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Experimental Biology 2010: Overcoming Heterogeneity In Pediatric Asthma: Tobacco Smoke And Asthma Characteristics Within Phenotypic Clusters
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Overcoming Heterogeneity In Pediatric Asthma: Tobacco Smoke And Asthma Characteristics Within Phenotypic Clusters
A.S. Benton1, Z. Wang1,2, J. Lerner1, M. Foerster1, S.J. Teach1,2, R.J. Freishtat1,2; 1. Children's National Medical Center, Washington, DC2. George Washington University School of Medicine and Health Sciences, Washington, DC
Purpose of Study: Asthma is a heterogeneous syndrome comprised of multiple poorly defined subgroups with variable disease expression and response to environmental exposures. We sought to define homogeneous phenotypic clusters within pediatric asthma and to determine overall and within-cluster associations between environmental tobacco smoke (ETS) exposure and asthma characteristics. Methods Used: A combined hierarchical/k-means cluster analysis of principal component variables was used to define phenotypic clusters within a cohort (n = 100) of 6 to 20 year-old urban and largely minority subjects with asthma. Summary of Results: Phenotypic cluster analysis defined three independent clusters within the cohort. Three individuals grouped into a very small fourth cluster and were ultimately excluded. Several characteristics defined the three remaining clusters. Of note, patients in Cluster 1 (n = 53) showed an abundance of nasal neutrophils (46%) relative to Clusters 2 and 3 (20% and 28%; P = 0.025). Patients in Cluster 2 (n = 23) were predominantly female (61% versus 26% and 48% in clusters 1 and 3, respectively; P < 0.001) with higher body mass index (BMI) percentile (90% versus 62% and 66%; P < 0.001) and later-onset asthma (7.1 years versus 2.0 and 1.2 years; P < 0.001). Patients in Cluster 3 (n = 21) had an allergic phenotype with an increased proportion of nasal eosinophils (65% versus 35% and 58% in clusters 1 and 2, respectively; P = 0.007) and inferior mean Asthma Control Test (ACT) scores (16.1 versus 22.4 and 20.6; P < 0.001). Within-cluster regression analysis revealed several significant associations that were not present in the overall cohort. For example, ETS exposure was associated with a significant reduction in the bronchodilator-induced change in FEV1 (Beta Coefficient = -3.23 [95%CI: -6.10 to -0.35]; P = 0.029) within Cluster 1 and a significantly increased National Asthma Education and Prevention Program (NAEPP) severity classification (B = 1.12 [0.11 to 2.13]; P = 0.030) within Cluster 2. Conclusions: Clustering techniques were used in this study to define more homogeneous subgroups allowing for the detection of otherwise undetectable associations between ETS and asthma characteristics.
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