromic cyanotic CHD. Metabolomic analyses using Ultra-High Performance Liquid Chromatography/Mass Spectrometry identified 468 metabolites in the saliva. Six different AI platforms were utilized for the detection of CCHD and CHD overall. AI achieved excellent accuracy for the CCHD detection: Area Under the ROC curve: AUC (95% CI) = 0.819 (0.635-1.00) with a sensitivity and specificity of 92.5% and 87.0%, and for CHD overall: AUC (95% CI) = 0.828 (0.635-1.00) with a sensitivity of 90.5% and specificity of 88.0%. Similarly high accuracies were achieved for the detection of CHD overall: AUC (95% CI) = 0.8488 (0.635-1.00) with a sensitivity of 92.5% and specificity of 91.0%. Pathway analysis showed significant alterations in Arachidonic Acid, Alpha-linoleic acid, and Tryptophan metabolism indicating significant lipid dysfunction in cyanotic CHD. In summary, we report for the first time, the accurate detection of non-syndromic cyanotic CHD using maternal salivary metabolomics. Further, analysis revealed significant alteration of lipid metabolism.

Comprehensive Evaluation System for Post-Metabolic Activity of Potential Thyroid-Disrupting Chemicals

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.

Annotation and Identification of Phytochemicals from Eleusine indica Using High-Performance Liquid Chromatography Tandem Mass Spectrometry: Databases-Driven Approach

Eleusine indica (L.) Gaertn is a perennial herb belonging to the Poaceae family. As the only species of Eleusine found abundantly in Malaysia, it is locally known as “rumput sambau” and has been traditionally used to treat various ailments including pain relief from vaginal bleeding, hastening the placenta delivery after childbirth, asthma, hemorrhoids, urinary infection, fever, and as a tonic for flu-related symptoms. A diverse array of biological activities have been reported for the plant, such as antimicrobial, cytotoxic, anticonvulsant, anti-inflammatory, analgesic, antipyretic, and hepatoprotective action. Despite many reports on its traditional uses and biological activities, limited chemical databases are available for the plant. Thus, the aims of this study were to annotate and identify the phytochemical constituents in the methanolic extract of E. indica through tandem LCMS-based analysis techniques using MZmine, GNPS, Compound Discoverer, and SIRIUS platforms. This technique managed to identify a total of 65 phytochemicals in the extract, comprising primary and secondary metabolites, and was verified by the isolation of one of the identified phytochemicals. The structural elucidation mainly using 1D and 2D NMR as well as comparison with values in the literature confirms the isolated phytochemical to be a 3-OH anomer of loliolide, a benzofuran-type of compound, which consequently increases the level of confidence in the applied technique. The research describes a useful method for the fast and simultaneous identification of phytochemicals in E. indica, contributing to the study of the chemical properties of the genus and family.

Efficacy of Triphala extracts on the changes of obese fecal microbiome and metabolome in the human gut model

Triphala is a mixture of tree fruits obtained from Terminalia chebula, Terminalia bellerica, and Phyllanthus emblica. It is one of the Ayurveda medicinal recipes used to treat health diseases such as obesity. The chemical composition analysis of Triphala extracts obtained from an equal portion of three fruits was performed. The contents of total phenolic compounds (62.87 ± 0.21 mg gallic acid equivalent/mL), total flavonoids (0.24 ± 0.01 mg catechin equivalent/mL), hydrolyzable tannins (177.27 ± 10.09 mg gallotannin equivalent/mL), and condensed tannins (0.62 ± 0.11 mg catechin equivalent/mL) were observed in Triphala extracts. The 1 mg/mL of Triphala extracts was applied to batch culture fermentation which contained the feces from voluntarily obese female adults (body mass index of 35.0-40.0 kg/m²) for 24 h. The extraction of DNA and metabolites was each conducted on the samples obtained from batch culture fermentation within and without Triphala extracts treatment. The 16S rRNA gene sequencing and untargeted metabolomic analysis were carried out. There was no statistically significant difference between Triphala extracts and control treatments on the changes in microbial profiles (p-value <0.05). While the metabolomic analysis showed statistically significant differences of 305 up-regulated and 23 down-regulated metabolites in the treatment of Triphala extracts when compared with the control (p-value <0.05 and fold-change ≥2) belonging to 60 pathways. The pathway analysis revealed that Triphala extracts play an important role in the activation of phenylalanine, tyrosine and tryptophan biosynthesis. In this study, phenylalanine and tyrosine were identified metabolites which involve in the regulation of energy metabolism. The treatment of Triphala extracts possesses the induction of phenylalanine, tyrosine and tryptophan biosynthesis in fecal batch culture fermentation of obese adults and therefore it can be suggested as a probable herbal medicinal recipe for obesity treatment.

