Identification of cough-variant asthma phenotypes based on clinical and pathophysiologic data

Abstract

Cough variant asthma (CVA) may respond differently to anti-asthmatic treatment. There is limited data on the heterogeneity of CVA. We aimed to classify patients with CVA using cluster analysis based on clinico-physiological parameters and to unveil the underlying molecular pathways of these phenotypes with transcriptomic data of sputum cells. K-mean clustering was applied to 342 newly physician-diagnosed patients with CVA from a prospective, multicenter, observational cohort using 10 pre-specified baseline clinic-pathophysiological variables. The clusters were compared based on clinical features, treatment response and sputum transcriptomic data. Three stable CVA clusters were identified. Cluster 1 (n= 176) was characterized by female predominance, late-onset, normal lung function, and a low proportion of complete resolution of cough (60.8%) after anti-asthmatic treatment. Cluster 2 (n=105) presented with young, nocturnal cough, atopy, type 2-high inflammation, and a high proportion of complete resolution of cough (73.3%) with highly upregulated co-expression gene network that related to type 2 immunity. Cluster 3 (n= 61) had a high body mass index, long duration, family history of asthma, low lung function, and low proportion of complete resolution of cough (54.1%). Th17 immunity and type 2 immunity co-expression gene networks were both upregulated in clusters 1 and 3. Three clusters of CVA were identified with different clinical, pathophysiological, and transcriptomic features and responses to anti-asthmatics treatment, which may improve our understanding of pathogenesis and develop individualized treatment of cough in asthma.