Journal of Allergy and Clinical Immunology

BACKGROUNDAeroallergen testing can improve precision care for persistent asthma and is recommended by the U.S. clinical guidelines. How testing benefits diverse populations of adults with asthma, and the importance of the testing modality used, are not fully understood. OBJECTIVEWe sought to evaluate whether receipt of aeroallergen testing was associated with a reduction in oral corticosteroid (OCS) bursts. METHODSWe used electronic health record data to conduct a retrospective, observational cohort study of adults with asthma who were prescribed an inhaled corticosteroid and had an Allergy/Immunology visit in a large health system between 1/1/2017-6/30/2022. Negative binomial regression models were used to evaluate whether OCS bursts in the 12-month period after an initial visit were reduced for patients who received aeroallergen testing. We also measured differences in benefit after excluding patients with chronic obstructive pulmonary disease (COPD) and smoking histories, and whether testing receipt was via skin prick or serum. RESULTS668/1,383 (48.3%) patients received testing. Receipt of testing was not associated with fewer bursts in all patients (incidence rate ratio (IRR)=0.83 versus no testing, p=0.059), but it was among never smokers without COPD (417/844 tested, IRR=0.68, p=0.004). The receipt of skin testing was associated with fewer bursts in all patients (418/1,383 tested, IRR=0.77, p=0.02) and among never smokers without COPD (283/844 tested, IRR=0.59 versus no testing, p=0.001). CONCLUSIONGuideline-concordant aeroallergen testing in the context of Allergy/Immunology care was associated with clinical benefit in a real-life, diverse cohort of adults with asthma. This benefit varied according to patient comorbidities and the testing modality.

RationaleEosinophilic airway inflammation is common in severe asthma and strongly associated with symptoms, exacerbations, and impaired lung function. Although type 2 (T2)-targeted biologics improve outcomes and reduce eosinophils, many patients experience residual symptoms and exacerbations. Emerging evidence suggests that these biologics may differentially affect specific airway eosinophil subpopulations, representing a potential mechanism of suboptimal treatment response. ObjectiveDetermine the effect of biologic treatment on eosinophil subpopulations in adults with severe asthma using in-depth immune profiling with mass cytometry (CyTOF). MethodsFifty adults with severe asthma (28 biologic-naive, 22 on stable-dose biologic therapy for [&ge;]6 months) underwent clinical phenotyping, spirometry, blood sampling, and sputum induction. Twenty-nine sputum samples passed quality control thresholds and were profiled by CyTOF. Manually gated sputum eosinophils were clustered using FlowSOM to identify eosinophil subpopulations, and cluster abundances and marker expression were compared across treatment groups. Measurements and Main ResultsCyTOF revealed treatment-associated shifts in circulating immune cells (lower CD4+ T cells and B cells, higher monocytes) and lower sputum CD8+ T cells. Unsupervised clustering of sputum eosinophils identified eight distinct subpopulations, and selective depletion of Cluster 6 was noted in biologic-treated participants (biologic-naive vs anti-TSLP logFC -4.98, p=0.003; biologic-naive vs anti-IL5 logFC -6.89, p=0.01). Higher Cluster 6 proportion correlated with worse ACT scores (rho = -0.44, p = 0.02) and lung function (FEV1 % predicted: rho = -0.47, p < 0.01; FEV1/FVC: rho = -0.40, p = 0.03). Functionally, Cluster 6 displayed enriched trafficking/activation markers (CCR3/Eotaxin-1, CD69, CD80, CRTH2) and non-T2 inflammatory mediators (TNF, IL-8, TLR7). ConclusionBiologic therapy in severe asthma was associated with selective depletion of a highly activated sputum eosinophil subpopulation with capability to drive both T2 and non-T2 inflammatory pathways. This cluster correlated with worse asthma control and lung function, indicating it may be a biologically important driver of persistent disease and potential biomarker to more accurately predict treatment response.

