RATIONALE: Airway obstruction in patients with asthma is associated with airway dysfunction and inflammation. Objective measurements including sputum analysis can guide therapy, but this is often not possible in typical clinical settings. Metabolomics is the study of molecules generated by metabolic pathways. We hypothesize that airway dysfunction and inflammation in an animal model of asthma would produce unique patterns of urine metabolites measured by multivariate statistical analysis of high-resolution proton nuclear magnetic resonance ((1)H NMR) spectroscopy data. OBJECTIVES: To develop a noninvasive means of monitoring asthma status by metabolomics and urine sampling. METHODS: Five groups of guinea pigs were studied: control, control treated with dexamethasone, sensitized (ovalbumin, administered intraperitoneally), sensitized and challenged (ovalbumin, administered intraperitoneally, plus ovalbumin aerosol), and sensitized-challenged with dexamethasone. Airway hyperreactivity (AHR) to histamine (administered intravenously) and inflammation were measured. Multivariate statistical analysis of NMR spectra based on a library of known urine metabolites was performed by partial least-squares discriminant analysis. In addition, the raw NMR spectra exported as xy-trace data underwent linear discriminant analysis. MEASUREMENTS AND MAIN RESULTS: Challenged guinea pigs developed AHR and increased inflammation compared with sensitized or control animals. Dexamethasone significantly improved AHR. Using concentration differences in metabolites, partial least-squares discriminant analysis could discriminate challenged animals with 90% accuracy. Using only three or four regions of the NMR spectra, linear discriminant analysis-based classification demonstrated 80-90% separation of the animal groups. CONCLUSIONS: Urine metabolites correlate with airway dysfunction in an asthma model. Urine NMR analysis is a promising, noninvasive technique for monitoring asthma in humans.
RATIONALE: Airway obstruction in patients with asthma is associated with airway dysfunction and inflammation. Objective measurements including sputum analysis can guide therapy, but this is often not possible in typical clinical settings. Metabolomics is the study of molecules generated by metabolic pathways. We hypothesize that airway dysfunction and inflammation in an animal model of asthma would produce unique patterns of urine metabolites measured by multivariate statistical analysis of high-resolution proton nuclear magnetic resonance ((1)H NMR) spectroscopy data. OBJECTIVES: To develop a noninvasive means of monitoring asthma status by metabolomics and urine sampling. METHODS: Five groups of guinea pigs were studied: control, control treated with dexamethasone, sensitized (ovalbumin, administered intraperitoneally), sensitized and challenged (ovalbumin, administered intraperitoneally, plus ovalbumin aerosol), and sensitized-challenged with dexamethasone. Airway hyperreactivity (AHR) to histamine (administered intravenously) and inflammation were measured. Multivariate statistical analysis of NMR spectra based on a library of known urine metabolites was performed by partial least-squares discriminant analysis. In addition, the raw NMR spectra exported as xy-trace data underwent linear discriminant analysis. MEASUREMENTS AND MAIN RESULTS: Challenged guinea pigs developed AHR and increased inflammation compared with sensitized or control animals. Dexamethasone significantly improved AHR. Using concentration differences in metabolites, partial least-squares discriminant analysis could discriminate challenged animals with 90% accuracy. Using only three or four regions of the NMR spectra, linear discriminant analysis-based classification demonstrated 80-90% separation of the animal groups. CONCLUSIONS: Urine metabolites correlate with airway dysfunction in an asthma model. Urine NMR analysis is a promising, noninvasive technique for monitoring asthma in humans.
Authors: Youngja Park; Dean P Jones; Thomas R Ziegler; Kichun Lee; Kavitha Kotha; Tianwei Yu; Greg S Martin Journal: Crit Care Med Date: 2011-10 Impact factor: 7.598
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