Abstracts from the 3rd International Severe Asthma Forum (ISAF)

ORAL ABSTRACT SESSION 1—Asthma: from mechanisms to managementO01 Serum IL-1RL1-A levels predict an eosinophilic subtype of asthma in preschool wheezing childrenM. E. Ketelaar1, K. Van De Kant2, F. N. Dijk1, E. M. M. Klaassen3, N. Grotenboer4, M. C. Nawijn4, E. Dompeling2, G. H. Koppelman1 1University Medical Center Groningen, Beatrix Children's Hospital, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands; 2Department of Pediatric Pulmonology, School for Public Health and Primary Care (CAPHRI), Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands; 3Department of General Practice, School for Public Health and Primary Care (CAPHRI), Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands; 4University Medical Center Groningen, Department of Pathology and Medical Biology, Laboratory of Experimental Pulmonology and Inflammation Research (EXPIRE), Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands Correspondence: Maria Elizabeth Ketelaar - m.e.ketelaar@student.rug.nl Clinical and Translational Allergy 2017, 7(Suppl 2):O01 Introduction: Respiratory symptoms are common in preschool children. However, which of these wheezers will develop asthma at school age, and what phenotype they will develop remains difficult to predict. Current models such as the asthma prediction index (API) are based on clinical parameters and have only modest predictive accuracy. Expression levels of well replicated asthma genes could potentially form novel biomarkers for asthma prediction. IL1RL1 is an asthma susceptibility gene, and has also been linked to eosinophilia. Therefore, we hypothesized that expression levels of IL1RL1 in the form of soluble IL-1RL1-a measured in serum from wheezing preschool children contribute to the prediction of asthma at school age. Moreover, since IL1RL1 was previously associated with blood eosinophilia, our second aim was to determine whether serum IL-1RL1-a levels predict eosinophilic asthma. Method: We used logistic predictive modeling in a prospective Dutch birth cohort (n = 202 wheezers), and calculated the area under the curve (AUC) of the sensitivity/1-specificity curves of potential models. Results: Neither IL-1RL1-a serum levels at age 2–3 years alone nor its combination with the API had predictive value for doctors' diagnosed asthma at age 6y (IL-1RL1-a alone: AUC = 0.50 [95 CI 0.41–0.59, P = 0.98], API + IL-1RL1-a: AUC = 0.57 [95 CI 0.49–0.66, P = 0.12]).However, IL-1RL1-a serum levels at age 2–3 years correlated with the severity of airway eosinophilia (determined by levels of exhaled fraction of NO, [FeNO]) in children who had developed asthma at age 6y (Pearson's R = −0.24, P = 0.046, N = 59). Logistic predictive modeling of eosinophilic asthma at age 6y (asthma with FeNO ≥ 20 ppb) showed that IL-1RL1-a serum levels itself and in combination with the API could predict this eosinophilic subphenotype of asthma (IL-1RL1-a alone: AUC = 0.65 [95 CI 0.52–0.79, P = 0.04], API + IL-1RL1-a: AUC = 0.70 [95 CI 0.56–0.84, P = 0.01]). Interestingly, IL-1RL1-a levels had a negative direction of effect. Conclusion: Our study shows that serum IL-1RL1–a levels measured in wheezing children at age 2–3 years do not predict doctors' diagnosed asthma as general phenotype at age 6 years, but negatively predict an eosinophilic subphenotype of asthma.This suggests that IL-1RL1 might play a protective role in the development of eosinophilia in children who experience asthma at school age and implies that IL-1RL1 targeted therapy could rather be further explored in the subphenotype of asthmatic children with predominant eosinophilic inflammation. Keywords: Childhood Asthma, Eosinophilic Asthma, Prediction, IL-1RL1, SerumFigure 1 Prediction of eosinophilic childhood using IL-1 RL1-a serum levels and the API O03 Diagnosing asthma in symptomatic children using lung function: evidence from a birth cohort studyClare Murray1, Philip Foden1, Lesley Lowe1, Hannah Durrington1, Adnan Custovic2, Angela Simpson1 1University of Manchester, Manchester, United Kingdom; 2Imperial College, London, United Kingdom Correspondence: Angela Simpson - angela.simpson@manchester.ac.uk Clinical and Translational Allergy 2017, 7(Suppl 2):O03 Introduction: In the UK, new national draft guidance for the diagnosis of childhood asthma proposes algorithms based on four tests of lung function, each used as a dichotomous variable (FEV1/FVC ratio less than the lower limit of normal [LLN], bronchodilator reversibility [BDR] ≥12%, FeNO ≥ 35 ppb and PEFR variability). However, accuracy of these tests in diagnosing asthma in children is unknown, as the evidence is largely derived from studies of adults. Within the setting of a population-based birth cohort (Manchester Asthma and Allergy Study—MAAS), we investigated the value of FEV1/FVC, BDR and FeNO in diagnosing asthma in children. Method: Using validated questionnaires we