Serum metabolites associated with wholegrain consumption using nontargeted metabolic profiling: a discovery and reproducibility study

PURPOSE

To identify fasting serum metabolites associated with WG intake in a free-living population adjusted for potential confounders.

METHODS

We selected fasting serum samples at baseline from a subset (n = 364) of the prospective population-based Kuopio Ischaemic Heart Disease Risk Factor Study (KIHD) cohort. The samples were analyzed using nontargeted metabolomics with liquid chromatography coupled with mass spectrometry (LC-MS). Association with WG intake was investigated using both random forest followed by linear regression adjusted for age, BMI, smoking, physical activity, energy and alcohol consumption, and partial Spearman correlation adjusted for the same covariates. Features selected by any of these models were shortlisted for annotation. We then checked if we could replicate the findings in an independent subset from the same cohort (n = 200).

RESULTS

Direct associations were observed between WG intake and pipecolic acid betaine, tetradecanedioic acid, four glucuronidated alkylresorcinols (ARs), and an unknown metabolite both in discovery and replication cohorts. The associations remained significant (FDR<0.05) even after adjustment for the confounders in both cohorts. Sinapyl alcohol was positively correlated with WG intake in both cohorts after adjustment for the confounders but not in linear models in the replication cohort. Some microbial metabolites, such as indolepropionic acid, were positively correlated with WG intake in the discovery cohort, but the correlations were not replicated in the replication cohort.

CONCLUSIONS

The identified associations between WG intake and the seven metabolites after adjusting for confounders in both discovery and replication cohorts suggest the potential of these metabolites as robust biomarkers of WG consumption.

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.

Urinary metabolomics to develop predictors for pediatric acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is characterized by an abrupt decline in glomerular filtration rate (GFR). We sought to identify separate early urinary metabolomic signatures at AKI onset (with-AKI) and prior to onset of functional impairment (pre-AKI).

METHODS

Pre-AKI (n=15), AKI (n=22), and respective controls (n=30) from two prospective PICU cohort studies provided urine samples which were analyzed by GC-MS and DI-MS mass spectrometry (193 metabolites). The cohort (n=58) was 8.7±6.4 years old and 66% male. AKI patients had longer PICU stays, higher PRISM scores, vasopressors requirement, and respiratory diagnosis and less commonly had trauma or post-operative diagnosis. Urine was collected within 2-3 days after admission and daily until day 5 or 14.

RESULTS

The metabolite classifiers for pre-AKI samples (1.5±1.1 days prior to AKI onset) had a cross-validated area under receiver operator curve (AUC)=0.93 (95%CI 0.85-1.0); with-AKI samples had an AUC=0.94 (95%CI 0.87-1.0). A parsimonious pre-AKI classifier with 13 metabolites was similarly robust (AUC=0.96, 95%CI 0.89-1.0). Both classifiers were similar and showed modest correlation of high-ranking metabolites (tau=0.47, p<0.001).

CONCLUSIONS

This exploratory study demonstrates the potential of a urine metabolite classifier to detect AKI-risk in pediatric populations earlier than the current standard of diagnosis with the need for external validation. A higher resolution version of the Graphical abstract is available as Supplementary information with inner reference to ESM for GA.

