BACKGROUND: The ability to diagnose and monitor asthma on the basis of noninvasive measurements of airway cellular dysfunction is difficult in the typical clinical setting. OBJECTIVE: Metabolomics is the study of molecules created by cellular metabolic pathways. We hypothesized that the metabolic activity of children with asthma would differ from healthy children without asthma. Furthermore, children having an asthma exacerbation would be different compared with children with stable asthma in outpatient clinics. Finally, we hypothesized that (1)H-nuclear magnetic resonance (NMR) would measure such differences using urine samples, one of the least invasive forms of biofluid sampling. METHODS: Children (135 total, ages 4-16 years) were enrolled, having met the criteria of healthy controls (C), stable asthma in the outpatient clinic (AO), or unstable asthma in the emergency department (AED). Partial least squares discriminant analysis was performed on the NMR data to create models of separation (70 metabolites were measured/urine sample). Some NMR data were withheld from modeling to be run blindly to determine possible diagnostic accuracy. RESULTS: On the basis of the model of AO versus C, 31 of 33 AO samples were correctly diagnosed with asthma (94% accuracy). Only 1 of 20 C samples was incorrectly labeled as asthma (5% misclassification). On the basis of the AO versus AED model, 31 of the 33 AO samples were correctly diagnosed as outpatient asthma (94% accurate). CONCLUSION: This is the first report suggesting that (1)H-NMR analysis of human urine samples has the potential to be a useful clinical tool for physicians treating asthma.
BACKGROUND: The ability to diagnose and monitor asthma on the basis of noninvasive measurements of airway cellular dysfunction is difficult in the typical clinical setting. OBJECTIVE: Metabolomics is the study of molecules created by cellular metabolic pathways. We hypothesized that the metabolic activity of children with asthma would differ from healthy children without asthma. Furthermore, children having an asthma exacerbation would be different compared with children with stable asthma in outpatient clinics. Finally, we hypothesized that (1)H-nuclear magnetic resonance (NMR) would measure such differences using urine samples, one of the least invasive forms of biofluid sampling. METHODS:Children (135 total, ages 4-16 years) were enrolled, having met the criteria of healthy controls (C), stable asthma in the outpatient clinic (AO), or unstable asthma in the emergency department (AED). Partial least squares discriminant analysis was performed on the NMR data to create models of separation (70 metabolites were measured/urine sample). Some NMR data were withheld from modeling to be run blindly to determine possible diagnostic accuracy. RESULTS: On the basis of the model of AO versus C, 31 of 33 AO samples were correctly diagnosed with asthma (94% accuracy). Only 1 of 20 C samples was incorrectly labeled as asthma (5% misclassification). On the basis of the AO versus AED model, 31 of the 33 AO samples were correctly diagnosed as outpatientasthma (94% accurate). CONCLUSION: This is the first report suggesting that (1)H-NMR analysis of human urine samples has the potential to be a useful clinical tool for physicians treating asthma.
Authors: William Checkley; Maria P Deza; Jost Klawitter; Karina M Romero; Jelena Klawitter; Suzanne L Pollard; Robert A Wise; Uwe Christians; Nadia N Hansel Journal: Respir Med Date: 2016-10-21 Impact factor: 3.415
Authors: Wanxing Eugene Ho; Yong-Jiang Xu; Fengguo Xu; Chang Cheng; Hong Yong Peh; Steven R Tannenbaum; W S Fred Wong; Choon Nam Ong Journal: Am J Respir Cell Mol Biol Date: 2012-11-09 Impact factor: 6.914
Authors: Jeremy K Nicholson; Elaine Holmes; James M Kinross; Ara W Darzi; Zoltan Takats; John C Lindon Journal: Nature Date: 2012-11-15 Impact factor: 49.962