Longitudinal trajectories of childhood asthma phenotypes and allergic comorbidities in Korean childhood asthma study (KAS)

초록

Background: Asthma is a heterogeneous airway disease with various clinical phenotypes accompanied with other allergic comorbidities in children. Little is currently known about longitudinal clinical features of asthma and allergic comorbidities in children. The aim of this study was to define and validate clinical asthma phenotypes and other allergic diseases using cohorts of Korean children from their birth to adolescent period. Method: This study enrolled 958 children with physician-diagnosed asthma from the Korean childhood Asthma Study (KAS) cohort. Questionnaires regarding subjects’ baseline characteristics, laboratory tests, pulmonary function and bronchial provocation tests were performed to assess allergy and airway inflammation at the time of enrollment. Children with asthma were classified by hierarchical cluster analysis. Participants’ past medical records of diagnosis and treatments relating asthma, allergic rhinitis (AR), and atopic dermatitis (AD) were acquired from the Health Insurance Review & Assessment Service. Results: Of the 958 patients in the KAS cohort, about half of patients had a history of atopic dermatitis before in infancy, and the prevalence gradually decreased toward adolescence. The prevalence of allergic rhinitis increased in school age as we expected. Among those children, 794 were included in cluster analysis. Four phenotypes were identified in the KAS cohort with distinct clinical trajectories of allergic comorbidities. Cluster 1 was “Male dominant atopic asthma”. Cluster 2 had an “early onset atopic asthma with AD” with persistent AD until adolescence. Cluster 3 was a “Puberty onset female dominant atopic asthma” phenotype with low pulmonary function and low remission rate asthma and progressing AR. Cluster 4 had a “Early onset less atopic asthma” with the lowest comorbidities of AD and AR. Conclusion: Identification of asthma phenotypes and their allergic comorbidities based on baseline cluster analysis may facilitate prediction of prognosis and response to treatment. Clear differentiation of clinical phenotypes can provide better asthma management and prediction of prognosis.