Background Little is known about longitudinal patterns of the development of IgE to distinct allergen components. Objective We sought to investigate the evolution of IgE responses to allergenic ...components of timothy grass and dust mite during childhood. Methods In a population-based birth cohort (n = 1184) we measured IgE responses to 15 components from timothy grass and dust mite in children with available samples at 3 time points (ages 5, 8, and 11 years; n = 235). We designed a nested, 2-stage latent class analysis to identify cross-sectional sensitization patterns at each follow-up and their longitudinal trajectories. We then ascertained the association of longitudinal trajectories with asthma, rhinitis, eczema, and lung function in children with component data for at least 2 time points (n = 534). Results Longitudinal latent class analysis revealed 3 grass sensitization trajectories: (1) no/low sensitization; (2) early onset; and (3) late onset. The early-onset trajectory was associated with asthma and diminished lung function, and the late-onset trajectory was associated with rhinitis. Four longitudinal trajectories emerged for mite: (1) no/low sensitization; (2) group 1 allergens; (3) group 2 allergens; and (3) complete mite sensitization. Children in the complete mite sensitization trajectory had the highest odds ratios (ORs) for asthma (OR, 7.15; 95% CI, 3.80-13.44) and were the only group significantly associated with comorbid asthma, rhinitis, and eczema (OR, 5.91; 95% CI, 2.01-17.37). Among children with wheezing, those in the complete mite sensitization trajectory (but not other longitudinal mite trajectories) had significantly higher risk of severe exacerbations (OR, 3.39; 95% CI, 1.62-6.67). Conclusions The nature of developmental longitudinal trajectories of IgE responses differed between grass and mite allergen components, with temporal differences (early vs late onset) dominant in grass and diverging patterns of IgE responses (group 1 allergens, group 2 allergens, or both) in mite. Different longitudinal patterns bear different associations with clinical outcomes, which varied by allergen.
Aim: The individual effects of climate and soil properties on functional trait distributions have become increasingly clear with recent syntheses of large datasets. However, the distribution of ...traits in a given climate may depend on the fertility of the soil. Our aim was to quantify how soil-climate interactions explain community-level variation in functional traits from every plant organ to improve predictions of plant community responses to environmental change. Location: Temperate forests throughout New Zealand. Methods: We measured traits of foliar, stem, root and reproductive tissue for 64 species and calculated abundance-weighted mean trait values on 324 forest plots. Multiple linear regression was used to model the variation in each of the traits as functions of mean annual temperature (MAT), vapour pressure deficit (VPD), soil pH, soil total phosphorus (P) and their interactions. Results: Soil-climate interactions explained significant variation in functional traits. For example, specific leaf area (SLA) was highest in high-P soil within a wet and warm climate; however, strong interactions indicate that SLA was lowest in wet and warm climates in low-P soil. Root tissue density was lowest in warm climates and high-P soil, but it was high in warm climates and low-P soil and in cold climates and high-P soil. According to model predictions, the largest potential responses of vegetation to warming may occur in fertile and wet environments. Main conclusions: Pervasive soil-climate interactions demonstrate that interpreting simple bivariate relationships between traits and climate must be done with caution because the adaptive value of traits in a given climate depends on the fertility of the soil. Predictions of vegetation responses to climate change will improve significantly by incorporating local-scale soil properties into modelling frameworks. Rising global temperatures may shift community-level trait values in opposite directions depending on whether the soil is fertile or infertile.
Atopic dermatitis (AD) affects up to 20% of children worldwide and is an increasing public health problem, particularly in developed countries. Although AD in infants and young children can resolve, ...there is a well-recognized increased risk of sequential progression from AD to other atopic diseases, including food allergy (FA), allergic rhinitis, allergic asthma, and allergic rhinoconjunctivitis, a process referred to as the atopic march. The mechanisms underlying the development of AD and subsequent progression to other atopic comorbidities, particularly FA, are incompletely understood and the subject of intense investigation. Other major research objectives are the development of effective strategies to prevent AD and FA, as well as therapeutic interventions to inhibit the atopic march. In 2017, the Division of Allergy, Immunology, and Transplantation of the National Institute of Allergy and Infectious Diseases sponsored a workshop to discuss current understanding and important advances in these research areas and to identify gaps in knowledge and future research directions. International and national experts in the field were joined by representatives from several National Institutes of Health institutes. Summaries of workshop presentations, key conclusions, and recommendations are presented herein.
There is a paucity of information about longitudinal patterns of IgE responses to allergenic proteins (components) from multiple sources.
This study sought to investigate temporal patterns of ...component-specific IgE responses from infancy to adolescence, and their relationship with allergic diseases.
In a population-based birth cohort, we measured IgE to 112 components at 6 follow-ups during childhood. We used a Bayesian method to discover cross-sectional sensitization patterns and their longitudinal trajectories, and we related these patterns to asthma and rhinitis in adolescence.
