Recommendations for asthma monitoring in children: A PeARL document endorsed by APAPARI, EAACI, INTERASMA, REG, and WAO.

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 well-being 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.

Determinants of lung function development from birth to age 5 years: an interrupted time series analysis of a South African birth cohort.

BACKGROUND: Early life is a key period that determines long-term health. Lung development in childhood predicts lung function attained in adulthood and morbidity and mortality across the life course. We aimed to assess the effect of early-life lower respiratory tract infection (LRTI) and associated risk factors on lung development from birth to school age in a South African birth cohort. METHODS: We prospectively followed children enrolled in a population-based cohort from birth (between March 5, 2012 and March 31, 2015) to age 5 years with annual lung function assessment. Data on multiple early-life exposures, including LRTI, were collected. The effect of early-life risk factors on lung function development from birth to age 5 years was assessed using the Generalised Additive Models for Location, Scale and Shape and Interrupted Time Series approach. FINDINGS: 966 children (475 [49·2%] female, 491 [50·8%] male) had lung function measured with oscillometry, tidal flow volume loops, and multiple breath washout. LRTI occurred in 484 (50·1%) children, with a median of 2·0 LRTI episodes (IQR 1·0-3·0) per child. LRTI was independently associated with altered lung function, as evidenced by lower compliance (0·959 [95% CI 0·941-0·978]), higher resistance (1·028 [1·016-1·041]), and higher respiratory rate (1·018 [1·063-1·029]) over 5 years. Additional impact on lung function parameters occurred with each subsequent LRTI. Respiratory syncytial virus (RSV) LRTI was associated with lower expiratory flow ratio (0·97 [0·95-0·99]) compared with non-RSV LRTI. Maternal factors including allergy, smoking, and HIV infection were also associated with altered lung development, as was preterm birth, low birthweight, female sex, and coming from a less wealthy household. INTERPRETATION: Public health interventions targeting LRTI prevention, with RSV a priority, are vital, particularly in low-income and middle-income settings. FUNDING: UK Medical Research Council Grant, The Wellcome Trust, The Bill & Melinda Gates Foundation, US National Institutes of Health Human Heredity and Health in Africa, South African Medical Research Council, Hungarian Scientific Research Fund, and European Respiratory Society.

Component-specific clusters for diagnosis and prediction of allergic airway diseases.

BACKGROUND: Previous studies which applied machine learning on multiplex component-resolved diagnostics arrays identified clusters of allergen components which are biologically plausible and reflect the sources of allergenic proteins and their structural homogeneity. Sensitization to different clusters is associated with different clinical outcomes. OBJECTIVE: To investigate whether within different allergen component sensitization clusters, the internal within-cluster sensitization structure, including the number of c-sIgE responses and their distinct patterns, alters the risk of clinical expression of symptoms. METHODS: In a previous analysis in a population-based birth cohort, by clustering component-specific (c-s)IgEs, we derived allergen component clusters from infancy to adolescence. In the current analysis, we defined each subject's within-cluster sensitization structure which captured the total number of c-sIgE responses in each cluster and intra-cluster sensitization patterns. Associations between within-cluster sensitization patterns and clinical outcomes (asthma and rhinitis) in early-school age and adolescence were examined using logistic regression and binomial generalized additive models. RESULTS: Intra-cluster sensitization patterns revealed specific associations with asthma and rhinitis (both contemporaneously and longitudinally) that were previously unseen using binary sensitization to clusters. A more detailed description of the subjects' within-cluster c-sIgE responses in terms of the number of positive c-sIgEs and unique sensitization patterns added new information relevant to allergic diseases, both for diagnostic and prognostic purposes. For example, the increase in the number of within-cluster positive c-sIgEs at age 5 years was correlated with the increase in prevalence of asthma at ages 5 and 16 years, with the correlations being stronger in the prediction context (e.g. for the largest 'Broad' component cluster, contemporaneous: r = .28, p = .012; r = .22, p = .043; longitudinal: r = .36, p = .004; r = .27, p = .04). CONCLUSION: Among sensitized individuals, a more detailed description of within-cluster c-sIgE responses in terms of the number of positive c-sIgE responses and distinct sensitization patterns, adds potentially important information relevant to allergic diseases.

