Sputum inflammatory, neural, and remodelling mediators in eosinophilic and non-eosinophilic asthma

Clinical Significance of Combined Detection of CCL22 and IL-1 as Potential New Bronchial Inflammatory Mediators in Children's Asthma

BACKGROUNDS

Severe asthma is a significant health burden because children with severe asthma are vulnerable to medication-related side effects, life-threatening deterioration, and impaired quality of life. However, there is a lack of data to elucidate the role of inflammatory variables in asthma. This study aimed to compare the levels of inflammatory factors in serum and sputum in children with acute and stable asthma to those in healthy children and the ability to predict clinical response to azithromycin therapy.

METHODS

This study recruited 95 individuals aged 1-3 years old and collected data from January 2018 to 2020. We examined serum and sputum inflammatory factors and constructed the least absolute shrinkage and selection operator (LASSO) model. Predictive models were constructed through multifactor logistic regression and presented in the form of column-line plots. The performance of the column-line diagrams was measured by subject work characteristics (ROC) curves, calibration plots, and decision curve analysis (DCA). Then, filter-paper samples were collected from 45 children with acute asthma who were randomly assigned to receive either azithromycin (10 mg/kg, n = 22) or placebo (n = 23). Pretreatment levels of immune mediators were then analyzed and compared with clinical response to azithromycin therapy.

RESULTS

Of the 95 eligible participants, 21 (22.11%) were healthy controls, 29 (30.53%) had stable asthma, and 45 (47.37%) had acute asthma. The levels of interferon-γ (IFN-γ), tumor necrosis factor-a (TNF-α), chemokine CCL22 (CCL22), interleukin 12 (IL-12), chemokine CCL4 (CCL4), chemokine CCL2 (CCL2), and chemokine CCL13 (CCL13）were significantly higher in the acute asthma group than in the stable asthma group. A logistic regression analysis was performed using CCL22 and IL-1 as independent variables. Additionally, IFN-γ, TNF-α, IL-1, IL-13, and CCL22 were identified in the LASSO model. Finally, we found that CCL22 and IL-1 were more responsive in predicting the response to azithromycin treatment.

CONCLUSION

Our results show that CCL22 and IL-1 are both representative markers during asthma symptom exacerbations and an immune mediator that can predict response to azithromycin therapy.

Asthma Inflammatory Phenotypes: How Can We Distinguish Them?

BACKGROUND AND OBJECTIVES

induced sputum is used to assess different inflammatory phenotypes in asthma, but is not used routinely. We aimed to determine the proportion of inflammatory asthma phenotypes based on induced sputum, to find biomarkers that can discriminate between phenotypes, and to evaluate biomarkers in patients with and without biological therapy in different inflammatory asthma phenotypes.

MATERIALS AND METHODS

this cross-sectional study investigated clinical characteristics, asthma control tests, skin prick test, impulse oscillometry (IOS), spirometry, induced sputum, biomarkers (IgE, eosinophils, fractional exhaled nitric oxide (FeNO), serum periostin, IL-5, IL-6, IL-8, IL-17A, IL-33) in 80 asthmatics. A total of 17/80 patients were treated with biologics (10 with omalizumab, 7 with benralizumab).

RESULTS

a total of 31% of patients had eosinophilic asthma (EA), 30% had mixed granulocytic asthma (MGA), 24% had paucigranulocytic asthma (PGA), and 15% had neutrophilic asthma (NA). The difference was found in blood eosinophils (p = 0.002), the highest observed in EA. The cut-off ≥ 240/μL eosinophils, with 64% sensitivity and 72.7% specificity, identified EA (AUC = 0.743, p = 0.001). A higher IL-8 level was associated with NA (p = 0.025). In 63 non-biologic asthma group, eosinophils were higher in EA than in NA, MGA, and PGA (p = 0.012, p = 0.028, and p = 0.049, respectively). A higher IL-17A was associated with EA without biologics (p = 0.004). A significantly higher IL-5 was found in EA treated with biologics, in comparison with EA without biologics (p = 0.043). The number of leucocytes and neutrophils was higher in MGA without biologics (p = 0.049, p = 0.019), while IL-5, IL-6, and IL-8 levels were higher in MGA treated with biologics (p = 0.012, p = 0.032, p = 0.038, respectively).

CONCLUSIONS

EA and MGA were the most prevalent asthma phenotypes. Blood eosinophils can identify EA, both in patients with and without biologics. Apart from the clinical profile, a broad spectrum of biomarkers for assessing inflammatory phenotypes is necessary for an adequate therapy approach to patients with asthma.