Antonio Noto

Metabolomics in newborns with intrauterine growth retardation (IUGR): urine reveals markers of metabolic syndrome

To date, we have little knowledge on the overall metabolic status of neonates with intrauterine growth retardation (IUGR). In the last few years, the analysis of metabolomics has assumed an important clinical role in identifying “disorders” in the metabolic profile of patients. The aim of this work has been to analyze the urine metabolic profiles of neonates with IUGR and compare them with controls to define the metabolic patterns associated with this pathology. To our knowledge, this is the first study of metabolomics performed on neonates with IUGR. Recruited for the study were 26 neonates with IUGR diagnosed in the neonatal period and with weight at birth below the 10th percentile and 30 neonates of proper gestational weight at birth (controls). In the first 24 hours (prior to feeding) (T1) and about 4 days after birth (T2), a urine sample was taken non-invasively from each neonate. The samples were then frozen at −80°C up to the time of the analysis by proton nuclear magnetic resonance spectroscopy (1H-NMR). The data contained in the NMR spectra obtained from the single samples were statistically analyzed using the Principal Components Analysis and the Partial Least Squares-Discriminate Analysis. By means of a multivariate analysis of the NMR spectra obtained, it was possible to highlight the differences between the two groups (IUGRs and controls) owing to the presence of different metabolic patterns. The discriminants in the urine metabolic profiles derived essentially from significant differences in certain metabolites such as: myo-inositol, sarcosine, creatine and creatinine. The metabolomic analysis showed different urine metabolic profiles between neonates with IUGR and controls and made it possible to identify the molecules responsible for such differences.

Monitoring the Modifications of the Vitreous Humor Metabolite Profile after Death: An Animal Model

We applied a metabolomic approach to monitor the modifications occurring in goat vitreous humor (VH) metabolite composition at different times (0, 6, 12, 18, and 24 hours) after death. The 1H-NMR analysis of the VH samples was performed for the simultaneous determination of several metabolites (i.e., the metabolite profile) representative of the VH status at different times. Spectral data were analyzed by Principal Component Analysis (PCA) and by Orthogonal Projection to Latent Structures (OPLS) regression technique. PCA and OPLS suggested that different spectral regions were involved in time-related changes. The major time-related compositional changes, here detected, were the increase of lactate, hypoxanthine, alanine, total glutathione, choline/phosphocholine, creatine, and myo-inositol and the decrease of glucose and 3-hydroxybutyrate. We attempted a speculative interpretation of the biological mechanisms underlying these changes. These results show that multivariate statistical approach, based on 1H NMR metabolite profiling, is a powerful tool for detecting ongoing differences in VH composition and may be applied to investigate several physiological and pathological conditions.

A metabolomic study of preterm human and formula milk by high resolution NMR and GC/MS analysis: preliminary results

Objective: The aim of the present study was to investigate the metabolic profile of preterm human breast milk (HBM) by using a metabolomic approach. Methods: NMR spectroscopy and GC/MS were used to analyze the water-soluble and lipid fractions extracted from milk samples obtained from mothers giving birth at 26–36 weeks of gestation. For the sake of comparison, preterm formula milk was also studied. Results: The multivariate statistical analysis of the data evidenced biochemical variability both between preterm HBM and commercial milk and within the group of HBM samples. Conclusions: The preliminary results of this study suggest that metabolomics may provide a promising tool to study aspects related to the nutrition and health of preterm infant.

Soluble CD14 subtype presepsin (sCD14-ST) and lipopolysaccharide binding protein (LBP) in neonatal sepsis: new clinical and analytical perspectives for two old biomarkers

Several biochemical markers have been proposed over the past years to manage critically ill newborns with acute inflammation and sepsis. The state of the art in diagnosing and monitoring neonatal sepsis, severe sepsis and septic shock consists of the measurement of plasma C-reactive protein (CRP) and procalcitonin (PCT) at the onset and in the course of the disease. CRP and PCT in combination are clinically significant in diagnosing and monitoring septic newborns; however, CRP and PCT have a very limited value for risk stratification and in predicting outcome. The availability of commercial methods for the automated measurement of the soluble CD14 subtype presepsin (sCD14-ST) and lipopolysaccharide binding protein (LBP) represent a challenge for the evaluation in clinical practice of reliable markers of neonatal sepsis, specifically for the very early diagnosis, the classification into class of severity, and the prediction of complications and death.

The importance of biomarkers in neonatology

Despite a 35% decline in the mortality rate for infants aged <5 years over the past two decades, every year nearly 40% of all deaths in this age group occur in the neonatal period, defined as the first 28 days of life. New knowledge on molecular and biochemical pathways in neonatal diseases will lead to the discovery of new candidate biomarkers potentially useful in clinical practice. In the era of personalized medicine, biomarkers may play a strategic role in accelerating the decline in neonatal mortality by assessing the risk of developing neonatal diseases, by implementing tailored therapeutic treatment, and by predicting the clinical outcome. However, there is an urgent need to reduce the gap in translating newly acquired knowledge from bench to bedside. Traditional and candidate biomarkers for neonatal sepsis and necrotizing enterocolitis will be discussed in this review, such as C-reactive protein (CRP), procalcitonin (PCT), serum amyloid A (SAA), soluble form of CD14 subtype presepsin (sCD14-ST), lipolysaccharide binding protein (LBP), angiopoietins (Ang)-1 and -2, soluble form of triggering receptor expressed on myeloid cells (sTREM-1), soluble form of urokinase-type plasminogen activator receptor (suPAR), platelet-activating factor (PAF) and calprotectin. New frontiers in managing critically ill newborns may be opened by metabolomics, a diagnostic tool based on the recognition of metabolites contained in biological fluids. Metabolomics represents the passage from a descriptive science to a predictive science, having the potential to translate benchtop research to real clinical benefits.

