Heterogeneity of severe asthma in childhood: confirmation by cluster analysis of children in the National Institutes of Health/National Heart, Lung, and Blood Institute Severe Asthma Research Program

Abstract

Background: Asthma in children is a heterogeneous disorder with many phenotypes. Although unsupervised cluster analysis is a useful tool for identifying phenotypes, it has not been applied to school-age children with persistent asthma across a wide range of severities.

Objectives: This study determined how children with severe asthma are distributed across a cluster analysis and how well these clusters conform to current definitions of asthma severity.

Methods: Cluster analysis was applied to 12 continuous and composite variables from 161 children at 5 centers enrolled in the Severe Asthma Research Program.

Results: Four clusters of asthma were identified. Children in cluster 1 (n = 48) had relatively normal lung function and less atopy. Children in cluster 2 (n = 52) had slightly lower lung function, more atopy, and increased symptoms and medication use. Cluster 3 (n = 32) had greater comorbidity, increased bronchial responsiveness, and lower lung function. Cluster 4 (n = 29) had the lowest lung function and the greatest symptoms and medication use. Predictors of cluster assignment were asthma duration, the number of asthma controller medications, and baseline lung function. Children with severe asthma were present in all clusters, and no cluster corresponded to definitions of asthma severity provided in asthma treatment guidelines.

Conclusion: Severe asthma in children is highly heterogeneous. Unique phenotypic clusters previously identified in adults can also be identified in children, but with important differences. Larger validation and longitudinal studies are needed to determine the baseline and predictive validity of these phenotypic clusters in the larger clinical setting.

Figure 1

(A) Frequency of children with mild, moderate and severe asthma defined by NAEPP or GINA guidelines and (B) frequency of children with mild-to-moderate and severe asthma defined by ATS criteria in each cluster (Cluster 1, black bars; Cluster 2, white bars; Cluster 3, gray bars; Cluster 3, hatched bars).

Figure 2

Scatterplot of the discriminant functions generated from discriminant analysis of asthma duration, the extent of asthma controller therapy, and baseline FEV₁ percent predicted values. Each data point represents a single subject. The plot depicts clustering and separation of Cluster 1 (white triangles), Cluster 2 (gray circles), Cluster 3 (black squares), and Cluster 4 (white diamonds) using these three variables.