Lung-function trajectories: relevance and implementation in clinical practice.

Lung development starts in utero and continues during childhood through to adolescence, reaching its peak in early adulthood. This growth is followed by gradual decline due to physiological lung ageing. Lung-function development can be altered by several host and environmental factors during the life course. As a result, a range of lung-function trajectories exist in the population. Below average trajectories are associated with respiratory, cardiovascular, metabolic, and mental health comorbidities, as well as with premature death. This Review presents progressive research into lung-function trajectories and assists the implementation of this knowledge in clinical practice as an innovative approach to detect poor lung health early, monitor respiratory disease progression, and promote lung health. Specifically, we propose that, similar to paediatric height and weight charts used globally to monitor children's growth, lung-function charts could be used for both children and adults to monitor lung health status across the life course. To achieve this proposal, we introduce our free online Lung Function Tracker tool. Finally, we discuss challenges and opportunities for effective implementation of the trajectory concept at population level and outline an agenda for crucial research needed to support such implementation.

Association between polymorphisms on chromosome 17q12-q21 and rhinovirus-induced interferon responses.

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes on chromosome 17q12-q21 are associated with childhood-onset asthma and rhinovirus-induced wheeze. There are few mechanistic data linking chromosome 17q12-q21 to wheezing illness. OBJECTIVE: We investigated whether 17q12-q21 risk alleles were associated with impaired interferon responses to rhinovirus. METHODS: In a population-based birth cohort of European ancestry, we stimulated peripheral blood mononuclear cells with rhinovirus A1 (RV-A1) and rhinovirus A16 (RV-A16) and measured IFN and IFN-induced C-X-C motif chemokine ligand 10 (aka IP10) responses in supernatants. We investigated associations between virus-induced cytokines and 6 SNPs in 17q12-q21. Bayesian profile regression was applied to identify clusters of individuals with different immune response profiles and genetic variants. RESULTS: Five SNPs (in high linkage disequilibrium, r2 ≥ 0.8) were significantly associated with RV-A1-induced IFN-ß (rs9303277, P = .010; rs11557467, P = .012; rs2290400, P = .006; rs7216389, P = .008; rs8079416, P = .005). A reduction in RV-A1-induced IFN-ß was observed among individuals with asthma risk alleles. There were no significant associations for RV-A1-induced IFN-α or CXCL10, or for any RV-A16-induced IFN/CXCL10. Bayesian profile regression analysis identified 3 clusters that differed in IFN-ß induction to RV-A1 (low, medium, high). The typical genetic profile of the cluster associated with low RV-A1-induced IFN-ß responses was characterized by a very high probability of being homozygous for the asthma risk allele for all SNPs. Children with persistent wheeze were almost 3 times more likely to be in clusters with reduced/average RV-A1-induced IFN-ß responses than in the high immune response cluster. CONCLUSIONS: Polymorphisms on chromosome 17q12-q21 are associated with rhinovirus-induced IFN-ß, suggesting a novel mechanism-impaired IFN-ß induction-links 17q12-q21 risk alleles with asthma/wheeze.

Understanding the heterogeneity of childhood allergic sensitization and its relationship with asthma.

