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.

GC-MS-based metabolomic analysis of the urinary metabolome suggests to have the required sensitivity and specificity to gain insight into ASD phenotypes and aid a personalized network-based medicine approach.

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.

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.