Sputum cell IL-1 receptor expression level is a marker of airway neutrophilia and airflow obstruction in asthmatic patients

Abstract

Background: Various clinical, biologic, or physiologic markers of asthma have been used to identify patient clusters and potential targets for therapy. However, these identifiers frequently overlap among the different asthma groups. For instance, both eosinophil and neutrophil counts are often increased in the airways of asthmatic patients despite their typical association with type 2 and type 17 immune response, respectively.

Objectives: We sought to determine whether inflammatory gene expression is related to patterns of airway inflammation and lung function and identify molecular markers for neutrophilic asthma.

Methods: Expression levels of 17 genes characterizing type 1, type 2, and type 17 lymphocytes were measured in sputum samples from 48 participants with asthma. The relationships between gene expression levels and sputum cell differentials or measures of pulmonary function were examined by using partial least squares regression.

Results: Gene expression levels were strongly associated with cell differentials, explaining 71% of variation in eosinophil counts and 64% of variation in neutrophil counts. The 3 genes with the strongest relationships to sputum neutrophil counts were IL1R1 (standardized regression coefficient [β] = +0.27, P = .005), IL1RAP (β = +0.32, P = .0004), and IL4R (β = +0.29, P = .002). Higher expression levels of IL1R1, IL1RAP, and IL4R were associated with reduced FEV₁/forced vital capacity ratio (β = -0.11, -0.08, and -0.10; P = .005, .07, and .05).

Conclusion: IL-1 receptor appears to be a marker of neutrophilic inflammation and airflow obstruction in patients with asthma, who have a wide range of disease severity. The IL-1 pathway might contribute to airway neutrophilia and is a potential therapeutic target in patients with neutrophilic asthma.

Keywords: Asthma; IL-1 receptor; lymphocyte; neutrophil; partial least squares; pulmonary function; sputum samples; type 1; type 17; type 2.

Figure 1. Correlation plot of sputum gene expression, sputum cell differentials, and pulmonary function measures

Visualization of the correlations between each pair of variables. Variables are grouped by: gene expression levels, sputum inflammatory cells, and pulmonary function measurements. Similar variables are placed adjacently using correlation-based variable ordering. Stronger correlations are represented by darker colors and larger circles. Blue indicates positive correlation and red indicates negative correlation.

Figure 2. Loadings plot for the three orthogonal latent components

Structure of the three independent components of the PLS regression analysis of gene expression levels vis-à-vis cell differentiation in sputum A. X loadings (genes) and the corresponding Y loadings (cells) for the first component. B. X and Y loadings for the second component. C. X and Y loadings for the third component. D. X and Y loadings for the second component (horizontal axis) and third component (vertical axis).

Figure 3. Regression coefficients for gene expression level and sputum cell PLS model with approximate 95% confidence intervals

Standardized regression coefficients; for example, a 1 standard deviation (SD) increase in IL1RAP expression is associated with a 0.33 SD increase in neutrophils. Coefficient direction is represented by color, with blue and red indicating positive and negative relationships, respectively. Larger coefficients are represented by darker colors. The ordering of the genes is carried over from Figure 1.

Figure 4. Regression coefficients for gene expression level and pulmonary function PLS models with approximate 95% confidence intervals

Standardized regression coefficients. Coefficient direction is represented by color, with blue and red indicating positive and negative relationships, respectively. Larger coefficients are represented by darker colors. The ordering of the genes is carried over from Figure 1.