Inhaled Corticosteroid Response Research Articles

The effects of inhaled corticosteroids on healthy airways.

The effects of inhaled corticosteroids (ICS) on healthy airways are poorly defined. To delineate the effects of ICS on gene expression in healthy airways, without confounding caused by changes in disease-related genes and disease-related alterations in ICS responsiveness. Randomized open-label bronchoscopy study of high-dose ICS therapy in 30 healthy adult volunteers randomized 2:1 to (i) fluticasone propionate 500 mcg bd daily or (ii) no treatment, for 4 weeks. Laboratory staff were blinded to allocation. Biopsies and brushings were analysed by immunohistochemistry, bulk RNA sequencing, DNA methylation array and metagenomics. ICS induced small between-group differences in blood and lamina propria eosinophil numbers, but not in other immunopathological features, blood neutrophils, FeNO, FEV1, microbiome or DNA methylation. ICS treatment upregulated 72 genes in brushings and 53 genes in biopsies, and downregulated 82 genes in brushings and 416 genes in biopsies. The most downregulated genes in both tissues were canonical markers of type-2 inflammation (FCER1A, CPA3, IL33, CLEC10A, SERPINB10 and CCR5), T cell-mediated adaptive immunity (TARP, TRBC1, TRBC2, PTPN22, TRAC, CD2, CD8A, HLA-DQB2, CD96, PTPN7), B-cell immunity (CD20, immunoglobulin heavy and light chains) and innate immunity, including CD48, Hobit, RANTES, Langerin and GFI1. An IL-17-dependent gene signature was not upregulated by ICS. In healthy airways, 4-week ICS exposure reduces gene expression related to both innate and adaptive immunity, and reduces markers of type-2 inflammation. This implies that homeostasis in health involves tonic type-2 signalling in the airway mucosa, which is exquisitely sensitive to ICS.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

GSDMB/ORMDL3 Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma.

Inhaled corticosteroids (ICS) are efficacious in the treatment of asthma, which affects more than 300 million people in the world. While genome-wide association studies have identified genes involved in differential treatment responses to ICS in asthma, few studies have evaluated the effects of combined rare and common variants on ICS response among children with asthma. Among children with asthma treated with ICS with whole exome sequencing (WES) data in the PrecisionLink Biobank (91 White and 20 Black children), we examined the effect and contribution of rare and common variants with hospitalizations or emergency department visits. For 12 regions previously associated with asthma and ICS response (DPP10, FBXL7, NDFIP1, TBXT, GLCCI1, HDAC9, TBXAS1, STAT6, GSDMB/ORMDL3, CRHR1, GNGT2, FCER2), we used the combined sum test for the sequence kernel association test (SKAT) adjusting for age, sex, and BMI and stratified by race. Validation was conducted in the Biorepository and Integrative Genomics (BIG) Initiative (83 White and 134 Black children). Using a Bonferroni threshold for the 12 regions tested (i.e., 0.05/12 = 0.004), GSDMB/ORMDL3 was significantly associated with ICS response for the combined effect of rare and common variants (p-value = 0.003) among White children in the PrecisionLink Biobank and replicated in the BIG Initiative (p-value = 0.02). Using WES data, the combined effect of rare and common variants for GSDMB/ORMDL3 was associated with ICS response among asthmatic children in the PrecisionLink Biobank and replicated in the BIG Initiative. This proof-of-concept study demonstrates the power of biobanks of pediatric real-life populations in asthma genomic investigations.