Measuring the Systemic Inflammatory Response to On- and Off-Pump Coronary Artery Bypass Graft (CABG) Surgeries Using the Tryptophan/Kynurenine Pathway

Background: Cardiac surgeries induce many inflammatory responses with remarkable clinical implications. Tryptophan (Trp) is a precursor for serotonin, melatonin and kynurenine (Kyn). Plasma kynurenic acid (Kyna) and Kyn concentrations are thought to be related to the severity of inflammation. Plasma Trp/Kyn ratio is used to measure inflammatory cytokine activity.Methods: We performed the current longitudinal study in a tertiary care center and included 62 patients divided into two groups; group A (on-pump CABG patients) and group B (off-pump CABG patients). Plasma Trp and Kyn were measured using the high-performance liquid chromatography (HPLC) technique. Serum interlukin-6 (IL-6) and white blood cells (WBCs) were measured using ELISA and routine blood count, respectively.Results: The present study revealed that the intraoperative levels of plasma Kyn, IL-6 and WBCs were significantly increased while the plasma Trp/Kyn ratio was significantly decreased in both the groups; however, the changes were more significant in the on-pump CABG group. Moreover, the levels in both the groups returned to preoperative levels 72 h postoperative. Our study has shown that WBCs is positively correlated with IL-6, but has negative correlation with Trp/Kyn ratio.Conclusions: Kyn and Trp/Kyn ratio might be utilized as markers of the severity of inflammation in major surgery. In addition, off-pump CABG might be more preferable than on-pump CABG regarding stress and release of inflammatory markers.

Study on Absorption, Distribution, Metabolism, and Excretion Properties of Novel Insecticidal GABA Receptor Antagonist, Pyraquinil, in Diamondback Moth Combining MALDI Mass Spectrometry Imaging and High-Resolution Mass Spectrometry

A thorough understanding of absorption, distribution, metabolism, and excretion (ADME) of insecticide candidates is essential in insecticide development and structural optimization. Here, ADME of pyraquinil, a novel insecticidal GABA receptor antagonist, in Plutella xylostella larvae during the accumulation phase and depuration phase was investigated separately using a combination of UHPLC-Q-Orbitrap, HPLC-MS/MS, and MALDI-MSI. Five new metabolites of pyraquinil were identified, and a metabolic pathway was proposed. The oxidative metabolite (pyraquinil-sulfone) was identified as the main metabolite and confirmed by its standard. Quantitative results showed that pyraquinil was taken up by the larvae rapidly and then undergone a cytochrome P450s-mediated oxidative transformation into pyraquinil-sulfone. Both fecal excretion and oxidative metabolism were demonstrated to be predominant ways to eliminate pyraquinil in P. xylostella larvae during accumulation, while oxidative metabolism followed by fecal excretion was probably the major pathway during depuration. MALDI-MSI revealed that pyraquinil was homogeneously distributed in the larvae, while pyraquinil-sulfone presented a continuous enrichment in the midgut during accumulation. Conversely, pyraquinil-sulfone located in hemolymph can be preferentially eliminated during depuration, suggesting its tissue tropism. It improves the understanding of the fate of pyraquinil in P. xylostella and provides useful information for insecticidal mechanism elucidation and structural optimization of pyraquinil.

Metabolomic profiling demonstrates evidence for kidney and urine metabolic dysregulation in a piglet model of cardiac surgery-induced acute kidney injury

Acute kidney injury (AKI) is a common cause of morbidity after congenital heart disease surgery. Progress on diagnosis and therapy remains limited, however, in part due to poor mechanistic understanding and a lack of relevant translational models. Metabolomic approaches could help identify novel mechanisms of injury and potential therapeutic targets. In the present study, we used a piglet model of cardiopulmonary bypass with deep hypothermic circulatory arrest (CPB/DHCA) and targeted metabolic profiling of kidney tissue, urine, and serum to evaluate metabolic changes specific to animals with histological acute kidney injury. CPB/DHCA animals with acute kidney injury were compared with those without acute kidney injury and mechanically ventilated controls. Acute kidney injury occurred in 10 of 20 CPB/DHCA animals 4 h after CPB/DHCA and 0 of 7 control animals. Injured kidneys showed a distinct tissue metabolic profile compared with uninjured kidneys (R² = 0.93, Q² = 0.53), with evidence of dysregulated tryptophan and purine metabolism. Nine urine metabolites differed significantly in animals with acute kidney injury with a pattern suggestive of increased aerobic glycolysis. Dysregulated metabolites in kidney tissue and urine did not overlap. CPB/DHCA strongly affected the serum metabolic profile, with only one metabolite that differed significantly with acute kidney injury (pyroglutamic acid, a marker of oxidative stress). In conclusion, based on these findings, kidney tryptophan and purine metabolism are candidates for further mechanistic and therapeutic investigation. Urine biomarkers of aerobic glycolysis could help diagnose early acute kidney injury after CPB/DHCA and warrant further evaluation. The serum metabolites measured at this early time point did not strongly differentiate based on acute kidney injury.