PURPOSE OF REVIEW: To review the current state of knowledge on the relationship between allergic sensitization and asthma; to lay out a roadmap for the development of IgE biomarkers that differentiate, in individual sensitized patients, whether their sensitization is important for current or future asthma symptoms, or has little or no relevance to the disease. RECENT FINDINGS: The evidence on the relationship between sensitization and asthma suggests that some subtypes of allergic sensitization are not associated with asthma symptoms, whilst others are pathologic. Interaction patterns between IgE antibodies to individual allergenic molecules on component-resolved diagnostics (CRD) multiplex arrays might be hallmarks by which different sensitization subtypes relevant to asthma can be distinguished. These different subtypes of sensitization are associated amongst sensitized individuals at all ages, with different clinical presentations (no disease, asthma as a single disease, and allergic multimorbidity); amongst sensitized preschool children with and without lower airway symptoms, with different risk of subsequent asthma development; and amongst sensitized patients with asthma, with differing levels of asthma severity. SUMMARY: The use of machine learning-based methodologies on complex CRD data can help us to design better diagnostic tools to help practising physicians differentiate between benign and clinically important sensitization.

Updated grading system for systemic allergic reactions: Joint Statement of the World Allergy Organization Anaphylaxis Committee and Allergen Immunotherapy Committee.

There is a lack of consensus over the description and severity assignment of allergic adverse reactions to immunotherapy, although there seems to be a consensus at least in terms of using the World Allergy Organization (WAO) grading systems to describe local adverse events for Sublingual Immunotherapy (SLIT) and Systemic Allergic Reactions (SARs) to Subcutaneous Immunotherapy (SCIT) amongst the major national/regional allergy societies. In this manuscript, we propose a modification of the previous WAO Grading system for SARs, which aligns with the newly-proposed Consortium for Food Allergy Research (CoFAR) Grading Scale for Systemic Allergic Reactions in Food Allergy (version 3.0). We hope this can facilitate a unified grading system appropriate to SARs due to allergen immunotherapy, independent of allergen and route of administration, and across clinical and research practice.

Evaluation of measurement errors in the Patient-Oriented Eczema Measure (POEM) outcome.

BACKGROUND: The Patient-Oriented Eczema Measure (POEM) is the recommended core outcome instrument for atopic dermatitis (AD) symptoms. POEM is reported by recalling the presence/absence of seven symptoms in the last 7 days. OBJECTIVE: To evaluate measurement errors in POEM recordings due to imperfect recall. METHODS: Using data from a clinical trial of 247 AD patients aged 12-65 years, we analysed the reported POEM score (r-POEM) and the POEM derived from the corresponding daily scores for the same seven symptoms without weekly recall (d-POEM). We quantified recall error by comparing the r-POEM and d-POEM for 777 patient-weeks collected from 207 patients, and estimated two components of recall error: (1) recall bias due to systematic errors in measurements and (2) recall noise due to random errors in measurements, using a bespoke statistical model. RESULTS: POEM scores have a relatively low recall bias, but a high recall noise. Recall bias was estimated at 1.2 points lower for the r-POEM on average than the d-POEM, with a recall noise of 5.7 points. For example, a patient with a recall-free POEM of 11 (moderate) could report their POEM score anywhere from 5 to 14 (with 95% probability) because of recall error. Model estimates suggested that patients tend to recall itch and dryness more often than experienced (positive bias of less than 1 day), but less often for the other symptoms (bleeding, cracking, flaking, oozing/weeping and sleep disturbance; negative bias ranging 1-4 days). CONCLUSIONS: In this clinical trial data set, we found that patients tended to slightly underestimate their symptoms when reporting POEM, with significant variation in how well they were able to recall the frequency of their symptoms every time they reported POEM. A large recall noise should be taken into consideration when interpreting POEM scores.

Obstructive and restrictive spirometry from school age to adulthood: three birth cohort studies.