Assessing Inhaled Corticosteroid Adherence and Responsiveness in Severe Asthma Using Beclometasone Dipropionate/Formoterol NEXThaler Dose-Counting and Nitric Oxide Monitoring

65% of people with severe asthma and a FeNO ≥45 ppb are non-adherent to inhaled corticosteroids (ICS). Digital devices recording both time-of-use and inhaler technique identify non-adherence and ICS responsiveness but are not widely available. As the NEXThaler™ dose counter only activates at an inspiratory flow of 35 L/min, this may provide an alternative to identifying ICS responsiveness. To assess ICS adherence and responsiveness in severe asthma using beclometasone/formoterol (200/6 mcg) NEXThaler™ (BFN) dose-counting. Severe asthmatics with a FeNO ≥45 ppb were invited to use BFN in place of their usual ICS/long-acting β2-agonist (LABA). FeNO, ACQ6, lung function and blood eosinophil count were monitored for 3 months. A log10ΔFeNO ≥0.24 was used to define FeNO suppression as the primary marker of ICS responsiveness at day 28. 27/48 (56%) patients demonstrated significant FeNO suppression at month 1 (median pre-114, post-48 ppb, p<0.001). A small but significant reduction occurred in FeNO non-suppressors. ACQ6 fell a median 1.2 units in FeNO suppressors (p<0.001) and 0.5 units in non-suppressors (p=0.025). These effects were sustained until month 3 in FeNO suppressors with a significant improvement in FEV1 and blood eosinophils. 67% (18/27) of those with baseline ICS/LABA prescription refills of ≥80% were FeNO suppressors suggesting prior non-adherence despite adequate prescription collection. 79% of FeNO suppressors did not require biologics within mean 11.4 months from initial dose counting. BFN dose counting identifies ICS responsiveness in severe asthma with the implication that these patients may not need to progress to biological therapies.

Machine Learning Prediction of Treatment Response to Inhaled Corticosteroids in Asthma.

Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma. The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest. The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independent test cohort, and the random forest model achieved an AUC of 0.74 (95% CI 0.70-0.78; sensitivity: 0.70; specificity: 0.68). The genes contributing to the prediction of ICS response included those associated with ICS responses in asthma (TPSAB1, FBXL16), asthma symptoms and severity (ABCA7, CNN2, PTRN3, and BSG/CD147), airway remodeling (ELANE, FSTL3), mucin production (GAL3ST), leukotriene synthesis (GPX4), allergic asthma (ZFPM1, SBNO2), and others. An accurate risk prediction of ICS response can be obtained using machine learning methods, with the potential to inform personalized treatment decisions. Further studies are needed to examine if the integration of richer phenotype data could improve risk prediction.

Association of Sputum Eosinophilia With Easily Measured Type-2 Inflammatory Biomarkers in Untreated Mild Persistent Asthma

A multicenter clinical trial in patients with mild persistent asthma indicated that response to inhaled corticosteroids (ICS) is limited to those with sputum eosinophilia. However, testing for sputum eosinophilia is impractical in most clinical settings. We examined associations between sputum eosinophilia and type 2 inflammatory biomarkers in untreated mild persistent asthma. Induced sputum, blood eosinophil count (BEC), fractional exhaled nitric oxide (FeNO), and serum periostin were obtained twice during the 6-week run-in period in a clinical trial that enrolled patients 12 years and older with symptomatic, mild persistent asthma without controller therapy. The optimal threshold for each biomarker was based on achieving 80% or greater sensitivity. Performance of biomarkers (area under the receiver operating characteristics curve [AUC], range 0.0-1.0) in predicting sputum eosinophilia 2% or greater was determined; AUCs of 0.8 to 0.9 and more than 0.9 define excellent and outstanding discrimination, respectively. Of 564 participants, 27% were sputum eosinophilic, 83% were atopic, 70% had BEC of 200/uL or higher or FeNO of 25 ppb or greater; 64% of participants without sputum eosinophilia had elevated BEC or FeNO. The AUCs for BEC, FeNO, and both together in predicting sputum eosinophilia were all below the threshold for excellent discrimination (AUC 0.75, 0.78, and 0.79, respectively). Periostin (in adults) had poor discrimination (AUC 0.59; P= .02). In untreated mild persistent asthma, there is substantial discordance between sputum eosinophilia, BEC, and FeNO. Until prospective trials test the ability of alternative biomarkers to predict ICS response, BEC or FeNO phenotyping may be an option to consider ICS through a shared decision-making process with consideration of other clinical features.

