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Published Online First: 13 March 2007. doi:10.1136/thx.2006.064428
Thorax 2007;62:595-601
Copyright © 2007 BMJ Publishing Group Ltd & British Thoracic Society.

CHRONIC OBSTRUCTIVE PULMONARY DISEASE

Profiling serum biomarkers in patients with COPD: associations with clinical parameters

Victor Pinto-Plata1, John Toso2, Kwan Lee2, Daniel Park2, John Bilello2, Hana Mullerova2, Mary M De Souza2, Rupert Vessey2, Bartolome Celli1

1 Pulmonary, Critical Care and Sleep Division, Caritas St Elizabeth’s Medical Center, Tufts University, Boston, Massachusetts, USA
2 Discovery Medicine, High Throughput Biology and Biomedical Data Sciences, GlaxoSmithKline R&D, USA

Correspondence to:
Dr Bartolome R Celli
Caritas St Elizabeth’s Medical Center, 736 Cambridge Street, Boston, Massachusetts 02135, USA; bcelli{at}copdnet.org

Background: Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease associated with significant systemic consequences. Recognition of the systemic manifestations has stimulated interest in identifying circulating biomarkers in these patients. A systematic analysis was undertaken of multiple protein analytes in the serum of well characterised patients with COPD and matched controls using novel protein microarray platform (PMP) technology.

Methods: Forty-eight patients (65% men) with COPD (forced expiratory volume in 1 s <55%) and 48 matched controls were studied. Anthropometric parameters, pulmonary function tests, 6-minute walk distance, the BODE index and the number of exacerbations were measured and the association of these outcomes with the baseline levels of 143 serum biomarkers measured by PMP was explored.

Results: Thirty biomarker clusters were identified and ranked by computing the predictive value of each cluster for COPD (partial least squares discriminant analysis). From the 19 best predictive clusters, 2–3 biomarkers were selected based on their pathophysiological profile (chemoattractants, inflammation, tissue destruction and repair) and the statistical significance of their relationship with clinically important end points was tested. The selected panel of 24 biomarkers correlated (p<0.01) with forced expiratory volume in 1 s, carbon monoxide transfer factor, 6-minute walk distance, BODE index and exacerbation frequency.

Conclusion: PMP technology can be useful in identifying potential biomarkers in patients with COPD. Panels of selected serum markers are associated with important clinical predictors of outcome in these patients.

Abbreviations: AR, amphiregulin; BAL, bronchoalveolar lavage; BDNF, brain-derived neurotropic factor; BMI, body mass index; BODE index, body mass index (B), degree of obstruction (O), perception of dyspnoea (D) and exercise capacity (E); COPD, chronic obstructive pulmonary disease; FDR_p, false discovery adjusted p value; FEV1, forced expiratory volume in 1 s; IFN{gamma}, interferon {gamma}; IL, interleukin; MMP, metalloproteinase; 6MWD, 6-minute walk distance; ßNGF, nerve growth factor ß; PLS-DA, partial least squares discriminant analysis; PMP, protein microarray platform; RCA, rolling cell amplification; TGF{alpha}, tissue growth factor {alpha}; TIMP-1, tissue inhibitor of metalloproteinase 1; TLCO, carbon monoxide transfer factor; TNF{alpha}, tumour necrosis factor {alpha}; VEGF, vascular endothelial growth factor


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