RT Journal Article
SR Electronic
T1 Unbiased clustering of children with asthma or pre-school wheeze using the U-BIOPRED electronic nose platform
JF European Respiratory Journal
JO Eur Respir J
FD European Respiratory Society
SP 431
VO 44
IS Suppl 58
A1 P. Brinkman
A1 S. Hashimoto
A1 L.J. Fleming
A1 G. Hedlin
A1 H. Knobel
A1 T.J. Vink
A1 N. Rattray
A1 M. Santonico
A1 G. Pennazza
A1 A. D'Amico
A1 P. Montuschi
A1 S. Fowler
A1 J. Corfield
A1 A. Rowe
A1 P.F Singer
A1 U. Frey
A1 H. Bisgaard
A1 A. Bush
A1 S.S. Wagers
A1 K.F. Chung
A1 D.E. Shaw
A1 I. Pandis
A1 C. Compton
A1 W. Siebold
A1 A.T. Bansal
A1 G. Roberts
A1 W.M. van Aalderen
A1 P.J. Sterk
A1 U-BIOPRED study group
YR 2014
UL http://erj.ersjournals.com/content/44/Suppl_58/431.abstract
AB Rationale: Children with asthma or pre-school wheeze represent a heterogeneous group, characterized by a variety of underlying pathophysiological molecular mechanisms. Recent 'omics' technologies provide composite molecular samples in inflammatory airway diseases [Wheelock ERJ 2013]. This includes breathomics, non-invasive metabolomics in exhaled air.Aim: To reveal phenotypes by unbiased cluster analysis based on metabolomic fingerprints from exhaled breath by electronic nose (eNose) in children with asthma or pre-school wheeze.Methods: This was a cross-sectional analysis from a subset of the paediatric U-BIOPRED cohort. Exhaled volatile organic compounds trapped on adsorption tubes were analyzed by an centralized eNose platform [Brinkman ERS 2012 A4307]. Ward clustering based on Similarity Profile Analysis [Clarke JEMBE 2008] was performed on eNose platform data, followed by ANOVA and chi-square tests.Results: 106 children were included (age (IQR)7.6 (4.0-13.0)yrs, 62% male, skin prick test (SPT) positive 54%). Five clusters were delineated that differed significantly regarding age, asthma control, asthma related quality of life, SPT.View this table:Conclusion: In this preliminary analysis, unbiased fingerprinting by eNose provides clinical clusters of children with asthma or pre-school wheeze. This suggests that metabolomics in exhaled air is suitable for phenotyping of airways disease in childhood.