1Department of Gastroenterology, Imperial College Healthcare NHS Trust, St Mary's Hospital, London W2 1NY United Kingdom.
2Department of Surgery and Cancer, Imperial College London, 10 Floor QEQM Wing, St Mary's Hospital, London W2 1NY United Kingdom.
3Department of Surgery and Cancer, Imperial College London, 10 Floor QEQM Wing, St Mary's Hospital, London W2 1NY United Kingdom firstname.lastname@example.org.
Background and Aims: Distinguishing between the inflammatory bowel diseases (IBD), Crohn's disease (CD) and ulcerative colitis (UC), is important for determining management and prognosis. Selected ion flow tube mass spectrometry (SIFT-MS) may be used to analyse volatile organic compounds (VOCs) in exhaled breath: these may be altered in disease states, and distinguishing breath VOC profiles can be identified. The aim of this pilot study was to identify, quantify and analyse VOCs present in the breath of IBD patients and controls, potentially providing insights into disease pathogenesis and complementing current diagnostic algorithms.Methods: SIFT-MS breath profiling of 56 individuals (20 UC, 18 CD and 18 healthy controls) was undertaken. Multivariate analysis included principal components analysis (PCA) and partial least squares discriminant analysis with orthogonal signal correction (OSC-PLS-DA). Receiver Operator Characteristic (ROC) analysis was performed for each comparative analysis using statistically significant VOCs.Results: OSC-PLS-DA modelling was able to distinguish both CD and UC from healthy controls and from one other with good sensitivity and specificity. ROC analysis using combinations of statistically significant VOCs (dimethyl sulphide, hydrogen sulphide, hydrogen cyanide, ammonia, butanal and nonanal) gave integrated areas under the curve (AUC) of 0.86 (CD vs healthy controls), 0.74 (UC vs healthy controls) and 0.83 (CD vs UC).Conclusions: Exhaled breath VOC profiling was able to distinguish IBD patients from controls, as well as separate UC from CD, using both multivariate and univariate statistical techniques.