NEW & NOTEWORTHY This project explored the metabolic underpinnings of postoperative acute kidney injury (AKI) following pediatric cardiac surgery in a translationally relevant large animal model of cardiopulmonary bypass with deep hypothermic circulatory arrest. Here, we present novel evidence for dysregulated tryptophan catabolism and purine catabolism in kidney tissue and increased urinary glycolysis intermediates in animals who developed histological AKI. These pathways represent potential diagnostic and therapeutic targets for postoperative AKI in this high-risk population.

Non-targeted high-resolution mass spectrometry study for evaluation of milk freshness

Milk freshness is an important parameter for both consumers' health and quality of milk-based products. Up to now there have been neither analytical methods nor specific parameters to uniquely define milk freshness from a complete and univocal chemical perspective. In this study, 8 molecules were selected and identified as responsible for milk aging, using a liquid chromatography-high-resolution mass spectrometry approach followed by chemometric data elaboration. For model setup and marker selection, 30 high-quality pasteurized fresh milk samples were collected directly from the production site and analyzed immediately and after storage at 2 to 8°C for 7 d. The markers were then validated by challenging the model with a set of 10 milk samples, not previously analyzed. Our results demonstrated that the markers identified within this study can be successfully used for the correct classification of non-fresh milk samples, complementing and successfully enhancing parallel evaluations obtainable through sensory measures.

Serum metabolic profile of postoperative acute kidney injury following infant cardiac surgery with cardiopulmonary bypass

BACKGROUND

We sought to determine differences in the circulating metabolic profile of infants with or without acute kidney injury (AKI) following cardiothoracic surgery with cardiopulmonary bypass (CPB).

METHODS

We performed a secondary analysis of preoperative and 24-h postoperative serum samples from infants ≤ 120 days old undergoing CPB. Metabolic profiling of the serum samples was performed by targeted analysis of 165 serum metabolites via tandem mass spectrometry. We then compared infants who did or did not develop AKI in the first 72 h postoperatively to determine global differences in the preoperative and 24-h metabolic profiles in addition to specific differences in individual metabolites.

RESULTS

A total of 57 infants were included in the study. Six infants (11%) developed KDIGO stage 2/3 AKI and 13 (23%) developed stage 1 AKI. The preoperative metabolic profile did not differentiate between infants with or without AKI. Infants with severe AKI could be moderately distinguished from infants without AKI by their 24-h metabolic profile, while infants with stage 1 AKI segregated into two groups, overlapping with either the no AKI or severe AKI groups. Differences in these 24-h metabolic profiles were driven by 21 metabolites significant at an adjusted false discovery rate of < 0.05. Prominently altered pathways include purine, methionine, and kynurenine/nicotinamide metabolism.

CONCLUSION

Moderate-to-severe AKI after infant cardiac surgery is associated with changes in the serum metabolome, including prominent changes to purine, methionine, and kynurenine/nicotinamide metabolism. A portion of infants with mild AKI demonstrated similar metabolic changes, suggesting a potential role for metabolic analysis in the evaluation of lower stage injury.

A systematic approach to metabolic characterization of thyroid-disrupting chemicals and their in vitro biotransformants based on prediction-assisted metabolomic analysis

Thyroid-disrupting compounds (TDCs) are chemicals that modify thyroid gland function and disrupt hormonal homeostasis. Like other endocrine-disrupting chemicals (EDCs), TDCs often show altered activities following post-metabolic modification via endogenous enzymatic reaction. Hence, we developed evaluation system consisting of (1) in vitro metabolic reaction module, (2) high-resolution mass-spectrometry, and (3) human cell-based reporter gene assay. We developed the reaction module using rat S9 fraction where levothyroxine (T4) as a model compound, was subjected to phase-I or phase-I+II biotransformation. The metabolic profiles of the biotransformants were systematically configured based on in-silico prediction of potential products and experimental validation using liquid-chromatography Orbitrap mass-spectrometry. Thyroid agonistic activities of the biotransformants were evaluated by thyroid receptor-mediated stably transfected transcriptional activation assay using hTRE_HeLa cells. Indeed, we detected the increased activities following metabolic conversion of T4 in a dose-dependent manner. Note that the activity by phase-I+II reaction was much greater than by phase-I reaction (3.8-fold increase). Subsequently, we explored metabolic signatures, which potentially contributed to the hyperactivity by phase-I+II reaction. A total of 77 metabolic features were annotated based on the in-silico prediction, which included biotransformants with deiodination and conjugation. The glucuronide-conjugated form was found at the highest fold-increase (970-fold increase) whereas marginal increases were determined in the deiodinized forms (1.6-fold increase in T3 and 2.0-fold increase in rT3). Further, the systematic approach was evaluated and comparably analyzed by the metabolic profiles of bithionol, which is structurally related to T4. Our current result suggested the potential application of in vitro evaluation system to risk assessment of thyroid-disrupting activity.