Association of GAB1 gene with asthma susceptibility and the efficacy of inhaled corticosteroids in children

Asthma is a polygenic disease that may onset during childhood. Inhaled corticosteroids (ICS) are the main therapy in asthma, although their efficacy varies among individuals. Nuclear factor κB (NF-κB) is an important target of ICS treatment of asthma. Recent research has reported that GRB2 associated binding protein 1 (GAB1) gene may participate in the pathogenesis of asthma by regulating the NF-κB pathway. Therefore, we used the technique of an improved multiplex ligation detection reaction to sequence GAB1 gene and investigated the involvement of Single-nucleotide variants (SNVs) in GAB1 gene in asthma and ICS efficacy in asthmatic children. We found no differences between asthma cases and controls in allele or genotype frequencies of GAB1. Haplotype analysis showed an increased tendency for AGGAGC frequency in asthma patients compared with controls (OR = 2.69, p = 0.018). The percentage of EOS and genotype distribution of rs1397527 were associated (p = 0.007). The EOS percentage was higher in GT genotype when compared to the GG genotype (5.50 vs 3.00, Bonferroni adjusted p = 0.005). After 12-weeks ICS treatment, GAB1 rs1397527 TT and GT genotype carriers had a smaller change in forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) than GG carriers (p = 0.009), and rs3805236 GG and AG genotype carriers also had a smaller change in FEV1/FVC than AA carriers (p = 0.025). For ICS response, the frequency of GG genotype of rs1397527 was significantly higher in good responders (p = 0.038). The generalized multifactor dimensionality reduction (GMDR) analysis showed a best significant four-order model (rs1397527, allergen exposure, environmental tobacco smoke exposure, and pet exposure) involving gene-environment interactions (p = 0.001). In summary, we found that GAB1 SNVs were not associated with asthma susceptibility. Haplotype AGGAGC was a risk factor for asthma. GAB1 variants were associated with eosinophils and ICS response in asthmatics. Furthermore, gene-environment interaction was observed.

Optimizing inhaled corticosteroid use in patients with chronic obstructive pulmonary disease: assessing blood eosinophils, neutrophil-to-lymphocyte ratio, and mortality outcomes in US adults.

Accurate biomarkers for evaluating mortality rates in patients with chronic obstructive pulmonary disease (COPD) remain scarce. This study aimed to explore the relationships between mortality rates in patients with COPD and blood eosinophil counts, neutrophil counts, and lymphocyte counts, along with the neutrophil-to-lymphocyte ratio (NLR). Additionally, we sought to identify the optimal response values for these biomarkers when utilizing inhaled corticosteroids (ICS). Utilizing a nationally representative, multistage cross-sectional design and mortality correlation study, we analyzed data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 involving US adults aged 40 years or older with COPD. The primary endpoint was all-cause mortality, with Kaplan-Meier survival curves and restricted cubic splines applied to illustrate the relationship between leukocyte-based inflammatory markers and mortality. The analysis was conducted in 2023. Our analysis included 1,715 COPD participants, representing 6,976,232 non-institutionalized US residents [weighted mean age (SE), 62.09 (0.28) years; range, 40-85 years]. Among the participants, men constituted 50.8% of the population, and the weighted mean follow-up duration was 84.9 months. In the ICS use group, the weighted proportion of participants over 70 years old was significantly higher compared with the non-ICS use group (31.39% vs 25.52%, p < 0.0001). The adjusted hazard ratios for all-cause mortality related to neutrophil counts, lymphocyte counts, and NLR were 1.10 [95% confidence interval (CI), 1.04-1.16, p < 0.001], 0.83 (95% CI, 0.71-0.98; p = 0.03), and 1.10 (95% CI, 1.05-1.15; p < 0.0001), respectively. Optimal ICS response was linked with higher levels of eosinophil count (≥240 cells/μL), neutrophil count (≥3,800 cells/μL), NLR (≥4.79), and lower levels of lymphocyte count (<2,400 cells/μL). Adjusted baseline neutrophil, lymphocyte counts, and NLR serve as independent risk factors for all-cause mortality in patients with COPD. Further, ICS application appears to mitigate mortality risk, particularly when NLR levels reach 4.79 or higher, underlining the importance of ICS in COPD management.

