B RINDLISBACHER¹, C STREBEL², S GULER³, T GEISER³, C BOVET¹, M FUNKE<sup>3

1</sup>Clinical Metabolomics Facility, University Institute of Clinical Chemistry, Inselspital, Bern University Hospital, Bern, Switzerland, ²Internal Medicine, Spital STS AG, Zweisimmen, Switzerland, ³Pulmonary Medicine, Inselspital, Bern University Hospital, Bern, Switzerland

Idiopathic pulmonary fibrosis (IPF) is a fast progressing lung disease causing fatal respiratory failure. IPF diagnosis and monitoring remains a challenge as limited indicators for disease progression exist. Sampling of exhaled breath condensate (EBC) holds great potential for diagnosis and monitoring of the disease as the material is easily and non-invasively collected. However, biomarkers found in EBC are difficult to identify due to low metabolite concentrations and methodological limitations. The aim of this study was to identify discriminatory metabolic profiles in EBC between IPF patients and healthy controls (n=10) using ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-MS). Additionally, intra-day and inter-day variability of EBC metabolic profiles were assessed in three subjects. An in-house established bioinformatics pipeline was applied for data processing and analysis. Principal component analysis (PCA) and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) were used to identify discriminative metabolites between IPF and controls. In total, 31 potential metabolites were found to be discriminative between IPF and controls (FDR corrected Mann-Whitney q-value ≤0.05). Changes up to 5-fold were observed and the majority of the discriminative metabolites (84%) were down-regulated in IPF compared to controls. Even though the results require confirmation in a larger cohort, non-targeted metabolic profiling by UHPLC-MS of EBC exhibits great potential to improve diagnosis and monitoring of IPF patients and therefore deserves further exploration.