Heterogeneity of severe asthma in childhood: confirmation by cluster analysis of children in the National Institutes of Health/National Heart, Lung, and Blood Institute Severe Asthma Research Program. J Allergy Clin Immunol. 2011;127:382-389.e1-13. [PMID: 21195471 DOI: 10.1016/j.jaci.2010.11.015]

Activated non-neuronal cholinergic system correlates with non-type 2 inflammation and exacerbations in severe asthma

BACKGROUND

Non-neuronal cholinergic system (NNCS) contributes to various inflammatory airway diseases. However, the role of NNCS in severe asthma (SA) remains largely unexplored.

OBJECTIVE

To explore airway NNCS in SA.

METHODS

In this prospective cohort study based on the Australasian Severe Asthma Network in a real-world setting, patients with SA (n = 52) and non-SA (n = 104) underwent clinical assessment and sputum induction. The messenger RNA (mRNA) levels of NNCS components and proinflammatory cytokines in the sputum were detected using real-time quantitative polymerase chain reaction, and the concentrations of acetylcholine (Ach)-related metabolites were evaluated using liquid chromatography coupled with tandem mass spectrometry. Asthma exacerbations were prospectively investigated during the next 12 months. The association between NNCS and future asthma exacerbations was also analyzed.

RESULTS

Patients with SA were less controlled and had worse airway obstruction, a lower bronchodilator response, higher doses of inhaled corticosteroids, and more add-on treatments. The sputum mRNA levels of NNCS components, such as muscarinic receptors M1R-M5R, OCT3, VACHT, and ACHE; proinflammatory cytokines; and Ach concentration in the SA group were significantly higher than those in the non-SA group. Furthermore, most NNCS components positively correlated with non-type (T) 2 inflammatory profiles, such as sputum neutrophils, IL8, and IL1B. In addition, the mRNA levels of sputum M2R, M3R, M4R, M5R, and VACHT were independently associated with an increased risk of moderate-to-severe asthma exacerbations.

CONCLUSION

This study indicated that the NNCS was significantly activated in SA, leading to elevated Ach and was associated with clinical features, non-T2 inflammation, and future exacerbations of asthma, highlighting the potential role of the NNCS in the pathogenesis of SA.

CLINICAL TRIAL REGISTRATION

ChiCTR-OOC-16009529 (http://www.chictr.org.cn).

Benralizumab in children with severe eosinophilic asthma: Pharmacokinetics and long-term safety (TATE study)

BACKGROUND

Benralizumab is an anti-interleukin-5 receptor α monoclonal antibody approved as an add-on maintenance treatment for patients with uncontrolled severe asthma. Prior Phase 3 studies have evaluated benralizumab in patients aged ≥12 years with severe uncontrolled asthma. The TATE study evaluated the pharmacokinetics (PK), pharmacodynamics (PD), and safety of benralizumab treatment in children.

METHODS

TATE was an open-label, Phase 3 study of benralizumab in children aged 6-11 years from the United States and Japan (plus participants aged 12-14 years from Japan) with severe eosinophilic asthma. Participants received benralizumab 10/30 mg according to weight (<35/≥35 kg). Primary endpoints included maximum serum concentration (Cmax ), clearance, half-life (t1/2 ), and blood eosinophil count. Clearance and t1/2 were derived from a population PK (popPK) analysis. Safety and tolerability were also assessed.

RESULTS

Twenty-eight children aged 6-11 years were included, with an additional two participants from Japan aged 12-14 years also included in the popPK analysis. Mean Cmax was 1901.2 and 3118.7 ng/mL in the 10 mg/<35 kg and 30 mg/≥35 kg groups, respectively. Clearance was 0.257, and mean t1/2 was 14.5 days. Near-complete depletion of blood eosinophils was shown across dose/weight groups. Exploratory efficacy analyses found numerical improvements in mean FEV1 , mean ACQ-IA, patient/clinician global impression of change, and exacerbation rates. Adverse events occurred in 22/28 (78.6%) of participants; none led to discontinuation/death.

CONCLUSION

PK, PD, and safety data support long-term benralizumab in children with severe eosinophilic asthma, and were similar to findings in adolescents and adults.

TRIAL REGISTRATION

ClinicalTrials.gov-ID: NCT04305405.

COBRAPed cohort: Do sensitization patterns differentiate children with severe asthma from those with a milder disease?

BACKGROUND

It is unclear whether sensitization patterns differentiate children with severe recurrent wheeze (SRW)/severe asthma (SA) from those with non-severe recurrent wheeze (NSRW)/non-severe asthma (NSA). Our objective was to determine whether sensitization patterns can discriminate between children from the French COBRAPed cohort with NSRW/NSA and those with SRW/SA.

METHODS

IgE to 112 components (c-sIgE) (ImmunoCAP® ISAC) were analyzed in 125 preschools (3-6 years) and 170 school-age children (7-12 years). Supervised analyses and clustering methods were applied to identify patterns of sensitization among children with positive c-sIgE.

RESULTS

We observed c-sIgE sensitization in 51% of preschool and 75% of school-age children. Sensitization to house dust mite (HDM) components was more frequent among NSRW than SRW (53% vs. 24%, p < .01). Sensitization to non-specific lipid transfer protein (nsLTP) components was more frequent among SA than NSA (16% vs. 4%, p < .01) and associated with an FEV1/FVC < -1.64 z-score. Among sensitized children, seven clusters with varying patterns were identified. The two broader clusters identified in each age group were characterized by "few sensitizations, mainly to HDM." One cluster (n = 4) with "multiple sensitizations, mainly to grass pollen, HDM, PR-10, and nsLTP" was associated with SA in school-age children.

CONCLUSIONS

Although children with wheeze/asthma display frequent occurrences and high levels of sensitization, sensitization patterns did not provide strong signals to discriminate children with severe disease from those with milder disease. These results suggest that the severity of wheeze/asthma may depend on both IgE- and non-IgE-mediated mechanisms.

Emergency management and asthma risk in young Medicaid-enrolled children with recurrent wheeze

OBJECTIVES

To describe clinical characteristics of young children presenting to the emergency department (ED) for early recurrent wheeze, and determine factors associated with subsequent persistent wheeze and risk for early childhood asthma.

METHODS

Retrospective cohort study of Medicaid-enrolled children 0-3 years old with an index ED visit for wheeze (e.g. bronchiolitis, reactive airway disease) from 2009 to 2013, and at least one prior documented episode of wheeze at an ED or primary care visit. The primary outcome was persistent wheeze between 4 and 6 years of age. Demographics and clinical characteristics were collected from the index ED visit. Logistic regression was used to estimate the association between potential risk factors and subsequent persistent wheeze.

RESULTS

During the study period, 41,710 children presented to the ED for recurrent wheeze. Mean age was 1.3 years; 59% were male, 42% Black, and 6% Hispanic. At index ED visits, the most common diagnosis was acute bronchiolitis (40%); 77% of children received an oral corticosteroid prescription. Between 4 and 6 years of age, 11,708 (28%) children had persistent wheeze. A greater number of wheezing episodes was associated with an increased odds of ED treatment with asthma medications. Subsequent persistent wheeze was associated with male sex, Black race, atopy, prescription for bronchodilators or corticosteroids, and greater number of visits for wheeze.

CONCLUSIONS

Young children with persistent wheeze are at risk for childhood asthma. Thus, identification of risk factors associated with persistent wheeze in young children with recurrent wheeze might aid in early detection of asthma and initiation of preventative therapies.

Management of the pediatric patient with asthma and obesity

Asthma and obesity are 2 of the most significant chronic diseases of childhood. Both are major public health problems that have been increasing in prevalence. Obesity increases the risk of developing asthma in children, and in children with asthma, obesity increases asthma severity and morbidity. The nature of this relationship is complex and not fully understood, but some pediatric patients with "obesity-related asthma" may represent a phenotype that differs from the more classical, atopic pediatric asthma. In this review, we investigate and discuss some of the currently available literature regarding treatment for asthma complicated by obesity in the pediatric population. We cover the importance of healthy lifestyle modifications, management of obesity-related comorbidities, and the potential role of nutritional supplementation or modification. We then review recent literature, mostly in adults, investigating the potential role of obesity or diabetes medications in the management of patients with asthma who have obesity. Finally, we discuss some of the necessary next steps before these potential new treatments can be considered as part of the standard clinical management of asthma.

