Emerging Biomarkers of Illness Severity: Urinary Metabolites Associated with Sepsis and Necrotizing Methicillin-Resistant Staphylococcus aureus Pneumonia.

Our objective was to illustrate the potential of metabolomics to identify novel biomarkers of illness severity in a child with fatal necrotizing pneumonia caused by methicillin-resistant Staphylococcus aureus (MRSA). We present a case report with two control groups and a metabolomics analysis: an infant with fatal MRSA pneumonia, four children with influenza pneumonia (pneumonia control group), and seven healthy children with no known infections (healthy control group). Urine samples were collected from all children. Metabolites were identified and quantified using H-nuclear magnetic resonance spectrometry. Normalized metabolite concentration data from children with influenza pneumonia and healthy controls were compared by using an unpaired Student t test. To identify differentiating metabolites of MRSA pneumonia, the fold change of each metabolite was calculated by dividing each urine metabolite concentration of the patient with fatal MRSA pneumonia by the median urine concentration values of the same metabolite of the patients with influenza pneumonia and healthy controls, respectively. MetScape (http://metscape.ncibi.org/), a bioinformatics tool, was used for data visualization and interpretation. Urine metabolite concentrations previously identified as associated with sepsis in children (e.g., 3-hydroxybutyrate, carnitine, and creatinine) were higher in the patient with fatal MRSA pneumonia compared with those of patients with influenza pneumonia and healthy controls. The concentrations of additional metabolites-acetone, acetoacetate, choline, fumarate, glucose, and 3-aminoisobutyrate-were more than 25-fold higher in the patient with MRSA pneumonia than those of patients with influenza pneumonia and healthy controls. These metabolic changes in the urine preceded the clinical severe sepsis phenotype, suggesting that detection of the extent of metabolic disruption can aid in the early identification of a sepsis phenotype in advance of the clinical diagnosis. These data also support the utility of metabolomics for the development of clinical assays to identify patients with pediatric pneumonia at high risk for deterioration.