Airway smooth muscle area to predict steroid responsiveness in COPD patients receiving triple therapy (HISTORIC): a randomised, placebo-controlled, double-blind, investigator-initiated trial.

Although inhaled corticosteroids (ICS) are highly effective in asthma, they provide significant but modest clinical benefit in COPD. Here, we tested the hypothesis that high bronchial airway smooth muscle (ASMC) area in COPD is associated to ICS responsiveness.In this investigator-initiated and -driven, double-blind, randomised, placebo-controlled trial (HISTORIC), 190 COPD patients, GOLD stage B-D, underwent bronchoscopy with endobronchial biopsy. Patients divided in groups A and B with high ASMC area (HASMC: >20% of the bronchial tissue area) and with low ASMC area (LASMC: ≤20% of the bronchial tissue area), respectively and followed a run-in period of 6 weeks on open-label triple inhaled therapy with aclidinium/formoterol/budesonide (ACL/FOR/BUD:400/12/400 mcg/bid). Subsequently, patients were randomised to receive either ACL/FOR/BUD or ACL/FOR/Placebo and followed for 12 months. The primary end point of the study was the difference in post-bronchodilator FEV1 over 12 months between patients with LASMC and HASMC receiving or not receiving ICS.In patients with LASMC, ACL/FOR/BUD did not significantly improve FEV1 over 12 months, as compared to ACL/FOR/placebo p=0.675. In patients with HASMC, however, ACL/FOR/BUD significantly improved FEV1, as compared to ACL/FOR/placebo p=0.020. Over 12 months, the difference of FEV1 change between the group of ACL/FOR/BUD and the group of ACL/FOR/placebo was 50.6 mL·year-1 within the group of patients with LASMC and 183.0 mL·year-1 within the group of patients with HASMC.COPD patients with ΗASMC respond better to ICS than patients with LASMC, suggesting that this type of histological analysis may predict ICS responsiveness in COPD patients receiving triple therapy.

Human genetics influences microbiome composition involved in asthma exacerbations despite inhaled corticosteroid treatment

The upper-airway microbiome is involved in asthma exacerbations despite inhaled corticosteroid (ICS) treatment. Although human genetics regulates microbiome composition, its influence on asthma-related airway bacteria remains unknown. We sought to identify genes and biological pathways regulating airway-microbiome traits involved in asthma exacerbations and ICS response. Saliva, nasal, and pharyngeal samples from 257 European patients with asthma were analyzed. The association of 6,296,951 genetic variants with exacerbation-related microbiome traits despite ICS treatment was tested through microbiome genome-wide association studies. Variants with 1×10-4<P< 1×10-6 were examined in gene-set enrichment analyses. Significant results were sought for replication in 114 African American and 158 Latino children with and without asthma. ICS-response-associated single nucleotide polymorphisms reported in the literature were evaluated as microbiome quantitative trait loci. Multiple comparisons were adjusted by the false discovery rate. Genes associated with exacerbation-related airway-microbiome traits were enriched in asthma comorbidities development (ie, reflux esophagitis, obesity, and smoking), and were likely regulated by trichostatin Aand the nuclear factor-κB, the glucocorticosteroid receptor, and CCAAT/enhancer-binding protein transcription factors (7.8×10-13≤ false discovery rate≤ 0.022). Enrichment in smoking, trichostatin A, nuclear factor-κB, and glucocorticosteroid receptor were replicated in the saliva samples from diverse populations (4.42×10-9≤ P≤ .008). The ICS-response-associated single nucleotide polymorphisms rs5995653 (APOBEC3B-APOBEC3C), rs6467778 (TRIM24), and rs5752429 (TPST2) were identified as microbiome quantitative trait loci of Streptococcus, Tannerella, and Campylobacter in the upper airway (0.027≤ false discovery rate≤ 0.050). Genes associated with asthma exacerbation-related microbiome traits might influence asthma comorbidities. We reinforced the therapeutic interest of trichostatin A, nuclear factor-κB, the glucocorticosteroid receptor, and CCAAT/enhancer-binding protein in asthma exacerbations.

