Differential serum protein markers and the clinical severity of asthma
Norbert Meyer,1,2 Sarah Janine Nuss,1 Thomas Rothe,1 Alexander Siebenhüner,1 Cezmi A Akdis,2 Günter Menz1
1Hochgebirgsklinik Davos, Davos-Wolfgang, Switzerland; 2Swiss Institute of Allergy and Asthma Research (SIAF), Davos Platz, Switzerland
Background: Asthma is a heterogeneous disease characterized by different clinical phenotypes and the involvement of multiple inflammatory pathways. During airway inflammation, many cytokines and chemokines are released and some are detectable in the sera.
Objective: Serum chemokines and cytokines, involved in airway inflammation in asthma patients, were investigated.
Methods: A total of 191 asthma patients were classified by hierarchical cluster analysis, including the following parameters: forced expiratory volume in 1 second (FEV1), eosinophil cationic protein (ECP) serum levels, blood eosinophils, Junipers asthma symptom score, and the change in FEV1, ECP serum levels, and blood eosinophils after 3 weeks of asthma therapy. Serum proteins were measured by multiplex analysis. Receiver operating characteristic (ROC) curves were used to evaluate the validity of serum proteins for discriminating between asthma clusters.
Results: Classification of asthma patients identified one cluster with high ECP serum levels, increased blood eosinophils, low FEV1 values, and good FEV1 improvement in response to asthma therapy (n=60) and one cluster with low ECP serum levels, low numbers of blood eosinophils, higher FEV1 values, and no FEV1 improvement in response to asthma therapy (n=131). Serum interleukin (IL)-8, eotaxin, vascular endothelial growth factor (VEGF), cutaneous T-cell-attracting chemokine (CTACK), growth-related oncogene (GRO)-α, and hepatocyte growth factor (HGF) were significantly different between the two clusters of asthma patients. ROC analysis for serum proteins calculated a sensitivity of 55.9% and specificity of 75.8% for discriminating between them.
Conclusion: Serum cytokine and chemokine levels might be predictors for the severity of asthmatic inflammation, asthma control, and response to therapy, and therefore might be useful for treatment optimization.
Keywords: asthma, cluster, phenotype, serum cytokines
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