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1.
Artigo em Inglês | MEDLINE | ID: mdl-31629803

RESUMO

BACKGROUND: We hypothesized that filaggrin loss-of-function mutations modify the impact of allergen exposure on the development of allergic sensitization. OBJECTIVE: To determine whether early-life exposure to inhalant allergens increases the risk of specific sensitization, and whether filaggrin mutations modulate these odds. METHODS: In a population-based birth cohort, we measured mite, cat and dog allergen levels in dust samples collected from homes within the first year of life. Sensitization was assessed at 6 time-points between infancy and age 16 years. Genotyping was performed for six filaggrin mutations. RESULTS: In the longitudinal multivariable model (age 1-16 years), we observed a significant interaction between filaggrin and Fel d 1 exposure on cat sensitization, with the effect of exposure being significantly greater among children with filaggrin mutations compared to those without (OR 1.36, 95% CI 1.02-1.80, p=0.035). The increase in risk of mite sensitization with increasing Der p 1 exposure was consistently higher among children with filaggrin mutations, but the interaction did not reach statistical significance. Different association were observed for dog: there was a significant interaction between filaggrin and dog ownership, but the risk of sensitization to any allergen was significantly lower among children with filaggrin mutations who were exposed to dog in infancy (OR 0.16, 95% CI 0.03-0.86, p=0.03). CONCLUSIONS: Filaggrin loss-of function mutations modify the relationship between allergen exposure and sensitization, but effects differ at different ages and between different allergens.

2.
Eur Respir J ; 2019 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-31558662

RESUMO

This document provides clinical recommendations for the management of severe asthma. Comprehensive evidence syntheses, including meta-analyses, were performed to summarise all available evidence relevant to the Task Force's questions. The evidence was appraised using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach and the results were summarised in evidence profiles. The evidence syntheses were discussed and recommendations formulated by a multidisciplinary Task Force of asthma experts, who made specific recommendations on 6 specific questions. After considering the balance of desirable and undesirable consequences, quality of evidence, feasibility, and acceptability of various interventions, the Task Force made the following recommendations: 1) Suggest using anti-IL5 and anti IL-5Rα for severe uncontrolled adult eosinophilic asthma phenotypes; 2) suggest using blood eosinophil cut-point of ≥150/µL to guide anti-IL5 initiation in adult patients with severe asthma; and 3) Suggest considering specific eosinophil (≥260/µL) and FeNO (≥19.5 ppb) cutoffs to identify adolescents or adults with the greatest likelihood or response to anti-IgE therapy; 4) Suggest using inhaled tiotropium for adolescents and adults with severe uncontrolled asthma despite GINA step 4-5 or NAEPP step 5 therapies; 5) Suggest a trial of chronic macrolide therapy to reduce asthma exacerbations in persistently symptomatic or uncontrolled patients on GINA step 5 or NAEPP step 5 therapies, irrespective of asthma phenotype; 6) Suggest using anti-IL4/13 for adult patients with severe eosinophilic asthma, and for those with severe corticosteroid-dependent asthma regardless of blood eosinophil levels. These recommendations should be reconsidered as new evidence becomes available.

3.
Hum Mol Genet ; 2019 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-31504550

RESUMO

Although hundreds of GWAS-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity, and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of thirty studies consisting of up to 13,005 cases (≥95th percentile of BMI achieved 2-18 years old) and 15,599 controls (consistently <50th percentile of BMI) of European, African, North/South American and East Asian ancestry. Suggestive loci were taken forward for replication in a sample of 1,888 cases and 4,689 controls from seven cohorts of European and North/South American ancestry. In addition to observing eighteen previously implicated BMI or obesity loci, for both early and late onset, we uncovered one completely novel locus in this trans-ancestral analysis (nearest gene: METTL15). The variant was nominally associated in only the European subgroup analysis but had a consistent direction of effect in other ethnicities. We then utilized trans-ancestral Bayesian analysis to narrow down the location of the probable causal variant at each genome-wide significant signal. Of all the fine-mapped loci, we were able to narrow down the causative variant at four known loci to fewer than ten SNPs (FAIM2, GNPDA2, MC4R and SEC16B loci). In conclusion, an ethnically diverse setting has enabled us to both identify an additional pediatric obesity locus and further fine-map existing loci.

