title: Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study.
abstract: Clinicians lack objective tests to help determine the severity of bronchiolitis or to distinguish a viral from bacterial causes of respiratory distress. We hypothesized that children with respiratory syncytial virus (RSV) infection would have a different metabolomic profile compared to those with bacterial infection or healthy controls, and this might also vary with bronchiolitis severity.
  
  
  
  Clinical information and urine-based metabolomic data were collected from healthy age-matched children (n = 37) and those admitted to hospital with a proven infection (RSV n = 55; Non-RSV viral n = 16; bacterial n = 24). Nuclear magnetic resonance (NMR) measured 86 metabolites per urine sample. Partial least squares discriminant analysis (PLS-DA) was performed to create models of separation.
  
  
  
  Using a combination of metabolites, a strong PLS-DA model (R2 = 0.86, Q2 = 0.76) was created differentiating healthy children from those with RSV infection. This model had over 90 % accuracy in classifying blinded infants with similar illness severity. Two other models differentiated length of hospitalization and viral versus bacterial infection.
  
  
  
  While the sample sizes remain small, this is the first report suggesting that metabolomic analysis of urine samples has the potential to become a diagnostic aid. Future studies with larger sample sizes are required to validate the utility of metabolomics in pediatric patients with respiratory distress.
authors.affiliation: The Department of Pediatrics, University of Alberta, T6G 1C9, Edmonton, Canada. darryl.adamko@usask.ca.|University of Saskatchewan, S7N 0W8, Saskatoon, Saskatchewan, Canada. darryl.adamko@usask.ca.
authors.forename: Darryl J
authors.initials: DJ
authors.lastname: Adamko
authors.affiliation: Department of Emergency Medicine, University of Calgary, T2N 2T9, Calgary, Alberta, Canada.
authors.forename: Erik
authors.initials: E
authors.lastname: Saude
authors.affiliation: University of Saskatchewan, S7N 0W8, Saskatoon, Saskatchewan, Canada.
authors.forename: Matthew
authors.initials: M
authors.lastname: Bear
authors.affiliation: The Department of Pediatrics, University of Alberta, T6G 1C9, Edmonton, Canada.
authors.forename: Shana
authors.initials: S
authors.lastname: Regush
authors.affiliation: The Department of Pediatrics, University of Alberta, T6G 1C9, Edmonton, Canada.
authors.forename: Joan L
authors.initials: JL
authors.lastname: Robinson
mesh_terms: D001424:Bacterial Infections / Q000378:metabolism / Q000382:microbiology / Q000473:pathology; D015415:Biomarkers / Q000652:urine*; D016022:Case-Control Studies; D002675:Child, Preschool; D016002:Discriminant Analysis; D004636:Emergency Service, Hospital; D005260:Female; D006760:Hospitalization; D006801:Humans; D007223:Infant; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D055432:Metabolomics; D010865:Pilot Projects; D018357:Respiratory Syncytial Virus Infections / Q000378:metabolism / Q000473:pathology / Q000821:virology; D012141:Respiratory Tract Infections / Q000378:metabolism* / Q000382:microbiology / Q000473:pathology / Q000821:virology
chemical_list: D015415:Biomarkers
keywords: Bacteria; Biomarkers; Bronchiolitis; Children; Metabolomics; Respiratory syncytial virus