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« Previous AbstractIncreasing analytical space in gas chromatography-differential mobility spectrometry with dispersion field amplitude programming    Next AbstractExhaled volatile organic compounds for phenotyping chronic obstructive pulmonary disease: a cross-sectional study »

Analyst


Title:Non-invasive metabolomic analysis of breath using differential mobility spectrometry in patients with chronic obstructive pulmonary disease and healthy smokers
Author(s):Basanta M; Jarvis RM; Xu Y; Blackburn G; Tal-Singer R; Woodcock A; Singh D; Goodacre R; Thomas CL; Fowler SJ;
Address:"Respiratory Research Group, Manchester Academic Health Science Centre, University of Manchester, Wythenshawe Hospital, Manchester, UK"
Journal Title:Analyst
Year:2010
Volume:20100105
Issue:2
Page Number:315 - 320
DOI: 10.1039/b916374c
ISSN/ISBN:1364-5528 (Electronic) 0003-2654 (Linking)
Abstract:"The rapid, accurate and non-invasive diagnosis of respiratory disease represents a challenge to clinicians, and the development of new treatments can be confounded by insufficient knowledge of lung disease phenotypes. Exhaled breath contains a complex mixture of volatile organic compounds (VOCs), some of which could potentially represent biomarkers for lung diseases. We have developed an adaptive sampling methodology for collecting concentrated samples of exhaled air from participants with impaired respiratory function, against which we employed two-stage thermal desorption gas chromatography-differential mobility spectrometry (GC-DMS) analysis, and showed that it was possible to discriminate between participants with and without chronic obstructive pulmonary disease (COPD). A 2.5 dm(3) volume of end tidal breath was collected onto adsorbent traps (Tenax TA/Carbotrap), from participants with severe COPD and healthy volunteers. Samples were thermally desorbed and analysed by GC-DMS, and the chromatograms analysed by univariate and multivariate analyses. Kruskal-Wallis ANOVA indicated several discriminatory (p < 0.01) signals, with good classification performance (receiver operator characteristic area up to 0.82). Partial least squares discriminant analysis using the full DMS chromatograms also gave excellent discrimination between groups (alpha = 19% and beta = 12.4%)"
Keywords:"Aged Biomarkers/*analysis Breath Tests Exhalation Female Humans Male *Metabolomics Middle Aged Pulmonary Disease, Chronic Obstructive/*diagnosis/*metabolism *Smoking Volatile Organic Compounds/*analysis;"
Notes:"MedlineBasanta, Maria Jarvis, Roger M Xu, Yun Blackburn, Gavin Tal-Singer, Ruth Woodcock, Ashley Singh, Dave Goodacre, Royston Thomas, C L Paul Fowler, Stephen J eng BB/C519038/1/BB_/Biotechnology and Biological Sciences Research Council/United Kingdom Research Support, Non-U.S. Gov't England 2010/01/26 Analyst. 2010 Feb; 135(2):315-20. doi: 10.1039/b916374c. Epub 2010 Jan 5"

 
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