Exhaled nitric oxide measurement confirms 2 severe wheeze phenotypes in young children from the Trousseau Asthma Program

Recent Diagnosis Techniques in Pediatric Asthma: Impulse Oscillometry in Preschool Asthma and Use of Exhaled Nitric Oxide

Objective measures of lung function are important in the diagnosis and management of asthma. Spirometry, the pulmonary function test most widely used in asthma, requires respiratory maneuvers that may be difficult for preschoolers. Impulse oscillometry (IOS) is a noninvasive method of measuring lung function during tidal breathing; hence, IOS is an ideal test for use in preschool asthma. Fractional exhaled nitric oxide (FeNO) levels correspond to eosinophilic inflammation and predict responsiveness to corticosteroids. Basic concepts of IOS, methodology, and interpretation, including available normative values, and recent findings regarding FeNO are reviewed in this article.

Question 3: Can we diagnose asthma in children under the age of 5 years?

The diagnosis of asthma in children under five years has been controversial due to changing concepts of what true asthma is in this age group. Previous diagnostic algorithms that used clinical indices to predict the persistence of asthma symptoms or phenotypes based on asthma triggers do not predict which children will benefit from asthma medication. A pragmatic approach to asthma diagnosis in this age group is based on identifying signs and symptoms of reversible airflow obstruction and documenting their response to asthma medication. Hopefully, this approach will provide clearer guidance to clinicians and improve asthma morbidity in these young children.

Biomarkers for severe allergic asthma in children: could they be useful to guide disease control and use of omalizumab?

INTRODUCTION

Although symptom controls in asthmatic children can be achieved through compliant use of conventional medication, some children have uncontrolled severe persistent asthma, especially if they are allergic. For these children, omalizumab (approved by the EMA and FDA in children aged > 6 years) could be a therapeutic option. However, response to omalizumab varies from one child to another. Predictive biomarkers of omalizumab effectiveness could be useful to monitor response to treatment. Area covered: The authors searched in the PubMed database for publications related to the use of biomarkers in allergic asthma. Supported by their own experience in phenotyping asthma in children, they analyzed whether these biomarkers could be useful in assessing response to omalizumab. Expert commentary: Th2 inflammation in children with allergic asthma can be assessed by measuring several biomarkers (blood eosinophil, serum ECP or periostin, FeNO). While a single measurement may be insufficient, a combination of biomarkers assessments may improve the follow-up of children treated by omalizumab.

The IL-4 rs2070874 polymorphism may be associated with the severity of recurrent viral-induced wheeze

BACKGROUND

Childhood recurrent wheezing and consequently asthma corresponds to various phenotypes. Our aim was to link genetic variants of asthma candidate genes to the phenotypes of early onset wheezing.

STUDY DESIGN

We included very young consecutive children presenting with recurrent wheezing who had been evaluated for the severity of wheezing, associated atopic comorbidities, and tested for biomarkers of atopy and inflammation. All were genotyped for 16 single nucleotide polymorphisms (SNPs) linked with asthma or atopy. An unsupervised hierarchical bottom-up method was used for clustering the phenotypes and a multinomial logistic regression was performed for each individual SNP.

RESULTS

We replicated the three phenotypes previously described Trousseau Asthma Program in 317 children aged 21.5 ± 7.9 months: cluster 1 (nonatopic uncontrolled severe wheeze), n = 207, a severe viral-induced wheeze, cluster 2 (atopic multiple trigger wheeze), n = 61, with multiple allergic comorbidities, and cluster 3 (episodic viral wheeze), n = 49, a mild viral-induced wheeze. The TT-genotype of the IL-4 rs2070874 polymorphism was significantly associated with the nonatopic uncontrolled severe wheeze compared to the episodic viral wheeze (OR 7.9; CI95% [2.5-25.3]; P = 0.001).

