4.7 Article

Metabolomic profiling of asthma: Diagnostic utility of urine nuclear magnetic resonance spectroscopy

期刊

JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
卷 127, 期 3, 页码 757-U408

出版社

MOSBY-ELSEVIER
DOI: 10.1016/j.jaci.2010.12.1077

关键词

Asthma; inflammation; biomarkers; urine; NMR; metabolomics

资金

  1. Sick Kids Foundation
  2. AllerGen
  3. Magnetic Resonance Diagnostic Centre (MRDC)
  4. Canadian Institutes for Health Research (CIHR)
  5. Genome Prairie
  6. Genome Canada
  7. AHFMR
  8. Canadian National High Field NMR Centre
  9. Natural Science and Engineering Research Council of Canada
  10. University of Alberta Hospital Foundation
  11. Alberta Science and Research Authority, and Western Economic Development
  12. Government of Canada (Ottawa, Ontario)
  13. GlaxoSmithKline
  14. MedImmune
  15. Canadian Institutes of Health Research
  16. Afexa
  17. Merck

向作者/读者索取更多资源

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 H-1-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 H-1-NMR analysis of human urine samples has the potential to be a useful clinical tool for physicians treating asthma. (J Allergy Clin Immunol 2011;127:757-64.)

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