The Potential of Fractional Exhaled Nitric Oxide as a Biomarker in Predicting and Optimizing Use of Treatment in Asthma

Asthma affects the respiratory system and causes airway inflammation. The indication of asthma includes a triad of airway inflammation, hyperresponsiveness, and obstruction. Nitric Oxide (NO) is a gas that is exhaled and is a sign of airway inflammation. NO levels in the exhaled breath of patients with type 2 asthma are elevated, and fractional exhaled nitric oxide (FeNO) is an objective biomarker of airway inflammation. Measurements of FeNO are noninvasive, require minimal patient effort, and are easy to collect in clinical settings. The current review is a systematic review performed using PubMed, Science Direct, and Google Scholar according to The Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P) guidelines. This review discusses the entanglement of understanding FeNO measurement and supplementing existing diagnostic and assessment tools for inflammatory lung diseases. Monitoring FeNO can also help identify different asthma phenotypes within the asthma syndrome and suggest the optimal administration of inhaled corticosteroids (ICS) as elevated FeNO levels indicate ICS response. Non-adherence to ICS is a significant contributor to the failure of asthma treatment. A FeNO suppression test can be done to determine non-adherence. FeNO levels should be used with a careful history, conventional spirometric testing with bronchodilator reversibility, measures of bronchial hyperreactivity using methacholine, and other measures of eosinophilic inflammation, such as a peripheral blood eosinophil cell count. FeNO is more sensitive and specific when paired with other lung function tests.

Systems Genomics Reveals microRNA Regulation of ICS Response in Childhood Asthma.

Asthmatic patients' responses to inhaled corticosteroids (ICS) are variable and difficult to quantify. We have previously defined a Cross-sectional Asthma STEroid Response (CASTER) measure of ICS response. MicroRNAs (miRNAs) have shown strong effects on asthma and inflammatory processes. The purpose of this study was to identify key associations between circulating miRNAs and ICS response in childhood asthma. Small RNA sequencing in peripheral blood serum from 580 children with asthma on ICS treatment from The Genetics of Asthma in Costa Rica Study (GACRS) was used to identify miRNAs associated with ICS response using generalized linear models. Replication was conducted in children on ICS from the Childhood Asthma Management Program (CAMP) cohort. The association between replicated miRNAs and the transcriptome of lymphoblastoid cell lines in response to a glucocorticoid was assessed. The association study on the GACRS cohort identified 36 miRNAs associated with ICS response at 10% false discovery rate (FDR), three of which (miR-28-5p, miR-339-3p, and miR-432-5p) were in the same direction of effect and significant in the CAMP replication cohort. In addition, in vitro steroid response lymphoblastoid gene expression analysis revealed 22 dexamethasone responsive genes were significantly associated with three replicated miRNAs. Furthermore, Weighted Gene Co-expression Network Analysis (WGCNA) revealed a significant association between miR-339-3p and two modules (black and magenta) of genes associated with immune response and inflammation pathways. This study highlighted significant association between circulating miRNAs miR-28-5p, miR-339-3p, and miR-432-5p and ICS response. miR-339-3p may be involved in immune dysregulation, which leads to a poor response to ICS treatment.