Background: Spirometric obstruction and restriction are two patterns of impaired lung function which are predictive of poor health. We investigated the development of these phenotypes and their transitions through childhood to early adulthood. Methods: In this study, we analysed pooled data from three UK population-based birth cohorts established between 1989 and 1995. We applied descriptive statistics, regression modelling and data-driven modelling to data from three population-based birth cohorts with at least three spirometry measures from childhood to adulthood (mid-school: 8-10 years, n = 8404; adolescence: 15-18, n = 5764; and early adulthood: 20-26, n = 4680). Participants were assigned to normal, restrictive, and obstructive spirometry based on adjusted regression residuals. We considered two transitions: from 8-10 to 15-18 and from 15-18 to 20-26 years. Findings: Obstructive phenotype was observed in ∼10%, and restrictive in ∼9%. A substantial proportion of children with impaired lung function in school age (between one third in obstructive and a half in restricted phenotype) improved and achieved normal and stable lung function to early adulthood. Of those with normal lung function in school-age, <5% declined to adulthood. Underweight restrictive and obese obstructive participants were less likely to transit to normal. Maternal smoking during pregnancy and current asthma diagnosis increased the risk of persistent obstruction and worsening. Significant associate of worsening in restrictive phenotypes was lower BMI at the first lung function assessment. Data-driven methodologies identified similar risk factors for obstructive and restrictive clusters. Interpretation: The worsening and improvement in obstructive and restrictive spirometry were observed at all ages. Maintaining optimal weight during childhood and reducing maternal smoking during pregnancy may reduce spirometry obstruction and restriction and improve lung function. Funding: MRC Grant MR/S025340/1.

Identification of differences in CD4+ T-cell gene expression between people with asthma and healthy controls.

Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4+ T-cells play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4+ T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data, we identified PTPRC, a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).

Component-resolved diagnosis in childhood and prediction of asthma in early adolescence: A birth cohort study.

INTRODUCTION: Component-resolved diagnosis (CRD) has been decisive in exploring the mechanisms of IgE sensitization, but the predictive ability to detect asthma has not been addressed. We aim to develop and evaluate the performance of a personalized predictive algorithm for asthma that integrates information on allergic sensitization using CRD. METHODS: One thousand one hundred one twenty-five children from the Generation XXI birth cohort were randomly selected to perform a screening test for allergic sensitization and a subsample was characterized using CRD against 112 allergen components. Allergen components were analyzed using volcano plots and partial least squares (PLS) analysis. Logistic regression was performed to assess the associations between the obtained latent components (LC) and allergic outcomes (asthma, rhinitis, eczema) including other potential predictors used in previous asthma risk scores. The accuracy of the model in predicting asthma was assessed using Receiver Operating Characteristic (ROC) curve statistics. RESULTS: In the PLS, the first LC was positively associated with asthma, rhinitis, and eczema. This LC was mainly driven by positive weights for Der p 1/2/23, Der f 1/2, and Fel d 1. The main components in the second LC were pollen and food allergens. History of early wheezing and parental allergy were included in the predictive model and the area under the curve improved to 0.82. CONCLUSIONS: This is the first approach to improve the clinical applicability of CRD by combining CRD and clinical data to predict asthma at 13 years. Sensitization to distinct allergen molecules seems relevant to improve the accuracy of asthma prediction models.

Understanding progression from pre-school wheezing to school-age asthma: Can modern data approaches help?

Preschool wheezing and childhood asthma create a heavy disease burden which is only exacerbated by the complexity of the conditions. Preschool wheezing exhibits both "curricular" and "aetiological" heterogeneity: that is, heterogeneity across patients both in the time-course of its development and in its underpinning pathological mechanisms. Since these are not fully understood, but clinical presentations across patients may nonetheless be similar, current diagnostic labels are imprecise-not mapping cleanly onto underlying disease mechanisms-and prognoses uncertain. These uncertainties also make a identifying new targets for therapeutic intervention difficult. In the past few decades, carefully designed birth cohort studies have collected "big data" on a large scale, incorporating not only a wealth of longitudinal clinical data, but also detailed information from modalities as varied as imaging, multiomics, and blood biomarkers. The profusion of big data has seen the proliferation of what we term "modern data approaches" (MDAs)-grouping together machine learning, artificial intelligence, and data science-to make sense and make use of this data. In this review, we survey applications of MDAs (with an emphasis on machine learning) in childhood wheeze and asthma, highlighting the extent of their successes in providing tools for prognosis, unpicking the curricular heterogeneity of these conditions, clarifying the limitations of current diagnostic criteria, and indicating directions of research for uncovering the etiology of the diseases underlying these conditions. Specifically, we focus on the trajectories of childhood wheeze phenotypes. Further, we provide an explainer of the nature and potential use of MDAs and emphasize the scope of what we can hope to achieve with them.

