Two novel, severe asthma phenotypes identified during childhood using a clustering approach

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Abstract
Unsupervised cluster analysis has already been used to identify severe phenotypes of childhood asthma, but without taking into account inflammatory markers. The aim of this study was to define independent homogeneous phenotypic clusters of severe asthma in a cohort of asthmatic children.Cluster analysis was applied to 19 variables from 315 children enrolled in the Trousseau Asthma Program in Paris, France.Three independent clusters of asthma were identified. Cluster 1, asthma with severe exacerbations and multiple allergies: 103 children had more sensitisations to inhaled allergens and food allergens, more blood eosinophils and basophils, more uncontrolled asthma despite high doses of inhaled corticosteroid and more hospitalisations for exacerbation. Cluster 2, severe asthma with bronchial obstruction: 72 children were significantly older, had the highest body mass index, a lower forced expiratory volume in 1 s, more pronounced blood neutrophils and significantly higher levels of all classes of immunoglobulin (Ig), except IgE. Cluster 3, mild asthma: 140 children did not show statistically significant features.These results could lead to improved management of severe asthma in children by optimising treatment strategies,i.e.anti-allergic drugs, such as anti-IgE for children with the allergic phenotype, and anti-neutrophil drugs, such as macrolides for those with the obstructive phenotype.