GEMA 5.3. Spanish Guideline on the Management of Asthma

The Spanish Guideline on the Management of Asthma, better known by its acronym in Spanish GEMA, has been available for more than 20 years. Twenty-one scientific societies or related groups both from Spain and internationally have participated in the preparation and development of the updated edition of GEMA, which in fact has been currently positioned as the reference guide on asthma in the Spanish language worldwide. Its objective is to prevent and improve the clinical situation of people with asthma by increasing the knowledge of healthcare professionals involved in their care. Its purpose is to convert scientific evidence into simple and easy-to-follow practical recommendations. Therefore, it is not a monograph that brings together all the scientific knowledge about the disease, but rather a brief document with the essentials, designed to be applied quickly in routine clinical practice. The guidelines are necessarily multidisciplinary, developed to be useful and an indispensable tool for physicians of different specialties, as well as nurses and pharmacists. Probably the most outstanding aspects of the guide are the recommendations to: establish the diagnosis of asthma using a sequential algorithm based on objective diagnostic tests; the follow-up of patients, preferably based on the strategy of achieving and maintaining control of the disease; treatment according to the level of severity of asthma, using six steps from least to greatest need of pharmaceutical drugs, and the treatment algorithm for the indication of biologics in patients with severe uncontrolled asthma based on phenotypes. And now, in addition to that, there is a novelty for easy use and follow-up through a computer application based on the chatbot-type conversational artificial intelligence (ia-GEMA).

Severe Asthma and Biological Therapies: Now and the Future

Recognition of phenotypic variability in pediatric asthma allows for a more personalized therapeutic approach. Knowledge of the underlying pathophysiological and molecular mechanisms (endotypes) of corresponding biomarkers and new treatments enables this strategy to progress. Biologic therapies for children with severe asthma are becoming more relevant in this sense. The T2 phenotype is the most prevalent in childhood and adolescence, and non-T2 phenotypes are usually rare. This document aims to review the mechanism of action, efficacy, and potential predictive and monitoring biomarkers of biological drugs, focusing on the pediatric population. The drugs currently available are omalizumab, mepolizumab, benralizumab, dupilumab, and 1ezepelumab, with some differences in administrative approval prescription criteria between the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Previously, we described the characteristics of severe asthma in children and its diagnostic and therapeutic management.

Exploring redox imbalance and inflammation for asthma therapy

BACKGROUND

Asthma is a prolonged inflammatory disorder of the airways, that affects an estimated 300 million people worldwide. Asthma is triggered by numerous endogenous and exogenous stimuli with symptoms like wheezing, cough, short of breath, chest tightening, airway obstruction, and hyperreactivity observed in patients.

OBJECTIVE

The review seeks to identify targets of redox imbalance and inflammation that could be explored to create effective treatments for asthma.

METHODS

The methodology involved a search and review of literature relating to asthma pathogenesis, redox homeostasis, and inflammation.

RESULTS

 Eosinophils and neutrophils are involved in asthma pathogenesis. These inflammatory cells generate high levels of endogenous oxidants such as hydrogen peroxide and superoxide, which could result in redox imbalance in the airways of asthmatics. Redox imbalance occurs when the antioxidant systems becomes overwhelmed resulting in oxidative stress. Oxidative stress and inflammation have been linked with asthma inflammation and severity. Reactive oxygen species (ROS)/reactive nitrogen species (RNS) cause lung inflammation by activating nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK), activator protein-1, as well as additional transcription factors. These factors stimulate cytokine production which ultimately activates inflammatory cells in the bronchi, causing lung cellular injury and destruction. ROS/RNS is also produced by these inflammatory cells to eradicate invading bacteria. Antioxidant treatments for asthma have not yet been fully explored.

CONCLUSION

Redox and inflammatory processes are viable targets that could be explored to create better therapy for asthma.

Controversies in Allergy: Are Biologic Treatment Responses in Severe Asthma the Same in Adults and Children?

The availability of biologic agents for patients with severe asthma has increased dramatically over the last several decades. The absence of direct head-to-head comparative data and relative lack of biomarkers to predict response can make it difficult to choose the right biologic medication for a given patient. Selecting a biologic agent for the pediatric population presents further challenges due to more limited approved biologic agents and fewer clinical trials in children. In addition, the outcome data that are currently available suggest that treatment responses for a given biologic may be different between adult and pediatric patients. To better understand this possible difference in treatment response, this review focuses on the available efficacy data for biologics evaluated in adult and pediatric patients with severe asthma in addition to other considerations when choosing a biologic agent. Finally, this review discusses how asthma phenotypes differ across age groups and their contributions to the responses to biologic treatment across age groups.

Childhood asthma phenotypes and endotypes: a glance into the mosaic

BACKGROUND

Asthma is an inflammatory lung disease that constitutes the most common noncommunicable chronic disease in childhood. Childhood asthma shows large heterogeneity regarding onset of disease, symptoms, severity, prognosis, and response to therapy.

MAIN BODY

Evidence suggests that this variability is due to distinct pathophysiological mechanisms, which has led to an exhaustive research effort to understand and characterize these distinct entities currently designated as "endotypes." Initially, studies focused on identifying specific groups using clinical variables yielding different "clinical phenotypes." In addition, the identification of specific patterns based on inflammatory cell counts and cytokine data has resulted in "inflammatory endotypes." More recently, an increasing number of molecular data from high-throughput technology ("omics" data) have allowed to investigate more complex "molecular endotypes."

CONCLUSION

A better definition and comprehension of childhood asthma heterogeneity is key for improving diagnosis and treatment. This review aims at summarizing the current knowledge on this topic and discusses some limitations in their application as well as recommendations for future studies.

Subtyping Social Determinants of Health in All of Us: Network Analysis and Visualization Approach

Background

Social determinants of health (SDoH), such as financial resources and housing stability, account for between 30-55% of people's health outcomes. While many studies have identified strong associations among specific SDoH and health outcomes, most people experience multiple SDoH that impact their daily lives. Analysis of this complexity requires the integration of personal, clinical, social, and environmental information from a large cohort of individuals that have been traditionally underrepresented in research, which is only recently being made available through the All of Us research program. However, little is known about the range and response of SDoH in All of Us, and how they co-occur to form subtypes, which are critical for designing targeted interventions.

Objective

To address two research questions: (1) What is the range and response to survey questions related to SDoH in the All of Us dataset? (2) How do SDoH co-occur to form subtypes, and what are their risk for adverse health outcomes?

Methods

For Question-1, an expert panel analyzed the range of SDoH questions across the surveys with respect to the 5 domains in Healthy People 2030 (HP-30), and analyzed their responses across the full All of Us data (n=372,397, V6). For Question-2, we used the following steps: (1) due to the missingness across the surveys, selected all participants with valid and complete SDoH data, and used inverse probability weighting to adjust their imbalance in demographics compared to the full data; (2) an expert panel grouped the SDoH questions into SDoH factors for enabling a more consistent granularity; (3) used bipartite modularity maximization to identify SDoH biclusters, their significance, and their replicability; (4) measured the association of each bicluster to three outcomes (depression, delayed medical care, emergency room visits in the last year) using multiple data types (surveys, electronic health records, and zip codes mapped to Medicaid expansion states); and (5) the expert panel inferred the subtype labels, potential mechanisms that precipitate adverse health outcomes, and interventions to prevent them.

Results

For Question-1, we identified 110 SDoH questions across 4 surveys, which covered all 5 domains in HP-30. However, the results also revealed a large degree of missingness in survey responses (1.76%-84.56%), with later surveys having significantly fewer responses compared to earlier ones, and significant differences in race, ethnicity, and age of participants of those that completed the surveys with SDoH questions, compared to those in the full All of Us dataset. Furthermore, as the SDoH questions varied in granularity, they were categorized by an expert panel into 18 SDoH factors. For Question-2, the subtype analysis (n=12,913, d=18) identified 4 biclusters with significant biclusteredness (Q=0.13, random-Q=0.11, z=7.5, P<0.001), and significant replication (Real-RI=0.88, Random-RI=0.62, P<.001). Furthermore, there were statistically significant associations between specific subtypes and the outcomes, and with Medicaid expansion, each with meaningful interpretations and potential targeted interventions. For example, the subtype Socioeconomic Barriers included the SDoH factors not employed, food insecurity, housing insecurity, low income, low literacy, and low educational attainment, and had a significantly higher odds ratio (OR=4.2, CI=3.5-5.1, P-corr<.001) for depression, when compared to the subtype Sociocultural Barriers. Individuals that match this subtype profile could be screened early for depression and referred to social services for addressing combinations of SDoH such as housing insecurity and low income. Finally, the identified subtypes spanned one or more HP-30 domains revealing the difference between the current knowledge-based SDoH domains, and the data-driven subtypes.

Conclusions

The results revealed that the SDoH subtypes not only had statistically significant clustering and replicability, but also had significant associations with critical adverse health outcomes, which had translational implications for designing targeted SDoH interventions, decision-support systems to alert clinicians of potential risks, and for public policies. Furthermore, these SDoH subtypes spanned multiple SDoH domains defined by HP-30 revealing the complexity of SDoH in the real-world, and aligning with influential SDoH conceptual models such as by Dahlgren-Whitehead. However, the high-degree of missingness warrants repeating the analysis as the data becomes more complete. Consequently we designed our machine learning code to be generalizable and scalable, and made it available on the All of Us workbench, which can be used to periodically rerun the analysis as the dataset grows for analyzing subtypes related to SDoH, and beyond.

