The Role of Interleukin-13 in Chronic Airway Diseases: A Cross-Sectional Study in COPD and Asthma-COPD Overlap

Abstract

Background: Distinguishing chronic obstructive pulmonary disease (COPD) from asthma-COPD overlap (ACO) remains challenging due to shared clinical and inflammatory features. Interleukin-13 (IL-13) is implicated in airway inflammation and remodeling and may represent a potential treatable trait. This study aimed to evaluate whether serum IL-13 could differentiate between COPD and ACO or define ACO subtypes and to explore its relationship with clinical and phenotype parameters.

Materials and methods: We conducted a cross-sectional bicentric study in 215 COPD and ACO patients recruited from outpatient clinics. The study measured blood IL-13 levels in COPD vs. ACO patients, across five ACO subtypes, and evaluated IL-13's ability to predict ACO. Additionally, correlations were explored among endotype (IL-13) and different phenotype traits (e.g., fractional exhaled nitric oxide (FeNO), sputum eosinophilia, serum total immunoglobulin E (tIgE) levels, blood eosinophilia, and neutrophilia) and clinical outcomes (annualized exacerbation rate, symptom scores, and pulmonary function parameters).

Results: No significant differences in IL-13 levels were found between COPD and ACO patients or among ACO subtypes. IL-13 did not predict ACO occurrence. We observed a weak correlation between IL-13 and tIgE levels in the entire cohort. Additionally, there was a weak correlation between IL-13 and FeNO in patients with eosinophil counts exceeding 300 cells/μL, as well as between IL-13 and age in the COPD cohort. No correlation was found between IL-13 and other phenotypic features or clinical outcomes in the overall cohort, including within both COPD and ACO groups.

Conclusions: IL-13 cannot differentiate between COPD and ACO or ACO's subtypes.

Keywords: ACO; COPD; endotype; interleukin-13; phenotype; treatable traits.

Figure 1

Flow diagram illustrating patient selection and data completeness in the study.

Figure 2

Differences in therapy between COPD and ACO groups.

Figure 3

Correlelogram of measured variables (Spearman’s correlation). Colors indicate the strength and direction of correlation coefficients (r), ranging from strong positive (red) to no correlation (green) and strong negative (blue). Numbers in the cells represent correlation coefficients (r) with corresponding p-values and sample size (n).