4.
Eur Respir J ; 54(3)2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31467120

RESUMO

Despite the use of effective medications to control asthma, severe exacerbations in asthma are still a major health risk and require urgent action on the part of the patient and physician to prevent serious outcomes such as hospitalisation or death. Moreover, severe exacerbations are associated with substantial healthcare costs and psychological burden, including anxiety and fear for patients and their families. The European Academy of Allergy and Clinical Immunology (EAACI) and the European Respiratory Society (ERS) set up a task force to search for a clear definition of severe exacerbations, and to also define research questions and priorities. The statement includes comments from patients who were members of the task force.

5.
Clin Exp Allergy ; 2019 Aug 23.
Artigo em Inglês | MEDLINE | ID: mdl-31441980

RESUMO

BACKGROUND: Allergic diseases (eczema, wheeze and rhinitis) in children often present as heterogeneous phenotypes. Understanding genetic associations of specific patterns of symptoms might facilitate understanding of the underlying biological mechanisms. OBJECTIVE: To examine associations between allergic disease-related variants identified in a recent genome-wide association study and latent classes of allergic diseases (LCADs) in two population-based birth cohorts. METHODS: Eight previously defined LCADs between birth and 11 years: "No disease," "Atopic march," "Persistent eczema and wheeze," "Persistent eczema with later-onset rhinitis," "Persistent wheeze with later-onset rhinitis," "Transient wheeze," "Eczema only" and "Rhinitis only" were used as the study outcome. Weighted multinomial logistic regression was used to estimate associations between 135 SNPs (and a polygenic risk score, PRS) and LCADs among 6345 individuals from The Avon Longitudinal Study of Parents and Children (ALSPAC). Heterogeneity across LCADs was assessed before and after Bonferroni correction. Results were replicated in Manchester Asthma and Allergy Study (MAAS) (n = 896) and pooled in a meta-analysis. RESULTS: We found strong evidence for differential genetic associations across the LCADs; pooled PRS heterogeneity P-value = 3.3 × 10-14 , excluding "no disease" class. The associations between the PRS and LCADs in MAAS were remarkably similar to ALSPAC. Two SNPs (a protein-truncating variant in FLG and a SNP within an intron of GSDMB) had evidence for differential association (pooled P-values ≤ 0.006). The FLG locus was differentially associated across LCADs that included eczema, with stronger associations for LCADs with comorbid wheeze and rhinitis. The GSDMB locus in contrast was equally associated across LCADs that included wheeze. CONCLUSIONS AND CLINICAL RELEVANCE: We have shown complex, but distinct patterns of genetic associations with LCADs, suggesting that heterogeneous mechanisms underlie individual disease trajectories. Establishing the combination of allergic diseases with which each genetic variant is associated may inform therapeutic development and/or predictive modelling.

6.
Expert Rev Respir Med ; 13(10): 929-936, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31369320

RESUMO

Introduction: Amongst allergic asthmatics, high allergen exposure increases asthma severity. However, there is no consensus on the role of mite allergen avoidance in the management of asthma, and various guidelines differ in their recommendations. Areas covered: Several systematic reviews/meta-analyses on mite avoidance in the management of asthma have been published, and their findings have been used for a call to provide a recommendation in British guidelines that dust-mite control measures should not be recommended. However, there are several problems with such analysis (such as combining studies in adults and children), and we question whether these are appropriate tools to evaluate available evidence about mite allergen avoidance, and whether it is correct to rely disproportionately on the results of meta-analyses/systematic reviews to inform clinical practice in this area. Recent evidence in children suggests that mite-impermeable bed encasings reduce emergency hospital attendance with severe asthma exacerbations. Expert opinion: The practical questions include how to achieve a sufficient real-life reduction allergen exposure, and how to identify patients who will benefit from effective intervention. The intervention should start early in the natural history of asthma, and consideration for choosing patients should include using the titre of allergen-specific IgE antibodies or the size of skin test wheal as an indicator.