Ιnterleukin-17A-Enriched Neutrophil Extracellular Traps Promote Immunofibrotic Aspects of Childhood Asthma Exacerbation

Childhood asthma is a chronic inflammatory airway disorder that can drive tissue remodeling. Neutrophils are amongst the most prominent inflammatory cells contributing to disease manifestations and may exert a potent role in the progression of inflammation to fibrosis. However, their role in asthma exacerbation is still understudied. Here, we investigate the association between neutrophil extracellular traps (NETs) and lung fibroblasts in childhood asthma pathophysiology using serum samples from pediatric patients during asthma exacerbation. Cell-based assays and NETs/human fetal lung fibroblast co-cultures were deployed. Increased levels of NETs and interleukin (IL)-17A were detected in the sera of children during asthma exacerbation. The in vitro stimulation of control neutrophils using the sera from pediatric patients during asthma exacerbation resulted in IL-17A-enriched NET formation. The subsequent co-incubation of lung fibroblasts with in vitro-generated IL-17A-enriched NETs led fibroblasts to acquire a pre-fibrotic phenotype, as assessed via enhanced CCN2 expression, migratory/healing capacity, and collagen release. These data uncover the important pathogenic role of the NET/IL-17A axis in asthma exacerbation, linking lung inflammation to fibroblast dysfunction and fibrosis.

Exhaled volatile organic compounds for diagnosis and monitoring of asthma

The asthmatic inflammatory process results in the generation of volatile organic compounds (VOCs), which are subsequently secreted by the airways. The study of these elements through gas chromatography-mass spectrometry (GC-MS), which can identify individual molecules with a discriminatory capacity of over 85%, and electronic-Nose (e-NOSE), which is able to perform a quick onboard pattern-recognition analysis of VOCs, has allowed new prospects for non-invasive analysis of the disease in an "omics" approach. In this review, we aim to collect and compare the progress made in VOCs analysis using the two methods and their instrumental characteristics. Studies have described the potential of GC-MS and e-NOSE in a multitude of relevant aspects of the disease in both children and adults, as well as differential diagnosis between asthma and other conditions such as wheezing, cystic fibrosis, COPD, allergic rhinitis and last but not least, the accuracy of these methods compared to other diagnostic tools such as lung function, FeNO and eosinophil count. Due to significant limitations of both methods, it is still necessary to improve and standardize techniques. Currently, e-NOSE appears to be the most promising aid in clinical practice, whereas GC-MS, as the gold standard for the structural analysis of molecules, remains an essential tool in terms of research for further studies on the pathophysiologic pathways of the asthmatic inflammatory process. In conclusion, the study of VOCs through GC-MS and e-NOSE appears to hold promise for the non-invasive diagnosis, assessment, and monitoring of asthma, as well as for further research studies on the disease.

Maternal stress increases risk of allergic lung inflammation in adult mice

BACKGROUND

Allergies are increasing worldwide. The presence of atopic diseases in the mother propagates the onset of allergic diseases in the offspring with a considerably stronger penetrance than atopic diseases of the father. Such observation challenges genetic predispositions as the sole cause of allergic diseases. Epidemiological studies suggest that caregiver stress in the perinatal period may predispose offspring to asthma. Only one group has studied the link between prenatal stress and neonatal asthma susceptibility in a murine model.

OBJECTIVES

We aimed to study if the neonatal increased risk of developing allergic lung inflammation persists after puberty and if there are sex differences in susceptibility.

METHODS

Pregnant BALB/c mice were subjected to a single restraint stress exposure at day 15 of gestation. Pups were separated by gender and subjected to a well-known sub-optimal asthma model after puberty.

RESULTS

Adult mice born to stressed dams were more susceptible to developing allergic pulmonary inflammation since an increase in the number of eosinophils in bronchoalveolar lavage (BAL), a greater peribronchial and perivascular infiltrate, a higher proportion of mucus-producing cells, and increased IL-4 and IL-5 levels in BAL were detected compared to control mice. These effects were more profound in females than males. Moreover, only females from stressed dams showed an increase in IgE levels.

CONCLUSIONS

Increased litter susceptibility to develop allergic lung inflammation induced by maternal stress persists after puberty and is more potent in females than in male mice.

Cluster analysis of plasma cytokines identifies two unique endotypes of children with asthma in the pediatric intensive care unit

Children with life-threatening asthma exacerbations who are admitted to a pediatric intensive care unit (PICU) are a heterogeneous group with poorly studied inflammatory features. We hypothesized that distinct clusters of children with asthma in a PICU would be identified based on differences in plasma cytokine levels and that these clusters would have differing underlying inflammation and asthma outcomes within 1 year. Plasma cytokines and differential gene expression were measured in neutrophils isolated from children admitted to a PICU for asthma. Participants were clustered by differential plasma cytokine abundance. Gene expression differences were compared by cluster and pathway over-representation analysis was performed. We identified two clusters in 69 children with no clinical differences. Cluster 1 (n = 41) had higher cytokines compared to Cluster 2 (n = 28). Cluster 2 had a hazard ratio of 2.71 (95% CI 1.11-6.64) compared to Cluster 1 for time to subsequent exacerbation. Gene expression pathways that differed by cluster included interleukin-10 signaling; nucleotide-binding domain, leucine rich repeat containing receptor (NLR signaling); and toll-like receptor (TLR) signaling. These observations suggest that a subset of children may have a unique pattern of inflammation during PICU hospitalization that might require alternative treatment approaches.

Biologics in the treatment of asthma in children and adolescents

Severe asthma in childhood confers substantial patient- and society-level burdens. Although biologics have been available for the management in adults and adolescents for nearly 20 years, research on the efficacy and safety of biologics in children and adolescents has lagged. Fortunately, more recent research specifically in children has provided an evidence base for biologic use in this age group. Most children with severe asthma demonstrate a type 2 inflammatory phenotype, the primary target of currently approved biologics. Three biologics, omalizumab, mepolizumab, and duplilumab, are Food and Drug Administration-approved for children as young as 6 years, whereas benralizumab and tezepelumab are approved for adolescents older than 12 years. All these agents reduce the rates of severe asthma exacerbations, whereas their effects on pulmonary function vary across agents. Safety profiles are reassuring, although additional long-term safety data in children are still needed. The choice of a biologic agent follows a careful assessment of other factors that contribute to uncontrolled asthma and includes biomarkers of blood eosinophils, fractional exhaled nitric oxide, allergic sensitization, and IgE levels. This review focuses on the underlying pathophysiology of childhood asthma, an approach to phenotyping patients, and the efficacy, safety, and use of biologics in children and adolescents with severe asthma.

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization

OBJECTIVE

Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. This study aimed to investigate different machine learning models and suggested the most effective one to classify two forms of asthma in preschool children (predominantly allergic asthma and non-allergic asthma) using a minimum number of features.

METHODS

After pre-processing, 127 patients (70 with non-allergic asthma and 57 with predominantly allergic asthma) were chosen for final analysis from the Frankfurt dataset, which had asthma-related information on 205 patients. The Random Forest algorithm and Chi-square were used to select the key features from a total of 63 features. Six machine learning models: random forest, extreme gradient boosting, support vector machines, adaptive boosting, extra tree classifier, and logistic regression were then trained and tested using 10-fold stratified cross-validation.

RESULTS

Among all features, age, weight, C-reactive protein, eosinophilic granulocytes, oxygen saturation, pre-medication inhaled corticosteroid + long-acting beta2-agonist (PM-ICS + LABA), PM-other (other pre-medication), H-Pulmicort/celestamine (Pulmicort/celestamine during hospitalization), and H-azithromycin (azithromycin during hospitalization) were found to be highly important. The support vector machine approach with a linear kernel was able to diffrentiate between predominantly allergic asthma and non-allergic asthma with higher accuracy (77.8%), precision (0.81), with a true positive rate of 0.73 and a true negative rate of 0.81, a F1 score of 0.81, and a ROC-AUC score of 0.79. Logistic regression was found to be the second-best classifier with an overall accuracy of 76.2%.

CONCLUSION

Predominantly allergic and non-allergic asthma can be classified using machine learning approaches based on nine features.

Supplemental data for this article is available online at at www.tandfonline.com/ijas .

EoE behaves as a unique Th2 disease: a narrative review

Background and Objective

To highlight and interpret two significant differences between eosinophilic esophagitis (EoE), a type 2 helper cell (Th2) disease, and three other representative Th2 diseases. EoE, asthma, atopic dermatitis (AD), chronic rhinosinusitis (CRS) and other Th2 diseases employ epithelial alarmins to recognize triggers, share a prototypical inflammatory cascade, and respond to glucocorticoids. However, EoE also has several distinguishing characteristics which may be explained by a distinct pathophysiologic mechanism.

