Phenotyping COPD by 1H NMR metabolomics of exhaled breath condensate

Metabolomics

Volumn 10, Issue 2, 2014, Pages 302-311

  Bertini, Ivano ^a   Luchinat, Claudio ^a   Miniati, Massimo ^b   Monti, Simonetta ^c,d   Tenori, Leonardo ^e  

^a UNIVERSITY OF FLORENCE   (Italy)

^b UNIVERSITY OF FLORENCE   (Italy)

^c INSTITUTE OF CLINICAL PHYSIOLOGY   (Italy)

^d Tuscany Foundation Gabriele Monasterio   (Italy)

^e FiorGen Foundation   (Italy)

Author keywords

Chronic obstructive pulmonary disease; Exhaled breath condensate; Metabolomics; Nuclear magnetic resonance spectroscopy; Phenotyping; Random forest

Indexed keywords

ACETIC ACID; ACETONE; LACTIC ACID; LYSINE; PROLINE; PROPIONIC ACID; SERINE; TYROSINE; VALINE;

ADULT; ARTICLE; CHRONIC OBSTRUCTIVE LUNG DISEASE; CLINICAL ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; EMPHYSEMA; EXPIRED AIR; FEMALE; FORCED EXPIRATORY VOLUME; FORCED VITAL CAPACITY; HUMAN; LIMIT OF DETECTION; LIMIT OF QUANTITATION; MALE; METABOLOMICS; NUCLEAR MAGNETIC RESONANCE; PROTON NUCLEAR MAGNETIC RESONANCE; SENSITIVITY AND SPECIFICITY; SPIROMETRY;

EID: 84921731937     PISSN: 15733882     EISSN: 15733890     Source Type: Journal    
DOI: 10.1007/s11306-013-0572-3     Document Type: Article

References (58)

