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Induced sputum proteome in healthy subjects and asthmatic patients.

ABSTRACT: Asthma is a heterogeneous disease characterized by abnormal airway pathophysiology and susceptibility to different stimuli, as exemplified by a subset of patients with exercise-induced bronchoconstriction. Induced sputum provides a noninvasive method to sample airway biofluids that are enriched in proteins.We hypothesized that novel mechanisms in the pathogenesis of asthma might be revealed by studying the patterns of protein expression in induced sputum.We used shotgun proteomics to analyze induced sputum from 5 healthy subjects and 10 asthmatic patients, including 5 with exercise-induced bronchoconstriction. Differential protein expression among asthmatic patients, asthma subphenotypes, and control subjects was determined by using spectral counting and computational methods.Using Gene Ontology analysis, we defined the functional landscape of the induced sputum proteome and applied network analysis to construct a protein interaction map for this airway compartment. Shotgun proteomics analysis identified a number of proteins the differential enrichment or depletion of which robustly distinguished asthmatic patients from healthy control subjects and captured the effects of exercise on induced sputum proteome. Functional and network analysis identified key processes, including proteolytic activity, that are known contributors to airway remodeling. Importantly, this approach highlighted previously unrecognized roles for differentially expressed proteins in pathways implicated in asthma, such as modulation of phospholipase A(2) by secretoglobin, a putative role for S100A8/9 in human asthma, and selective upregulation of complement component 3a in response to exercise in asthmatic patients.Computationally intensive analysis of induced sputum proteome is a powerful approach to understanding the pathophysiology of asthma and a promising methodology to investigating other diseases of the airways.

SUBMITTER: Gharib SA

PROVIDER: S-EPMC4065239 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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Induced sputum proteome in healthy subjects and asthmatic patients.

Gharib Sina A SA Nguyen Elizabeth V EV Lai Ying Y Plampin Jessica D JD Goodlett David R DR Hallstrand Teal S TS

The Journal of allergy and clinical immunology 20110908 6

<h4>Background</h4>Asthma is a heterogeneous disease characterized by abnormal airway pathophysiology and susceptibility to different stimuli, as exemplified by a subset of patients with exercise-induced bronchoconstriction. Induced sputum provides a noninvasive method to sample airway biofluids that are enriched in proteins.<h4>Objective</h4>We hypothesized that novel mechanisms in the pathogenesis of asthma might be revealed by studying the patterns of protein expression in induced sputum.<h4> ...[more]

PMID: 21906793

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Project description:BackgroundSputum eosinophil percentages are a strong predictor of airway inflammation and exacerbations and aid asthma management, whereas sputum neutrophil percentages indicate a different severe asthma phenotype that is potentially less responsive to TH2-targeted therapy. Variables, such as blood eosinophil counts, total IgE levels, fraction of exhaled nitric oxide (Feno) levels, or FEV1 percent predicted, might predict airway eosinophil percentages, whereas age, FEV1 percent predicted, or blood neutrophil counts might predict sputum neutrophil percentages. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway eosinophil and neutrophil percentages either individually or combined is not established.ObjectivesWe sought to determine whether blood eosinophil counts, Feno levels, and IgE levels accurately predict sputum eosinophil percentages and whether age, FEV1 percent predicted, and blood neutrophil counts accurately predict sputum neutrophil percentages.MethodsSubjects in the Wake Forest Severe Asthma Research Program (n = 328) were characterized by blood and sputum cell counts, health care use, lung function, Feno levels, and IgE levels. Multiple analytic techniques were used.ResultsDespite significant association with sputum eosinophil percentages, blood eosinophil counts, Feno levels, and total IgE levels did not accurately predict sputum eosinophil percentages, and combinations of these variables did not improve prediction. Age, FEV1 percent predicted, and blood neutrophil counts were similarly unsatisfactory for the prediction of sputum neutrophil percentages. Factor analysis and stepwise selection found Feno levels, IgE levels, and FEV1 percent predicted, but not blood eosinophil counts, correctly predicted 69% of sputum eosinophil percentages of less than 2% or 2% and greater. Likewise, age, asthma duration, and blood neutrophil counts correctly predicted 64% of sputum neutrophil percentages of less than 40% or 40% and greater. A model to predict both sputum eosinophil and neutrophil percentages accurately assigned only 41% of samples.ConclusionDespite statistically significant associations, Feno levels, IgE levels, blood eosinophil and neutrophil counts, FEV1 percent predicted, and age are poor surrogates, both separately and combined, for accurately predicting sputum eosinophil and neutrophil percentages.

Dataset Information

Induced sputum proteome in healthy subjects and asthmatic patients.

Publications

Induced sputum proteome in healthy subjects and asthmatic patients.

Similar Datasets

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