Methods

The following report consist of four related narrative reviews which combine comprehensive PubMed and Google searches. Two reviews were performed to identify and contrast all eligible studies describing serologic markers in EoE compared to asthma, AD, and CRS. Two additional reviews then compare the responses to parenteral biological therapies in EoE and in the same representative Th2 diseases.

Key Content and Findings

Comprehensive literature searches definitively differentiate the absence of serologic markers in EoE compared to their identification in the other representative Th2 diseases. Similarly, a summary of therapeutic trials demonstrates that while EoE is unable to clinically respond to a variety of parenteral biological therapies, asthma, AD and CRS are very effectively treated with this same approach. A novel pathophysiology for EoE is proposed, and the emerging literature that support its existence is summarized.

Conclusions

The fundamental properties described in this narrative regarding serologic signaling and response to parenteral therapy in EoE could be explained if EoE employs a unique application of the Th2 pathway. One potential mechanism consistent with these observations is that EoE employs exclusively esophageal mucosal constituents to initiate and generate the prototypical Th2 cascade and the fibrostenotic changes that follow.

Asthma with recurrent middle lobe syndrome in children: Clinical features and lung function patterns

BACKGROUND

Middle lobe syndrome (MLS) is a complication of childhood asthma. This study aimed to compare the clinical features and lung function between asthmatic children with recurrent MLS and transient right middle lobe (RML) and/or lingula atelectasis.

METHODS

This study retrospectively analyzed asthmatic children with RML and/or lingula atelectasis between 2010 and 2020 using data from the pediatric pulmonary department. According to the episodes of atelectasis, children were divided into recurrent (≥2 episodes) and non-recurrent (only 1 episode) MLS groups, to compare clinical features and lung function. Spirometry during acute asthma exacerbation and stable stages were recorded, and variations were calculated.

RESULTS

A total of 35 children with asthma and RML and/or lingula atelectasis were included, 15 of whom had recurrent MLS. The recurrent MLS group had a higher proportion of girls, infections, family allergy history, severe asthma, severe exacerbation, and higher levels of total IgE than the non-recurrent MLS group (P < 0.05). The recurrent MLS group had a significantly higher % predicted and z-scores for forced expiratory volume in 1 s (FEV₁) and forced vital capacity (FVC), a greater proportion of high FEV₁ and higher variations in FEV₁ and FVC than that in the non-recurrent group (P < 0.05). After excluding children with mild to moderate asthma in the recurrent MLS group, the differences in clinical features disappeared, but the results regarding lung function remained similar, when compared to severe asthma patients without RML and/or lingula atelectasis.

CONCLUSIONS

Childhood asthma with recurrent MLS has more frequent severe asthma and exacerbation but high lung function and variations.

A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach

BACKGROUND

A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes with the aim of designing targeted interventions. Although several studies have identified patient subgroups, there is a considerable gap between the identification of patient subgroups and their modeling and interpretation for clinical applications.

OBJECTIVE

This study aimed to develop and evaluate a novel analytical framework for modeling and interpreting patient subgroups (MIPS) using a 3-step modeling approach: visual analytical modeling to automatically identify patient subgroups and their co-occurring comorbidities and determine their statistical significance and clinical interpretability; classification modeling to classify patients into subgroups and measure its accuracy; and prediction modeling to predict a patient's risk of an adverse outcome and compare its accuracy with and without patient subgroup information.

METHODS

The MIPS framework was developed using bipartite networks to identify patient subgroups based on frequently co-occurring high-risk comorbidities, multinomial logistic regression to classify patients into subgroups, and hierarchical logistic regression to predict the risk of an adverse outcome using subgroup membership compared with standard logistic regression without subgroup membership. The MIPS framework was evaluated for 3 hospital readmission conditions: chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), and total hip arthroplasty/total knee arthroplasty (THA/TKA) (COPD: n=29,016; CHF: n=51,550; THA/TKA: n=16,498). For each condition, we extracted cases defined as patients readmitted within 30 days of hospital discharge. Controls were defined as patients not readmitted within 90 days of discharge, matched by age, sex, race, and Medicaid eligibility.

RESULTS

In each condition, the visual analytical model identified patient subgroups that were statistically significant (Q=0.17, 0.17, 0.31; P<.001, <.001, <.05), significantly replicated (Rand Index=0.92, 0.94, 0.89; P<.001, <.001, <.01), and clinically meaningful to clinicians. In each condition, the classification model had high accuracy in classifying patients into subgroups (mean accuracy=99.6%, 99.34%, 99.86%). In 2 conditions (COPD and THA/TKA), the hierarchical prediction model had a small but statistically significant improvement in discriminating between readmitted and not readmitted patients as measured by net reclassification improvement (0.059, 0.11) but not as measured by the C-statistic or integrated discrimination improvement.

CONCLUSIONS

Although the visual analytical models identified statistically and clinically significant patient subgroups, the results pinpoint the need to analyze subgroups at different levels of granularity for improving the interpretability of intra- and intercluster associations. The high accuracy of the classification models reflects the strong separation of patient subgroups, despite the size and density of the data sets. Finally, the small improvement in predictive accuracy suggests that comorbidities alone were not strong predictors of hospital readmission, and the need for more sophisticated subgroup modeling methods. Such advances could improve the interpretability and predictive accuracy of patient subgroup models for reducing the risk of hospital readmission, and beyond.

Asthma and Wheeze Severity and the Oropharyngeal Microbiota in Children and Adolescents

Rationale: There is a major unmet need for improving the care of children and adolescents with severe asthma and wheeze. Identifying factors contributing to disease severity may lead to improved diagnostics, biomarkers, or therapies. The airway microbiota may be such a key factor. Objectives: To compare the oropharyngeal airway microbiota of children and adolescents with severe and mild/moderate asthma/wheeze. Methods: Oropharyngeal swab samples from school-age and preschool children in the European U-BIOPRED (Unbiased BIOmarkers in the PREDiction of respiratory disease outcomes) multicenter study of severe asthma, all receiving severity-appropriate treatment, were examined using 16S ribosomal RNA gene sequencing. Bacterial taxa were defined as amplicon sequence variants. Results: We analyzed 241 samples from four cohorts: A) 86 school-age children with severe asthma; B) 39 school-age children with mild/moderate asthma; C) 65 preschool children with severe wheeze; and D) 51 preschool children with mild/moderate wheeze. The most common bacteria were Streptococcus (mean relative abundance, 33.5%), Veillonella (10.3%), Haemophilus (7.0%), Prevotella (5.9%), and Rothia (5.5%). Age group (school-age vs. preschool) was associated with the microbiota in β-diversity analysis (F = 3.32, P = 0.011) and in a differential abundance analysis (28 significant amplicon sequence variants). Among all children, we found no significant difference in the microbiota between children with severe and mild/moderate asthma/wheeze in univariable β-diversity analysis (F = 1.99, P = 0.08, N = 241), but a significant difference in a multivariable model (F = 2.66, P = 0.035), including the number of exacerbations in the previous year. Age was also significant when expressed as a microbial maturity score (Spearman Rho, 0.39; P = 4.6 × 10^-10); however, this score was not associated with asthma/wheeze severity. Conclusions: There was a modest difference in the oropharyngeal airway microbiota between children with severe and mild/moderate asthma/wheeze across all children but not in individual age groups, and a strong association between the microbiota and age. This suggests the oropharyngeal airway microbiota as an interesting entity in studying asthma severity, but probably without the strength to serve as a biomarker for targeted intervention.

Functional immunophenotyping of children with critical status asthmaticus identifies differential gene expression responses in neutrophils exposed to a poly(I:C) stimulus

The host immune response to a viral immune stimulus has not been examined in children during a life-threatening asthma attack. We determined whether we could identify clusters of children with critical asthma by functional immunophenotyping using an intracellular viral analog stimulus. We performed a single-center, prospective, observational cohort study of 43 children ages 6-17 years admitted to a pediatric intensive care unit for an asthma attack between July 2019 to February 2021. Neutrophils were isolated from children, stimulated overnight with LyoVec poly(I:C), and mRNA was analyzed using a targeted Nanostring immunology array. Network analysis of the differentially expressed transcripts for the paired LyoVec poly(I:C) samples was performed. We identified two clusters by functional immunophenotyping that differed by the Asthma Control Test score. Cluster 1 (n = 23) had a higher proportion of children with uncontrolled asthma in the four weeks prior to PICU admission compared with cluster 2 (n = 20). Pathways up-regulated in cluster 1 versus cluster 2 included chemokine receptor/chemokines, interleukin-10 (IL-10), IL-4, and IL-13 signaling. Larger validation studies and clinical phenotyping of children with critical asthma are needed to determine the predictive utility of these clusters in a larger clinical setting.

