Longitudinal Phenotypes of Respiratory Health in a High-Risk Urban Birth Cohort

Abstract

Rationale: Characterization of patterns of wheezing and allergic sensitization in early life may allow for identification of specific environmental exposures impacting asthma development.

Objectives: To define respiratory phenotypes in inner-city children and their associations with early-life environmental exposures.

Methods: Data were collected prospectively from 442 children in the URECA (Urban Environment and Childhood Asthma) birth cohort through age 7 years, reflecting symptoms (wheezing), aeroallergen sensitization, pulmonary function, and body mass index. Latent class mixed models identified trajectories of wheezing, allergic sensitization, and pulmonary function. Cluster analysis defined nonoverlapping groups (termed phenotypes). Potential associations between phenotypes and early-life environmental exposures were examined.

Measurements and main results: Five phenotypes were identified and mainly differentiated by patterns of wheezing and allergic sensitization (low wheeze/low atopy; low wheeze/high atopy; transient wheeze/low atopy; high wheeze/low atopy; high wheeze/high atopy). Asthma was most often present in the high-wheeze phenotypes, with greatest respiratory morbidity among children with frequent wheezing and allergic sensitization. These phenotypes differentially related to early-life exposures, including maternal stress and depression, antenatal environmental tobacco smoke, house dust microbiome, and allergen content (all P < 0.05). Prenatal smoke exposure, maternal stress, and depression were highest in the high-wheeze/low-atopy phenotype. The high-wheeze/high-atopy phenotype was associated with low household microbial richness and diversity. Early-life aeroallergen exposure was low in high-wheeze phenotypes.

Conclusions: Patterns of wheezing, allergic sensitization, and lung function identified five respiratory phenotypes among inner-city children. Early-life environmental exposure to stress, depression, tobacco smoke, and indoor allergens and microbes differentially associate with specific phenotypes.

Keywords: childhood asthma; environmental exposures; phenotypes.

Figure 1.

Pictorial representation of the methods used for determining URECA clusters/phenotypes. After construction of the latent class mixed models, we selected the optimal number of cluster solution for each variable under consideration. We subsequently combined all trajectories and nontrajectory variables into cluster analyses and determined the optimal solution using an ensemble model. AIC = Akaike information criterion; HA = high atopy; HW = high wheeze; IOS = impulse oscillometry; LA = low atopy; LW = low wheeze; TW = transient wheeze; URECA = Urban Environment and Childhood Asthma; XA = area of reactance.

Figure 2.

Observed trajectories with SEs for variables used in clustering algorithm among URECA participants through age 7 years. Latent class mixed models were performed, and the optimal number of classes selected is plotted. Each model is constructed separately for each variable; thus, the classes are unrelated between variables. IOS = impulse oscillometry; URECA = Urban Environment and Childhood Asthma; XA = area of reactance.

Figure 3.

Distributions of asthma diagnosis by URECA clusters. (A) The frequency (%) of asthma was greater in the high-wheeze/low-atopy and high-wheeze/high-atopy clusters (P < 0.01). (B and C) A two-dimensional distance matrix used in the construction of childhood URECA phenotype by asthma (B) and cluster group (C) is described by using t-distributed stochastic neighbor embedding, a novel dimension-reduction technique for high-dimensional data. HA = high atopy; HW = high wheeze; LA = low atopy; LW = low wheeze; t-SNE = t-distributed stochastic neighbor embedding; TW = transient wheeze; URECA = Urban Environment and Childhood Asthma.

Figure 4.

Observed results from Perceived Stress Scale (A), Edinburgh Postnatal Depression Scale (B), detection levels of cotinine (C), sum of Allergen Exposure Index at first year (D), microbiota dust exposure richness (E), and phylogenetic diversity (F). All show a significant difference (P < 0.01) between phenotypes. HA = high atopy; HW = high wheeze; LA = low atopy; LW = low wheeze; TW = transient wheeze.