We identified 1 sensitization cluster at age 1, 3 at age 3, 4 at ages 5 and 8, 5 at age 11, and 6 at age 16 years. “Broad” cluster was the only cluster present at every follow-up, comprising components from multiple sources. “Dust mite” cluster formed at age 3 years and remained unchanged to adolescence. At age 3 years, a single-component “Grass” cluster emerged, which at age 5 years absorbed additional grass components and Fel d 1 to form the “Grass/cat” cluster. Two new clusters formed at age 11 years: “Cat” cluster and “PR-10/profilin” (which divided at age 16 years into “PR-10” and “Profilin”). The strongest contemporaneous associate of asthma at age 16 years was sensitization to dust mite cluster (odds ratio: 2.6; 95% CI: 1.2-6.1; P < .05), but the strongest early life predictor of subsequent asthma was sensitization to grass/cat cluster (odds ratio: 3.5; 95% CI: 1.6-7.4; P < .01).
We describe the architecture of the evolution of IgE responses to multiple allergen components throughout childhood, which may facilitate development of better diagnostic and prognostic biomarkers for allergic diseases.
The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because ...allergic sensitisation may not be a single entity (as considered conventionally) but a collection of several different classes of sensitisation. We hypothesise that pairings between immunoglobulin E (IgE) antibodies to individual allergenic molecules (components), rather than IgE responses to 'informative' molecules, are associated with increased risk of asthma.
In a cross-sectional analysis among 461 children aged 11 years participating in a population-based birth cohort, we measured serum-specific IgE responses to 112 allergen components using a multiplex array (ImmunoCAP Immuno‑Solid phase Allergy Chip ISAC). We characterised sensitivity to 44 active components (specific immunoglobulin E sIgE > 0.30 units in at least 5% of children) among the 213 (46.2%) participants sensitised to at least one of these 44 components. We adopted several machine learning methodologies that offer a powerful framework to investigate the highly complex sIgE-asthma relationship. Firstly, we applied network analysis and hierarchical clustering (HC) to explore the connectivity structure of component-specific IgEs and identify clusters of component-specific sensitisation ('component clusters'). Of the 44 components included in the model, 33 grouped in seven clusters (C.sIgE-1-7), and the remaining 11 formed singleton clusters. Cluster membership mapped closely to the structural homology of proteins and/or their biological source. Components in the pathogenesis-related (PR)-10 proteins cluster (C.sIgE-5) were central to the network and mediated connections between components from grass (C.sIgE-4), trees (C.sIgE-6), and profilin clusters (C.sIgE-7) with those in mite (C.sIgE-1), lipocalins (C.sIgE-3), and peanut clusters (C.sIgE-2). We then used HC to identify four common 'sensitisation clusters' among study participants: (1) multiple sensitisation (sIgE to multiple components across all seven component clusters and singleton components), (2) predominantly dust mite sensitisation (IgE responses mainly to components from C.sIgE-1), (3) predominantly grass and tree sensitisation (sIgE to multiple components across C.sIgE-4-7), and (4) lower-grade sensitisation. We used a bipartite network to explore the relationship between component clusters, sensitisation clusters, and asthma, and the joint density-based nonparametric differential interaction network analysis and classification (JDINAC) to test whether pairwise interactions of component-specific IgEs are associated with asthma. JDINAC with pairwise interactions provided a good balance between sensitivity (0.84) and specificity (0.87), and outperformed penalised logistic regression with individual sIgE components in predicting asthma, with an area under the curve (AUC) of 0.94, compared with 0.73. We then inferred the differential network of pairwise component-specific IgE interactions, which demonstrated that 18 pairs of components predicted asthma. These findings were confirmed in an independent sample of children aged 8 years who participated in the same birth cohort but did not have component-resolved diagnostics (CRD) data at age 11 years. The main limitation of our study was the exclusion of potentially important allergens caused by both the ISAC chip resolution as well as the filtering step. Clustering and the network analyses might have provided different solutions if additional components had been available.
Interactions between pairs of sIgE components are associated with increased risk of asthma and may provide the basis for designing diagnostic tools for asthma.
