posted on 2019-05-07, 13:20authored byM Soares, E Mirgorodskaya, H Koca, E Viklund, M Richardson, P Gustafsson, A-C Olin, S Siddiqui
RATIONALE: Asthma is often characterised by inflammation, damage and dysfunction of the small airways, but no standardised biomarkers are available. OBJECTIVES: Using a novel approach-particles in exhaled air (PExA)-we sought to (a) sample and analyse abundant protein biomarkers: surfactant protein A (SPA) and albumin in adult asthmatic and healthy patients and (b) relate protein concentrations with physiological markers using phenotyping. METHODS: 83 adult asthmatics and 21 healthy volunteers were recruited from a discovery cohort in Leicester, UK, and 32 adult asthmatics as replication cohort from Sweden. Markers of airways closure/small airways dysfunction were evaluated using forced vital capacity, impulse oscillometry and multiple breath washout. SPA/albumin from PEx (PExA sample) were analysed using ELISA and corrected for acquired particle mass. Topological data analysis (TDA) was applied to small airway physiology and PExA protein data to identify phenotypes. RESULTS: PExA manoeuvres were feasible, including severe asthmatic subjects. TDA identified a clinically important phenotype of asthmatic patients with multiple physiological markers of peripheral airway dysfunction, and significantly lower levels of both SPA and albumin. CONCLUSION: We report that the PExA method is feasible across the spectrum of asthma severity and could be used to identify small airway disease phenotypes.
Funding
Supported by an unrestricted grant from the Chiesi Onulus Foundation (Validation of Particle in Exhaled Air (PEx) as a Novel Matrix for Non-Invasive Detection of Small Airways Disease in Asthma) and additional support from the Leicester National Institute for Health Research (NIHR) Biomedical Research Centre: Respiratory Theme. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
The authors would like to thank Ayasdi (Menlo Park, California) and Dr Devi Ramanan for access to the Ayasdi CORE and Python SDK platforms for data analysis.
History
Citation
J Breath Res, 2018, 12 (4), pp. 046012-?
Author affiliation
/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Infection, Immunity and Inflammation
Version
AM (Accepted Manuscript)
Published in
J Breath Res
Publisher
IOP Publishing, International Association for Breath Research (IABR), International Society for Breath Odor Research (ISBOR)
The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.