Biomarkers in chronic obstructive pulmonary disease (COPD): Current concerns and future prospects

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Abstract

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome that encompasses a variety of obstructive diseases that differ in terms of the mechanisms and the response to therapy. Accordingly, it seems crucial to identify the distinct disease phenotypes within the range of this syndrome. In recent years there has been a growing interest in the field of biomarkers in COPD. Biomarkers may be local (i.e., measured in induced sputum or exhaled air) or systemic (i.e., measured in serum, plasma, or urine). Several studies are now available on exhaled biomarkers, but data with possible clinical implications are limited, in contrast to the widely used biomarkers of eosinophilic inflammation in asthma. Intense research has evaluated the possible role of systemic biomarkers in the assessment and management of patients with COPD. Data from large cohorts, including the ECLIPSE study, provide information on the association of biomarkers with clinically important parameters, including functional assessments, exacerbations, and mortality. This chapter provides a comprehensive summary of current evidence on exhaled and systemic biomarkers in COPD. The ideal approach is not to measure any single biomarker in order to detect elevated or decreased levels but to try to identify the particular phenotype that is related to the specific biomarker and the underlying mechanism. Most likely a single biomarker is not sufficient, and the combination of more than one may approach more effectively the recognition of the phenotype. The understanding of the pathophysiology of this world epidemic disease is essential to improve the management of these patients as well as to evaluate the plausible effects of new treatment regimens.

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Kostikas, K., Bakakos, P., & Loukides, S. (2015). Biomarkers in chronic obstructive pulmonary disease (COPD): Current concerns and future prospects. In General Methods in Biomarker Research and their Applications (Vol. 2–2, pp. 861–890). Springer International Publishing. https://doi.org/10.1007/978-94-007-7696-8_15

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