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Clinical utility of asthma biomarkers: from bench to bedside
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Authors: Vijverberg SJH, Hilvering B, Raaijmakers JA, Lammers JW, Maitland-van der Zee AH, Koenderman L
Published Date August 2013
Volume 2013:7 Pages 199 - 210
|Received:||10 April 2013|
|Accepted:||29 May 2013|
|Published:||29 August 2013|
1Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands; 2Department of Respiratory Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands
*These authors contributed equally to this work
Abstract: Asthma is a chronic disease characterized by airway inflammation, bronchial hyperresponsiveness, and recurrent episodes of reversible airway obstruction. The disease is very heterogeneous in onset, course, and response to treatment, and seems to encompass a broad collection of heterogeneous disease subtypes with different underlying pathophysiological mechanisms. There is a strong need for easily interpreted clinical biomarkers to assess the nature and severity of the disease. Currently available biomarkers for clinical practice – for example markers in bronchial lavage, bronchial biopsies, sputum, or fraction of exhaled nitric oxide (FeNO) – are limited due to invasiveness or lack of specificity. The assessment of markers in peripheral blood might be a good alternative to study airway inflammation more specifically, compared to FeNO, and in a less invasive manner, compared to bronchoalveolar lavage, biopsies, or sputum induction. In addition, promising novel biomarkers are discovered in the field of breath metabolomics (eg, volatile organic compounds) and (pharmaco)genomics. Biomarker research in asthma is increasingly shifting from the assessment of the value of single biomarkers to multidimensional approaches in which the clinical value of a combination of various markers is studied. This could eventually lead to the development of a clinically applicable algorithm composed of various markers and clinical features to phenotype asthma and improve diagnosis and asthma management.
Keywords: asthma, airway inflammation, biological markers, pharmacogenomics, metabolomics
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