Asthma and lower airway disease
Biomarker surrogates do not accurately predict sputum eosinophil and neutrophil percentages in asthmatic subjects

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Background

Sputum 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.

Objectives

We 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.

Methods

Subjects 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.

Results

Despite 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.

Conclusion

Despite 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.

Section snippets

Methods

Subjects with mild-to-severe asthma were comprehensively characterized according to the Severe Asthma Research Program (SARP) phenotype protocol at Wake Forest School of Medicine, as previously described.37 Briefly, nonsmoking subjects (<5 pack years) who met American Thoracic Society criteria for the diagnosis of asthma (enriched for severe asthma) provided informed consent (Wake Forest Institutional Review Board–approved protocol, BG01-425). Evaluation included spirometry, bronchodilator

Subjects' demographics

There were significant differences in lung function, bronchodilator reversibility, symptoms, and health care use for subjects with severe asthma compared with those with mild and moderate asthma (Table I). Age and duration of asthma were increased in subjects with more severe asthma, but there were no differences in atopic measures, including total serum IgE levels, frequency of positive skin test results, number of positive skin test results, serum eosinophil counts, or Feno levels.

Subjects

Discussion

Sputum eosinophilia and neutrophilia are characteristics of bronchial inflammation in asthmatic patients, reflect underlying airway pathology, and are useful in predicting responses to therapeutic interventions.3, 7, 8, 9, 10, 11, 12 Investigators have explored alternative biomarkers as surrogates because of the time-intensive and technically demanding methods for sputum induction, processing, and analysis in clinical settings. The potential usefulness of readily available predictive biomarkers

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    Supported by the National Heart, Lung, and Blood Institute Severe Asthma Research Program Awards HL69167, U10HL109164, and RC2HL101487.

    Disclosure of potential conflict of interest: A. T. Hastie, W. C. Moore, B. M Rector, and D. A. Meyers have received grants from the National Heart, Lung, and Blood Institute (NHLBI). R. M. Pascual has consultant arrangements with United Therapeutics and has received grants from Actelion. S. P. Peters has received a grant and travel support from the National Institutes of Health (NIH)/NHLBI; has served on advisory boards for AstraZeneca, Aerocrine, Merck, Targacept, and TEVA; has received payment for lectures from Merck and Integrity CE; and has received royalties from UpToDate. E. R. Bleecker has received grants and travel support from the NIH/NHLBI. The rest of the authors declare that they have no relevant conflicts of interest.

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