1. Agusti, A. G., Sauleda, J., Miralles, C., Gomez, C., Togores, B., Sala, E., et al. (2002). Skeletal muscle apoptosis and weight loss in chronic obstructive pulmonary disease. American Journal of Respiratory and Critical Care Medicine,166, 485–489.
2. Aranjbar, N., Ott, K. H., Roongta, V., & Mueller, L. (2006). Metabolomic analysis using optimized NMR and statistical methods. Analytical Biochemistry,355, 62–70.
3. Assfalg, M., Bertini, I., Colangiuli, D., Luchinat, C., Schafer, H., Schutz, B., et al. (2008). Evidence of different metabolic phenotypes in humans. Proceedings of the National Academy of Sciences of the United States of America,105, 1420–1424.
4. Barnes, P. J., Chowdhury, B., Kharitonov, S. A., Magnussen, H., Page, C. P., Postma, D., et al. (2006). Pulmonary biomarkers in chronic obstructive pulmonary disease. American Journal of Respiratory and Critical Care Medicine,174, 6–14.
5. Baumann, K. (2010). Cross-validation is dead. Long live cross-validation! Model validation based on resampling. Journal of Cheminformatics,. doi:10.1186/1758-2946-2-S1-O5.
6. Bensel, T., Stotz, M., Borneff-Lipp, M., Wollschlager, B., Wienke, A., Taccetti, G., et al. (2011). Lactate in cystic fibrosis sputum. Journal of Cystic Fibrosis,10, 37–44.
7. Bertini, I., Cacciatore, S., Jensen, B. V., Schou, J. V., Johansen, J. S., Kruhoffer, M., et al. (2012). Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Research,72, 356–364.
8. Bertini, I., Calabro, A., De Carli, V., Luchinat, C., Nepi, S., Porfirio, B., et al. (2009). The metabonomic signature of celiac disease. Journal of Proteome Research,8, 170–177.
9. Bertram, H. C., Eggers, N., & Eller, N. (2009). Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification. Analytical Chemistry,81, 9188–9193.
10. Bofan, M., Mores, N., Baron, M., Dabrowska, M., Valente, S., Schmid, M., et al. (2013). Within-day and between-day repeatability of measurements with an electronic nose in patients with COPD. Journal of Breath Research,7(1), 017103.
11. Borrill, Z. L., Roy, K., & Singh, D. (2008). Exhaled breath condensate biomarkers in COPD. European Respiratory Journal,32, 472–486.
12. Borrill, Z. L., Starkey, R. C., & Singh, S. D. (2007). Variability of exhaled breath condensate leukotriene B4 and 8-isoprostane in COPD patients. International Journal of Chronic Obstructive Pulmonary Disease,2, 71–76.
13. Breiman, L. (2001). Random forests. Machine Learning,45, 5–32.
14. Carraro, S., Rezzi, S., Reniero, F., Heberger, K., Giordano, G., Zanconato, S., et al. (2007). Metabolomics applied to exhaled breath condensate in childhood asthma. American Journal of Respiratory and Critical Care Medicine,175, 986–990.
15. Cerveri, I., Corsico, A. G., Grosso, A., Albicini, F., Ronzoni, V., Tripon, B., et al. (2013). The rapid FEV(1) decline in chronic obstructive pulmonary disease is associated with predominant emphysema: A longitudinal study. Journal of Chronic Obstructive Pulmonary Disease, 10, 55–61.
16. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Mahwah: L. Erlbaum Associates.
17. De Jong, S. (1993). SIMPLS: An alternative approach to partial least-squares regression. Chemometrics and Intelligent Laboratory Systems,18, 251–263.
18. de Laurentiis, G., Paris, D., Melck, D., Maniscalco, M., Marsico, S., Corso, G., et al. (2008). Metabonomic analysis of exhaled breath condensate in adults by nuclear magnetic resonance spectroscopy. European Respiratory Journal,32, 1175–1183.
19. DeMeo, D. L., Hersh, C. P., Hoffman, E. A., Litonjua, A. A., Lazarus, R., Sparrow, D., et al. (2007). Genetic determinants of emphysema distribution in the national emphysema treatment trial. American Journal of Respiratory and Critical Care Medicine,176, 42–48.
20. 1H NMR metabonomics. Analytical Chemistry,78, 4281–4290.
21. 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: The INTERMAP study. Analytical Chemistry,78, 2199–2208.
22. Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics,7, 179–188.
23. Franklin, P., Moeller, A., Hall, G. L., Horak, F, Jr, Patterson, H., & Stick, S. M. (2006). Variability of nitric oxide metabolites in exhaled breath condensate. Respiratory Medicine,100, 123–129.
24. Horvíth, I., Hunt, J., Barnes, P. J., & On behalf of the ATS/ERS Task Force on Exhaled Breath Condensate. (2005). Exhaled breath condensate: methodological recommendations and unresolved questions. European Respiratory Journal,26, 523–548.
25. Hurst, J. R., Vestbo, J., Anzueto, A., Locantore, N., Mullerova, H., Tal-Singer, R., et al. (2010). Susceptibility to exacerbation in chronic obstructive pulmonary disease. New England Journal of Medicine,363, 1128–1138.
26. Izquierdo-Garcia, J. L., Peces-Barba, G., Heili, S., Diaz, R., Want, E., & Ruiz-Cabello, J. (2011). Is NMR-based metabolomic analysis of exhaled breath condensate accurate? European Respiratory Journal,37, 468–470.
27. Lanza, I. R., Zhang, S., Ward, L. E., Karakelides, H., Raftery, D., & Nair, K. S. (2010). Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes. PLoS One,5, e10538.
28. Lucidi, V., Ciabattoni, G., Bella, S., Barnes, P. J., & Montuschi, P. (2008). Exhaled 8-isoprostane and prostaglandin E2 in patients with stable and unstable cystic fibrosis. Free Radical Biology and Medicine,45, 913–919.