CONCLUSION

Association between the TT-genotype of IL-4 rs2070874 polymorphism and a severe phenotype of viral-induced wheeze further underlines the role IL-4 plays in the inflammation pathway leading to viral respiratory infections.

Differences in airway remodeling and airway inflammation among moderate-severe asthma clinical phenotypes

Background

To identify asthma clinical phenotypes using cluster analysis and improve our understanding of heterogeneity in asthma.

Methods

Clustering approaches were applied to 203 patients who were diagnosed with asthma in XinHua Hospital (January 2012 to December 2015). One hundred and twenty patients underwent multi-slice spiral computed tomography (MSCT) examination and 30 underwent bronchial mucosal biopsy for evaluation of airway remodeling and airway inflammation among the phenotypes.

Results

Four groups were identified. Patients in cluster 1 (n=52) had early onset atopic asthma and patients in cluster 2 (n=65) had small airway obstruction and atopic asthma. Cluster 3 (n=52) was a unique group of patients with late-onset and non-atopic asthma. Patients in cluster 4 (n=34) had severe airflow obstruction and obvious airway remodeling as observed on MSCT (P<0.05). According to the immunohistochemistry of IL-5 and IL-17 (P<0.05), the results of clusters 1 and 2 may be attributable to the Th2 immune response, whereas those of clusters 3 and 4 to the Th17 immune response.

Conclusions

Four distinct clinical phenotypes of asthma were identified by cluster analysis. The results of the MSCT and pathological examinations may suggest specific pathogeneses among the phenotypes.

Identification of Asthma Subtypes Using Clustering Methodologies

Asthma is a heterogeneous disease comprising a number of subtypes which may be caused by different pathophysiologic mechanisms (sometimes referred to as endotypes) but may share similar observed characteristics (phenotypes). The use of unsupervised clustering in adult and paediatric populations has identified subtypes of asthma based on observable characteristics such as symptoms, lung function, atopy, eosinophilia, obesity, and age of onset. Here we describe different clustering methods and demonstrate their contributions to our understanding of the spectrum of asthma syndrome. Precise identification of asthma subtypes and their pathophysiological mechanisms may lead to stratification of patients, thus enabling more precise therapeutic and prevention approaches.

An Overview of Fractional Exhaled Nitric Oxide and Children with Asthma

Asthma is the most common pediatric chronic disease and is characterized by lung inflammation. Fractional exhaled nitric oxide (FeNO) is thought to reflect the presence of eosinophilic airway inflammation, and is an easy, non-invasive test that has held promise in providing additional objective data. However, not all studies have shown a clinical benefit in the use of FeNO to guide management of asthma in children. This review will describe the results of the most recent studies examining the use of FeNO in the diagnosis and treatment of asthma in infants, preschool-aged children and in school-aged children. It will aid the clinician in providing a clinical context in which FeNO may be most useful in treating pediatric asthma.

What lessons can be learned about asthma phenotypes in children from cohort studies?

'Phenotyping' asthma by multivariate analyses and more recently by unsupervised analysis has been performed in children cohorts. We describe the key findings that have emerged from these cohorts. It would appear that there are three wheeze phenotypes in children of preschool age: the mild episodic viral wheeze phenotype; the multitrigger atopic wheeze; and, less often encountered, the severe non-atopic wheeze. Early onset of allergy in asthma (more prevalent in boys) is associated with poor prognosis unlike the severe non-atopic wheeze phenotype which has a female predominance. The prognosis of the severe non-atopic wheeze depends on time of onset (early or late) of allergic expression. At school age, the risk of severe asthmatic exacerbations is associated with eosinophil predominant inflammation frequently related to allergic asthma, whereas neutrophil inflammation is associated with moderate-to-severe asthma with poorer lung function. Nevertheless, allergic asthma is also a heterogeneous disease with a severe allergic phenotype strongly associated with atopic dermatitis and very high eosinophil-driven inflammatory markers. Further studies are required to find non-invasive biological markers in very young children to better define wheezing phenotypes associated with an elevated risk of developing severe asthma with a view to personalizing treatment.

