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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. [ABSTRACT FROM AUTHOR]

Perinatal asphyxia is one of the leading causes of morbidity and mortality in the neonatal period. Response to oxygen treatment is unpredictable and the optimum concentration of oxygen in neonatal resuscitation is still a matter of debate among neonatologists. A metabolomic approach was used to characterize the metabolic profiles of newborn hypoxic-reoxygenated piglets. Urine samples were collected from newborn piglets ( n = 40) undergoing hypoxia followed by resuscitation at different oxygen concentrations (ranging from 18% to 100%) and analyzed by 1H NMR spectroscopy. Despite reoxygenation 7 piglets, out of 10 which became asystolic, did not respond to resuscitation. Profiles of the 1H NMR spectra were submitted to unsupervised (principal component analysis) and supervised (partial least squares-discriminant analysis) multivariate analysis. The supervised analyses showed differences in the metabolic profile of the urine collected before the induction of hypoxia between survivors and deaths. Metabolic variations were observed in the urine of piglets treated with different oxygen concentrations comparing T0 (basal value) and end of the experiment (resuscitation). Some of the individual metabolites discriminating between these groups were urea, creatinine, malonate, methylguanidine, hydroxyisobutyric acid. The metabolomic approach appears a promising tool for investigating newborn hypoxia over time, for monitoring the response to the treatment with different oxygen concentrations, and might lead to a tailored management of the disorder. [ABSTRACT FROM AUTHOR]

ABSTRACT: 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 (1H-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). [Copyright &y& Elsevier]