RationaleAsthma is a multifactorial disease with a role of genetic susceptibility and environmental exposures. These aspects are poorly understood for pediatric obesity-related asthma, a phenotype of non-allergic asthma. ObjectiveTo quantify gene by environment interactions in obesity-related asthma MethodsUsing expression quantitative trait loci (eQTLs) as measure of genetic susceptibility, and obesity-mediated effects on anthropometrics, metabolic measures, and T helper cell proportions as biological sequelae of obesogenic environment, we quantified the association of eQTLs with asthma burden, and its modulation by obesity-mediated effects, in primary cohort of 144 children, and validation cohort of 101 children. Measurements and Main ResultsOf the 3,904 eQTLs associated with gene expression, up to 30% were associated with pulmonary function indices, including FVC, FEV1, TLC, FRC and IC, and were enriched for African ancestry. These eQTLs encoded for antigen presentation, cell mobility, autophagy, small GTPase signal transduction, fatty acid metabolism, and chromosome segregation pathways. Neck and waist circumference, insulin resistance, leptin and adiponectin levels, and T helper 1 and 17 cell proportions attenuated association of up to 51% eQTLs with pulmonary function, which encoded for all but fatty acid metabolism and chromosome segregation pathways. eQTLs associated with ATF6 and MEI1 retained significance. eQTLs for RNASET2, FBLN5, STX2, HEATR3 and SERPINB6 genes were associated with pulmonary function in the validation cohort. ConclusionsWe report novel genetic susceptibility markers of asthma burden in pediatric obesity-related asthma that are enriched for African ancestry and are partly attenuated by truncal fat load and obesity-mediated inflammation and metabolic dysregulation.

Biologic monoclonal antibody therapies for severe asthma target the Type 2 endotype through blockade of the IgE, IL-5/eosinophil, or IL-4/13 pathways, which represents at least two-thirds of patients, and have led to significant clinical benefits in severe asthma management. However, studies show that 10-20% of patients may be non-responders and require a change in therapy. There is also the emerging concept that a significant percentage of patients may enter clinical remission, with a very high level of disease control and virtually symptom-free. These clinical scenarios and heterogeneity increase the need to develop blood-based biomarkers that can predict outcome. Identifying markers of clinical remission may also have potential for expanding access to other severe asthma patients not currently identified through serum IgE, blood eosinophils, or FeNO. In this study, blood was taken prior to therapy from severe asthma patients (n=31) with a Type 2 endotype, high serum IgE, atopy, and blood eosinophilia who qualified for both Omalizumab (anti-IgE) and Mepolizumab (anti-IL-5) and were randomised to receive either treatment. White blood cells underwent single cell RNA-sequencing and patients were assessed for clinical outcomes over a 6-month period. Non-response to either Omalizumab or Mepolizumab was predicted by a gene signature expressed in antiviral plasmacytoid dendritic cells. Clinical remission was predicted by a common gene signature in rarer CD34+ blood progenitors and circulating MAIT cells with a ROC Curve AUC of 0.91 and 0.88, respectively. This discovery study identifies novel blood biomarkers that predict clinical outcome to multiple biologic therapies in severe asthma.

Pediatric asthma exacerbations are a frequent cause of emergency department (ED) visits and hospitalizations, yet accurate risk prediction remains limited and no consensus risk scores exist. Using UF Health electronic health records (EHRs) from 2011-2023, we evaluated two computable phenotypes (i.e., CAPriCORN and COMPAC) to predict exacerbations over 6-, 12-, and 24-month horizons. Exacerbations were defined using a validated composite of diagnosis codes from ED, inpatient, or outpatient encounters combined with systemic corticosteroids prescriptions. Several commonly used machine learning (ML) models were trained with stratified five-fold cross-validation, Bayesian hyperparameter optimization, and Youdens J thresholding. XGBoost achieved the best performance, with SHapley Additive exPlanations (SHAP) highlighting note-derived symptom terms and rescue-medication use as dominant predictors. Future work will focus on external validation and assessment of generalizability. This interpretable, text-integrated framework may support child-specific risk stratification and inform EHR-based decision support for timely pediatric asthma management.

