Challenges in interpreting allergen microarrays in relation to clinical symptoms: a machine learning approach.

Identifying different patterns of allergens and understanding their predictive ability in relation to asthma and other allergic diseases is crucial for the design of personalized diagnostic tools.Allergen-IgE screening using ImmunoCAP ISAC(®) assay was performed at age 11 yrs in children participating a population-based birth cohort. Logistic regression (LR) and nonlinear statistical learning models, including random forests (RF) and Bayesian networks (BN), coupled with feature selection approaches, were used to identify patterns of allergen responses associated with asthma, rhino-conjunctivitis, wheeze, eczema and airway hyper-reactivity (AHR, positive methacholine challenge). Sensitivity/specificity and area under the receiver operating characteristic (AUROC) were used to assess model performance via repeated validation.Serum sample for IgE measurement was obtained from 461 of 822 (56.1%) participants. Two hundred and thirty-eight of 461 (51.6%) children had at least one of 112 allergen components IgE > 0 ISU. The binary threshold >0.3 ISU performed less well than using continuous IgE values, discretizing data or using other data transformations, but not significantly (p = 0.1). With the exception of eczema (AUROC~0.5), LR, RF and BN achieved comparable AUROC, ranging from 0.76 to 0.82. Dust mite, pollens and pet allergens were highly associated with asthma, whilst pollens and dust mite with rhino-conjunctivitis. Egg/bovine allergens were associated with eczema.After validation, LR, RF and BN demonstrated reasonable discrimination ability for asthma, rhino-conjunctivitis, wheeze and AHR, but not for eczema. However, further improvements in threshold ascertainment and/or value transformation for different components, and better interpretation algorithms are needed to fully capitalize on the potential of the technology

Evolution pathways of IgE responses to grass and mite allergens throughout childhood

Little is known about longitudinal patterns of the development of IgE to distinct allergen components.We sought to investigate the evolution of IgE responses to allergenic components of timothy grass and dust mite during childhood.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).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).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

Lung function trajectories from pre-school age to adulthood and their associations with early life factors : a retrospective analysis of three population-based birth cohort studies

Funding: MAAS and STELAR cohorts are funded by the The UK Medical Research Council (MRC) Grants G0601361 and MR/K002449/1. The UK Medical Research Council and the Wellcome Trust (Grant ref:102215/2/13/2) and the University of Bristol provide core support for ALSPAC. ALSPAC lung function was funded by MRC grants G0401540 and MR/M022501/1. PIAF was funded by the National Health and Medical Research Council of Australia. DB is supported by the MRC Career Development Award in Biostatistics Grant MR/M015181/1Peer reviewedPostprin

Intestinal carriage of Staphylococcus aureus: How does its frequency compare with that of nasal carriage and what is its clinical impact?

The bacterial species Staphylococcus aureus, including its methicillin-resistant variant (MRSA), finds its primary ecological niche in the human nose, but is also able to colonize the intestines and the perineal region. Intestinal carriage has not been widely investigated despite its potential clinical impact. This review summarizes literature on the topic and sketches the current state of affairs from a microbiological and infectious diseases' perspective. Major findings are that the average reported detection rate of intestinal carriage in healthy individuals and patients is 20% for S. aureus and 9% for MRSA, which is approximately half of that for nasal carriage. Nasal carriage seems to predispose to intestinal carriage, but sole intestinal carriage occurs relatively frequently and is observed in 1 out of 3 intestinal carriers, which provides a rationale to include intestinal screening for surveillance or in outbreak settings. Colonization of the intestinal tract with S. aureus at a young age occurs at a high frequency and may affect the host's immune system. The frequency of intestinal carriage is generally underestimated and may significantly contribute to bacterial dissemination and subsequent risk of infections. Whether intestinal rather than nasal S. aureus carriage is a primary predictor for infections is still ill-defined

Antibiotic use in infancy and development of childhood asthma

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