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Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control.

ABSTRACT: BACKGROUND:Recent studies have used cluster analysis to identify phenotypic clusters of asthma with differences in clinical traits, as well as differences in response to therapy with anti-inflammatory medications. However, the correspondence between different phenotypic clusters and differences in the underlying molecular mechanisms of asthma pathogenesis remains unclear. OBJECTIVE:We sought to determine whether clinical differences among children with asthma in different phenotypic clusters corresponded to differences in levels of gene expression. METHODS:We explored differences in gene expression profiles of CD4(+) lymphocytes isolated from the peripheral blood of 299 young adult participants in the Childhood Asthma Management Program study. We obtained gene expression profiles from study subjects between 9 and 14 years of age after they participated in a randomized, controlled longitudinal study examining the effects of inhaled anti-inflammatory medications over a 48-month study period, and we evaluated the correspondence between our earlier phenotypic cluster analysis and subsequent follow-up clinical and molecular profiles. RESULTS:We found that differences in clinical characteristics observed between subjects assigned to different phenotypic clusters persisted into young adulthood and that these clinical differences were associated with differences in gene expression patterns between subjects in different clusters. We identified a subset of genes associated with atopic status, validated the presence of an atopic signature among these genes in an independent cohort of asthmatic subjects, and identified the presence of common transcription factor binding sites corresponding to glucocorticoid receptor binding. CONCLUSION:These findings suggest that phenotypic clusters are associated with differences in the underlying pathobiology of asthma. Further experiments are necessary to confirm these findings.

SUBMITTER: Howrylak JA

PROVIDER: S-EPMC4860055 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control.

Howrylak Judie A JA Moll Matthew M Weiss Scott T ST Raby Benjamin A BA Wu Wei W Xing Eric P EP

The Journal of allergy and clinical immunology 20160112 5

<h4>Background</h4>Recent studies have used cluster analysis to identify phenotypic clusters of asthma with differences in clinical traits, as well as differences in response to therapy with anti-inflammatory medications. However, the correspondence between different phenotypic clusters and differences in the underlying molecular mechanisms of asthma pathogenesis remains unclear.<h4>Objective</h4>We sought to determine whether clinical differences among children with asthma in different phenotyp ...[more]

PMID: 26792209

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Project description:BackgroundLittle is known about the concordance of atopy with asthma COPD overlap. Among individuals with COPD, a better understanding of the phenotypes characterized by asthma overlap and atopy is needed to better target therapies.Research questionWhat is the overlap between atopy and asthma status among individuals with COPD, and how are categories defined by the presence of atopy and asthma status associated with clinical and radiologic phenotypes and outcomes in the Genetic Epidemiology of COPD Study (COPDGene) and Subpopulation and Intermediate Outcome Measures in COPD Study (SPIROMICS)?Study design and methodsFour hundred three individuals with COPD from SPIROMICS and 696 individuals from COPDGene with data about specific IgEs to 10 common allergens and mixes (simultaneous assessment of combination of allergens in similar category) were included. Comparison groups were defined by atopic and asthma status (neither, atopy alone, atopic asthma, nonatopic asthma, with atopy defined as any positive specific IgE (≥0.35 KU/L) to any of the 10 allergens or mixes and asthma defined as self-report of doctor-diagnosed current asthma). Multivariable regression analyses (linear, logistic, and zero inflated negative binomial where appropriate) adjusted for age, sex, race, lung function, smoking status, pack-years smoked, and use of inhaled corticosteroids were used to determine characteristics of groups and relationship with outcomes (exacerbations, clinical outcomes, CT metrics) separately in COPDGene and SPIROMICS, and then adjusted results were combined using meta-analysis.ResultsThe prevalence of atopy was 35% and 36% in COPD subjects from SPIROMICS and COPDGene, respectively, and less than 50% overlap was seen between atopic status with asthma in both cohorts. In meta-analysis, individuals with nonatopic asthma had the most impaired symptom scores (effect size for St. George's Respiratory Questionnaire total score, 4.2; 95% CI, 0.4-7.9; effect size for COPD Assessment Test score, 2.8; 95% CI, 0.089-5.4), highest risk for exacerbations (incidence rate ratio, 1.41; 95% CI, 1.05-1.88) compared with the group without atopy or asthma. Those with atopy and atopic asthma were not at increased risk for adverse outcomes.InterpretationAsthma and atopy had incomplete overlap among former and current smokers with COPD in COPDGene and SPIROMICS. Nonatopic asthma was associated with adverse outcomes and exacerbation risk in COPD, whereas groups having atopy alone and atopic asthma had less risk.

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Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control.

Publications

Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control.

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