7.
EBioMedicine ; 46: 486-498, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31353293

RESUMO

BACKGROUND: A critical window in infancy has been proposed, during which the microbiota may affect subsequent health. The longitudinal development of the oropharyngeal microbiota is under-studied and may be associated with early-life wheeze. We aimed to investigate the temporal association of the development of the oropharyngeal microbiota with early-life wheeze. METHODS: A population-based birth cohort based in London, UK was followed for 24 months. We collected oropharyngeal swabs at six time-points. Microbiota was determined using sequencing of the V3-V5 region of the 16S rRNA-encoding gene. Medical records were reviewed for the outcome of doctor diagnosed wheeze. We used a time-varying model to investigate the temporal association between the development of microbiota and doctor-diagnosed wheeze. FINDINGS: 159 participants completed the study to 24 months and for 98 there was complete sequencing data at all timepoints and outcome data. Of these, 26 had doctor-diagnosed wheeze. We observed significant increase in the abundance of Neisseria between 9 and 24 months in children who developed wheeze (p = 0∙003), while in those without wheezing there was a significant increment in the abundance of Granulicatella (p = 0∙012) between 9 and 12 months, and of Prevotella (p = 0∙018) after 18 months. INTERPRETATION: A temporal association between the respiratory commensal Granulicatella and also Prevotella with wheeze (negative), and between Neisseria and wheeze (positive) was identified in infants prior to one year of age. This adds to evidence for the proposed role of the microbiota in the development of wheeze. FUND: Research funding from the Winnicott Foundation, Meningitis Now and Micropathology Ltd.

8.
J Allergy Clin Immunol ; 144(1): 25-33, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31145940

RESUMO

Despite the development of novel treatments, improvement in the design of delivery devices, and new technologies for monitoring and improving adherence, the burden of asthma is not decreasing. Predicting an individual patient's response to asthma drugs remains challenging, and the provision of personalized treatment remains elusive. Although biomarkers, such as allergic sensitization and blood eosinophilia, might be important predictors of response to inhaled corticosteroids in preschool children, these relatively cheap and available investigations are seldom used in clinical practice to select patients for corticosteroid prescription. However, for the majority of patients, response to different treatments cannot be accurately predicted. One of the key factors preventing further advances is the reductionist view of asthma as a single disease, which is forcing patients with different asthma subtypes into a single group for empiric treatment. This inevitably results in treatment failures and, for some, an unacceptable risk/benefit ratio. The approach to asthma today is an example of the traditional symptom (diagnosis)-based, one-size-fits-all approach rather than a stratified approach, and our guidelines-driven management based on a unitary diagnosis might not be the optimal way to deliver care. The only way to deliver stratified medicine and find a cure is through the understanding of asthma endotypes. We propose that the way to discover endotypes, biomarkers, and personalized treatments is through the iterative process based on interpretation of big data analytics from birth and patient cohorts, responses to treatments in randomized controlled trials, and in vitro mechanistic studies using human samples and experimental animal models, with technological and methodological advances at its core.

9.
Allergy ; 74(10): 1835-1851, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30953574

RESUMO

Inflammation, structural, and functional abnormalities within the airways are key features of asthma. Although these processes are well documented, their expression varies across the heterogeneous spectrum of asthma. Type 2 inflammatory responses are characterized by increased levels of eosinophils, FeNO, and type 2 cytokines in blood and/or airways. Presently, type 2 asthma is the best-defined endotype, typically found in patients with allergic asthma, but surprisingly also in nonallergic patients with (severe) asthma. The etiology of asthma with non-type 2 inflammation is less clear. During the past decade, targeted therapies, including biologicals and small molecules, have been increasingly integrated into treatment strategies of severe asthma. These treatments block specific inflammatory pathways or single mediators. Single or composite biomarkers help to identify patients who will benefit from these treatments. So far, only a few inflammatory biomarkers have been validated for clinical application. The European Academy of Allergy & Clinical Immunology Task Force on Biomarkers in Asthma was initiated to review different biomarker sampling methods and to investigate clinical applicability of new and existing inflammatory biomarkers (point-of-care) to support diagnosis, targeted treatment, and monitoring of severe asthma. Subsequently, we discuss existing and novel targeted therapies for asthma as well as applicable biomarkers.

