Title |
Blood and sputum eosinophils in COPD; relationship with bacterial load
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Published in |
Respiratory Research, May 2017
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DOI | 10.1186/s12931-017-0570-5 |
Pubmed ID | |
Authors |
Umme Kolsum, Gavin C. Donaldson, Richa Singh, Bethan L. Barker, Vandana Gupta, Leena George, Adam J. Webb, Sarah Thurston, Anthony J Brookes, Timothy D. McHugh, Jadwiga A. Wedzicha, Christopher E. Brightling, Dave Singh |
Abstract |
Sputum and blood eosinophil counts predict corticosteroid effects in COPD patients. Bacterial infection causes increased airway neutrophilic inflammation. The relationship of eosinophil counts with airway bacterial load in COPD patients is uncertain. We tested the hypothesis that bacterial load and eosinophil counts are inversely related. COPD patients were seen at stable state and exacerbation onset. Sputum was processed for quantitative polymerase chain reaction detection of the potentially pathogenic microorganisms (PPM) H. influenzae, M. catarrhalis and S. pneumoniae. PPM positive was defined as total load ≥1 × 10(4)copies/ml. Sputum and whole blood were analysed for differential cell counts. At baseline, bacterial counts were not related to blood eosinophils, but sputum eosinophil % was significantly lower in patients with PPM positive compared to PPM negative samples (medians: 0.5% vs. 1.25% respectively, p = 0.01). Patients with PPM positive samples during an exacerbation had significantly lower blood eosinophil counts at exacerbation compared to baseline (medians: 0.17 × 10(9)/L vs. 0.23 × 10(9)/L respectively, p = 0.008), while no blood eosinophil change was observed with PPM negative samples. These findings indicate an inverse relationship between bacterial infection and eosinophil counts. Bacterial infection may influence corticosteroid responsiveness by altering the profile of neutrophilic and eosinophilic inflammation. |
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Geographical breakdown
Country | Count | As % |
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United Kingdom | 4 | 57% |
Australia | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
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Members of the public | 6 | 86% |
Scientists | 1 | 14% |
Mendeley readers
Geographical breakdown
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Unknown | 91 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 12 | 13% |
Other | 11 | 12% |
Student > Ph. D. Student | 9 | 10% |
Student > Bachelor | 7 | 8% |
Student > Master | 5 | 5% |
Other | 18 | 20% |
Unknown | 29 | 32% |
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Immunology and Microbiology | 7 | 8% |
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 5% |
Biochemistry, Genetics and Molecular Biology | 4 | 4% |
Nursing and Health Professions | 4 | 4% |
Other | 7 | 8% |
Unknown | 33 | 36% |