Obeticholic Acid Inhibits Anxiety via Alleviating Gut Microbiota-Mediated Microglia Accumulation in the Brain of High-Fat High-Sugar Diet Mice

Anxiety is one of the complications of metabolic disorders (MDs). Obeticholic acid (OCA), the bile acids (BAs) derivative, is a promising agent for improving MDs in association with gut dysbiosis. Yet, its protective effect on MDs-driven anxiety remains unknown. Here, we assessed the serum biochemical parameters and behavioral performance by open field and Morris water maze tests in HFHS diet-induced MDs mice after OCA intervention for nine and 18 weeks. Moreover, antibiotics intervention for microbial depletion was conducted simultaneously. We found that OCA treatment inhibited the initiation and progression of anxiety in HFHS diet-MDs mice via a microbiota–BAs–brain axis: OCA decreased the neuroinflammatory microglia and IL-1β expression in the hippocampus, reversed intestinal barrier dysfunction and serum proinflammatory LPS to a normal level, modified the microbial community, including the known anxiety-related Rikenellaceae and Alistipes, and improved the microbial metabolites especially the increased BAs in feces and circulation. Moreover, the OCA-reversed bile acid taurocholate linked disordered serum lipid metabolites and indole derivatives to anxiety as assessed by network analysis. Additionally, microbial depletion with antibiotics also improved the anxiety, microgliosis and BAs enrichment in the experimental MDs mice. Together, these findings provide microbiota–BAs–brain axis as a novel therapeutic target for MDs-associated neuropsychiatric disorders.

Altered Gut Microbial Metabolites in Amnestic Mild Cognitive Impairment and Alzheimer's Disease: Signals in Host-Microbe Interplay

Intimate metabolic host-microbiome crosstalk regulates immune, metabolic, and neuronal response in health and disease, yet remains untapped for biomarkers or intervention for disease. Our recent study identified an altered microbiome in patients with pre-onset amnestic mild cognitive impairment (aMCI) and dementia Alzheimer's disease (AD). Thus, we aimed to characterize the gut microbial metabolites among AD, aMCI, and healthy controls (HC). Here, a cohort of 77 individuals (22 aMCI, 27 AD, and 28 HC) was recruited. With the use of liquid-chromatography/gas chromatography mass spectrometry metabolomics profiling, we identified significant differences between AD and HC for tryptophan metabolites, short-chain fatty acids (SCFAs), and lithocholic acid, the majority of which correlated with altered microbiota and cognitive impairment. Notably, tryptophan disorders presented in aMCI and SCFAs decreased progressively from aMCI to AD. Importantly, indole-3-pyruvic acid, a metabolite from tryptophan, was identified as a signature for discrimination and prediction of AD, and five SCFAs for pre-onset and progression of AD. This study showed fecal-based gut microbial signatures were associated with the presence and progression of AD, providing a potential target for microbiota or dietary intervention in AD prevention and support for the host-microbe crosstalk signals in AD pathophysiology.

Alterations in Metabolites Associated with Hypoxemia in Neonates and Infants with Congenital Heart Disease

Objectives:

(1) To measure the global shift in the metabolome in hypoxemic versus non-hypoxemic infants with congenital heart disease; (2) To identify metabolites and metabolic pathways that are altered in hypoxemia.

Study Design:

Analysis of serum samples obtained prior to cardiopulmonary bypass from 82 infants ≤120 days old with congenital heart disease requiring surgery at Children’s Hospital Colorado. Infants were divided into groups based on pre-operative oxygen saturations: non-hypoxemic (>92%), mild hypoxemia (85–92%), and severe hypoxemia (<85%). Tandem mass spectrometry was used to analyze 165 targeted metabolites. Partial least squares discriminant analysis and t-tests were used to determine differences among metabolic profiles and individual metabolites respectively.