Discerning asthma endotypes through comorbidity mapping

Asthma is a heterogeneous, complex syndrome, and identifying asthma endotypes has been challenging. We hypothesize that distinct endotypes of asthma arise in disparate genetic variation and life-time environmental exposure backgrounds, and that disease comorbidity patterns serve as a surrogate for such genetic and exposure variations. Here, we computationally discover 22 distinct comorbid disease patterns among individuals with asthma (asthma comorbidity subgroups) using diagnosis records for >151 M US residents, and re-identify 11 of the 22 subgroups in the much smaller UK Biobank. GWASs to discern asthma risk loci for individuals within each subgroup and in all subgroups combined reveal 109 independent risk loci, of which 52 are replicated in multi-ancestry meta-analysis across different ethnicity subsamples in UK Biobank, US BioVU, and BioBank Japan. Fourteen loci confer asthma risk in multiple subgroups and in all subgroups combined. Importantly, another six loci confer asthma risk in only one subgroup. The strength of association between asthma and each of 44 health-related phenotypes also varies dramatically across subgroups. This work reveals subpopulations of asthma patients distinguished by comorbidity patterns, asthma risk loci, gene expression, and health-related phenotypes, and so reveals different asthma endotypes.

Predictive characteristics to discriminate the longitudinal outcomes of childhood asthma: a retrospective program-based study

BACKGROUND

Childhood asthma is an inflammatory disease with heterogeneous outcomes. We sought to determine the impact of total IgE, blood eosinophil, allergen sensitization, and inhaled corticosteroid (ICS) on longitudinal outcomes and to identify characteristics for discriminating different outcomes.

METHODS

We conducted a retrospective study in 383 childhood asthma patients and another 313 patients with blood eosinophil data only receiving regular program-based visits from September 1, 2004, to December 31, 2018. Peak expiratory flow (PEF) variability, PEF predicted %, asthma severity, and asthma control at each visit were assessed as clinical outcomes.

RESULTS

Our data show that the percentage of blood eosinophils was significantly associated with increased asthma severity (OR: 1.043, 95% CI: 1.002-1.086, P = 0.0392). Mold sensitization was significantly associated with asthma severity (OR: 2.2485, 95% CI: 1.3253-3.8150, P = 0.0027). Characteristics including sensitization status plus ICS dosage had the best area under the receiver operating characteristic curve (AUC) value for predicting longitudinal PEF predicted % (0.6609), PEF variability (0.6885), asthma severity (0.5918), and asthma control (0.6441), respectively.

CONCLUSIONS

We showed that the risk for adverse clinical outcomes at follow-up differed between serum IgE, blood eosinophil, and allergen sensitization identified at baseline. Sensitization and ICS dosage were predictive characteristics of long-term clinical outcomes.

IMPACT

The unique aspects of the study are its longitudinal assessment of patients receiving guideline-based asthma management program to help characterize the stability of the clinical outcomes over time. Characteristics including allergen sensitization and ICS dosage demonstrated an improved capability for distinguishing between better and worse clinical outcomes. Through longitudinal serial assessment, this study indicates the risk for adverse clinical outcomes differed between children with serum IgE/blood eosinophil/allergen sensitization characterized at baseline.

The Impact of Asthma on COVID-19 Disease Severity in Children and Adolescents

Background: Atopy and allergic asthma have been found to be protective against coronavirus disease (COVID-19) in adults but have not been studied in children.Objective: To identify whether children and adolescents with asthma had less severe disease and lower morbidity from COVID-19 than their counterparts without asthma.Methods: This was a retrospective chart review from March 1, 2020, through January 31, 2021. Charts were eligible for inclusion if patients were over 6 years of age and below 20 years of age and tested positive for COVID-19 by PCR or antigen testing or were COVID-19 antibody positive when they presented to the emergency department (ED). Patients were grouped according to disease severity and divided into two groups, those with asthma and those without. A total of 1,585 patients were included-1,492 without asthma and 93 with asthma.Results: Children and adolescents with asthma are less likely to be seen in the ED for COVID-19-related disease (p value< 0.0001, but if they presented to the ED, they were significantly more likely to be hospitalized, require oxygen, and have more severe forms of COVID-19 than children and adolescents without asthma (p value< 0.0001).Conclusions: Children and adolescents with asthma, though less likely to be seen in ED with COVID-19, were more likely to have severe disease than patients without asthma, once they presented to the ED.

Obesity-related asthma in children and adolescents

There is substantial epidemiological and experimental evidence of an obesity-related asthma phenotype. Compared to children of healthy weight, children with obesity are at higher risk of asthma. Children with obesity who have asthma have greater severity and poorer control of their asthma symptoms, more frequent asthma exacerbations, and overall lower asthma-related quality of life than children with asthma who have a healthy weight. In this Review, we examine some of the latest evidence on the characteristics of this phenotype and its main underlying mechanisms, including genetics and genomics, changes in airway mechanics and lung function, sex hormone differences, alterations in immune responses, systemic and airway inflammation, metabolic dysregulation, and modifications in the microbiome. We also review current recommendations for the treatment of these children, including in the management of their asthma, and current evidence for weight loss interventions. We then discuss initial evidence for potential novel therapeutic approaches, such as dietary modifications and supplements, antidiabetic medications, and statins. Finally, we identify knowledge gaps and future directions to improve our understanding of asthma in children with obesity, and to improve outcomes in these susceptible children. We highlight important needs, such as designing paediatric-specific studies, implementing large multicentric trials with standardised interventions and outcomes, and including racial and ethnic groups along with other under-represented populations that are particularly affected by obesity and asthma.

A retrospective observational study on pheno-endotypes of severe asthma among adults attending asthma clinic in a tertiary care centre in India

Background and Objective

Severe asthma phenotyping based on invasive and non-invasive bio-markers assists in a better understanding of heterogeneity of clinical presentations and thereby using targeted therapies. Therefore, the current study was conducted to evaluate phenotypes based on non-invasive bio-markers of severe asthma patients attending a tertiary care hospital in North India.

Methods

This was a retrospective, observational study conducted on the patients who visited the respiratory department of a tertiary care hospital in North India. Patients aged 18 years and above diagnosed with severe asthma were classified into distinct phenotypes, namely, atopic asthma, eosinophilic asthma, and Type 2 low asthma. Patients with their clinical and functional parameters were classified based on the levels of bio-chemical and hematological results [such as total/specific IgE, blood absolute eosinophil count (AEC)], skin prick tests, history of allergy, and the presence of allergic symptoms.

Results

Out of total 100 severe asthmatics, the majority of the patients had an eosinophilic asthma (49%) phenotype, followed by atopic (allergic) asthma (36%) and Type 2 low asthma (15%) phenotypes. However, it was found that 29% of these patients had overlap of both atopy and eosinophilia. The atopic phenotype showed allergic symptoms, positive skin prick tests, and elevated IgE levels. The eosinophilic phenotype had high AEC (≥300 cells/uL) and low IgE (< 30 IU/ml) levels. The Type 2 low phenotype showed low AEC and IgE levels along with the absence of allergic symptoms. However, among these 100 patients, overlapping traits of both atopy and eosinophilia were labelled as overlap phenotypes. 50% of type 2 low severe asthma cases had eosinophils >150 cells/cmm and were eligible for mepolizumab.

Conclusions

Identification of severe asthma pheno-endotypes based on simple non-invasive bio-markers is feasible in Indian settings, and it is of utmost importance for future treatment planning in these patients with available biologicals. Overlap of eosinophilic and atopic endotypes in one-third cases would challenge physicians to choose upfront appropriate biologicals in our country. Type 2 low asthma was least common with only <10% cases of severe asthma being ineligible for any biological.

In-home environmental exposures predicted from geospatial characteristics of the built environment and electronic health records of children with asthma

PURPOSE

Children may be exposed to numerous in-home environmental exposures (IHEE) that trigger asthma exacerbations. Spatially linking social and environmental exposures to electronic health records (EHR) can aid exposure assessment, epidemiology, and clinical treatment, but EHR data on exposures are missing for many children with asthma. To address the issue, we predicted presence of indoor asthma trigger allergens, and estimated effects of their key geospatial predictors.

METHODS

Our study samples were comprised of children with asthma who provided self-reported IHEE data in EHR at a safety-net hospital in New England during 2004-2015. We used an ensemble machine learning algorithm and 86 multilevel features (e.g., individual, housing, neighborhood) to predict presence of cockroaches, rodents (mice or rats), mold, and bedroom carpeting/rugs in homes. We reduced dimensionality via elastic net regression and estimated effects by the G-computation causal inference method.

RESULTS

Our models reasonably predicted presence of cockroaches (area under receiver operating curves [AUC] = 0.65), rodents (AUC = 0.64), and bedroom carpeting/rugs (AUC = 0.64), but not mold (AUC = 0.54). In models adjusted for confounders, higher average household sizes in census tracts were associated with more reports of pests (cockroaches and rodents). Tax-exempt parcels were associated with more reports of cockroaches in homes. Living in a White-segregated neighborhood was linked with lower reported rodent presence, and mixed residential/commercial housing and newer buildings were associated with more reports of bedroom carpeting/rugs in bedrooms.