Background: Biologically distinct asthma subgroups may obscure genetic effects when analyzed as a single phenotype. We examined whether asthma susceptibility signals are shared, heterogeneous, or stratum-specific across ancestry, obesity status, and sex. Methods: We performed ancestry-specific GWAS meta-analyses in African ancestry participants (9,965 asthma cases; 37,391 controls) and European ancestry participants (6,074 cases; 116,255 controls), followed by obesity- and sex-stratified analyses. Analyses used imputed dosages and fixed-effect meta-analysis within ancestry. Results: Stratification detected asthma association signals that were less apparent in the combined phenotype. Shared cross-ancestry loci implicated epithelial antiviral susceptibility and immune regulation, represented by signals near CDHR3 and FOXO1. An ancestry-heterogeneous signal at the 17q21 locus, harboring ORMDL3/GSDMB, supported population-dependent effects at an epithelial inflammatory locus. Obesity stratification mapped the genome-wide significant burden to asthma without obesity. Sex stratification detected genome-wide significant signals in AFR females with asthma and obesity and in both sex strata with asthma without obesity, with the strongest signal burden in EU females without obesity. Conclusions: Asthma genetic architecture differed by ancestry, obesity status, and sex. Stratified analyses identified group-specific susceptibility related to epithelial and immune regulation, airway inflammation, remodeling, and neural signaling, supporting precision approaches to asthma.

The prevalence, inter-relationships, and longitudinal behavior of type 1 (T1) and type 2 (T2) immune responses in asthma are uncertain, as is the role of viruses as determinants of these responses. Here, we performed whole transcriptome network analysis on sputum cells collected from Severe Asthma Research Program (SARP)-3 patients before and after treatment with intramuscular corticosteroid and again at 1 and 3-year follow-up visits. We used network analysis to analyze whole-transcriptome gene expression and metagenomic analysis of these RNA-seq data to detect viruses. We identified T1 and T2 airway networks, the expression of which showed that 26% and 44% of patients had T1-high and T2-high asthma at baseline, respectively. Asthma severity outcomes were worse in T2-high asthma than in T1-high asthma and most severe in the subgroup of patients (14%) with combined T1- and T2-high disease. Corticosteroid treatment suppressed T2 but not T1 gene expression, and corticosteroid-associated improvements in FEV1 occurred only in patients with T1-L/T2-H disease and not in T1-H/T2-H patients. Although T1 and T2 inflammation at baseline was a significant predictor of T1 and T2 inflammation at follow-up visits, most patients had variable rather than persistent expression of T1 and T2 network genes. Viral metagenomic analyses uncovered that 24% of asthma sputum samples tested positive for a virus and high viral carriage was associated with an 11-fold increased risk of T1-high disease. Together our results uncover a relatively high burden of T1-high and T1/T2-high disease subtypes in severe asthma, which are corticosteroid-resistant and manifest with sub-clinical viral infection.

Eosinophilic esophagitis (EoE) is a chronic allergic disease driven by exposure to culprit antigens. Due to the local nature of the inflammation, diagnosis and assessment are limited to invasive procedures. Based on prior single-cell RNA sequencing (scRNA-seq) data linking peripheral GPR15+ pathogenic effector Th2 (peTh2) cells to esophageal tissue peTh2s, we hypothesized the direct involvement of GPR15+ peTh2 cells in EoE pathogenesis and aimed to further evaluate their association with EoE disease status. We subjected samples from subjects with or without EoE to flow cytometry (n = 74 peripheral blood, 17 biopsy) and scRNA-seq (n = 27 peripheral blood, 10 biopsy). Expression of GPR15 by peripheral peTh2 cells was increased in EoE, and these cells expressed increased CD38 in active EoE--findings recapitulated in esophageal biopsies. We also identified a peTh2-associated, CD38-containing gene expression program that peripheral GPR15+ peTh2 cells upregulated in active EoE. The level of upregulation was distinct from other circulating peTh2 cells and was more similar to that seen in esophageal peTh2 cells. An association between expression of GPR15 by peripheral peTh2 cells, the aryl hydrocarbon receptor was strongest in subjects with EoE, suggesting an environmental exposure or susceptibility. The magnitude of GPR15 expression by peripheral peTh2 cells could effectively in discriminate active EoE from no EoE in our study population (AUC 0.93). Our data suggest that EoE-related peTh2 cells are identifiable and accessible in the peripheral blood, and could be exploited in both clinical practice as a non-invasive biomarker and continued investigation into mechanisms driving EoE. One sentence summaryGPR15 marks a subset of peripheral blood pathogenic effector Th2 cells associated with eosinophilic esophagitis (EoE) that upregulate CD38 during active disease - an observation that has potential to be used for non-invasive diagnosis and monitoring of EoE and that has suggests new mechanisms driving this increasingly prevalent allergic disease.

