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Multidimensional Assessment of Asthma Identifies Clinically Relevant Phenotype Overlap: A Cross-Sectional Study
Yu Yu Han1, Xin Zhang1, Ji Wang1
1Pneumology Group, Department of Integrated Traditional Chinese and Western Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Pneumology Group, Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Laboratory of Pulmonary Immunology and Inflammation, Frontiers Science Center for Disease-related Molecular Network, Sichuan University, Chengdu, Sichuan, China.
Background:
Asthma is a heterogeneous disease with multiple phenotypes; however, the relevance of phenotype overlap remains largely unexplored.
Objective:
To examine the relationship between phenotype overlap and clinical and inflammatory profiles of asthma.
Methods:
In this cross-sectional study, adult participants with stable asthma (n = 522) underwent multidimensional assessments. The 10 most common phenotypes of asthma were defined and then classified into those commonly associated with Type (T) 2 or non-T2 inflammation. Furthermore, phenotype overlap scores (POS), representing the cumulative concomitant phenotypes, were used to analyze its association with clinical and inflammatory asthmatic profiles.
Results:
Among the 522 participants, 73.4% (n = 383) had phenotype overlap, and mixed T2 and non-T2 inflammation coexisted in 47.5% (n = 248). T2 POS was positively associated with eosinophils, IgE, and fractional exhaled nitric oxide (FeNO), and negatively with Asthma Quality of Life Questionnaire (AQLQ), sputum neutrophils, IL-17A, IL-8, and TNF-α. Non-T2 POS was positively associated with Asthma Control Questionnaire, neutrophils and sputum IL-8, and negatively with AQLQ, forced expiratory volume in 1 s, blood eosinophils, IgE, and FeNO (all P < .05). Patients with phenotypes that are associated with mixed T2 and non-T2 inflammation had elevated T2 inflammation biomarkers but worse asthma control. Both T2 (adjusted β = -0.191, P = .035) and non-T2 (adjusted β = 0.310, P < .001) POS were significantly associated with severe exacerbations.
Conclusions:
Phenotype overlap is extremely common in asthmatic patients and significantly associated with clinical and inflammatory profiles. Patients with phenotypes associated with mixed T2 and non-T2 inflammation might be unresponsive to medications owing to increased non-T2 inflammation. Multidimensional asthma assessment identifies clinically relevant phenotype overlap.
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