CONCLUSIONS

We innovatively applied a machine learning and causal inference mixture methodology to detail IHEE among children with asthma using EHR and geospatial data, which could have wide applicability and utility.

Body Composition-Specific Asthma Phenotypes: Clinical Implications

Background: Previous studies have indicated the limitations of body mass index for defining disease phenotypes. The description of asthma phenotypes based on body composition (BC) has not been largely reported. Objective: To identify and characterize phenotypes based on BC parameters in patients with asthma. Methods: A study with two prospective observational cohorts analyzing adult patients with stable asthma (n = 541 for training and n = 179 for validation) was conducted. A body composition analysis was performed for the included patients. A cluster analysis was conducted by applying a 2-step process with stepwise discriminant analysis. Logistic regression models were used to evaluate the association between identified phenotypes and asthma exacerbations (AEs). The same algorithm for cluster analysis in the independent validation set was used to perform an external validation. Results: Three clusters had significantly different characteristics associated with asthma outcomes. An external validation identified the similarity of the participants in training and the validation set. In the training set, cluster Training (T) 1 (29.4%) was “patients with undernutrition”, cluster T2 (18.9%) was “intermediate level of nutrition with psychological dysfunction”, and cluster T3 (51.8%) was “patients with good nutrition”. Cluster T3 had a decreased risk of moderate-to-severe and severe AEs in the following year compared with the other two clusters. The most important BC-specific factors contributing to being accurately assigned to one of these three clusters were skeletal muscle mass and visceral fat area. Conclusion: We defined three distinct clusters of asthma patients, which had distinct clinical features and asthma outcomes. Our data reinforced the importance of evaluating BC to determining nutritional status in clinical practice.

Severe asthma in children: Description of a large multidisciplinary clinical cohort

BACKGROUND

Children with severe asthma have substantial morbidity and healthcare utilization. Pediatric severe asthma is a heterogeneous disease, and a multidisciplinary approach can improve the diagnosis and management of these children.

METHODS

We reviewed the electronic health records for patients seen in the Severe Asthma Clinic (SAC) at UPMC Children's Hospital of Pittsburgh between August 2012 and October 2019.

RESULTS

Of the 110 patients in whom we extracted data, 46% were female, 48% were Black/African American, and 41% had ≥1 admission to the pediatric intensive care unit (PICU) for asthma. Compared to patients without a PICU admission, those with ≥1 PICU admission were more likely to be non-White (64.4% vs. 41.5%, p = 0.031) and more atopic (eosinophil count geometric mean = 673 vs. 319 cells/mm3 , p = 0.002; total IgE geometric mean = 754 vs. 303 KU/L, p = 0.003), and to have lower pre-bronchodilator FEV1 (58.6% [±18.1%] vs. 69.9% [±18.7%], p = 0.002) and elevated FeNO (60% vs. 22%, p = 0.02). In this cohort, 84% of patients were prescribed high-dose ICS/LABA and 36% were on biologics. Following enrollment in the SAC, severe exacerbations decreased from 3.2/year to 2.2/year (p < 0.0001); compared to the year before joining the SAC, in the following year the group had 106 fewer severe exacerbations.

CONCLUSIONS

This large cohort of children with severe asthma had a high level of morbidity and healthcare utilization. Patients with a history of PICU admissions for asthma were more likely to be nonwhite and highly atopic, and to have lower lung function. Our data support a positive impact of a multidisciplinary clinic on patients with severe childhood asthma.

Characteristics, phenotypes, mechanisms and management of severe asthma

ABSTRACT

Severe asthma is "asthma which requires treatment with high dose inhaled corticosteroids (ICS) plus a second controller (and/or systemic corticosteroids) to prevent it from becoming 'uncontrolled' or which remains 'uncontrolled' despite this therapy." The state of control was defined by symptoms, exacerbations and the degree of airflow obstruction. Therefore, for the diagnosis of severe asthma, it is important to have evidence for a diagnosis of asthma with an assessment of its severity, followed by a review of comorbidities, risk factors, triggers and an assessment of whether treatment is commensurate with severity, whether the prescribed treatments have been adhered to and whether inhaled therapy has been properly administered. Phenotyping of severe asthma has been introduced with the definition of a severe eosinophilic asthma phenotype characterized by recurrent exacerbations despite being on high dose ICS and sometimes oral corticosteroids, with a high blood eosinophil count and a raised level of nitric oxide in exhaled breath. This phenotype has been associated with a Type-2 (T2) inflammatory profile with expression of interleukin (IL)-4, IL-5, and IL-13. Molecular phenotyping has also revealed non-T2 inflammatory phenotypes such as Type-1 or Type-17 driven phenotypes. Antibody treatments targeted at the T2 targets such as anti-IL5, anti-IL5Rα, and anti-IL4Rα antibodies are now available for treating severe eosinophilic asthma, in addition to anti-immunoglobulin E antibody for severe allergic asthma. No targeted treatments are currently available for non-T2 inflammatory phenotypes. Long-term azithromycin and bronchial thermoplasty may be considered. The future lies with molecular phenotyping of the airway inflammatory process to refine asthma endotypes for precision medicine.

Metabo-Endotypes of Asthma Reveal Differences in Lung Function: Discovery and Validation in Two TOPMed Cohorts

Rationale: Current guidelines do not sufficiently capture the heterogeneous nature of asthma; a more detailed molecular classification is needed. Metabolomics represents a novel and compelling approach to derive asthma endotypes (i.e., subtypes defined by functional and/or pathobiological mechanisms). Objectives: To validate metabolomic-driven endotypes of asthma and explore their underlying biology. Methods: In the Genetics of Asthma in Costa Rica Study (GACRS), untargeted metabolomic profiling, similarity network fusion, and spectral clustering was used to identify metabo-endotypes of asthma, and differences in asthma-relevant phenotypes across these metabo-endotypes were explored. The metabo-endotypes were recapitulated in the Childhood Asthma Management Program (CAMP), and clinical differences were determined. Metabolomic drivers of metabo-endotype membership were investigated by meta-analyzing findings from GACRS and CAMP. Measurements and Main Results: Five metabo-endotypes were identified in GACRS with significant differences in asthma-relevant phenotypes, including prebronchodilator (p-ANOVA = 8.3 × 10^-5) and postbronchodilator (p-ANOVA = 1.8 × 10^-5) FEV₁/FVC. These differences were validated in the recapitulated metabo-endotypes in CAMP. Cholesterol esters, trigylcerides, and fatty acids were among the most important drivers of metabo-endotype membership. The findings suggest dysregulation of pulmonary surfactant homeostasis may play a role in asthma severity. Conclusions: Clinically meaningful endotypes may be derived and validated using metabolomic data. Interrogating the drivers of these metabo-endotypes has the potential to help understand their pathophysiology.

Bilirubin represents a negative regulator of ILC2 in allergic airway inflammation

Group 2 innate lymphoid cells (ILC2s) play an important role in allergic airway inflammation. Despite recent advances in defining molecular mechanisms that control ILC2 development and function, the role of endogenous metabolites in the regulation of ILC2s remains poorly understood. Herein, we demonstrated that bilirubin, an end product of heme catabolism, was a potent negative regulator of ILC2s. Bilirubin metabolism was found to be significantly induced during airway inflammation in mouse models. The administration of unconjugated bilirubin (UCB) dramatically suppressed ILC2 responses to interleukin (IL)-33 in mice, including cell proliferation and the production of effector cytokines. Furthermore, UCB significantly alleviated ILC2-driven airway inflammation, which was aggravated upon clearance of endogenous UCB. Mechanistic studies showed that the effects of bilirubin on ILC2s were associated with downregulation of ERK phosphorylation and GATA3 expression. Clinically, newborns with hyperbilirubinemia displayed significantly lower levels of ILC2 with impaired function and suppressed ERK signaling. Together, these findings indicate that bilirubin serves as an endogenous suppressor of ILC2s and might have potential therapeutic value in the treatment of allergic airway inflammation.

Machine learning: A modern approach to pediatric asthma

Among modern methods of statistical and computational analysis, the application of machine learning (ML) to healthcare data has been gaining recognition in helping us understand the heterogeneity of asthma and predicting its progression. In pediatric research, ML approaches may provide rapid advances in uncovering asthma phenotypes with potential translational impact in clinical practice. Also, several accurate models to predict asthma and its progression have been developed using ML. Here, we provide a brief overview of ML approaches recently proposed to characterize pediatric asthma.

Visualizing the knowledge domains and research trends of childhood asthma: A scientometric analysis with CiteSpace

BACKGROUND

Asthma is one of the most common chronic diseases in children globally. In recent decades, advances have been made in understanding the mechanism, diagnosis, treatment and management for childhood asthma, but few studies have explored its knowledge structure and future interests comprehensively.

OBJECTIVE

This scientometric study aims to understand the research status and emerging trends of childhood asthma.

