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 â¼1 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.
Pharmacometabolomics via real-time breath analysis captures metabotypes of asthmatic children associated with salbutamol responsiveness.
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作者:Zeng Jiafa, Usemann Jakob, Singh Kapil Dev, Jochmann Anja, Trachsel Daniel, Frey Urs, Sinues Pablo
| 期刊: | iScience | 影响因子: | 4.100 |
| 时间: | 2024 | 起止号: | 2024 Nov 20; 27(12):111446 |
| doi: | 10.1016/j.isci.2024.111446 | ||
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