IntroductionAsthma risk is a complex interplay between genetic susceptibility and environment. Despite many significantly-associated common variants, the contribution of rarer variants with potentially greater effect sizes has not been as extensively studied. We present an exome-based study adopting 24,576 cases and 120,530 controls to assess the contribution of rare protein-coding variants to the risk of early-onset or all-comer asthma. MethodsWe performed case-control analyses on three genetic units: variant-, gene- and pathway-level, using sequence data from the Scandinavian Asthma Genetic Study and UK Biobank participants with asthma. Cases were defined as all-comer asthma (n=24,576) and early-onset asthma (n=5,962). Controls were 120,530 UK Biobank participants without reported history of respiratory illness. ResultsVariant-level analyses identified statistically significant variants at moderate-to-common allele frequency, including protein-truncating variants in FLG and IL33. Asthma risk was significantly increased not only by individual, common FLG protein-truncating variants, but also among the collection of rare-to-private FLG protein-truncating variants (p=6.8x10-7). This signal was driven by early-onset asthma and did not correlate with circulating eosinophil levels. In contrast, a single splice variant in IL33 was significantly protective (p=8.0x10-10), while the collection of remaining IL33 protein-truncating variants showed no class effect (p=0.54). A pathway-based analysis identified that protein-truncating variants in loss-of-function intolerant genes were significantly enriched among individuals with asthma. ConclusionsAccess to the full allele frequency spectrum of protein-coding variants provides additional clarity about the potential mechanisms of action for FLG and IL33. Beyond these two significant drivers, we detected a significant enrichment of protein-truncating variants in loss-of-function intolerant genes.

RationaleAsthma is a chronic airway disease driven by multiple immunologic pathways that determine the clinical response to therapy. Current diagnostic methods are incapable of discriminating subtypes of asthma and guiding targeted treatment. We hypothesized that sputum cytokine profiles could help to identify immunologically-defined disease subtypes and individualize therapy in patients with severe asthma. ObjectivesDefine asthma subtypes associated with sputum alarmin and cytokine levels. MethodsCross-sectional analysis of clinical features and sputum from 200 asthmatic patients was performed. 10 cytokines belonging to alarmin, T2, and non-T2 pathways were measured. Pearson correlation was used to identify cytokine modules. Latent class analysis was used to cluster patients by cytokine expression. Measurements and Main ResultsThree modules of highly correlated cytokines were identified including a non-T2 module, the IL-1{beta}mod (IL-1{beta}, IL-6, GCSF), and two distinct T2 modules: TSLPmod (TSLP, IL-4, IL-5, IL-9) and IL-33mod (IL-33, IL-13, IL-21). The TSLPmod was associated with asthma severity, airway obstruction, eosinophilia, and elevated FeNO. Patient clustering revealed three subgroups; two different subgroups showed expression of T2 modules. ConclusionsAnalysis of sputum cytokines revealed three discrete signaling modules in patients with asthma. Unexpectedly, the inclusion of alarmins led to separation of canonical T2 cytokines into two unique modules; IL-5 grouped with TSLP, while IL-13 grouped with IL-33. In addition, patient clustering revealed two distinct endotypes associated with T2 immune signaling. These findings indicate a new layer of immunologic heterogeneity within the T2 paradigm, and suggest that sputum cytokine profiling may hold diagnostic utility for patients with asthma.