29. 1H-NMR reveals differences between chronic lymphocytic leukaemia molecular subgroups. Leukemia,24, 788–797.
30. Malerba, M., & Montuschi, P. (2012). Non-invasive biomarkers of lung inflammation in smoking subjects. Current Medicinal Chemistry,19, 187–196.
31. Mannino, D. M., Homa, D. M., Akinbami, L. J., Ford, E. S., & Redd, S. C. (2002). Chronic obstructive pulmonary disease surveillance—United States, 1971–2000. Respiratory Care,47, 1184–1199.
32. Miller, M. R., Hankinson, J., Brusasco, V., Burgos, F., Casaburi, R., Coates, A., et al. (2005). Standardisation of spirometry. European Respiratory Journal,26, 319–338.
33. Miniati, M., Catapano, G. A., Monti, S., Mannucci, F., & Bottai, M. (2013). Effects of emphysema on oxygen uptake during maximal exercise in COPD. Internal and Emergency Medicine, 8, 41–47.
34. Miniati, M., Monti, S., Stolk, J., Mirarchi, G., Falaschi, F., Rabinovich, R., et al. (2008). Value of chest radiography in phenotyping chronic obstructive pulmonary disease. European Respiratory Journal,31, 509–515.
35. Montuschi, P. (2009). LC/MS/MS analysis of leukotriene B4 and other eicosanoids in exhaled breath condensate for assessing lung inflammation. Journal of Chromatography B,877, 1272–1280.
36. Montuschi, P. (2010). Toward a personalized pharmacotherapy of respiratory diseases. Frontiers in Pharmacology,1, 131.
37. Montuschi, P., Currò, D., Ragazzoni, E., Preziosi, P., & Ciabattoni, G. (1999). Anaphylaxis increases 8-iso-prostaglandin Fα release from guinea-pig lung in vitro. European Journal of Pharmacology,365, 59–64.
38. Montuschi, P., Mores, N., Trove, A., Mondino, C., & Barnes, P. J. (2013). The electronic nose in respiratory medicine. Respiration,85, 72–84.
39. Montuschi, P., Paris, D., Melck, D., Lucidi, V., Ciabattoni, G., Raia, V., et al. (2012). NMR spectroscopy metabolomic profiling of exhaled breath condensate in patients with stable and unstable cystic fibrosis. Thorax,67, 222–228.
40. Motta, A., Paris, D., Melck, D., de Laurentiis, G., Maniscalco, M., Sofia, M., et al. (2012). Nuclear magnetic resonance-based metabolomics of exhaled breath condensate: methodological aspects. European Respiratory Journal,39, 498–500.
41. Nicholson, J. K., & Lindon, J. C. (2008). Systems biology: Metabonomics. Nature,455, 1054–1056.
42. Nicholson, J. K., Lindon, J. C., & Holmes, E. (1999). ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica,29, 1181–1189.
43. Oakman, C., Tenori, L., Biganzoli, L., Santarpia, L., Cappadona, S., Luchinat, C., et al. (2010). Uncovering the metabolomic fingerprint of breast cancer. International Journal of Biochemistry and Cell Biology,43(7), 1010–1020.
44. Pers, T. H., Albrechtsen, A., Holst, C., Sorensen, T. I., & Gerds, T. A. (2009). The validation and assessment of machine learning: A game of prediction from high-dimensional data. PLoS One,4, e6287.
45. Rabe, K. F., Hurd, S., Anzueto, A., Barnes, P. J., Buist, S. A., Calverley, P., et al. (2007). Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. American Journal of Respiratory and Critical Care Medicine,176, 532–555.
46. Saetta, M., Kim, W. D., Izquierdo, J. L., Ghezzo, H., & Cosio, M. G. (1994). Extent of centrilobular and panacinar emphysema in smokers’ lungs: pathological and mechanical implications. European Respiratory Journal,7, 664–671.
47. Saude, E., Adamko, D., Rowe, B., Marrie, T., & Sykes, B. (2007). Variation of metabolites in normal human urine. Metabolomics,3, 439–451.
48. 1H-NMR-based metabolomics. Expert Review of Molecular Diagnostics,6, 717–731.
49. Shockcor, J. P., & Holmes, E. (2002). Metabonomic applications in toxicity screening and disease diagnosis. Current Topics in Medicinal Chemistry,2, 35–51.
50. Slupsky, C. M., Rankin, K. N., Wagner, J., Fu, H., Chang, D., Weljie, A. M., et al. (2007). Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles. Analytical Chemistry,79, 6995–7004.
51. Sreekumar, A., Poisson, L. M., Rajendiran, T. M., Khan, A. P., Cao, Q., Yu, J., et al. (2009). Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature,457, 910–914.
52. Sutinen, S., Christofordis, A. J., Klough, G. A., & Pratt, P. C. (1965). Roentgenologic criteria for the recognition of nonsymptomatic pulmonary emphysema. Correlation between roentgenologic findings and pulmonary pathology. American Review of Respiratory Disease,91, 69–76.
53. Szymanska, E., Saccenti, E., Smilde, A., & Westerhuis, J. (2011). Double-check: Validation of diagnostic statistics for PLS-DA models in metabolomics studies. Metabolomics,8(Suppl 1), 3–16.
54. Ubhi, B. K., Riley, J. H., Shaw, P. A., Lomas, D. A., Tal-Singer, R., MacNee, W., et al. (2012). Metabolic profiling detects biomarkers of protein degradation in COPD patients. European Respiratory Journal,40, 345–355.
55. Vapnik, V. N. (1995). The nature of statistical learning theory. New York: Springer-Verlag.
56. Vestbo, J., Edwards, L. D., Scanlon, P. D., Yates, J. C., Agusti, A., Bakke, P., et al. (2011). Changes in forced expiratory volume in 1 s over time in COPD. New England Journal of Medicine,365, 1184–1192.
57. Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., et al. (2008). Assessment of PLSDA cross validation. Metabolomics,4, 81–89.
58. Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., et al. (2007). HMDB: The human metabolome database. Nucleic Acids Research,35, D521–D526.