Identification of eczema clusters and their association with filaggrin and atopic comorbidities: analysis of five birth cohorts.

BACKGROUND: Longitudinal modelling of the presence/absence of current eczema through childhood has identified similar phenotypes, but their characteristics often differ between studies. OBJECTIVES: To demonstrate that a more comprehensive description of longitudinal pattern of symptoms may better describe trajectories than binary information on eczema presence. METHODS: We derived six multidimensional variables of eczema spells from birth to 18 years of age (including duration, temporal sequencing and the extent of persistence/recurrence). Spells were defined as consecutive observations of eczema separated by no eczema across 5 epochs in five birth cohorts: infancy (first year); early childhood (age 2-3 years); preschool/early school age (4-5 years); middle childhood (8-10 years); adolescence (14-18 years). We applied Partitioning Around Medoids clustering on these variables to derive clusters of the temporal patterns of eczema. We then investigated the stability of the clusters, within-cluster homogeneity and associated risk factors, including FLG mutations. RESULTS: Analysis of 7464 participants with complete data identified five clusters: (i) no eczema (51.0%); (ii) early transient eczema (21.6%); (iii) late-onset eczema (LOE; 8.1%); (iv) intermittent eczema (INT; 7.5%); and (v) persistent eczema (PE; 11.8%). There was very-high agreement between the assignment of individual children into clusters when using complete or imputed (n = 15 848) data (adjusted Rand index = 0.99; i.e. the clusters were very stable). Within-individual symptom patterns across clusters confirmed within-cluster homogeneity, with consistent patterns of symptoms among participants within each cluster and no overlap between the clusters. Clusters were characterized by differences in associations with risk factors (e.g. parental eczema was associated with all clusters apart from LOE; sensitization to inhalant allergens was associated with all clusters, with the highest risk in the PE cluster). All clusters apart from LOE were associated with FLG mutations. Of note, the strongest association was for PE [relative risk ratio (RRR) 2.70, 95% confidence interval (CI) 2.24-3.26; P < 0.001] followed by INT (RRR 2.29, 95% CI 1.82-2.88; P < 0.001). CONCLUSIONS: Clustering of multidimensional variables identified stable clusters with different genetic architectures. Using multidimensional variables may capture eczema development and derive stable and internally homogeneous clusters. However, deriving homogeneous symptom clusters does not necessarily mean that these are underpinned by completely unique mechanisms.

Phenotype and endotype based treatment of preschool wheeze.

INTRODUCTION: Preschool wheeze (PSW) is a significant public health issue, with a high presentation rate to emergency departments, recurrent symptoms, and severe exacerbations. A heterogenous condition, PSW comprises several phenotypes that may relate to a range of pathobiological mechanisms. However, treating PSW remains largely generalized to inhaled corticosteroids and a short acting beta agonist, guided by symptom-based labels that often do not reflect underlying pathways of disease. AREAS COVERED: We review the observable features and characteristics used to ascribe phenotypes in children with PSW and available pathobiological evidence to identify possible endotypes. These are considered in the context of treatment options and future research directions. The role of machine learning (ML) and modern analytical techniques to identify patterns of disease that distinguish phenotypes is also explored. EXPERT OPINION: Distinct clusters (phenotypes) of severe PSW are characterized by different underlying mechanisms, some shared and some unique. ML-based methodologies applied to clinical, biomarker, and environmental data can help design tools to differentiate children with PSW that continues into adulthood, from those in whom wheezing resolves, identifying mechanisms underpinning persistence and resolution. This may help identify novel therapeutic targets, inform mechanistic studies, and serve as a foundation for stratification in future interventional therapeutic trials.

A concept for integrated care pathways for atopic dermatitis-A GA2 LEN ADCARE initiative.

