TY - JOUR T1 - Urinary metabolomics-based molecular sub-phenotyping of the U-BIOPRED asthma cohort JF - European Respiratory Journal JO - Eur Respir J DO - 10.1183/1393003.congress-2017.PA4939 VL - 50 IS - suppl 61 SP - PA4939 AU - Craig Wheelock AU - Shama Naz AU - Stacey Reinke AU - Romanas Chaleckis AU - James Schofield AU - Paul Skipp AU - Jeanette Bigler AU - Matthew Loza AU - Fred Baribaud AU - Per Bakke AU - Massimo Caruso AU - Pascal Chanez AU - Stephen Fowler AU - Kiss Horvath AU - Norbert Krug AU - Paolo Montuschi AU - Marek Sanak AU - Thomas Sandstrom AU - Dominick Shaw AU - Fan Chung AU - Ratko Djukanovic AU - Florian Singer AU - Ana Sousa AU - Ioannis Pandis AU - Aruna Bansal AU - Peter Sterk AU - Sven-Erik Dahén AU - the U-BIOPRED Study Group Y1 - 2017/09/01 UR - http://erj.ersjournals.com/content/50/suppl_61/PA4939.abstract N2 - Introduction: Asthma is heterogeneous disease consisting of multiple sub-phenotypes that are poorly definedAim: To investigate the utility of the urinary metabolome to identify sub-phenotypes of severe asthma via molecular phenotypingMethods: Spot urine was collected from healthy controls (HC, n=108), mild-to-moderate asthmatics (MMA, n=87), severe asthmatics (SA); including both non-smokers (SAns, n=310) and smokers (SAs, n=108) from the U-BIOPRED cohort (Shaw et al, Eur Respir J. 2015; 46:1308). Metabolomics data were acquired using liquid chromatography coupled to mass spectrometry. Data were analysed using Principal Components–Canonical Variate Analysis (PC-CVA), topological data analysis (TDA), and hierarchical clustering.Results: 90 metabolites were conclusively identified, of which 44 were significantly altered with asthma (FDR<0.05). PC-CVA modeling showed that HC and MMA differed significantly from all SA (p=1.4x10-14), and that SAns differed significantly from SAs (p=0.003). Hierarchical clustering of metabolomics data identified 7 sub-groups characterized by shifts in sputum cell counts (p<0.05). Pathway enrichment analysis identified the tryptophan pathway to be dysregulated with asthma (FDR=0.007). Blood tryptophan dehydrogenase mRNA levels were elevated in SA (p=0.0007), corresponding with increased levels of urinary serotonin (FDR<0.0001). TDA analysis of blood transcriptome data identified 9 clusters that demonstrated significant dysregulation of mRNAs of enzymes involved in tryptophan metabolism.Conclusions: SA evidence an altered urinary metabolic profile relative to HC. These shifts are associated with tryptophan metabolism, which may represent a useful strategy for sub-phenotyping asthma. ER -