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. 2011 Mar;106(3):205-13.
doi: 10.1016/j.anai.2010.11.019. Epub 2011 Jan 14.

Detection of immunological biomarkers correlated with asthma control and quality of life measurements in sera from chronic asthmatic patients

Sangita P Patil  1 , Juan P Wisnivesky, Paula J Busse, Ethan A Halm, Xiu-Min Li
Affiliations

Detection of immunological biomarkers correlated with asthma control and quality of life measurements in sera from chronic asthmatic patients

Sangita P Patil et al. Ann Allergy Asthma Immunol. 2011 Mar.

Abstract

Background: Clinical outcomes of patients with asthma are highly variable. Immunological biomarkers associated with asthma control have not been elucidated.

Objective: To identify the association between clinical control of asthma and serum immunological profiles of asthmatics and compare these profiles with those of healthy controls by using a multiplex assay.

Methods: Sera were obtained from 28 nonsmokers 18 to 55 years of age with moderate and severe persistent asthma. Patients were classified as having well-controlled (WC, n = 14) or poorly controlled (PC, n = 14) asthma based on their responses to the Asthma Control Questionnaire and Asthma Quality of Life Questionnaire. Sera from nonasthmatic control individuals (NAC, n = 14) were used for comparison. Levels of 50 analytes, including cytokines, chemokines, angiogenic, and growth factors, were determined, using a multiplex assay.

Results: Twelve of the 29 cytokines levels were significantly higher in patients with asthma than in NACs, but only interferon gamma levels were significantly lower in patients with asthma than in the NAC group. Among these, interleukin (IL)-3 and IL-18 levels were significantly higher in the PC group than the WC group. Five of the 12 tested chemokine levels were significantly higher in patients with asthma than in NACs. Five of six growth factor levels were significantly higher in patients with asthma than in NACs, and 3 were higher in PC than WC. Interleukin-18, fibroblast growth factor, hepatocyte growth factor, and stem cell growth factor-beta were positively correlated with poor asthma control and negatively with quality of life scores.

Conclusions: Increased serum levels of fibroblast growth factor, hepatocyte growth factor, and stem cell growth factor-beta might be useful biomarkers of asthma control status and targets of future asthma therapy.

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Figures

Figure 1
Figure 1. Serum cytokine Levels of IL-3, IL-18, and correlation of IL-18 with asthma control and quality of life
Serum IL-3 and IL-18, levels were compared in poorly controlled (PC), well controlled (WC) and non-asthmatic controls (NAC) by multiplex assay (A-B). A One Way Anova on ranks with Student-Newman-Keuls correction was used to calculate statistical significance between the three groups and a p< 0.05 was considered statistically significant. Spearman's Rank correlation method was used to calculate the correlation coefficient ‘r’ value. A positive ‘r’ value shows increase in cytokine level correlated with increase in ACQ score (poor control of asthma) and a negative value shows increase in cytokine level correlated with decrease in AQLQ score (poor quality of life). A p< 0.05 value was considered significant. C) Correlation between serum IL-18 levels vs. ACQ score. D) Correlation between IL-18 levels and AQLQ score. ● - PC and ○- WC.
Figure 2
Figure 2. Comparison of serum growth factors FGF-basic, HGF and SCGF-β levels in PC, WC and NAC groups and their correlation with ACQ and AQLQ score
A) Serum growth factors FGF-basic, HGF and SCGF-β levels were compared in poorly controlled (PC), well controlled (WC) and non-asthmatic controls (NAC) by multiplex assay. A One Way Anova with Student-Newman-Keuls correction was used to calculate statistical significance between the three groups and a p< 0.05 was considered statistically significant. Spearman's Rank correlation method was used to calculate the correlation coefficient ‘r’ value. A p< 0.05 value was considered significant. B) Correlation between FGF-basic values and ACQ score. C) Correlation between FGF-basic value and AQLQ score. D) Correlation between HGF value and ACQ score. E) Correlation between HGF value and AQLQ score. F) Correlation between SCGF-β value and ACQ score. G) Correlation between SCGF-β and AQLQ score. ● - PC and ○- WC.
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