BackgroundGastroesophageal reflux disease (GERD) is highly prevalent in systemic sclerosis (SSc) and frequently persists despite proton pump inhibitor (PPI) therapy. However, the mechanisms underlying PPI-refractory GERD in SSc remain incompletely understood. MethodsWe conducted a singlel7lcentre, retrospective study of adults with SSc who underwent ambulatory pH-multichannel intraluminal impedance (pH/MII) monitoring while receiving twicel7ldaily PPI therapy (2021-2025). Esophageal motility (highl7lresolution manometry, HREM) and gastric emptying scintigraphy were integrated to examine associations between gastro-esophageal dysmotility and reflux phenotypes. ResultsThirty patients were included, of whom 67% had PPI-refractory reflux symptoms and 33% were undergoing pre-lung transplantation evaluation. Refractory GERD was present in 29/30 patients (97%) based on Lyon 2.0 classification, with conclusive evidence in 53% and borderline evidence in 43%. Esophageal dysmotility was identified in 80%, most commonly absent contractility (67%), and was associated with impaired reflux clearance, reflected by longer acid clearance times (2.20 [1.15-3.75] vs 1.15 [0.43-1.90] min) and prolonged reflux episode duration (16.60 [4.38-40.63] vs 1.95 [0.53-20.43] min). Gastric dysmotility was identified in 60.7% and was associated with an increased reflux episode burden (51.00 [30.00-81.50] vs 25.00 [21.00-54.00] episodes/24h). ConclusionsPPIl7lrefractory GERD is nearly universal in this SSc cohort and reflects heterogeneous, quantifiable abnormalities across the foregut, including impaired esophageal clearance and increased reflux burden related to gastric retention. These findings support integrated physiologic evaluation to define reflux mechanisms, inform risk stratification (including lung transplantation), and guide targeted, mechanism-based therapies beyond acid suppression.

Serum total immunoglobulin E levels (total IgE) capture the state of the immune system in relation to allergic sensitization. High levels are associated with airway obstruction and poor clinical outcomes in pediatric asthma. Inconsistent patient response to anti-IgE therapies motivates discovery of molecular mechanisms underlying serum IgE level differences in children with asthma. To uncover these mechanisms using complementary metabolomic and transcriptomic data, abundance levels of 529 named metabolites and expression levels of 22,772 genes were measured among children with asthma in the Childhood Asthma Management Program (CAMP, N=564) and the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS, N=309) via the TOPMed initiative. Gene-metabolite associations dependent on IgE were identified within each cohort using multivariate linear models and were interpreted in a biochemical context using network topology, pathway and chemical enrichment, and representation within reactions. A total of 1,617 total IgE-dependent gene-metabolite associations from GACRS and 29,885 from CAMP met significance cutoffs. Of these, glycine and guanidinoacetic acid (GAA) were associated with the most genes in both cohorts, and the associations represented reactions central to glycine, serine, and threonine metabolism and arginine and proline metabolism. Pathway and chemical enrichment analysis further highlighted additional related pathways of interest. The results of this study suggest that GAA may modulate total IgE levels in two independent pediatric asthma cohorts with different characteristics, supporting the use of L-Arginine as a potential therapeutic for asthma exacerbation. Other potentially new targetable pathways are also uncovered.