INTRODUCTION: The integrated care pathways for atopic dermatitis (AD-ICPs) aim to bridge the gap between existing AD treatment evidence-based guidelines and expert opinion based on daily practice by offering a structured multidisciplinary plan for patient management of AD. ICPs have the potential to enhance guideline recommendations by combining interventions and aspects from different guidelines, integrating quality assurance, and describing co-ordination of care. Most importantly, patients can enter the ICPs at any level depending on AD severity, resources available in their country, and economic factors such as differences in insurance reimbursement systems. METHODS: The GA2 LEN ADCARE network and partners as well as all stakeholders, abbreviated as the AD-ICPs working group, were involved in the discussion and preparation of the AD ICPs during a series of subgroup workshops and meetings in years 2020 and 2021, after which the document was circulated within all GAL2 EN ADCARE centres. RESULTS: The AD-ICPs outline the diagnostic procedures, possible co-morbidities, different available treatment options including differential approaches for the pediatric population, and the role of the pharmacists and other stakeholders, as well as remaining unmet needs in the management of AD. CONCLUSION: The AD-ICPs provide a multidisciplinary plan for improved diagnosis, treatment, and patient feedback in AD management, as well as addressing critical unmet needs, including improved access to care, training specialists, implementation of educational programs, assessment on the impact of climate change, and fostering a personalised treatment approach. By focusing on these key areas, the initiative aims to pave the way for a brighter future in the management of AD.

Prediction of adult asthma risk in early childhood using novel adult asthma predictive risk scores.

BACKGROUND: Numerous risk scores have been developed to predict childhood asthma. However, they may not predict asthma beyond childhood. We aim to create childhood risk scores that predict development and persistence of asthma up to young adult life. METHODS: The Isle of Wight Birth Cohort (n = 1456) was prospectively assessed up to 26 years of age. Asthma predictive scores were developed based on factors during the first 4 years, using logistic regression and tested for sensitivity, specificity and area under the curve (AUC) for prediction of asthma at (i) 18 and (ii) 26 years, and persistent asthma (PA) (iii) at 10 and 18 years, and (iv) at 10, 18 and 26 years. Models were internally and externally validated. RESULTS: Four models were generated for prediction of each asthma outcome. ASthma PredIctive Risk scorE (ASPIRE)-1: a 2-factor model (recurrent wheeze [RW] and positive skin prick test [+SPT] at 4 years) for asthma at 18 years (sensitivity: 0.49, specificity: 0.80, AUC: 0.65). ASPIRE-2: a 3-factor model (RW, +SPT and maternal rhinitis) for asthma at 26 years (sensitivity: 0.60, specificity: 0.79, AUC: 0.73). ASPIRE-3: a 3-factor model (RW, +SPT and eczema at 4 years) for PA-18 (sensitivity: 0.63, specificity: 0.87, AUC: 0.77). ASPIRE-4: a 3-factor model (RW, +SPT at 4 years and recurrent chest infection at 2 years) for PA-26 (sensitivity: 0.68, specificity: 0.87, AUC: 0.80). ASPIRE-1 and ASPIRE-3 scores were replicated externally. Further assessments indicated that ASPIRE-1 can be used in place of ASPIRE-2-4 with same predictive accuracy. CONCLUSION: ASPIRE predicts persistent asthma up to young adult life.

Current state and prospects of artificial intelligence in allergy.

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. 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.

Circulating CC16 and Asthma: A Population-based, Multicohort Study from Early Childhood through Adult Life.

