Interaction of Atopy and Airway Dysbiosis Promotes Asthma Persistence in Children With Chronic Rhinosinusitis—5 Years Prospective Study
Funding: The study was financed by a grant from the Polpharma Scientific Foundation (5/XIX/2020).
Summary
- Atopy and reduced biodiversity of the nasal microbiome synergistically increase the risk of asthma persistence
- Synergy between nasal dysbiosis and atopy in predicting asthma persistence suggests a possible immunological interplay.
Both epidemiological and mechanistic studies have confirmed a close relationship between chronic rhinosinusitis (CRS) and asthma. The underlying mechanism involves complex interactions between epithelial barrier dysfunction, dysbiosis (especially reduced biodiversity), and the immune response, particularly the innate system, including alarmins and lymphoid cells [1]. Long-term observations indicate a significant remission rate of asthma in early childhood. Although risk factors for its persistence have been identified, the topic of early childhood asthma persistence remains relatively unexplored [2].
We aimed to investigate the clinical, immunological, and microbiological factors contributing to asthma persistence from preschool to school age.
This study was based on a prospective, multi-omix study, The Response of the Airway in Sinusitis and Asthma (RAISe) conducted in children with rhinosinusitis and asthma [3]. A total of 133 children aged 4–8 years with CRS, diagnosed by otorhinolaryngologists according to EPOS (European Position Paper on Rhinosinusitis and Nasal Polyps) criteria (clinical history and nasal endoscopy), were enrolled. Asthma diagnosis was made by a paediatric pulmonologist based on clinical symptoms and clinical improvement during anti-inflammatory therapy (100% of participants) and/or a positive bronchial reversibility test (11% of participants). Various exclusion criteria were included to minimise the bias of the results, for example, adenoid hypertrophy, confirmed immunodeficiency, obesity, exposure to tobacco smoke, or intranasal corticosteroids within 4 weeks. Written informed consent was obtained from all patients and their parents before any procedures. At baseline, the following procedures were performed in all patients: standardised questionnaire—Sinus and Nasal Quality of Life Survey (SN-5), nasopharynx swab for microbiome analysis by next-generation sequencing (NGS) methods, and nasal mucosa sampling for mRNA expression of predefined molecules and the abundance of innate lymphoid cells (ILCs). During a further 5-year prospective follow-up, the final diagnosis of asthma was made based on clinical history, symptoms, physical findings, and variable airflow obstruction as suggested by the Global Initiative for Asthma (GINA) report.
Of the 133 children in the RAISE cohort, 117 completed 5 years of prospective follow-up. Initially, asthma was diagnosed in 82 children, 74 of whom were prospectively followed. After 5 years of prospective follow-up, asthma persisted in 23% (17 of 74) of the children, whereas 77% (57 of 74) experienced remission.
Receiver operating characteristic (ROC) curve analysis revealed a significant association between persistent asthma and the Shannon index (a measure of biodiversity) of the nasopharynx microbiome (AUC = 0.7, 95% CI: 0.5–0.9; p = 0.01). Additionally, the optimal cut-off for the Shannon index was calculated. Consequently, the Shannon index below 4.564 was defined as reduced biodiversity of the upper airway microbiome, while the Shannon index above or equal to 4.564 was defined as average biodiversity. Asthma persistence vs. remission was included as a dependent variable in the logistic regression analysis to search for potential variables influencing the clinical course of asthma in young children (Table 1A). A multivariate model of logistic regression analysis showed that the persistence of asthma in young children was independently associated with atopy (defined as a positive skin prick test and/or presence of serum IgE specific to inhaled allergens of which house dust mite had the strongest prediction) (OR = 8.5, 95% CI: 1.7–43) and reduced biodiversity of the upper airway microbiome (OR = 6.0, 95% CI: 1.7–22). Reduced biodiversity concomitant with atopy was associated with increased positive predictive value and consequently improved accuracy of the prediction of asthma persistence in young children.