10.
Ann Am Thorac Soc ; 16(7): 868-876, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-30888842

RESUMO

Rationale: Pooling data from multiple cohorts and extending the time frame across childhood should minimize study-specific effects, enabling better characterization of childhood wheezing. Objectives: To analyze wheezing patterns from early childhood to adolescence using combined data from five birth cohorts. Methods: We used latent class analysis to derive wheeze phenotypes among 7,719 participants from five birth cohorts with complete report of wheeze at five time periods. We tested the associations of derived phenotypes with late asthma outcomes and lung function, and investigated the uncertainty in phenotype assignment. Results: We identified five phenotypes: never/infrequent wheeze (52.1%), early onset preschool remitting (23.9%), early onset midchildhood remitting (9%), persistent (7.9%), and late-onset wheeze (7.1%). Compared with the never/infrequent wheeze, all phenotypes had higher odds of asthma and lower forced expiratory volume in 1 second and forced expiratory volume in 1 second/forced vital capacity in adolescence. The association with asthma was strongest for persistent wheeze (adjusted odds ratio, 56.54; 95% confidence interval, 43.75-73.06). We observed considerable within-class heterogeneity at the individual level, with 913 (12%) children having low membership probability (<0.60) of any phenotype. Class membership certainty was highest in persistent and never/infrequent, and lowest in late-onset wheeze (with 51% of participants having membership probabilities <0.80). Individual wheezing patterns were particularly heterogeneous in late-onset wheeze, whereas many children assigned to early onset preschool remitting class reported wheezing at later time points. Conclusions: All wheeze phenotypes had significantly diminished lung function in school-age children, suggesting that the notion that early life episodic wheeze has a benign prognosis may not be true for a proportion of transient wheezers. We observed considerable within-phenotype heterogeneity in individual wheezing patterns.

11.
Pediatr Pulmonol ; 54(6): 847-857, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30927345

RESUMO

BACKGROUND: Neuropeptide S Receptor 1 ( NPSR1) and Retinoid Acid Receptor-Related Orphan Receptor Alpha (RORA ) interact biologically, are both known candidate genes for asthma, and are involved in controlling circadian rhythm. Thus, we assessed (1) whether interactions between RORA and NPSR1 specifically affect the nocturnal asthma phenotype and (2) how this may differ from other asthma phenotypes. METHODS: Interaction effects between 24 single-nucleotide polymorphisms (SNPs) in RORA and 35 SNPs in NPSR1 on asthma and nocturnal asthma symptoms were determined in 1432 subjects (763 asthmatics [192 with nocturnal asthma symptoms]; 669 controls) from the Multicenter Asthma Genetic in Childhood/International Study of Asthma and Allergies in Childhood studies. The results were validated and extended in children from the Manchester Asthma and Allergy Study (N = 723) and the Children Allergy Milieu Stockholm and Epidemiological cohort (N = 1646). RESULTS: RORA* NPSR1 interactions seemed to affect both asthma and nocturnal asthma. In stratified analyses, however, interactions mainly affected nocturnal asthma and less so asthma without nocturnal symptoms or asthma severity. Results were replicated in two independent cohorts and seemed to remain constant over time throughout youth. CONCLUSION: RORA* NPSR1 interactions appear to be involved in mechanisms specific for nocturnal asthma. In contrast to previous studies focusing on the role of beta 2 receptor polymorphisms in nocturnal asthma as a feature of asthma control or severity in general, our data suggest that changes in circadian rhythm control are associated with nighttime asthma symptoms.

12.
J Infect Dis ; 220(2): 184-186, 2019 Jun 19.
Artigo em Inglês | MEDLINE | ID: mdl-30783666

RESUMO

We are ignoring evidence suggesting that the diagnosis of bronchiolitis encompasses several diseases with distinct underlying mechanisms, considerable heterogeneity in treatment responses, and ultimately different therapeutic targets. Understanding this heterogeneity may be the only way to deliver appropriate, stratified treatments.

13.
Clin Exp Allergy ; 49(4): 410-418, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30657220

RESUMO

BACKGROUND: There is uncertainty about the clinical usefulness of currently available asthma predictive tools. Validation of predictive tools in different populations and clinical settings is an essential requirement for the assessment of their predictive performance, reproducibility and generalizability. We aimed to critically appraise asthma predictive tools which have been validated in external studies. METHODS: We searched MEDLINE and EMBASE (1946-2017) for all available childhood asthma prediction models and focused on externally validated predictive tools alongside the studies in which they were originally developed. We excluded non-English and non-original studies. PROSPERO registration number is CRD42016035727. RESULTS: From 946 screened papers, eight were included in the review. Statistical approaches for creation of prediction tools included chi-square tests, logistic regression models and the least absolute shrinkage and selection operator. Predictive models were developed and validated in general and high-risk populations. Only three prediction tools were externally validated: the Asthma Predictive Index, the PIAMA and the Leicester asthma prediction tool. A variety of predictors has been tested, but no studies examined the same combination. There was heterogeneity in definition of the primary outcome among development and validation studies, and no objective measurements were used for asthma diagnosis. The performance of tools varied at different ages of outcome assessment. We observed a discrepancy between the development and validation studies in the tools' predictive performance in terms of sensitivity and positive predictive values. CONCLUSIONS: Validated asthma predictive tools, reviewed in this paper, provided poor predictive accuracy with performance variation in sensitivity and positive predictive value.