Responsiveness of Inhaled Corticosteroid Treatment in Children with Asthma: The Role of rs242941 Polymorphism of CRHR1 Gene.

Inhaled corticosteroid (ICS) is the most widely used and effective treatment of asthma. However, some patients do not respond to ICS, which might be due to various genetic factors. Hence, understanding the genetic factors involved in the ICS response could help physicians to individualize their treatment decision and action plans for given patients. This study aimed to analyze the characteristics of corticotropin-releasing hormone receptor 1 (CRHR1) genotypes in children with asthma and the correlation between rs242941 polymorphism of CRHR1 gene and ICS responsiveness. This prospective study included children with uncontrolled asthma, assessing their eosinophil count, IgE concentration, lung function, and fractional concentration of nitric oxide in exhaled breath (FENO) and performing CRHR1 polymorphism sequencing. The level of asthma control was assessed by asthma control test (ACT); the responsiveness of asthma treatment with ICS was evaluated by measuring the change of ACT and forced expiratory volume in 1s (FEV1) after treatment versus at inclusion. In total, 107 patients were analyzed for CRHR1 at rs242941. Among these, 86 (80.3%) had homozygous wild-type GG, 20 (18.7%) had heterozygous GT genotypes, and 1 (1.0%) had a homozygous variant for TT. Children with personal and family history of atopy were more likely to have GT and TT genotypes. The severity of asthma was similar between children with asthma in the three groups of GG, GT, and TT genotypes of CRHR1 at rs242941. FENO level, total IgE concentration, and eosinophilic count in children with asthma were not significantly different between GG and GT genotypes. The patient with a TT homozygous variant genotype had a higher level of FENO. There was no correlation between CRHR1 polymorphism at rs242941 and asthma control evaluated by asthma control test and lung function parameters. TT genotype of rs242941 in the CRHR1 gene is not frequent. Clinical and functional characteristics of children with asthma with rs242941 polymorphism of CRHR1 gene remain homogeneously similar. There is no correlation between rs242941 polymorphism and ACT or FEV1.

New Perspectives on Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide; many recent advances have been made in many aspects of the disease. The aim of this article is to illustrate and discuss some of these advances in the management of different types of patients. Large-scale trials have confirmed that long-acting bronchodilator therapy, particularly using the combination of LABA/LAMA, remains the mainstay of COPD treatment, with special attention being paid to careful selection of inhaler devices. The initial choice of pharmacological therapy is based on the GOLD ABCD grouping of patients. It is very important to stress that there is a need to implement a management cycle because COPD is a chronic disease with varying clinical course and a high number of potential comorbidities that may affect morbidity and mortality. Therefore, regular reevaluation of the patient is mandatory. This allows identification of characteristics aimed at maximizing the benefits for a specific patient or a subset of patients. Within this context, the role of the blood eosinophil count as a marker of inhaled corticosteroids response to prevent future exacerbations in patients who, despite appropriate bronchodilator therapy, still suffer from them has been proven to be a useful simple biomarker in medication selection. These advances support the concept of precision medicine, with the goal that patients get the right medicine at the right time for the right reason. Finally, recent studies have shown that early life events may be of critical relevance for the development of COPD. With this as a background, concepts to identify individuals at risk and early identification of cases have become an important objective of current research with the hope of maximizing the effects of therapy and the possibility of impacting disease progression.