Results:

The broad metabolic fingerprint of neonates or older infants did not vary by degree of hypoxemia. There were 12 individual metabolites that differed between hypoxemic and non-hypoxemic neonates, including lower methylmalonic acid (p = 2.44 × 10⁻⁴), glutamate (p = 0.001), and hypoxanthine (p = 0.003), and higher thymine (p = 8.67 × 10⁻⁴) and myo-inositol (p = 0.014) seen in hypoxemic neonates. Individual metabolites did not vary significantly between older infants with or without hypoxemia.

Conclusions:

We did not find evidence supporting global metabolic changes associated with cyanotic congenital heart disease in neonates or older infants. However, specific metabolites did discriminate between hypoxemic and non-hypoxemic neonates. These include methylmalonic acid, as well as several metabolites known to change in hypoxia-reoxygenation states (hypoxanthine) and chronic hypoxemic states (glutamate, thymine, myo-inositol) and may represent specific metabolic changes triggered by hypoxemia among neonates with cyanotic congenital heart disease.

Activation of kynurenine pathway of tryptophan metabolism after infant cardiac surgery with cardiopulmonary bypass: a prospective cohort study

BACKGROUND

Serum kynurenic acid is associated with poor outcomes after infant cardiopulmonary bypass (CPB), but comprehensive mapping of the kynurenine pathway (KP) after CPB has yet to be performed.

AIMS

To map changes in the KP induced by infant CPB.

METHODS

Compared changes in serum KP metabolites through 48hrs post-op with liquid-chromatography-tandem mass spectrometry.

RESULTS

Infant CPB results in marked increase in proximal, but not distal metabolites of the KP.

CONCLUSIONS

Infant CPB leads to accumulation of circulating KP metabolites, which have important neurologic and immunologic activities. Thus, further exploration of the KP is warranted in these high-risk infants.

Early Urinary Metabolomics in Patent Ductus Arteriosus Anticipates the Fate: Preliminary Data

Introduction: In premature neonates, the persistence of hemodynamically significant ductus arteriosus (hsPDA) can be associated with short- and long-term consequences, impairing their outcome. The correct strategy of management for such condition is under debate, especially regarding contraindications and/or side effects. In recent years, metabolomics was applied to several perinatal, pediatric, and adult conditions to investigate potential biomarkers of disease, which have become useful for early diagnosis and/or therapeutic management. Aim of the Study: The main purpose of our exploratory study was to asses, through ¹H-NMR metabolomics analysis of urinary samples at birth, possible metabolic pathways differentiating, with a significant predictive power, those preterm neonates who will subsequently develop hsPDA and neonates of comparable gestational age (GA) who will undergo spontaneous ductal closure or the persistence of an irrelevant PDA (no-hsPDA). Moreover, we investigated potential prenatal or perinatal clinical factors potentially influencing the development of hsPDA. Materials and Methods: We enrolled n = 35 preterm neonates with GA between 24 and 32 weeks; urinary samples were collected within the first 12 h of life. Patients were closely monitored regarding intensive care, respiratory support, fluid balance and administered drugs; an echocardiogram was performed at 48-72 h. Results: Our results reported a significant correlation between lower GA at birth and the development of hsPDA. Moreover, neonates with GA ≤ 30w developing hsPDA were characterized by lower Apgar scores at 1' and 5', higher rates of perinatal asphyxia, higher need of delivery room resuscitation and subsequent surfactant administration. Interestingly, metabolomics analysis at birth detected a clear separation between the ¹H-NMR urinary spectra of subjects GA ≤ 30w not developing hsPDA (n = 19) and those of subjects born at GA ≤ 30w in which hsPDA was confirmed at 48-72 h of life (n = 5). Conclusions: This is the first study applying metabolomics to investigate the PDA condition. Although preliminary and conducted on a limited sample, our results reveal that metabolomics could be a promising tool in the early identification of hsPDA, potentially superior to the clinical or laboratory predictive tools explored to date and even to the clinical observations and correlations in our sample, through the detection of specific urinary metabolites.