(A) Coefficient | Asthma remission n = 57 | Asthma persistent n = 17 | p level | ORa | 95% CI | |||
---|---|---|---|---|---|---|---|---|
N | % | N | % | |||||
Age (years) ≥ 7b | 16 | 28% | 6 | 35% | 0.5405 | 1.43 | 0.45 | 4.52 |
Male gender | 35 | 60% | 11 | 65% | 0.7456 | 1.20 | 0.39 | 3.71 |
BMI (kg/m2) > median | 40 | 70% | 11 | 65% | 0.7672 | 0.78 | 0.25 | 2.45 |
Preterm deliveryfig | 7 | 12% | 7 | 41% | 0.0105 | 5.10 | 1.46 | 17.76 |
Natural delivery | 34 | 59% | 5 | 29% | 0.0398 | 0.29 | 0.09 | 0.94 |
Family history of allergy | 38 | 66% | 14 | 82% | 0.1951 | 2.46 | 0.63 | 9.56 |
Food allergy in infancy | 27 | 47% | 10 | 59% | 0.3758 | 1.64 | 0.55 | 4.90 |
Antibiotic courses (n/year) ≥ 1.4b | 40 | 69% | 13 | 76% | 0.5515 | 1.46 | 0.42 | 5.11 |
Environmental tobacco smokec | 9 | 16% | 1 | 6% | 0.4389 | 0.34 | 0.04 | 2.90 |
SN5 score (points) ≥ 5b | 3 | 5% | 6 | 35% | 0.0032 | 10.0 | 2.17 | 46.17 |
Peripheral eosinophils (cell/mm3) ≥ 528b | 3 | 13% | 5 | 62% | 0.0119 | 11.11 | 1.70 | 72.56 |
Shannon index < 4.564b | 14 | 24% | 12 | 71% | 0.0009 | 7.54 | 2.26 | 25.15 |
Sensitization profile: | ||||||||
House dust mite | 12 | 21% | 9 | 53% | 0.0123 | 4.31 | 1.37 | 13.55 |
Tree | 17 | 29% | 7 | 41% | 0.3591 | 1.69 | 0.55 | 5.17 |
Grass | 9 | 16% | 6 | 35% | 0.0810 | 2.97 | 0.87 | 10.09 |
Atopy | 24 | 41% | 15 | 88% | 0.0031 | 10.62 | 2.22 | 50.83 |
(B) Nasal expression of predefined cytokines/mediators | Different study outcomes | |||
---|---|---|---|---|
Reduced biodiversity | Atopy | Reduced biodiversity and atopy | Asthma persistent | |
TSLP | ↑↑ | |||
IL-17 | ↑↑ | ↑ | ||
IL-5 | ↑ | ↑↑ | ↑↑ | |
T1R3 | ↑ | |||
MUC5B | ↓ |
- Note: (A) Statistical comparisons using univariate logistic regression analysis. Odds ratios presented with 95% confidence intervals from univariate logistic regression analysis are given. (B) Nasal expression of predefined cytokines/mediators by different outcomes according to the results of direct comparisons. Shannon index (biodiversity index) is calculated as a proportion of species relative to the total number of species multiplied by the natural logarithm of this proportion. Bold values indicate statistically significant results (p < 0.05).
- a Dependent variable: persistent asthma versus remission of asthma.
- b Cut-off for optimal prediction of asthma persistence calculated in ROC curve analysis (see Figure E2 and E3 in the article's online repository).
- c One or more smoking persons at home.
Nasal expressions of predefined cytokines/mediators were compared by different outcomes (visualisation is shown in Table 1B). In children with persistent asthma compared to children with asthma remission, higher nasal expression of IL-5 was observed at baseline. We observed higher nasal expression of IL-17, TSLP, and T1R3 in children with reduced compared to children with normal biodiversity of the nasopharynx microbiome. In children with atopy compared to nonatopic subjects, higher nasal expression of IL-5 and lower expression of MUC5B were shown. Finally, in children with the coincidence of atopy and reduced biodiversity of the nasopharynx microbiome in comparison to nonatopic children with average biodiversity of the nasopharynx microbiome, higher nasal expression of IL-5 and IL-17 was noticed. ANOVA analysis did not show significant interactions between outcomes. Additionally, a significant positive correlation between nasal expression of IL-5 and TSLP was observed. We did not observe any significant differences between groups in nasal abundance of ILCs. A detailed description of the methods and results is available in the following repository: https://osf.io/abnq6.
The major finding of our 5-year prospective study was that reduced biodiversity, concomitant with atopy, significantly predicts asthma persistence in young children. Our findings regarding the impact of either microbial diversity or atopy alone on asthma development in early childhood can be considered confirmatory, as both phenomena have been previously described [4-6]. However, the relationship between them is complex, with studies suggesting a bidirectional association between the two conditions [1, 7, 8]. Interestingly, it has been previously reported that airway microbial diversity is inversely associated with mite-sensitised rhinitis and asthma in early childhood [9]. The observed synergy between nasal dysbiosis and atopy in increasing the risk of asthma persistence suggests a possible immunological interplay between them, such as IL-5 overproduction.
Our trial showed that atopy, mainly house dust mite sensitisation, and reduced biodiversity of the nasal microbiome are associated with the risk of asthma persistence in our patients. Our results emphasise the need to define clinical conditions for early qualification for immunotherapy with house dust mite allergens in preschoolers with symptoms of CRS and HDM sensitisation. Our data also highlight the need to further focus on the prevention of dysbiosis and/or its immunological consequences.
Author Contributions
Conception and study design: Łukasz Dobrakowski and Paweł Majak. Acquisition of data: Łukasz Dobrakowski, Piotr Łacwik, Marta Mucha, Błażej Rychlik, Andrzej Błauż, Michał Seweryn, Dominik Strapagiel and Joanna Majak. Analysis and interpretation: Łukasz Dobrakowski, Piotr Łacwik, Błażej Rychlik, Michał Seweryn, Wojciech Feleszko, Adam Antczak, Piotr Kuna and Paweł Majak. Manuscript preparation, response to reviewers' comments: Łukasz Dobrakowski, Piotr Łacwik, Marta Mucha, Błażej Rychlik, Andrzej Błauż, Michał Seweryn, Dominik Strapagiel, Joanna Majak, Wojciech Feleszko, Adam Antczak, Piotr Kuna and Paweł Majak.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
The data that support the findings of this study are openly available in Open Science Framework at https://osf.io/abnq6.