A Pragmatic Primary Practice Approach to Using Specific IgE in Allergy Testing in Asthma Diagnosis, Management, and Referral

Asthma afflicts an estimated 339 million people globally and is associated with ill health, disability, and early death. Strong risk factors for developing asthma are genetic predisposition and environmental exposure to inhaled substances that may provoke allergic reactions. Asthma guidelines recommend identifying causal or trigger allergens with specific IgE (sIgE) testing after a diagnosis of asthma has been made. Allergy testing with sIgE targets subpopulations of patients considered at high risk, such as those with frequent exacerbations, emergency visits or hospitalizations, or uncontrolled symptoms. Specific recommendations apply to preschool children, school-age children, patients with persistent or difficult-to-control asthma, patients needing oral corticosteroids or high-dose inhaled steroids, patients seeking understanding and guidance about their disease, and candidates for advanced therapies (biologics, allergen immunotherapy). Allergen skin testing is common in specialized settings but less available in primary care. Blood tests for total and sIgE are accessible and yield quantifiable results for tested allergens, useful for detecting sensitization. Results are interpreted in the context of the patient’s clinical presentation, age, and relevant allergen exposures. Incorporating sIgE testing into asthma management adds objective information to identify specific allergies and can guide personalized treatment plans, which reinforce patient-doctor communication. Test results can also be used to predict exacerbations and response to therapies. Additional diagnostic information can be gleaned from (i) eosinophil count ≥300 μL, which significantly increases the odds of having exacerbations, and emerging eosinophil biomarkers (eg, eosinophil-derived neurotoxin), which can be measured in plasma or serum samples, and (ii) fractional exhaled nitric oxide (FeNO), with values ≥25 ppb regarded as the cutoff for diagnosis, evaluating inhaled corticosteroid response, and of probable response to anti-IgE, anti-IL4 and anti-IL5 receptor biologics. Referral to asthma/allergy specialists is warranted when the initial diagnosis is uncertain, and when asthma symptoms, impairment, or exacerbations are repeated or severe.

Long-term pulmonary sequelae in adolescents post-SARS-CoV-2 infection.

RationaleSevere acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes long‐term pulmonary sequelae in adults, but little is known about pulmonary outcomes in pediatrics.Objective(s)The aim of this study was to describe long‐term subjective and objective pulmonary abnormalities after SARS‐CoV‐2 infection in pediatric populations.MethodsSingle‐center, retrospective cohort of patients seen in post‐coronavirus disease 2019 (COVID‐19) pulmonary clinic in 2021. Subjects evaluated had persistent pulmonary symptoms 4 weeks or more after initial infection. Clinical testing included a 6‐min walk test (6MWT), chest X‐ray, pre‐ and postbronchodilator spirometry, plethysmography, and diffusion capacity. Patients were followed 2‐to‐3‐months after the initial visit with repeat testing. The primary outcome was the presence of abnormal pulmonary function testing. Secondary measures included variables associated with pulmonary outcomes.ResultsEighty‐two adolescents were seen at a median of 3.5 months postinfection, with approximately 80% reporting two or more symptoms at clinic presentation (cough, chest pain, dyspnea at rest, and exertional dyspnea). At follow‐up (~6.5 months) exertional dyspnea persisted for most (67%). Spirometry was normal in 77% of patients, but 31% had a positive bronchodilator response. No abnormalities were noted on plethysmography or diffusion capacity. Clinical phenotypes identified included inhaled corticosteroid responsiveness, paradoxical vocal fold motion disorder, deconditioning, and dysautonomia. Multivariable modeling demonstrated that obesity, anxiety, and resting dyspnea were associated with reduced 6MWT, while female sex and resting dyspnea were associated with higher Borg Dyspnea and Fatigues scores.ConclusionsThis is the largest study to date of pediatric patients with long‐term pulmonary sequelae post‐COVID‐19. Identified clinical phenotypes and risk factors warrant further study and treatment.

Diagnostic accuracy of FeNO in asthma and predictive value for inhaled corticosteroid responsiveness: A prospective, multicentre study.

