title: The urinary metabolomics profile of an Italian autistic children population and their unaffected siblings.
abstract: OBJECTIVE
  A supervised multivariate model to classify the metabolome alterations between autistic spectrum disorders (ASD) patients and controls, siblings of autistic patients, has been realized and used to realize a network model of the ASD patients' metabolome.
  
  
  METHODS
  In our experiment we propose a quantification of urinary metabolites with the Mass Spectroscopy technique couple to Gas Chromatography. A multivariate model has been used to extrapolate the variables of importance for a network model of interaction between metabolites. In this way we are able to propose a network-based approach to ASD description.
  
  
  RESULTS
  Children with autistic disease composing our studied population showed elevated concentration of several organic acids and sugars. Interactions among diet, intestinal flora and genes may explain such findings. Among them, the 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid has been previously described as altered in autistic subjects. Other metabolites increased are 3,4-dihydroxybutyric acid, glycolic acid and glycine, cis-aconitic acid; phenylalanine, tyrosine, p-hydroxyphenylacetic acid, and homovanillic acid are all involved in the tyrosine pathway leading to neurotransmitter cathecolamine.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Neonatal Intensive Care Unit, Puericulture Institute and Neonatal Section, Department of Surgical Sciences, Azienda Ospedaliera Universitaria, University of Cagliari, Cagliari , Italy .
authors.forename: Antonio
authors.initials: A
authors.lastname: Noto
authors.forename: Vassilios
authors.initials: V
authors.lastname: Fanos
authors.forename: Luigi
authors.initials: L
authors.lastname: Barberini
authors.forename: Dmitry
authors.initials: D
authors.lastname: Grapov
authors.forename: Claudia
authors.initials: C
authors.lastname: Fattuoni
authors.forename: Marco
authors.initials: M
authors.lastname: Zaffanello
authors.forename: Andrea
authors.initials: A
authors.lastname: Casanova
authors.forename: Gianni
authors.initials: G
authors.lastname: Fenu
authors.forename: Andrea
authors.initials: A
authors.lastname: De Giacomo
authors.forename: Maria
authors.initials: M
authors.lastname: De Angelis
authors.forename: Corrado
authors.initials: C
authors.lastname: Moretti
authors.forename: Paola
authors.initials: P
authors.lastname: Papoff
authors.forename: Raffaella
authors.initials: R
authors.lastname: Ditonno
authors.forename: Ruggiero
authors.initials: R
authors.lastname: Francavilla
mesh_terms: D000293:Adolescent; D001321:Autistic Disorder / Q000652:urine*; D002648:Child; D002675:Child, Preschool; D005260:Female; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D006801:Humans; D007558:Italy; D016018:Least-Squares Analysis; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D012680:Sensitivity and Specificity; D035781:Siblings
keywords: ASD; GC-MS; network-driven medicine