title: Overcoming heterogeneity in pediatric asthma: tobacco smoke and asthma characteristics within phenotypic clusters in an African American cohort.
abstract: OBJECTIVE
  Asthma in children and adolescents is a heterogeneous syndrome comprised of multiple subgroups with variable disease expression and response to environmental exposures. The goal of this study was to define homogeneous phenotypic clusters within a cohort of children and adolescents with asthma and to determine overall and within-cluster associations between environmental tobacco smoke (ETS) exposure and asthma characteristics.
  
  
  METHODS
  A combined hierarchical/k-means cluster analysis of principal component variables was used to define phenotypic clusters within a cohort of 6- to 20-year-old urban and largely minority subjects.
  
  
  RESULTS
  Among the 154 subjects, phenotypic cluster analysis defined three independent clusters (Cluster 1 [n = 57]; Cluster 2 [n = 33]; Cluster 3 [n = 58]). A small fourth cluster (n = 6) was excluded. Patients in Cluster 1 were predominantly males, with a relative abundance of neutrophils in their nasal washes. Patients in Cluster 2 were predominantly females with high body mass index percentiles and later-onset asthma. Patients in Cluster 3 had higher eosinophil counts in their nasal washes and lower Asthma Control Test (ACT) scores. Within-cluster regression analysis revealed several significant associations between ETS exposure and phenotypic characteristics that were not present in the overall cohort. ETS exposure was associated with a significant increase in nasal wash neutrophils (beta coefficient = 0.73 [95% confidence interval, CI: 0.11 to 1.35]; p = .023) and a significant decrease in ACT score (-5.17 [-8.42 to -1.93]; p = .003) within Cluster 1 and a significant reduction in the bronchodilator-induced % change in forced expiratory volume in one second (FEV(1)) (-36.32 [-62.18 to -10.46]; p = .009) within Cluster 3.
  
  
  CONCLUSIONS
  Clustering techniques defined more homogeneous subgroups, allowing for the detection of otherwise undetectable associations between environmental tobacco smoke exposure and asthma characteristics.
authors.affiliation: Genomics and Bioinformatics Program, Columbian College of Arts and Sciences, George Washington University, and Children’s National Medical Center,Washington, D.C., U.S.A.
authors.forename: Angela S
authors.initials: AS
authors.lastname: Benton
authors.forename: Zuyi
authors.initials: Z
authors.lastname: Wang
authors.forename: Jennifer
authors.initials: J
authors.lastname: Lerner
authors.forename: Matthew
authors.initials: M
authors.lastname: Foerster
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Teach
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Freishtat
mesh_terms: D000293:Adolescent; D000328:Adult; D001741:Black or African American; D001249:Asthma / Q000208:ethnology / Q000209:etiology*; D002648:Child; D016000:Cluster Analysis; D015331:Cohort Studies; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D008297:Male; D010641:Phenotype; D025341:Principal Component Analysis; D014028:Tobacco Smoke Pollution / Q000009:adverse effects*
chemical_list: D014028:Tobacco Smoke Pollution