METHODS

CiteSpace (version 5.8.R3) was used to demonstrate national and institutional collaborations in childhood asthma, analyze research subjects and journal distribution, review research keywords and their clusters, as well as detect research bursts.

RESULTS

A total of 14,340 publications related to childhood asthma were extracted from Web of Science (core database) during January 2011 to December 2021. The results showed that academic activities of childhood asthma had increased steadily in the last decade. Most of the research was conducted by developed countries while China, as a developing country, was also actively engaged in this field. In addition to subjects of allergy and immunology, both public health aspects and ecological environmental impacts on the disease were emphasized recently in this research field. Keywords clustering analysis indicated that research on asthma management and atopy was constantly updated and became the two major research focuses recently, as a significant shift in research hotspots from etiology and diagnosis to atopic march and asthma management was identified. Subgroup analysis for childhood asthma management and atopy suggested that caregiver- or physician-based education and interventions were emerging directions for asthma management, and that asthma should be carefully studied in the context of atopy, together with other allergic diseases.

CONCLUSIONS

This study presented a comprehensive and systematic overview of the research status of childhood asthma, provided clues to future research directions, and highlighted two significant research trends of asthma management and atopy in this field.

Advances and Challenges of Antibody Therapeutics for Severe Bronchial Asthma

Asthma is a disease that consists of three main components: airway inflammation, airway hyperresponsiveness, and airway remodeling. Persistent airway inflammation leads to the destruction and degeneration of normal airway tissues, resulting in thickening of the airway wall, decreased reversibility, and increased airway hyperresponsiveness. The progression of irreversible airway narrowing and the associated increase in airway hyperresponsiveness are major factors in severe asthma. This has led to the identification of effective pharmacological targets and the recognition of several biomarkers that enable a more personalized approach to asthma. However, the efficacies of current antibody therapeutics and biomarkers are still unsatisfactory in clinical practice. The establishment of an ideal phenotype classification that will predict the response of antibody treatment is urgently needed. Here, we review recent advancements in antibody therapeutics and novel findings related to the disease process for severe asthma.

Considering biomarkers in asthma disease severity

Amongst patients with asthma, reliance on the type/dose of prescribed medication and symptom control does not adequately capture those at risk of adverse outcomes, and we need biomarkers for risk and treatment stratification which are consistently accurate, readily quantifiable and reproducible. The majority of patients with severe asthma, regardless of age, have predominant type-2 (T2) inflammation mediated disease, making airway/blood eosinophils, FeNO, periostin and/or allergic sensitization potentially important biomarkers for severe disease. In both adult and pediatric asthma, there is scope to improve prediction of severe attacks by using a composite T2 biomarkers of blood eosinophils and FeNO. Technological advances in component-resolved diagnostics (CRD) microarray technologies coupled with the development of interpretation software offer a possibility to use CRD as biomarkers of asthma severity amongst sensitized asthmatics. Genetic predisposition and polygenic risk scores of relevant traits (e.g., lung function, host immune responses, biomarkers of exposure from the indoor and outdoor environment, infection and microbial dysbiosis) may also contribute to prediction algorithms. We challenge the idea that asthma can be accurately defined in an individual patient by a discrete and static "endotype" (e.g., T2-high asthma). As we traverse the new era of molecular endotyping in asthma, we need to understand how relevant mechanisms impact patient outcomes, and in parallel develop new tools and approaches to stratify therapies and define individual patient trajectories.

Childhood asthma- pathogenesis and phenotypes

In the pathogenesis of asthma in children there is a pivotal role for a type 2 inflammatory response to early life exposures or events. Interactions between infections, atopy, genetic susceptibility, and environmental exposures (such as farmyard environment, air pollution, tobacco smoke exposure) influence the development of wheezing illness and the risk for progression to asthma. The immune system, lung function and the microbiome in gut and airways develop in parallel and dysbiosis of the microbiome may be a critical factor in asthma development. Increased infant weight gain and preterm birth are other risk factors for development of asthma and reduced lung function. The complex interplay between these factors explains the heterogeneity of asthma in children. Subgroups of patients can be identified as phenotypes based on clinical parameters, or endotypes, based on a specific pathophysiological mechanism. Paediatric asthma phenotypes and endotypes may ultimately help to improve diagnosis of asthma, prediction of asthma development and treatment of individual children, based on clinical, temporal, developmental or inflammatory characteristics. Unbiased, data-driven clustering, using a multidimensional or systems biology approach may be needed to better define phenotypes. The present knowledge on inflammatory phenotypes of childhood asthma has now been successfully applied in the treatment with biologicals of children with severe therapy resistant asthma, and it is to be expected that more personalized treatment options may become available.

Recent Insights into the Management of Inflammation in Asthma

The present prevailing inflammatory paradigm in asthma is of T2-high inflammation orchestrated by key inflammatory cells like Type 2 helper lymphocytes, innate lymphoid cells group 2 and associated cytokines. Eosinophils are key components of this T2 inflammatory pathway and have become key therapeutic targets. Real-world evidence on the predominant T2-high nature of severe asthma is emerging. Various inflammatory biomarkers have been adopted in clinical practice to aid asthma characterization including airway measures such as bronchoscopic biopsy and lavage, induced sputum analysis, and fractional exhaled nitric oxide. Blood measures like eosinophil counts have also gained widespread usage and multicomponent algorithms combining different parameters are now appearing. There is also growing interest in potential future biomarkers including exhaled volatile organic compounds, micro RNAs and urinary biomarkers. Additionally, there is a growing realisation that asthma is a heterogeneous state with numerous phenotypes and associated treatable traits. These may show particular inflammatory patterns and merit-specific management approaches that could improve asthma patient outcomes. Inhaled corticosteroids (ICS) remain the mainstay of asthma management but their use earlier in the course of disease is being advocated. Recent evidence suggests potential roles for ICS in combination with long-acting beta-agonists (LABA) for as needed use in mild asthma whilst maintenance and reliever therapy regimes have gained widespread acceptance. Other anti-inflammatory strategies including ultra-fine particle ICS, leukotriene receptor antagonists and macrolide antibiotics may show efficacy in particular phenotypes too. Monoclonal antibody biologic therapies have recently entered clinical practice with significant impacts on asthma outcomes. Understanding of the efficacy and use of those agents is becoming clearer with a growing body of real-world evidence as is their potential applicability to other treatable comorbid traits. In conclusion, the evolving understanding of T2 driven inflammation alongside a treatable traits disease model is enhancing therapeutic approaches to address inflammation in asthma.

Risk, Mechanisms and Implications of Asthma-Associated Infectious and Inflammatory Multimorbidities (AIMs) among Individuals With Asthma: a Systematic Review and a Case Study

Our prior work and the work of others have demonstrated that asthma increases the risk of a broad range of both respiratory (e.g., pneumonia and pertussis) and non-respiratory (e.g., zoster and appendicitis) infectious diseases as well as inflammatory diseases (e.g., celiac disease and myocardial infarction [MI]), suggesting the systemic disease nature of asthma and its impact beyond the airways. We call these conditions asthma-associated infectious and inflammatory multimorbidities (AIMs). At present, little is known about why some people with asthma are at high-risk of AIMs, and others are not, to the extent to which controlling asthma reduces the risk of AIMs and which specific therapies mitigate the risk of AIMs. These questions represent a significant knowledge gap in asthma research and unmet needs in asthma care, because there are no guidelines addressing the identification and management of AIMs. This is a systematic review on the association of asthma with the risk of AIMs and a case study to highlight that 1) AIMs are relatively under-recognized conditions, but pose major health threats to people with asthma; 2) AIMs provide insights into immunological and clinical features of asthma as a systemic inflammatory disease beyond a solely chronic airway disease; and 3) it is time to recognize AIMs as a distinctive asthma phenotype in order to advance asthma research and improve asthma care. An improved understanding of AIMs and their underlying mechanisms will bring valuable and new perspectives improving the practice, research, and public health related to asthma.

Identification of ROBO2 as a Potential Locus Associated with Inhaled Corticosteroid Response in Childhood Asthma

Inhaled corticosteroids (ICS) are the most common asthma controller medication. An important contribution of genetic factors in ICS response has been evidenced. Here, we aimed to identify novel genetic markers involved in ICS response in asthma. A genome-wide association study (GWAS) of the change in lung function after 6 weeks of ICS treatment was performed in 166 asthma patients from the SLOVENIA study. Patients with an improvement in lung function ≥8% were considered as ICS responders. Suggestively associated variants (p-value ≤ 5 × 10⁻⁶) were evaluated in an independent study (n = 175). Validation of the association with asthma exacerbations despite ICS use was attempted in European (n = 2681) and admixed (n = 1347) populations. Variants previously associated with ICS response were also assessed for replication. As a result, the SNP rs1166980 from the ROBO2 gene was suggestively associated with the change in lung function (OR for G allele: 7.01, 95% CI: 3.29–14.93, p = 4.61 × 10⁻⁷), although this was not validated in CAMP. ROBO2 showed gene-level evidence of replication with asthma exacerbations despite ICS use in Europeans (minimum p-value = 1.44 × 10⁻⁵), but not in admixed individuals. The association of PDE10A-T with ICS response described by a previous study was validated. This study suggests that ROBO2 could be a potential novel locus for ICS response in Europeans.