14.
J Allergy Clin Immunol ; 143(5): 1783-1790.e11, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30528616

RESUMO

BACKGROUND: Latent class analysis (LCA) has been used extensively to identify (latent) phenotypes of childhood wheezing. However, the number and trajectory of discovered phenotypes differed substantially between studies. OBJECTIVE: We sought to investigate sources of variability affecting the classification of phenotypes, identify key time points for data collection to understand wheeze heterogeneity, and ascertain the association of childhood wheeze phenotypes with asthma and lung function in adulthood. METHODS: We used LCA to derive wheeze phenotypes among 3167 participants in the ALSPAC cohort who had complete information on current wheeze recorded at 14 time points from birth to age 16½ years. We examined the effects of sample size and data collection age and intervals on the results and identified time points. We examined the associations of derived phenotypes with asthma and lung function at age 23 to 24 years. RESULTS: A relatively large sample size (>2000) underestimated the number of phenotypes under some conditions (eg, number of time points <11). Increasing the number of data points resulted in an increase in the optimal number of phenotypes, but an identical number of randomly selected follow-up points led to different solutions. A variable selection algorithm identified 8 informative time points (months 18, 42, 57, 81, 91, 140, 157, and 166). The proportion of asthmatic patients at age 23 to 24 years differed between phenotypes, whereas lung function was lower among persistent wheezers. CONCLUSIONS: Sample size, frequency, and timing of data collection have a major influence on the number and type of wheeze phenotypes identified by using LCA in longitudinal data.

15.
Am J Respir Crit Care Med ; 199(4): 414-422, 2019 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-30571146

RESUMO

A paradigm shift brought by the recognition that childhood asthma is an aggregated diagnosis that comprises several different endotypes underpinned by different pathophysiology, coupled with advances in understanding potentially important causal mechanisms, offers a real opportunity for a step change to reduce the burden of the disease on individual children, families, and society. Data-driven methodologies facilitate the discovery of "hidden" structures within "big healthcare data" to help generate new hypotheses. These findings can be translated into clinical practice by linking discovered "phenotypes" to specific mechanisms and clinical presentations. Epidemiological studies have provided important clues about mechanistic avenues that should be pursued to identify interventions to prevent the development or alter the natural history of asthma-related diseases. Findings from cohort studies followed by mechanistic studies in humans and in neonatal mouse models provided evidence that environments such as traditional farming may offer protection by modulating innate immune responses and that impaired innate immunity may increase susceptibility. The key question of which component of these exposures can be translated into interventions requires confirmation. Increasing mechanistic evidence is demonstrating that shaping the microbiome in early life may modulate immune function to confer protection. Iterative dialogue and continuous interaction between experts with different but complementary skill sets, including data scientists who generate information about the hidden structures within "big data" assets, and medical professionals, epidemiologists, basic scientists, and geneticists who provide critical clinical and mechanistic insights about the mechanisms underpinning the architecture of the heterogeneity, are keys to delivering mechanism-based stratified treatments and prevention.

16.
Clin Exp Allergy ; 2018 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-30447026

RESUMO

BACKGROUND: Current published asthma predictive tools have moderate positive likelihood ratios (LR+) but high negative likelihood ratios (-LR) based on their recommended cut-offs, which limit their clinical usefulness. OBJECTIVE: To develop a simple clinically applicable asthma prediction tool within a population-based birth cohort. METHOD: Children from the Manchester Asthma and Allergy Study (MAAS) attended follow-up at ages 3, 8 and 11 years. Data on pre-school wheeze was extracted from primary-care records. Parents completed validated respiratory questionnaires. Children were skin prick tested (SPT). Asthma at 8/11 years (school -age) was defined as parentally-reported (1) physician-diagnosed asthma and wheeze in the previous 12 months or (2) ≥3 wheeze attacks in the previous 12 months. An asthma prediction tool (MAAS APT) was developed using logistic regression of characteristics at age 3 years to predict school-age asthma. RESULTS: Of 336 children with physician-confirmed wheeze by age 3 years, 117(35%) had school-age asthma. Logistic regression selected 5 significant risk factors which formed the basis of the MAAS APT: wheeze after exercise; wheeze causing breathlessness; cough on exertion; current eczema and SPT sensitisation(maximum score 5). A total of 281(84%) children had complete data at age 3 years and were used to test the MAAS APT. Children scoring ≥3 were at high risk of having asthma at school-age(PPV>75%; +LR 6.3,-LR 0.6), whereas children who had a score of 0 had very low risk(PPV 9.3%; LR 0.2). CONCLUSION: MAAS APT is a simple asthma prediction tool which could easily be applied in clinical and research settings. This article is protected by copyright. All rights reserved.

