Monitoring is a major component of asthma management in children. Regular monitoring allows for diagnosis confirmation, treatment optimization and natural history review. Numerous factors that may affect disease activity and patient wellbeing need to be monitored: response and adherence to treatment, disease control, disease progression, comorbidities, quality of life, medication side-effects, allergen and irritant exposures, diet and more. However, the prioritization of such factors and the selection of relevant assessment tools is an unmet need. Furthermore, rapidly developing technologies promise new opportunities for closer, or even ‘real-time’, monitoring between visits. Following an approach that included needs assessment, evidence appraisal and Delphi consensus, the PeARL Think Tank, in collaboration with major international professional and patient organizations, has developed a set of 24 recommendations on pediatric asthma monitoring, to support healthcare professionals in decision-making and care pathway design.

The field of medicine is witnessing an exponential growth of interest in Artificial Intelligence (AI), which enables new research questions and the analysis of larger and new types of data. Nevertheless, applications that go beyond proof of concepts and deliver clinical value remain rare, especially in the field of allergy and immunology. This narrative review provides a fundamental understanding of the core concepts of AI and critically discusses its limitations and open challenges, such as data availability and bias, along with potential directions to surmount them. We provide a conceptual framework to structure AI applications within this field and discuss forefront case examples. Most of these applications of AI and machine learning in allergy concern supervised learning and unsupervised clustering, with a strong emphasis on diagnosis and subtyping. A perspective is shared on guidelines for good AI practice to guide readers in applying it effectively and safely, along with prospects of field advancement and initiatives to increase clinical impact. We anticipate that AI can further deepen our knowledge of disease mechanisms and contribute to precision medicine in allergy.

Background: Childhood allergic rhinitis (AR) is clinically highly heterogeneous. We aimed to identify distinct subgroups amongst children with AR, and to ascertain their association with patterns of symptoms, allergic sensitization and concomitant physician-diagnosed asthma. Methods: We recruited 510 children with physician-diagnosed AR, of whom 205 (40%) had asthma. Latent class analysis (LCA) was performed to identify latent structure within the data set using 17 variables (allergic conjunctivitis, eczema, asthma, family history of asthma, family history of allergic rhinitis, skin sensitization to 8 common allergens, tonsillectomy, adenoidectomy). Results: A four−class solution was selected as the optimal model based on statistical fit. We labeled AR latent classes as: (1) AR with grass mono-sensitization and conjunctivitis (n=361, 70.8%); (2) AR with house dust mite sensitization and asthma (n=75, 14.7%); (3) AR with pet and grass polysensitization and conjunctivitis (n=35, 6.9%) and (4) AR among children with tonsils and adenoids removed (n=39, 7.6%). Perennial AR was significantly more common among children in Class 2 (OR 5.83, 95%CI 3.42−9.94, p<0.001) and Class 3 (OR 2.88, 95%CI 1.36−6.13, p=0.006). Mild and intermittent AR symptoms were significantly more common in children in Class 3 compared to those in Class 1. AR was more severe in Class 1, compared to other 3 classes, indicating that upper respiratory symptoms are more severe among children with isolated seasonal rhinitis, than in those with rhinitis and coexisting asthma. Conclusion: We have identified 4 phenotypes in school-age children with AR, which were associated with different patterns of clinical symptoms and comorbidities.

Background: Chemokines are important mediators in immune cell recruitment, contributing to allergy development. However, extensive studies of chemokines in the circulation in relation to the presence and development of allergic diseases remain scarce. Our aim was to investigate associations of circulating allergy-related chemokines with development of asthma and sensitisation cross-sectionally and longitudinally in a population-based cohort. Methods: The chemokines CCL17, CCL22, CXCL10, CXCL11 and CCL18 were measured in plasma samples from children in the Manchester Asthma and Allergy Study. Samples were available from cord blood at birth (n=376), age 1 (n=195) and 8 years (n=334). Cross-sectional and longitudinal association analyses were performed in relation to asthma and allergic sensitisation, as well as allergic phenotype clusters previously derived using machine learning in the same study population. Results: In children with asthma and/or allergic sensitisation, CCL18 levels were consistently elevated at ages 1 and/or 8 years. In a longitudinal model including information on asthma from 4 time-points (ages 5, 8, 11 and 16 years), we observed a significant association between increasing CCL18 levels at age 1 and a higher risk of asthma from early school age to adolescence (OR=2.9, 95% CI 1.1-7.6, p=0.028). We observed similar associations in longitudinal models for allergic sensitisation. Asthma later in life was preceded by increased CXCL10 levels after birth, and decreased CXCL11 levels at birth. Conclusion: Elevated CCL18 levels throughout childhood precede the development of asthma and allergic sensitisation. The Th1-associated chemokines CXCL10 and CXCL11 also associated with development of both outcomes, with differential temporal effects.