Background The relationship between sensitization to allergens and disease is complex. Objective We sought to identify patterns of response to a broad range of allergen components and investigate ...associations with asthma, eczema, and hay fever. Methods Serum specific IgE levels to 112 allergen components were measured by using a multiplex array (Immuno Solid-phase Allergen Chip) in a population-based birth cohort. Latent variable modeling was used to identify underlying patterns of component-specific IgE responses; these patterns were then related to asthma, eczema, and hay fever. Results Two hundred twenty-one of 461 children had IgE to 1 or more components. Seventy-one of the 112 components were recognized by 3 or more children. By using latent variable modeling, 61 allergen components clustered into 3 component groups (CG1, CG2, and CG3); protein families within each CG were exclusive to that group. CG1 comprised 27 components from 8 plant protein families. CG2 comprised 7 components of mite allergens from 3 protein families. CG3 included 27 components of plant, animal, and fungal origin from 12 protein families. Each CG included components from different biological sources with structural homology and also nonhomologous proteins arising from the same biological source. Sensitization to CG3 was most strongly associated with asthma (odds ratio OR, 8.20; 95% CI, 3.49-19.24; P < .001) and lower FEV1 ( P < .001). Sensitization to CG1 was associated with hay fever (OR, 12.79; 95% CI, 6.84-23.90; P < .001). Sensitization to CG2 was associated with both asthma (OR, 3.60; 95% CI, 2.05-6.29) and hay fever (OR, 2.52; 95% CI, 1.38-4.61). Conclusions Latent variable modeling with a large number of allergen components identified 3 patterns of IgE responses, each including different protein families. In 11-year-old children the pattern of response to components of multiple allergens appeared to be associated with current asthma and hay fever but not eczema.
Trajectories of lung function during childhood Belgrave, Danielle C M; Buchan, Iain; Bishop, Christopher ...
American journal of respiratory and critical care medicine,
05/2014, Letnik:
189, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Developmental patterns of lung function during childhood may have major implications for our understanding of the pathogenesis of respiratory disease throughout life.
To explore longitudinal ...trajectories of lung function during childhood and factors associated with lung function decline.
In a population-based birth cohort, specific airway resistance (sRaw) was assessed at age 3 (n = 560), 5 (n = 829), 8 (n = 786), and 11 years (n = 644). Based on prospective data (questionnaires, skin tests, IgE), children were assigned to wheeze phenotypes (no wheezing, transient, late-onset, and persistent) and atopy phenotypes (no atopy, dust mite, non-dust mite, multiple early, and multiple late). We used longitudinal linear mixed models to determine predictors of change in sRaw over time.
Contrary to the assumption that sRaw is independent of age and sex, boys had higher sRaw than girls (mean difference, 0.080; 95% confidence interval CI, 0.049-0.111; P < 0.001) and a higher rate of increase over time. For girls, sRaw increased by 0.017 kPa ⋅ s(-1) per year (95% CI, 0.011-0.023). In boys this increase was significantly greater (P = 0.012; mean between-sex difference, 0.011 kPa ⋅ s(-1); 95% CI, 0.003-0.019). Children with persistent wheeze (but not other wheeze phenotypes) had a significantly greater rate of deterioration in sRaw over time compared with never wheezers (P = 0.009). Similarly, children with multiple early, but not other atopy phenotypes had significantly poorer lung function than those without atopy (mean difference, 0.116 kPa ⋅ s(-1); 95% CI, 0.065-0.168; P < 0.001). sRaw increased progressively with the increasing number of asthma exacerbations.
Children with persistent wheeze, frequent asthma exacerbations, and multiple early atopy have diminished lung function throughout childhood, and are at risk of a progressive loss of lung function from age 3 to 11 years. These effects are more marked in boys.
The term "atopic march" has been used to imply a natural progression of a cascade of symptoms from eczema to asthma and rhinitis through childhood. We hypothesize that this expression does not ...adequately describe the natural history of eczema, wheeze, and rhinitis during childhood. We propose that this paradigm arose from cross-sectional analyses of longitudinal studies, and may reflect a population pattern that may not predominate at the individual level.
Data from 9,801 children in two population-based birth cohorts were used to determine individual profiles of eczema, wheeze, and rhinitis and whether the manifestations of these symptoms followed an atopic march pattern. Children were assessed at ages 1, 3, 5, 8, and 11 y. We used Bayesian machine learning methods to identify distinct latent classes based on individual profiles of eczema, wheeze, and rhinitis. This approach allowed us to identify groups of children with similar patterns of eczema, wheeze, and rhinitis over time. Using a latent disease profile model, the data were best described by eight latent classes: no disease (51.3%), atopic march (3.1%), persistent eczema and wheeze (2.7%), persistent eczema with later-onset rhinitis (4.7%), persistent wheeze with later-onset rhinitis (5.7%), transient wheeze (7.7%), eczema only (15.3%), and rhinitis only (9.6%). When latent variable modelling was carried out separately for the two cohorts, similar results were obtained. Highly concordant patterns of sensitisation were associated with different profiles of eczema, rhinitis, and wheeze. The main limitation of this study was the difference in wording of the questions used to ascertain the presence of eczema, wheeze, and rhinitis in the two cohorts.
The developmental profiles of eczema, wheeze, and rhinitis are heterogeneous; only a small proportion of children (∼ 7% of those with symptoms) follow trajectory profiles resembling the atopic march. Please see later in the article for the Editors' Summary.
...we report the first case of FPIES in an adult patient that was confirmed by oral food challenge, indicating that FPIES can occur not only in children but also among adults.
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