Urinary 1H-NMR and GC-MS metabolomics predicts early and late onset neonatal sepsis

The purpose of this article is to study one of the most significant causes of neonatal morbidity and mortality: neonatal sepsis. This pathology is due to a bacterial or fungal infection acquired during the perinatal period. Neonatal sepsis has been categorized into two groups: early onset if it occurs within 3-6 days and late onset after 4-7 days. Due to the not-specific clinical signs, along with the inaccuracy of available biomarkers, the diagnosis is still a major challenge. In this regard, the use of a combined approach based on both nuclear magnetic resonance ((1)H-NMR) and gas-chromatography-mass spectrometry (GC-MS) techniques, coupled with a multivariate statistical analysis, may help to uncover features of the disease that are still hidden. The objective of our study was to evaluate the capability of the metabolomics approach to identify a potential metabolic profile related to the neonatal septic condition. The study population included 25 neonates (15 males and 10 females): 9 (6 males and 3 females) patients had a diagnosis of sepsis and 16 were healthy controls (9 males and 7 females). This study showed a unique metabolic profile of the patients affected by sepsis compared to non-affected ones with a statistically significant difference between the two groups (p = 0.05).

Clinical application of metabolomics in neonatology

The youngest and more rapidly increasing “omic” discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a “snapshot” of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine (“a window on the organism”) is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

The role of metabolomics in neonatal and pediatric laboratory medicine

Metabolomics consists of the quantitative analysis of a large number of low molecular mass metabolites involving substrates or products in metabolic pathways existing in all living systems. The analysis of the metabolic profile detectable in a human biological fluid allows to instantly identify changes in the composition of endogenous and exogenous metabolites caused by the interaction between specific physiopathological states, gene expression, and environment. In pediatrics and neonatology, metabolomics offers new encouraging perspectives for the improvement of critically ill patient outcome, for the early recognition of metabolic profiles associated with the development of diseases in the adult life, and for delivery of individualized medicine. In this view, nutrimetabolomics, based on the recognition of specific cluster of metabolites associated with nutrition and pharmacometabolomics, based on the capacity to personalize drug therapy by analyzing metabolic modifications due to therapeutic treatment may open new frontiers in the prevention and in the treatment of pediatric and neonatal diseases. This review summarizes the most relevant results published in the literature on the application of metabolomics in pediatric and neonatal clinical settings. However, there is the urgent need to standardize physiological and preanalytical variables, analytical methods, data processing, and result presentation, before establishing the definitive clinical value of results.

Clinical metabolomics and urinary NGAL for the early prediction of chronic kidney disease in healthy adults born ELBW

Background: Clinical metabolomics is a recent “omic” technology which is defined as a global holistic overview of the personal metabolic status (fingerprinting). This technique allows to prove metabolic differences in different groups of people with the opportunity to explore interactions such as genotype-phenotype and genotype-environment type, whether normal or pathological. Aim: To study chronic kidney injury 1) using urine metabolomic profiles of young adults born extremely low-birth weight (ELBW) and 2) correlating a biomarker of kidney injury, urinary neutrophil gelatinase-associated lipocalin (NGAL), in order to confirm the metabolomic injury profile. Method: Urine samples were collected from a group of 18 people (mean: 24-year-old, std: 4.27) who were born with ELBW and a group of 13 who were born at term appropriate for gestational age (AGA) as control (mean 25-year-old, std: 5.15). Urine samples were analyzed by 1H-nuclear magnetic resonance spectroscopy, and then submitted to unsupervised and supervised multivariate analysis. Urine NGAL (uNGAL) was measured using ARCHITECT (ABBOTT diagnostic NGAL kit). Results: With a multivariate approach and using a supervised analysis method, PLS-DA, (partial least squares discriminant analysis) we could correlate ELBW metabolic profiles with uNGAL concentration. Conversely, uNGAL could not be correlated to AGA. Conclusions: This study demonstrates the relevance of the metabolomic technique as a predictive tool of the metabolic status of exELBW. This was confirmed by the use of uNGAL as a biomarker which may predict a subclinical pathological process in the kidney such as chronic kidney disease.

Metabolomics in paediatric respiratory diseases and bronchiolitis

The metabolic study of an organism may make it possible to monitor, through the metabolites,the physiology and/or pathology of the organism itself. Metabolomics, in the strictest sense, “the set of metabolites, the final products of the genetic expression”. Most clinical chemistry tests available today rely on old technologies that measure only a single chemical in blood, urine or other biofluids, and these tests are neither sensitive nor specific for any particular disease. Metabolomics offers a holistic approach to systems medicine, with the promise to enhance clinical chemistry diagnostics in several pathologic conditions. The present review covers the application of clinical metabolomics in three different areas of respiratory diseases in pediatrics: asthma, pneumonia and bronchiolitis. Comparison between two 1H-NMR urine spectra by two bronchiolitis patients are also presented.