title: Urinary metabolomics (GC-MS) reveals that low and high birth weight infants share elevated inositol concentrations at birth.
abstract: OBJECTIVE
  Metabolomics is a new "omics" platform aimed at high-throughput identification, quantification and characterization of small-molecule metabolites. The metabolomics approach has been successfully applied to the classification different physiological states and identification of perturbed biochemical pathways. The purpose of the current investigation is the application of metabolomics to explore biological mechanisms which may lead to the onset of metabolic syndrome in adulthood.
  
  
  METHODS
  We evaluated differences in metabolites in the urine collected within 12 h from 23 infants with IUGR (IntraUterine Growth Restriction), or LGA (Large for Gestational Age), compared to control infants (10 patients defined AGA: Appropriate for Gestational Age). Urinary metabolites were quantified by GC-MS and used to highlight similarities between the two metabolic diseases and identify metabolic markers for their predisposition. Quantified metabolites were analyzed using a multivariate statistics coupled with receiver operator characteristic curve (ROC) analysis of identified biomarkers.
  
  
  RESULTS
  Urinary myo-inositol was the most important discriminant between LGA + IUGR and control infants, and displayed an area under the ROC curve = 1.
  
  
  CONCLUSIONS
  We postulate that the increase in plasma and consequently urinary inositol may constitute a marker of altered glucose metabolism during fetal development in both IUGR and LGA newborns.
authors.affiliation: Department of Public Health Clinical and Molecular Medicine, University of Cagliari , Cagliari , Italy .
authors.forename: Luigi
authors.initials: L
authors.lastname: Barberini
authors.forename: Antonio
authors.initials: A
authors.lastname: Noto
authors.forename: Claudia
authors.initials: C
authors.lastname: Fattuoni
authors.forename: Dmitry
authors.initials: D
authors.lastname: Grapov
authors.forename: Andrea
authors.initials: A
authors.lastname: Casanova
authors.forename: Gianni
authors.initials: G
authors.lastname: Fenu
authors.forename: Mauro
authors.initials: M
authors.lastname: Gaviano
authors.forename: Roberta
authors.initials: R
authors.lastname: Carboni
authors.forename: Giovanni
authors.initials: G
authors.lastname: Ottonello
authors.forename: Maurizio
authors.initials: M
authors.lastname: Crisafulli
authors.forename: Vassilios
authors.initials: V
authors.lastname: Fanos
authors.forename: Angelica
authors.initials: A
authors.lastname: Dessì
mesh_terms: D015415:Biomarkers / Q000652:urine*; D001724:Birth Weight; D005260:Female; D005317:Fetal Growth Retardation / Q000652:urine*; D008401:Gas Chromatography-Mass Spectrometry; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007232:Infant, Newborn, Diseases / Q000378:metabolism*; D007294:Inositol / Q000652:urine*; D007558:Italy; D008297:Male; D024821:Metabolic Syndrome / Q000652:urine*; D055432:Metabolomics / Q000379:methods*; D012372:ROC Curve
chemical_list: D015415:Biomarkers; D007294:Inositol
keywords: GC-MS; IUGR; OSC-PLS-DA; inositol; metabolomics