assessed study participants at age 16 years. Current asthma was defined as all three of: (1) doctor-diagnosed asthma ever, (2) wheezing in the previous 12 months and (3) current use of asthma treatment. We assigned children negative to all three features as non-asthmatic controls. Using ATS/ERS guidelines, we measured spirometry and FeNO (NIOX chemiluminescence analyser; Sweden). BDR was considered positive if FEV1 increased by ≥12% following administration of 400 mg of salbutamol. PEFR variability was not measured. To test the diagnostic algorithms simulating the clinic situation, we selected only children reporting recent symptoms of wheeze, cough or breathlessness who were not on regular inhaled corticosteroids (ICS). Results: Of the 630 MAAS children with full data available, 163 reported recent symptoms, but were not using regular ICS; 34 of these met our definition of current asthma, with 55 as non-asthmatic controls. In the multivariable logistic regression analysis, increasing FeNO was associated with an increased risk of asthma (OR 1.02, 95% CI 1.01–1.04, p = 0.006), with a trend for FEV1/FVC ratio (OR 0.95, 95% CI 0.87–1.02, p = 0.17), and no association for BDR (p = 0.94). The proportion of those with each combination of positive tests is show as a Venn diagram (Figure 1). Of 58 children with three negative tests, 29.3% had current asthma, accounting for 50% of those with asthma. Only 5.9% of those with asthma were positive to all three tests. Conclusion: Applying 3 tests of lung function to children with symptoms and a diagnosis of asthma failed to detect 50% of asthma cases. Proposed algorithms for the diagnosis of asthma in symptomatic children need to be tested prospectively. Keywords: Asthma, Diagnosis, FeNO, Lung Function, ChildrenFigure 2 Venn diagram showing number of children with symptoms (n163) who were positive for each combination of tests O04 Treatable traits in the European U-BIOPRED adult severe asthma cohortAndrew J. Simpson1, Dominick E. Shaw2, Ana R. Sousa3, Louise J. Fleming4, Graham Roberts5, Ioannis Pandis6, Aruna T. Bansal7, Julie Corfield8, Scott Wagers9, Ratko Djukanovic5, Kian Fan Chung4, Peter J. Sterk10, Jorgen Vestbo1, Stephen J. Fowler1 1Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester and University Hospital of South Manchester, NHS Foundation Trust, Manchester, United Kingdom; 2Respiratory Research Unit, University of Nottingham, Nottingham, United Kingdom; 3Respiratory Therapeutic Unit, GSK, Stockley Park, London, United Kingdom; 4National Heart and Lung Institute, Imperial College, London, United Kingdom; 5NIHR Southampton RespiratoryBiomedical Research Unit, Clinical and Experimental Sciences and Human Development and Health, Southampton, United Kingdom; 6Data Science Institute, South Kensington Campus, Imperial College London, London, United Kingdom; 7Acclarogen Ltd, St John's Innovation Centre, Cambridge, United Kingdom; 8AstraZeneca R&D, Mölndal, Sweden; 9BioSci Consulting, Maasmechelen, Belgium; 10Dept of Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands Correspondence: Andrew J. Simpson - Andrew.Simpson-2@Manchester.ac.uk Clinical and Translational Allergy 2017, 7(Suppl 2):O04 Introduction: Individuals with severe asthma may remain uncontrolled and exacerbation-prone despite intensive guideline-directed treatment, and management options are limited. The concept of treatable traits, based on the identification of treatable disease-associated characteristics, may thus be a particularly useful framework in this context. In the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project we have recruited individuals with severe asthma (SA) under specialist care, and controls with mild to moderate asthma (MMA). Aim: To identify and quantify treatable traits within the U-BIOPRED adult asthma cohorts. Method: We defined criteria for treatable traits based on Agusti (Eur Respir J, 2016) and identified prevalence rates within the U-BIOPRED database. Chi Square tests were used to examine differences in frequency between individuals with SA and MMA Results: Data from 509 individuals with asthma were included in the analysis; 421 with SA and 88 with MMA. Twenty-nine treatable traits were identified, including 13 pulmonary, 13 extra-pulmonary and three behavioral traits. Pulmonary treatable traits such as airflow limitation (SA 50% vs. MMA 6%, P < 0.001), reversibility (SA 58% vs. MMA 39%, P = 0.002), eosinophilia (SA 54% vs. MMA 43%, P = 0.067), exercise-induced asthma (SA 77% vs. MMA 54%, P = 0.002), allergic rhinitis (SA 47% vs. MMA 44%, P = 0.641), cough (SA 63% vs. MMA 19%, P < 0.001) and bronchitis (SA 51% Vs. MMA 16%, P = 0.000) were highly prevalent in the asthma cohorts, and typically more common in SA versus MMA. The most common extra-pulmonary treatable traits were; atopy (SA 74% vs. MMA 92%, P < 0.001), obesity (SA 30% vs. MMA 38%, P = 0.17

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