SummaryBackgroundFractional exhaled nitric oxide (FeNO) is promising for diagnosing asthma and could replace bronchial provocation (BP). To date, cut-off values have been derived by post hoc analysis only. The aim was to validate the diagnostic accuracy for predefined FeNO cut-off values and the predictive value for responsiveness to inhaled corticosteroids (ICS).MethodsWe conducted a prospective, diagnostic, multicentre study with patients attending three private practices of pneumologists in Upper Bavaria, Germany, from July 3, 2020 to Jan 21, 2022. Index test was FENO measurement. Reference standard was Tiffeneau ratio (FEV1/VC) or airway resistance as assessed by whole body plethysmography, with additional BP or bronchodilation test. Follow-up was performed after 12 weeks. Analyses of Receiver Operating Characteristics curves were conducted to determine the diagnostic accuracy and predictive value of FeNO.Findings308 patients with complete follow-up were recruited, 186 (60·4%) were female, average age was 44·7 years, 161 (52·3%) had asthma. Regarding diagnostic accuracy, the area under the curve (AUC) was 0·718 (95% CI 0·661–0·775; p < 0·001). Sensitivity at FeNO >50 ppb was 0·24 (95% CI 0·18–0·32), specificity 0·99 (0·95–1·0), positive predictive value (PPV) 0·95 (0·84–0·99), negative predictive value (NPV) 0·54 (0·48–0·60). In 66 patients with ´wheezing´ and ´allergic rhinitis´, the sensitivity at FeNO >33 ppb was 0·49 (0·34–0·64), specificity 0·88 (0·64–0·99), PPV 0·92 (0·75–0·99), NPV 0·38 (0·23–0·54). In 68 patients with ICS medication, responsiveness was predicted at the cut-off >43 ppb, with a sensitivity of 0·55 (95%CI 0·36–0·74), specificity 0·82 (0·66–0·92), PPV 0·70 (0·47–0·87), NPV 0·71 (0·56–0·84).InterpretationFeNO measurement allows a valid ruling-in of an asthma diagnosis, whereas ruling-out of asthma is not possible. Enhanced probability of ICS responsiveness is also given with increased FeNO values.FundingCircassia Germany gave 25% discount on the purchase of three NIOX VERO devices.

Asthma, bronchiectasis, and chronic obstructive pulmonary disease: the Bermuda Triangle of the airways

Asthma, bronchiectasis, and chronic obstructive pulmonary disease: the Bermuda Triangle of the airways

Novel genetic variants associated with inhaled corticosteroid treatment response in older adults with asthma

IntroductionOlder adults have the greatest burden of asthma and poorest outcomes. The pharmacogenetics of inhaled corticosteroid (ICS) treatment response is not well studied in older adults.MethodsA genome-wide association study of...

Predictors of High Sputum Eosinophils in Chronic Obstructive Pulmonary Disease.

Eosinophils are involved in the development of chronic obstructive pulmonary disease (COPD) and inhaled corticosteroid responsiveness. We evaluated clinical predictors of high sputum eosinophil levels in a COPD cohort in China. We conducted an observational, prospective, population-based, cross-sectional study. Participants were tested for COPD and underwent spirometry, computed tomography scans, and a blood test. Participants also produced induced sputum and responded to an information-gathering questionnaire. High sputum eosinophils were defined as ≥3.0%. Multivariate logistic regression was used to identify predictors of high sputum eosinophil levels. We recruited 895 patients with complete and quality control data. The median percentage of sputum eosinophil abundance was 2.00% (interquartile range: 0.75-5.00) and the prevalence of COPD with high sputum eosinophils was 38.0%. Covariance analysis indicated that the high sputum eosinophil group had lower lung function, more severe emphysema, and air trapping. Multivariate logistic regression indicated that high blood eosinophil levels, severe respiratory symptoms, being a former smoker, and a family history of respiratory diseases were associated with high sputum eosinophil levels. High blood eosinophil levels, severe respiratory symptoms, being a former smoker, and a family history of respiratory diseases may be predictors of high sputum eosinophil levels in Chinese COPD patients. High sputum eosinophils were associated with lower lung function, more emphysema, and gas trapping.