Defining pediatric asthma: phenotypes to endotypes and beyond

Asthma is the most common chronic pediatric lung disease that has traditionally been defined as a syndrome of airway inflammation characterized by clinical symptoms of cough and wheeze. Highlighting the complex and heterogeneous nature of asthma, this review summarizes recent advances in asthma classification that are based on pathobiology, and thereby directly addresses limitations of existent definitions of asthma. By reviewing and contrasting clinical and mechanistic features of adult and childhood asthma, the review summarizes key biomarkers that distinguish childhood asthma subtypes. While atopy and its severity are important features of childhood asthma, there is evidence to support the existence of a childhood asthma endotype distinct from the atopic endotype. Although biomarkers of non-atopic asthma are an area of future research, we summarize a clinical approach that includes existing measures of airway-specific and systemic measures of atopy, co-existing morbidities, and disease severity and control, in the definition of childhood asthma, to empower health care providers to better characterize asthma disease burden in children. Identification of biomarkers of non-atopic asthma and the contribution of genetics and epigenetics to pediatric asthma burden remains a research need, which can potentially allow delivery of precision medicine to pediatric asthma. IMPACT: This review highlights asthma as a complex and heterogeneous disease and discusses recent advances in the understanding of the pathobiology of asthma to demonstrate the need for a more nuanced definitions of asthma. We review current knowledge of asthma phenotypes and endotypes and put forth an approach to endotyping asthma that may be useful for defining asthma for clinical care as well as for future research studies in the realm of personalized medicine for asthma.

Overview of severe asthma, with emphasis on pediatric patients: a review for practitioners

Asthma is the most common life-threatening chronic disease in children. Although guidelines exist for the diagnosis and treatment of asthma, treatment of severe, pediatric asthma remains difficult. Limited studies in the pediatric population on new asthma therapies, complex issues with adolescence and adherence, health disparities, and unequal access to guideline-based care complicate the care of children with severe, persistent asthma. The purpose of this review is to provide an overview of asthma, including asthma subtypes, comorbidities, and risk factors, to discuss diagnostic considerations and pitfalls and existing treatments, and then present existing and emerging therapeutic approaches to asthma management. An improved understanding of asthma heterogeneity, clinical characteristics, inflammatory patterns, and pathobiology can help further guide the management of severe asthma in children. More studies are needed in the pediatric population to understand emerging therapeutics application in children. Effective multimodal strategies tailored to individual characteristics and a commitment to address risk factors, modifiers, and health disparities may help reduce the burden of asthma in the USA.

Novel therapeutic approaches targeting endotypes of severe airway disease

Introduction: Severe asthma and chronic rhinosinusitis (CRS), with nasal polyps (CRSwNP) and without nasal polyps (CRSsNP), are heterogeneous diseases characterized by different mechanistic pathways (endotypes) and variable clinical presentations (phenotypes).Areas covered: This review provides the clinician with an overview of the prevalence and clinical impact of severe chronic upper and lower airways disease and suggests a novel therapeutic approach with biological agents with possible biomarkers. To select relevant literature for inclusion in this review, we conducted a literature search using the PubMed database, using terms 'severe airways disease' AND 'endotype' AND 'treatment.' The literature review was performed for publication years 2010-2020, restricting the articles to humans and English language publications.Expert opinion: The coronavirus disease (COVID-19) pandemic has brought forth many challenges for patients with severe airway disease and healthcare practitioners involved in care. These patients could have an increased risk of developing severe SARS-CoV-2 disease, although treatment with biologics is not associated with a worse prognosis. Eosinopenia on hospital admission plays a key role as a diagnostic and prognostic biomarker.

Asthma clustering methods: a literature-informed application to the children's health study data

OBJECTIVE

The heterogeneity of asthma has inspired widespread application of statistical clustering algorithms to a variety of datasets for identification of potentially clinically meaningful phenotypes. There has not been a standardized data analysis approach for asthma clustering, which can affect reproducibility and clinical translation of results. Our objective was to identify common and effective data analysis practices in the asthma clustering literature and apply them to data from a Southern California population-based cohort of schoolchildren with asthma.

METHODS

As of January 1, 2020, we reviewed key statistical elements of 77 asthma clustering studies. Guided by the literature, we used 12 input variables and three clustering methods (hierarchical clustering, k-medoids, and latent class analysis) to identify clusters in 598 schoolchildren with asthma from the Southern California Children's Health Study (CHS).

RESULTS

Clusters of children identified by latent class analysis were characterized by exhaled nitric oxide, FEV₁/FVC, FEV₁ percent predicted, asthma control and allergy score; and were predictive of control at two year follow up. Clusters from the other two methods were less clinically remarkable, primarily differentiated by sex and race/ethnicity and less predictive of asthma control over time.

CONCLUSION

Upon review of the asthma phenotyping literature, common approaches of data clustering emerged. When applying these elements to the Children's Health Study data, latent class analysis clusters-represented by exhaled nitric oxide and spirometry measures-had clinical relevance over time.

T2-"Low" Asthma: Overview and Management Strategies

Although the term "asthma" has been applied to all patients with airway lability and variable chest symptoms for centuries, phenotypes of asthma with distinct clinical and molecular features that may warrant different treatment approaches are well recognized. Patients with type 2 (T2)-"high" asthma are characterized by upregulation of T2 immune pathways (ie, IL-4 and IL-13 gene sets) and eosinophilic airway inflammation, whereas these features are absent in patients with T2-"low" asthma and may contribute to poor responsiveness to corticosteroid treatment. This review details definitions and clinical features of T2-"low" asthma, potential mechanisms and metabolic aspects, pediatric considerations, and potential treatment approaches. Priority research questions for T2-"low" asthma are also discussed.

Diagnosis and Management of T2-High Asthma

Type 2 (T2) inflammation plays a key role in the pathogenesis of asthma. IL-4, IL-5, and IL-13, along with other inflammatory mediators, lead to increased cellular eosinophilic inflammation. It is likely that around half of all patients with asthma have evidence of T2-high inflammation. Sputum and blood eosinophils, exhaled nitric oxide, blood IgE levels, and airway gene expression markers are frequently used biomarkers of T2-high asthma. Individuals with T2-high asthma tend to have several features of increased asthma severity, including reduced lung function and increased rates of asthma exacerbations, and T2-high patients demonstrate distinct pathologic features including increased airway remodeling and alterations in airway mucus production. Several monoclonal antibodies are now available to treat individuals with T2-high asthma and these medications significantly reduce asthma exacerbation rates.

Novel Treatment-Refractory Preschool Wheeze Phenotypes Identified by Cluster Analysis of Lung Lavage Constituents

BACKGROUND

Preschool children with treatment-refractory wheeze often require unscheduled acute care. Current guidelines advise treatment of persistent wheeze with inhaled corticosteroids. Alternative treatments targeting structural abnormalities and specific inflammatory patterns could be more effective.

OBJECTIVE

To apply unsupervised analysis of lung lavage (bronchoalveolar lavage [BAL]) variables to identify clusters of preschool children with treatment-refractory wheeze.

METHODS

A total of 155 children 6 years or younger underwent bronchoscopy with BAL for evaluation of airway structure, inflammatory markers, and pathogens. Variables were screened with factor analysis and sorted into clusters by Ward's method, and membership was confirmed by discriminant analysis.

RESULTS

The model was repeatable in a 48-case validation sample and accurately classified 86% of cases. Cluster 1 (n = 60) had early-onset wheeze, 85% with structural abnormalities, mostly tracheamalacia, with low total IgE and agranulocytic BAL. Cluster 2 (n = 42) had later-onset wheeze, the highest prevalence of gastroesophageal reflux, little atopy, and two-third had increased BAL lipid-laden macrophages. Cluster 3 (n = 46) had mid-onset wheeze, low total IgE, and two-third had BAL viral transcripts, predominately human rhinovirus, with BAL neutrophilia. Cluster 4 (n = 7) was older, with high total IgE, blood eosinophilia, and mixed BAL eosinophils and neutrophils.

CONCLUSIONS

Preschool children with recurrent wheeze refractory to inhaled corticosteroid treatment include 4 clusters: airway malacia, gastroesophageal reflux, indolent human rhinovirus bronchoalveolitis, and type-2^high inflammation. The results support the risk and cost of invasive bronchoscopy to diagnose causes of treatment-refractory wheeze and develop novel therapies targeting airway malacia, human rhinovirus infection, and BAL neutrophilia in preschool children.