Identification of differences in CD4+ T-cell gene expression between people with asthma and healthy controls.

Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4+ T-cells play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4+ T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data, we identified PTPRC, a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).

Early-life predictors and risk factors of peanut allergy, and its association with asthma in later-life: Population-based birth cohort study.

BACKGROUND: Understanding risk factors for peanut allergy (PA) is essential to develop effective preventive measures. OBJECTIVE: The objective was to ascertain associates and predictors of PA, and the relationship between PA and asthma severity. METHODS: In a population-based birth cohort, we investigated the association between objectively confirmed PA with early-life environmental exposures, filaggrin (FLG)-loss-of-function mutations and other atopic disease. We then examined the association of PA with longitudinal trajectories of sensitization, wheeze and allergic comorbidities, which were previously derived using machine learning. Finally, we ascertained the relationship between PA and asthma severity. RESULTS: PA was confirmed in 30/959 participants with evaluable data. In the multivariate analysis, eczema in infancy (OR = 4.4, 95% CI 1.5-13.2, p = 0.007), egg sensitization at age 3 years (OR = 9.7, 95% CI 3.3-29.9, p < 0.001) and early-life cat ownership (OR = 3.0, 95% CI 1.1-8.4, p = 0.04) were independent associates of PA. In the stratified analysis among 700 participants with genetic information, in children with early-life eczema there was no difference in FLG mutations between children with and without PA (3/18 [16.7%] vs. 42/220 [19.1%], p = 1.00). In contrast, among children without eczema, those with PA were almost eight times more likely to have FLG mutations (2/6 [33.3%] vs. 27/456 [5.9%], p = 0.049). We observed associations between PA and multiple allergic sensitization profiles derived using machine learning, with ~60-fold increase in risk among individuals assigned to multiple early sensitization. PA was significantly associated with persistent wheeze (but not other wheeze phenotypes), and with trajectories of atopic disease characterized by co-morbid persistent eczema and wheeze (but not with transient phenotypes). Children with PA were more likely to have asthma, but among asthmatics we found no evidence of an association between PA and asthma severity. CONCLUSIONS: Peanut allergy is associated with multiple IgE sensitization and early-onset persistent eczema and wheeze. FLG loss-of-function mutations were associated with peanut allergy in children without eczema.

Cross-sectional association of dietary patterns with asthma and atopic sensitization in childhood - in a cohort study.

BACKGROUND: Many studies have investigated individual nutrients or foods as risk factors for allergic disease, but few have studied dietary patterns. We aimed to use principal component analysis (PCA) to determine dietary patterns in school age children and examine associations between these dietary patterns and wheeze, asthma and sensitization. METHODS: Participants in a population-based birth cohort attended review clinics at ages 8 and 11 yr. A validated questionnaire was interviewer-administered to collect information on parentally reported symptoms and doctor-diagnosed asthma. Atopic sensitization was ascertained by skin-prick tests. Current asthma was defined as doctor-diagnosed asthma and wheezing in the previous 12 months. A validated semi-quantitative food frequency questionnaire was completed at age 8 yr, and PCA was used to determine dietary patterns. RESULTS: Principal component analysis identified three dietary components, which based on their characteristics we termed as Traditional (mixed meat, fish, fruit and vegetables), Western (predominantly high fat content, processed foods) and Other (predominantly grains and nuts) dietary patterns. High adherence to the Western diet pattern was significantly associated with doctor-diagnosed asthma and current asthma at age 8 yr [aOR (95% CI): 2.19 (1.20-4.01), p = 0.01; 2.59 (1.15-5.81), p = 0.02; respectively]. A similar association was found for current asthma at age 11 yr [aOR (95% CI): 2.20 (1.07-4.51), p = 0.03]. There was no evidence of an association between dietary patterns and current wheeze and allergic sensitization at either age 8 or 11 yr. CONCLUSION: School age children adhering strongly to a Western diet, high in fat and processed foods, had a higher risk of current asthma and doctor-diagnosed asthma.

Allergy or tolerance in children sensitized to peanut: prevalence and differentiation using component-resolved diagnostics.

BACKGROUND: Not all peanut-sensitized children develop allergic reactions on exposure. OBJECTIVE: To establish by oral food challenge the proportion of children with clinical peanut allergy among those considered peanut-sensitized by using skin prick tests and/or IgE measurement, and to investigate whether component-resolved diagnostics using microarray could differentiate peanut allergy from tolerance. METHODS: Within a population-based birth cohort, we ascertained peanut sensitization by skin tests and IgE measurement at age 8 years. Among sensitized children, we determined peanut allergy versus tolerance by oral food challenges. We used open challenge among children consuming peanuts (n = 45); others underwent double-blind placebo-controlled challenge (n = 34). We compared sensitization profiles between children with peanut allergy and peanut-tolerant children by using a microarray with 12 pure components (major peanut and potentially cross-reactive components, including grass allergens). RESULTS: Of 933 children, 110 (11.8%) were peanut-sensitized. Nineteen were not challenged (17 no consent). Twelve with a convincing history of reactions on exposure, IgE > or =15 kUa/L and/or skin test > or =8mm were considered allergic without challenge. Of the remaining 79 children who underwent challenge, 7 had > or =2 objective signs and were designated as having peanut allergy. We estimated the prevalence of clinical peanut allergy among sensitized subjects as 22.4% (95% CI, 14.8% to 32.3%). By using component-resolved diagnostics, we detected marked differences in the pattern of component recognition between children with peanut allergy (n = 29; group enriched with 12 children with allergy) and peanut-tolerant children (n = 52). The peanut component Ara h 2 was the most important predictor of clinical allergy. CONCLUSION: The majority of children considered peanut-sensitized on the basis of standard tests do not have peanut allergy. Component-resolved diagnostics may facilitate the diagnosis of peanut allergy.