Background: The interplay between COVID-19 pandemic and asthma in children is still unclear. We evaluated the impact of COVID-19 on childhood asthma outcomes. Methods: The PeARL multinational cohort included 1,054 children with asthma and 505 non-asthmatic children aged between 4-18 years from 25 pediatric departments, from 15 countries globally. We compared the frequency of acute respiratory and febrile presentations during the first wave of the COVID-19 pandemic between groups and with data available from the previous year. In children with asthma, we also compared current and historical disease control. Results: During the pandemic, children with asthma experienced fewer upper respiratory tract infections, episodes of pyrexia, emergency visits, hospital admissions, asthma attacks and hospitalizations due to asthma, in comparison to the preceding year. Sixty-six percent of asthmatic children had improved asthma control while in 33% the improvement exceeded the minimal clinically important difference. Pre-bronchodilatation FEV1 and peak expiratory flow rate were improved during the pandemic. When compared to non-asthmatic controls, children with asthma were not at increased risk of LRTIs, episodes of pyrexia, emergency visits or hospitalizations during the pandemic. However, an increased risk of URTIs emerged. Conclusion: Childhood asthma outcomes, including control, were improved during the first wave of the COVID-19 pandemic, probably because of reduced exposure to asthma triggers and increased treatment adherence. The decreased frequency of acute episodes does not support the notion that childhood asthma may be a risk factor for COVID-19. Furthermore, the potential for improving childhood asthma outcomes through environmental control becomes apparent.

Montelukast therapy in asthmatic children with and without food allergyUmit Murat Sahiner1*, Ebru Arik Yilmaz1*, Sara Fontanella2, Sadia Haider2, Ozge Soyer1, Adnan Custovic2, Omer Kalayci1, Cansin Sackesen1,3*Equal contribution1 Hacettepe University School of Medicine, Division of Pediatric Allergy, Ankara, Turkey2 National Heart and Lung Institute, Imperial College London, UK3 Koc University School of Medicine, Division of Pediatric Allergy, Istanbul TukeyRunning Title: Montelukast in asthma and food allergyFunding Source: The study drugs, placebos and laboratory kits were provided by Merck Sharpe and Dohme Company. The protocol was developed by the corresponding author Prof Cansin Sackesen and reviewed by Merck Sharpe and Dohme Company. However, there is no contribution of Merck Sharpe and Dohme Company to the results and discussion of the article.Conflicts of Interest: The authors declare no conflicts of interest in relation to this study.

Background: Effector cells assays provide an overall measure of responsiveness to allergen, but the lack of reliable, high-throughput assays limits the clinical utility of this approach. The aim of this study was to develop a high-throughput Basophil Activation Test (BAT), based on human progenitor cell-derived basophils (PCB), and to investigate the role of PCB activation test (PCBAT) in allergy diagnosis. Methods: PCBs were differentiated from CD34+ progenitor cells, and sensitized with sera from subjects sensitized to cat (n=35, 17 subjects clinical reactivity validated), peanut-allergic (n=30, 15 subjects clinical reactivity validated), peanut-sensitized but tolerant subjects (n=13). Sensitized PCBs were then stimulated with a range of concentrations of the corresponding allergens and degranulation was measured using CD63 expression on flow cytometry. Results: Following passive sensitisation of the mature PCB (2D7+/FcεRI+/CD117-/HLADR-) with serum and stimulation with allergen, we saw a dose-dependent increase in CD63 expression which was allergen specific. In subjects sensititsed to cat there was a positive correlation between PCBAT area under curve (AUC) versus specific IgE (sIgE) to cat (p=0.001) and versus airway responsiveness to inhaled cat allergen (p=0.026). There was a significant negative correlation between PCBAT AUC for peanut allergen and response to oral food challenge test to peanut - subjects with higher PCBAT AUC reacted to a lower dose on the oral food challenge to peanut (p=0.001), and had higher sIgE to Ara h 1 (p=0.007). All peanut tolerant subjects showed no reaction to peanut on PCBAT. Conclusion: PCBAT may confer a powerful alternative tool in allergy testing.