Rationale: Club cell secretory protein (CC16) is an antiinflammatory protein highly expressed in the airways. CC16 deficiency has been associated with lung function deficits, but its role in asthma has not been established conclusively. Objectives: To determine 1) the longitudinal association of circulating CC16 with the presence of active asthma from early childhood through adult life and 2) whether CC16 in early childhood predicts the clinical course of childhood asthma into adult life. Methods: We assessed the association of circulating CC16 and asthma in three population-based birth cohorts: the Tucson Children's Respiratory Study (years 6-36; total participants, 814; total observations, 3,042), the Swedish Barn/Children, Allergy, Milieu, Stockholm, Epidemiological survey (years 8-24; total participants, 2,547; total observations, 3,438), and the UK Manchester Asthma and Allergy Study (years 5-18; total participants, 745; total observations, 1,626). Among 233 children who had asthma at the first survey in any of the cohorts, baseline CC16 was also tested for association with persistence of symptoms. Measurements and Main Results: After adjusting for covariates, CC16 deficits were associated with increased risk for the presence of asthma in all cohorts (meta-analyzed adjusted odds ratio per 1-SD CC16 decrease, 1.20; 95% confidence interval [CI], 1.12-1.28; P < 0.0001). The association was particularly strong for asthma with frequent symptoms (meta-analyzed adjusted relative risk ratio, 1.40; 95% CI, 1.24-1.57; P < 0.0001), was confirmed for both atopic and nonatopic asthma, and was independent of lung function impairment. After adjustment for known predictors of persistent asthma, children with asthma in the lowest CC16 tertile had a nearly fourfold increased risk for having frequent symptoms persisting into adult life compared with children with asthma in the other two CC16 tertiles (meta-analyzed adjusted odds ratio, 3.72; 95% CI, 1.78-7.76; P < 0.0001). Conclusions: Circulating CC16 deficits are associated with the presence of asthma with frequent symptoms from childhood through midadult life and predict the persistence of asthma symptoms into adulthood. These findings support a possible protective role of CC16 in asthma and its potential use for risk stratification.

Current and Optimal Practices in Childhood Asthma Monitoring Among Multiple International Stakeholders.

Importance: Childhood asthma control largely depends on rigorous and regular monitoring. Although various clinical parameters, biomarkers, and patient-reported outcomes are helpful for monitoring purposes, there is no consensus on the minimum and/or optimal set of parameters and their relative priority. Objective: To assess actual and perceived optimal childhood asthma monitoring practices used globally. Design, Setting, and Participants: This international, multistakeholder survey study surveyed health care professionals and clinical academics with a professional interest in and exposure to childhood asthma between April 12 and September 3, 2021, to test for differences between the frequency that different techniques are actually used in practice vs optimal practice, between-group differences, and differences across medical settings and country economies. Main Outcomes and Measures: Outcomes were frequency of duration of asthma monitoring visits as well as actual and perceived optimal use and importance of monitoring tools and domains. Results: A total of 1319 participants with expertise in childhood asthma from 88 countries completed the survey. Participants included 1228 health care professionals with a balanced distribution across different care settings (305 [22.7%] primary care, 401 [29.9%] secondary, and 522 [38.9%] tertiary care) and 91 researchers. Children with mild to moderate asthma attended regular monitoring visits at a median (IQR) of 5.0 (2.5-8.0) months, with visits lasting a median (IQR) of 25 (15-25) minutes, whereas severe asthma required more frequent visits (median [IQR], 2.5 [1.0-2.5] months; median [IQR] duration, 25 [25-35] minutes). Monitoring of symptoms and control, adherence, comorbidities, lung function, medication adverse effects, and allergy were considered to be very high or high priority by more than 75% of the respondents. Different patterns emerged when assessing differences between actual and perceived optimal use of monitoring tools. For some tools, current and optimal practices did not differ much (eg, spirometry), whereas in others, there was considerable space for improvement (eg, standardized control and adherence tests). The largest gap was observed for between-visit monitoring with electronic trackers, apps, and smart devices. Differences across country economies, care settings, and medical specialties were modest. Conclusions and Relevance: These survey results suggest that pediatric asthma monitoring is performed generally homogeneously worldwide, in most cases following evidence-based standards. Wider use of standardized instruments and the intensification of continuous between-visit monitoring, supported by electronic devices, is needed for further improvement of disease outcomes. The results of this survey, in conjunction with the available evidence base, can inform recommendations toward further optimization.