Pharmacometabolomics via real-time breath analysis captures metabotypes of asthmatic children associated with salbutamol responsiveness
Jiafa Zeng,
Jakob Usemann,
Kapil Dev Singh,
Anja Jochmann,
Daniel Trachsel,
Urs Frey,
Pablo Sinues
Affiliations
Jiafa Zeng
Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland
Jakob Usemann
University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland
Kapil Dev Singh
Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland
Anja Jochmann
University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland
Daniel Trachsel
University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland
Urs Frey
Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland; Corresponding author
Pablo Sinues
Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; University Children’s Hospital Basel UKBB, University of Basel, 4056 Basel, Switzerland; Corresponding author
Summary: Asthma is a widespread respiratory disease affecting millions of children. Salbutamol is a well-established bronchodilator available to treat asthma. However, response to bronchodilators is very heterogeneous, particularly in children. Pharmacometabolomics via exhaled breath analysis holds promise for patient stratification. Here, we integrate a real-time breath analysis platform in the workflow of an outpatient clinic to provide a detailed metabolic snapshot of patients with asthma undergoing standard clinical evaluations. We observed significant metabolic changes associated with salbutamol inhalation within ∼1 h. Our data supports the hypothesis that sphingolipid metabolism and arginine biosynthesis mediate the bronchodilator effect of salbutamol. Clustering analysis of 30 metabolites associated with these pathways revealed characteristic metabotypes related to clinical phenotypes of poor bronchodilator responsiveness. We propose that such a metabolic fingerprinting approach may be of utility in clinical practice to quantify response to inhaled medications or asthma outcomes.
