Metabolite-Based Endotypes of Asthma Reveal Distinct Clinical Characteristics and Immune Cell Signatures.

Abstract

Asthma control is commonly defined by symptom burden and recent exacerbation history. However, symptom-based clinical stability does not necessarily reflect biological quiescence, and heterogeneity in lung function and airway structure may persist despite apparent clinical control. This study aimed to determine whether blood-based metabolomic profiling can discriminate biologically distinct subgroups within a clinically stable asthma population. We conducted a prospective observational study of adults with clinically stable asthma, defined by sustained symptom control and absence of recent exacerbations under maintenance inhaled corticosteroid-based therapy. Untargeted plasma metabolomic profiling was performed using liquid chromatography-tandem mass spectrometry, and metabolite-derived subgroups were identified by consensus clustering. Lung function, airway structure, small-airway physiology, and peripheral immune cell profiles were compared across clusters, with associations assessed using regression analyses. Three metabolite-derived subgroups were identified based on patterns in the relative abundance of selected representative metabolites. Symptom control and exacerbation history were comparable across clusters, whereas lung function, airway wall thickness, small-airway physiology, and immune cell profiles differed substantially. Cluster 1 (C1; Remodeling-prone), characterized by greater relative abundance of glycerophospholipid-related metabolites, showed lower post-bronchodilator FEV₁, thicker airway walls, and increased innate lymphoid cells. Cluster 2 (C2; Biologically stable) had preserved airway structure, with thinner airway walls and higher post-bronchodilator FEV₁. Cluster 3 (C3; T2-high) exhibited metabolite patterns associated with type 2 inflammatory features, including higher FeNO levels and blood eosinophil counts, while maintaining preserved airway structure. Metabolomic profiling reveals biologically distinct subgroups among clinically stable asthma, indicating that symptom-based stability does not necessarily reflect biological homogeneity.