Novel severe wheezy young children phenotypes: Boys atopic multiple-trigger and girls nonatopic uncontrolled wheeze

Asthma phenotypes in childhood: conceptual thoughts on stability and transition

“…Other studies have also shown a strong association between atopy and asthma persistence, as reflected by the atopic asthma group in the present study [5,14]. Nonatopic asthma has resulted as a separate entity in some previous analyses [7,9,12]. In the two Leicestershire cohort studies, this entity was poorly replicated across the two cohorts [8], perhaps because it is characterised by a lot of transitions to the asymptomatic group, as the present study shows.…”

“…In fact, clustering studies that have used cross-sectional data [9][10][11][12][13] take a middle ground between these positions. These studies seek to identify phenotypes that optimally characterise the differences between children in a given age interval.…”

“…Inevitably, different phenotypes will result for different age intervals (deviation from the second viewpoint) and, within the same cohort, children will not be classified into the same groups as they grow older but will be reshuffled into new groups (deviation from first viewpoint). For instance, cluster analyses in a clinical cohort from Paris identified a phenotype of "uncontrolled wheeze" at age <3 years and again at 5 years [9,10]. However, this phenotype was predominately nonatopic at younger age and predominately atopic at older age.…”

Change in the manifestations of asthma and asthma-related traits in childhood: a latent transition analysis

“…Our study extends previous attempts to define respiratory disease phenotypes in childhood in two ways: 1) by extending longitudinal analyses of a single respiratory symptom (wheeze) [2][3][4] to include repeated measures of several manifestations of respiratory disease and define phenotypes at multiple time points, and 2) by extending cross-sectional studies of multiple manifestations of respiratory disease [8][9][10][11][12] to a longitudinal analysis that includes estimation of transition probabilities. To the best of our knowledge, this study is the first to simultaneously define phenotypes with multiple disease manifestations at more than two time points and examine transitions between phenotypes over time in a population-based sample of children using a data-driven approach.…”

“…So far, attempts to explore this heterogeneity and define distinct phenotypes of asthma in children have focused on either the time course of wheeze [1][2][3][4] and other symptoms [5][6][7] during childhood or on cross-sectional classification of disease manifestations at specified ages [8][9][10][11][12]. Recently, the use of unsupervised, data-driven statistical approaches, such as cluster analysis [9,11,12] and latent class analysis [2,3,8,10,13], has emerged as complementary to approaches based on the application of a priori definitions [1,14] to aid in identifying and defining objective, novel or previously unrecognised phenotypes. Phenotypes previously identified have varied due to differences in the populations and attributes included in the models.…”