[Characterization of asthma phenotypes in children of the tropics]

OBJECTIVE

Determine the main asthma phenotypes in a population of asthmatic children in Cartagena, Colombia.

METHODS

107 children (7 to 17 years old) with a previous diagnosis of asthma were recruited. Biomarkers of T2 inflammation were evaluated by measuring FeNO, eosinophil count in peripheral blood by hemocytometry, and determination of specific IgE to mite allergens by ELISA. The study was approved by the ethics committee of the University of Cartagena (SGR, Grant BPIN2020000100405).

RESULTS

The average age of patients was 10,9 years. 19,6% of the children did not show elevation of any of the T2 inflammation biomarkers evaluated (FeNO<20ppb, eos<300/ul, negative specific IgE), so they were considered patients with non-allergic asthma (non-T2). 71,9% of all patients were sensitized to at least one allergen, this phenotype was considered allergic asthma. 30,8% of the patients presented the three elevated biomarkers (FeNO>20ppb + eos >300/ul + positive specific IgE), this phenotype was classified as high T2 allergic asthma. A moderate correlation (Spearman rho=0,44, p<0,0001) was found between FeNO values and eosinophil counts.

CONCLUSION

In this study, the following phenotypes were found: allergic asthma, high T2 asthma, and non-allergic asthma. Most patients presented a type 2 inflammatory phenotype with allergic sensitization. In addition to the measurement of specific IgE, the use of FeNO and eosinophil count in peripheral blood help to accurately determine those patients with high T2 asthma phenotypes.

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization

OBJECTIVE

Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. This study aimed to investigate different machine learning models and suggested the most effective one to classify two forms of asthma in preschool children (predominantly allergic asthma and non-allergic asthma) using a minimum number of features.

METHODS

After pre-processing, 127 patients (70 with non-allergic asthma and 57 with predominantly allergic asthma) were chosen for final analysis from the Frankfurt dataset, which had asthma-related information on 205 patients. The Random Forest algorithm and Chi-square were used to select the key features from a total of 63 features. Six machine learning models: random forest, extreme gradient boosting, support vector machines, adaptive boosting, extra tree classifier, and logistic regression were then trained and tested using 10-fold stratified cross-validation.

RESULTS

Among all features, age, weight, C-reactive protein, eosinophilic granulocytes, oxygen saturation, pre-medication inhaled corticosteroid + long-acting beta2-agonist (PM-ICS + LABA), PM-other (other pre-medication), H-Pulmicort/celestamine (Pulmicort/celestamine during hospitalization), and H-azithromycin (azithromycin during hospitalization) were found to be highly important. The support vector machine approach with a linear kernel was able to diffrentiate between predominantly allergic asthma and non-allergic asthma with higher accuracy (77.8%), precision (0.81), with a true positive rate of 0.73 and a true negative rate of 0.81, a F1 score of 0.81, and a ROC-AUC score of 0.79. Logistic regression was found to be the second-best classifier with an overall accuracy of 76.2%.

CONCLUSION

Predominantly allergic and non-allergic asthma can be classified using machine learning approaches based on nine features.

Supplemental data for this article is available online at at www.tandfonline.com/ijas .

Associations of TNFA, IL17A, and RORC mRNA expression levels in peripheral blood leukocytes with obesity-related asthma in adolescents

Obesity is associated with a unique non-T2 asthma phenotype, characterised by a Th17 immune response. Retinoid-related orphan receptor C (RORC) is the master transcription factor for Th17 polarisation. We investigated the association of TNFA, IL17A, and RORC mRNA expression levels with the non-T2 phenotype. We conducted a cross-sectional study in adolescents, subdivided as follows: healthy (HA), allergic asthma without obesity (AA), obesity without asthma (OB), and non-allergic asthma with obesity (NAO). TNFA, IL17A, and RORC mRNA expression in peripheral blood leukocytes were assessed by RT-PCR. NAO exhibited higher TNFA mRNA expression levels than HA or OB, as well as the highest IL17A and RORC mRNA expression levels among the four groups. The best biomarker for discriminating non-allergic asthma among obese adolescents was RORC mRNA expression levels (area under the curve: 0.95). RORC mRNA expression levels were associated with the non-T2 asthma phenotype, hinting at a therapeutic target in obesity-related asthma.

Women using bleach for home cleaning are at increased risk of non-allergic asthma

BACKGROUND

Bleach is widely used for household cleaning. Although it is recognized that occupational use of bleach may have adverse respiratory health effects, it is unknown whether common domestic use of bleach may be a risk factor for asthma.

AIM

To assess whether the domestic use of bleach for home cleaning is associated with asthma and other respiratory outcomes.

METHODS

Questionnaire-based information on respiratory symptoms and cleaning habits and data from skin prick-tests, bronchial responsiveness challenge and white blood cells were analyzed in 607 women participating in the follow-up of the Epidemiological Study on the Genetics and Environment of Asthma (EGEA). Bleach use was evaluated in 3 categories (<1 day/week; 1-3 days/week; 4-7 days/week "frequent").

RESULTS

Overall, 37% of the women reported using bleach weekly. Women using bleach frequently (11%) were more likely to have current asthma as compared to non-users (adjusted Odds-Ratio (aOR) = 1.7; 95% Confidence Interval (95%CI) 1.0-3.0). Among women with asthma, frequent use of bleach was significantly associated with higher blood neutrophil cell counts. Bleach use was significantly associated with non-allergic asthma (aOR 3.3; 95%CI 1.5-7.1), and more particularly with non-allergic adult-onset asthma (aOR 4.9; 95%CI 2.0-11.6). Consistently, among women without allergic sensitization, significant positive associations were found between use of bleach and bronchial hyperresponsiveness, asthma like-symptoms and chronic cough. No association was observed for allergic asthma.

CONCLUSIONS

Frequent use of bleach for home-cleaning is associated with non-allergic adult-onset asthma, elevated neutrophil counts and lower-airway symptoms in women.

The roles of innate lymphoid cells in the development of asthma

Asthma is a common pulmonary disease with several different forms. The most studied form of asthma is the allergic form, which is mainly related to the function of Th2 cells and their production of cytokines (IL-4, IL-5, and IL-13) in association with allergen sensitization and adaptive immunity. Recently, there have been many advances in understanding non-allergic asthma, which seems to be related to environmental factors such as air pollution, infection, or even obesity. Cells of the innate immune system, including macrophages, neutrophils, and natural killer T cells as well as the newly described innate lymphoid cells, are effective producers of a variety of cytokines and seem to play important roles in the development of non-allergic asthma. In this review, we focus on recent findings regarding innate lymphoid cells and their roles in asthma.