BackgroundThe immunometabolic mechanisms underlying variable responses to oral immunotherapy (OIT) in patients with IgE-mediated food allergy are unknown. ObjectiveTo identify novel pathways associated with tolerance in food allergy, we used metabolomic profiling to find pathways important for food allergy in multi-ethnic cohorts and responses to OIT. MethodsUntargeted plasma metabolomics data were generated from the VDAART healthy infant cohort (N=384), a Costa Rican cohort of children with asthma (N=1040), and a peanut OIT trial (N=20) evaluating sustained unresponsiveness (SU, protection that lasts after therapy) versus transient desensitization (TD, protection that ends immediately afterwards). Generalized linear regression modeling and pathway enrichment analysis identified metabolites associated with food allergy and OIT outcomes. ResultsCompared with unaffected children, those with food allergy were more likely to have metabolomic profiles with altered histidines and increased bile acids. Eicosanoids (e.g., arachidonic acid derivatives) (q=2.4x10-20) and linoleic acid derivatives (q=3.8x10-5) pathways decreased over time on OIT. Comparing SU versus TD revealed differing concentrations of bile acids (q=4.1x10-8), eicosanoids (q=7.9x10-7), and histidine pathways (q=0.015). In particular, the bile acid lithocholate (4.97[1.93,16.14], p=0.0027), the eicosanoid leukotriene B4 (3.21[1.38,8.38], p=0.01), and the histidine metabolite urocanic acid (22.13[3.98,194.67], p=0.0015) were higher in SU. ConclusionsWe observed distinct profiles of bile acids, histidines, and eicosanoids that vary among patients with food allergy, over time on OIT and between SU and TD. Participants with SU had higher levels of metabolites such as lithocholate and urocanic acid, which have immunomodulatory roles in key T-cell subsets, suggesting potential mechanisms of tolerance in immunotherapy. Key Messages- Compared with unaffected controls, children with food allergy demonstrated higher levels of bile acids and distinct histidine/urocanic acid profiles, suggesting a potential role of these metabolites in food allergy. - In participants receiving oral immunotherapy for food allergy, those who were able to maintain tolerance-even after stopping therapyhad lower overall levels of bile acid and histidine metabolites, with the exception of lithocholic acid and urocanic acid, two metabolites that have roles in T cell differentiation that may increase the likelihood of remission in immunotherapy. Capsule summaryThis is the first study of plasma metabolomic profiles of responses to OIT in individuals with IgE-mediated food allergy. Identification of immunomodulatory metabolites in allergic tolerance may help identify mechanisms of tolerance and guide future therapeutic development. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/24308233v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1d199f3org.highwire.dtl.DTLVardef@1d24661org.highwire.dtl.DTLVardef@abb6corg.highwire.dtl.DTLVardef@96e3ca_HPS_FORMAT_FIGEXP M_FIG C_FIG

Allergic disorders are common diseases marked by the abnormal immune response towards foreign antigens that are not pathogens. Often patients with food allergy also suffer from asthma and eczema. Given the similarities of these diseases and a shortage of effective treatments, developing novel therapeutics against common targets of multiple allergies would offer an efficient and cost-effective treatment for patients. Herein, we employed the artificial intelligence-driven target discovery platform, PandaOmics, to identify common targets for treating asthma, eczema, and food allergy. Thirty-two case-control comparisons were generated from 15, 11, and 6 transcriptomics datasets related to asthma (558 cases, 315 controls), eczema (441 cases, 371 controls), and food allergy (208 cases, 106 controls) respectively, and allocated into three meta-analyses for target identification. Top-100 high-confidence targets and Top-100 novel targets were prioritized by PandaOmics for each allergic disease. Six common high-confidence targets (i.e., IL4R, IL5, JAK1, JAK2, JAK3, and NR3C1) across all three allergic diseases have approved drugs for treating asthma and eczema. Based on the targets dysregulated expression profiles and their mechanism of action in allergic diseases, three potential therapeutic targets were proposed. IL5 was selected as a high-confidence target due to its strong involvement in allergies. PTAFR was identified for drug repurposing, while RNF19B was selected as a novel target for therapeutic innovation. Analysis of the dysregulated pathways commonly identified across asthma, eczema, and food allergy revealed the well-characterized disease signature and novel biological processes that may underlie the pathophysiology of allergies. Altogether, our study dissects the shared pathophysiology of allergic disorders and reveals the power of artificial intelligence in the exploration of novel therapeutic targets.