17.
PLoS Med ; 15(11): e1002691, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-30422985

RESUMO

BACKGROUND: 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. METHODS AND FINDINGS: 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 Immuno­Solid 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. CONCLUSIONS: Interactions between pairs of sIgE components are associated with increased risk of asthma and may provide the basis for designing diagnostic tools for asthma.

18.
Artigo em Inglês | MEDLINE | ID: mdl-30312503

RESUMO

BACKGROUND: Despite remarkable advances in our understanding of asthma, there are still several unmet needs associated with the management of pediatric asthma. METHODS: A two-day, face-to-face meeting was held in London, United Kingdom, on October 28 and 29, 2017, involving a group of international expert clinicians and scientists in asthma management to discuss the challenges and unmet needs that remain to be addressed in pediatric asthma. RESULTS: These unmet needs include a lack of clinical efficacy and safety evidence, and limited availability of non-steroid-based alternative therapies in patients <6 years of age. An increased focus on children is needed in the context of clinical practice guidelines for asthma; current pediatric practice relies mostly on extrapolations from adult recommendations. Furthermore, no uniform definition of pediatric asthma exists, which hampers timely and robust diagnosis of the condition in affected patients. CONCLUSIONS: There is a need for a uniform definition of pediatric asthma, clearly distinguishable from adult asthma. Furthermore, guidelines which provide specific treatment recommendations for the management of pediatric asthma are also needed. Clinical trials and real-world evidence studies assessing anti-immunoglobulin E (IgE) therapies and other monoclonal antibodies in children <6 years of age with asthma may provide further information regarding the most appropriate treatment options in these vulnerable patients. Early intervention with anti-IgE and non-steroid-based alternative therapies may delay disease progression, leading to improved clinical outcomes.

19.
Elife ; 72018 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-30320550

RESUMO

Events in early life contribute to subsequent risk of asthma; however, the causes and trajectories of childhood wheeze are heterogeneous and do not always result in asthma. Similarly, not all atopic individuals develop wheeze, and vice versa. The reasons for these differences are unclear. Using unsupervised model-based cluster analysis, we identified latent clusters within a prospective birth cohort with deep immunological and respiratory phenotyping. We characterised each cluster in terms of immunological profile and disease risk, and replicated our results in external cohorts from the UK and USA. We discovered three distinct trajectories, one of which is a high-risk 'atopic' cluster with increased propensity for allergic diseases throughout childhood. Atopy contributes varyingly to later wheeze depending on cluster membership. Our findings demonstrate the utility of unsupervised analysis in elucidating heterogeneity in asthma pathogenesis and provide a foundation for improving management and prevention of childhood asthma.

20.
Front Pediatr ; 6: 258, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30298124

RESUMO

Advances in big data analytics have created an opportunity for a step change in unraveling mechanisms underlying the development of complex diseases such as asthma, providing valuable insights that drive better diagnostic decision-making in clinical practice, and opening up paths to individualized treatment plans. However, translating findings from data-driven analyses into meaningful insights and actionable solutions requires approaches and tools which move beyond mining and patterning longitudinal data. The purpose of this review is to summarize recent advances in phenotyping of asthma, to discuss key hurdles currently hampering the translation of phenotypic variation into mechanistic insights and clinical setting, and to suggest potential solutions that may address these limitations and accelerate moving discoveries into practice. In order to advance the field of phenotypic discovery, greater focus should be placed on investigating the extent of within-phenotype variation. We advocate a more cautious modeling approach by "supervising" the findings to delineate more precisely the characteristics of the individual trajectories assigned to each phenotype. Furthermore, it is important to employ different methods within a study to compare the stability of derived phenotypes, and to assess the immutability of individual assignments to phenotypes. If we are to make a step change toward precision (stratified or personalized) medicine and capitalize on the available big data assets, we have to develop genuine cross-disciplinary collaborations, wherein data scientists who turn data into information using algorithms and machine learning, team up with medical professionals who provide deep insights on specific subjects from a clinical perspective.

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