Prediction models for asthma remission in school-age are lacking, limiting clinicians' ability to tailor follow-up. Most prediction tools focus on pre-school diagnosis or require lung function testing. We developed and validated a simple, history-based clinical prediction tool for asthma remission. We analyzed prospective data from the Swiss Paediatric Airway Cohort (SPAC), including 1860 children (aged 5-16 years) with physician-diagnosed asthma. We derived asthma remission predictors from parental questionnaires capturing demographics, symptoms, triggers, and family history. We defined clinical remission at 2-3 years following asthma diagnosis, as absence of wheeze and inhaler use during the past 12 months. We developed the model using LASSO regression with multiple imputations for missing data, and assessed its performance by area under the curve (AUC), Hosmer-Lemeshow (HL) test, and calibration plots. We then derived a simplified score and validated it in the German All-Age Asthma Cohort (ALLIANCE). From 12 candidate variables, the final score retained: sex, wheeze frequency, night-time awakening, exercise-induced wheeze, pollen-triggered wheeze, animal-triggered wheeze, maternal asthma, and paternal asthma. The score demonstrated moderate discrimination in the development cohort (AUC 0.71) and maintained discriminative ability in the external validation (AUC 0.71). This practical, prognostic tool for asthma remission based only on clinical history, allows clinicians to identify children who have lower chances for remission, enabling their closer monitoring.

Childhood-onset asthma is characterized by Type 2-inflammation and airway wall remodeling, but mechanisms of asthma development in the first years of life remain unclear. Here, we investigate transcriptional changes in airway wall biopsies of 22 symptomatic one year old children and relate these to asthma at school age. We demonstrate that pre-asthmatic children (n = 10) overexpressed a gene signature characteristic for an airway epithelial differentiation trajectory via hillock cells towards squamous cells (adjusted p-value 8.06e-16), whilst there was no association with gene signatures of Type 2-inflammation or eosinophil activation. Genes expressed along this trajectory are linked to an altered epithelial barrier function, innate immune activation and extracellular matrix remodeling. Functional GWAS analysis supports a causal link between childhood-onset, but not adult-onset asthma, and the hillock-squamous cell differentiation trajectory. Next, we confirmed the presence of hillock-like cells at the RNA and protein level in pediatric upper and lower airway samples. These findings identify a novel mechanism by which an aberrant airway epithelial differentiation trajectory may contribute to a pre-asthmatic state, highlighting the difference between the early origins of childhood-onset asthma and adult asthma, and point to possible new targets for the early diagnosis and treatment of asthma in the first two years of life. One Sentence SummaryRNA sequencing in bronchial biopsies from wheezing infants and children < 2 years shows evidence for an airway epithelial hillock-to-squamous differentiation pathway that marks the development of asthma.

Obesity increases local inflammatory responses in adipose tissue. Individuals with obesity have increased asthma incidence and severity and reduced responses to asthma therapeutics through unknown mechanisms. To identify mechanisms by which increased fat mass augments asthma pathogenesis, single cell RNA sequencing of the immune-rich stromovascular fraction of subcutaneous adipose tissue was conducted from well-characterized adults with obesity-associated asthma matched to adults without asthma. Individuals with asthma had increased abundance of perivascular macrophages and lymphoid-associated macrophages (LAMs) and reduced abundance of classical monocytes and CD4+ and CD8+ naive T cells. Pseudo-bulk differential expression (DE) identified upregulation of cellular metabolism, specifically oxidative phosphorylation, and decreased immune homeostatic pathways in asthma across immune cell subsets. Cell type specific DE analysis of effector cell subtypes identified significant induction of metallothionein gene expression in asthma, a signature of immune cell dysfunction characterized by both an activation and exhaustion phenotype. Gene co-expression analysis identified gene modules associated with asthma diagnosis, lung function, and biomarkers of type 2 inflammation were enriched in effector cells. These data identify adipose tissue dysfunction occurs in obesity-associated asthma and support adipose tissue as therapeutic target to address the enhanced asthma risk among those with obesity. Grant SupportNIH U01AI155299, P30DK020593, R01AI182159, K23HL159351, UL1RR024975-03, P30CA68485, P30EY08126, G20RR030956, 5UL1TR002243, KL2TR002245, P30AI110527, DK020593, American Heart Association 17SFRN33520017.

BackgroundRecent guidelines differ in how fractional exhaled nitric oxide (FeNO) is used to diagnose school-age asthma, either as one of several tests with a cut-off at 25 ppb or as a single rule-in test at 35 ppb. Evidence on its diagnostic performance and clinical utility in subgroups remain limited. MethodsWe analysed data from 1,979 school-age children in the Swiss Paediatric Airway Cohort referred for suspected asthma. We investigated FeNO performance with diagnosis by paediatric pulmonologists as reference standard using receiver operating characteristics curves, selected cut-offs and simulated predictive values across different prevalence. Subgroup analyses considered allergic sensitisation with allergic rhinitis and current inhaled corticosteroid (ICS) use. ResultsIn the overall cohort (asthma diagnosis 70%), FeNO showed poor discrimination for asthma (AUC 0.66; 95% CI 0.64-0.68) with an optimal cut-off at 22 ppb. At 25 and 35 ppb, sensitivity was low (43%, 95% CI 40-46; 31%, 95% CI 29-34) and specificity moderate to high (84%, 95% CI 77-84; 90%, 95% CI 87-92). Positive predictive value at 35 ppb was 88% and was 57% when simulated at a prevalence of 30%. FeNO had no diagnostic value in non-sensitised children and lower performance in sensitised children with allergic rhinitis than in those without (AUC 0.59 vs 0.68). Current ICS use did not influence performance. ConclusionFeNO has limited diagnostic performance as a stand-alone test for school-age asthma, and underlying asthma prevalence and allergic characteristics should be considered in the interpretation.

BackgroundChildhood-onset asthma is highly heritable, with nearly 200 risk loci identified in genome-wide association studies. Aggregated polygenic risk scores can be used to quantify genetic predisposition to asthma, but their power to predict asthma severity in multi-ancestral groups has not been previously evaluated. ObjectiveOur aim was to examine the predictive power of biobank-derived asthma polygenic risk scores in four multi-ancestry asthma study cohorts of children living in U.S. urban environments. MethodsWe generated polygenic risk scores for asthma, derived from a large-scale genome-wide association meta-analysis, and assessed genetic predictions across different subphenotypes of asthma and tested for associations between genetic asthma risk and measures of asthma severity. ResultsPolygenic risk score prediction was significantly stronger for more symptomatic asthma phenotypes (P<0.001), and scores were significantly higher in difficult-to-control vs. easy-to-control asthma (P=0.02). Genetic risk was also significantly associated with more frequent exacerbations (P=0.03), higher blood eosinophil levels (P=0.01), and lower lung function (P<0.001). ConclusionCumulative genetic risk for asthma is associated with disease severity and exacerbation risk in children with asthma. Key MessagesO_LIPolygenic risk prediction is stronger in more symptomatic phenotypes C_LIO_LICumulative genetic risk for asthma is associated with greater asthma severity, higher exacerbation frequency, lower lung function, and increased eosinophil levels in children with asthma C_LI Capsule SummaryWe demonstrate that cumulative genetic risk for asthma is associated with disease severity in children with asthma living in urban environments.

IntroductionWhile reliable, quantitative in vitro testing for sensitivity to aeroallergens has been available for decades, if and how asthma severity markers might be predictably expressed in clusters matched for comparable multiple sensitizations is unknown. ObjectiveOur aim is to use machine learning techniques to explore how allergic poly-sensitization (APS) clusters may serve as precision markers in adult urban patients with moderate to severe asthma. MethodsWe constructed a database of sensitizations to the 25 aeroallergens in the Zone 1 Northeastern US ImmunoCAP(R) assay. We used the Scikit-Learn(R) machine learning library to perform model-based clustering to identify APS clusters. Clusters were compared for differences in common clinical markers of asthma. ResultsThe database consisted of 509 patients. Unbiased mixture modeling identified ten clusters of increasing APS of varying size (n = 1 to 339) characterized by significant increases in mean serum immunoglobulin E (p<.001), peripheral blood eosinophil count (p<.001), and DLCO (p=.02). There was a significant decline in mean age at presentation (p<.001), FEV1/FVC (p=.01), and FEF25-75 (p=.002), but not FEV1 (p=.29), nor RV/TLC (p=.14) with increasing APS by simple linear regression. Finally, we identified two divergent paths for the poly-atopic march, one driven by perennial and the other by seasonal allergens. ConclusionWe conducted a pilot study for a novel machine learning understanding and approach to the classification of APS and potential influences if included in asthma cluster analyses. The methods used here can be easily applied to other geographic regions with different allergens