Asthma phenotypes and the use of biologic medications in asthma and allergic disease: the next steps toward personalized care

Traditionally, asthma and allergic diseases have been defined by broad definitions and treated with nonspecific medications, including corticosteroids and bronchodilators. There is an increasing appreciation of heterogeneity within asthma and allergic diseases based primarily on recent cluster analyses, molecular phenotyping, biomarkers, and differential responses to targeted and nontargeted therapies. These pioneering studies have led to successful therapeutic trials of molecularly targeted therapies in defined phenotypes. This review analyzed randomized double-blind, placebo-controlled trials of molecularly targeted therapies in defined allergic disease and asthma phenotypes. IgE was the first successful biological target used in patients with allergic disease and asthma. This review shows that therapies targeting the canonical type 2 cytokines IL-4, IL-5, and IL-13 have shown consistent efficacy, especially in asthmatic patients with evidence of TH2/type 2 inflammation ("type 2 high"). As of yet, there are no successful trials of targeted therapies in asthmatic patients without evidence for type 2 inflammation. We conclude that further refinement of type 2 therapies to specific type 2 phenotypes and novel approaches for patients without type 2 inflammation are needed for asthma and allergic disease treatment.

Unsupervised phenotyping of Severe Asthma Research Program participants using expanded lung data

BACKGROUND

Previous studies have identified asthma phenotypes based on small numbers of clinical, physiologic, or inflammatory characteristics. However, no studies have used a wide range of variables using machine learning approaches.

OBJECTIVES

We sought to identify subphenotypes of asthma by using blood, bronchoscopic, exhaled nitric oxide, and clinical data from the Severe Asthma Research Program with unsupervised clustering and then characterize them by using supervised learning approaches.

METHODS

Unsupervised clustering approaches were applied to 112 clinical, physiologic, and inflammatory variables from 378 subjects. Variable selection and supervised learning techniques were used to select relevant and nonredundant variables and address their predictive values, as well as the predictive value of the full variable set.

RESULTS

Ten variable clusters and 6 subject clusters were identified, which differed and overlapped with previous clusters. Patients with traditionally defined severe asthma were distributed through subject clusters 3 to 6. Cluster 4 identified patients with early-onset allergic asthma with low lung function and eosinophilic inflammation. Patients with later-onset, mostly severe asthma with nasal polyps and eosinophilia characterized cluster 5. Cluster 6 asthmatic patients manifested persistent inflammation in blood and bronchoalveolar lavage fluid and exacerbations despite high systemic corticosteroid use and side effects. Age of asthma onset, quality of life, symptoms, medications, and health care use were some of the 51 nonredundant variables distinguishing subject clusters. These 51 variables classified test cases with 88% accuracy compared with 93% accuracy with all 112 variables.

CONCLUSION

The unsupervised machine learning approaches used here provide unique insights into disease, confirming other approaches while revealing novel additional phenotypes.

Atopy is important in the management of asthma

Allergic diseases are a public health problem in industrialized countries due to the increasing number of allergies related to Western lifestyle. The multiplicity of organs affected by allergy (skin (atopic dermatitis), airway epithelium (respiratory allergy), and digestive tract (food allergy)) worsens the prognosis of each of the allergic diseases and specially asthma. The importance of allergy in management of asthma is also underlined by the risk of fatal or near fatal acute asthma attacks due to multiple allergic sensitizations. Preliminary studies suggest that specific treatment of allergy could change the asthma course.

Exhaled nitric oxide in symptomatic children at preschool age predicts later asthma

BACKGROUND

Prediction of asthma in young children with respiratory symptoms is hampered by the lack of objective measures applicable in clinical routine. In this prospective study in a preschool children cohort, we assessed whether the fraction of exhaled nitric oxide (FeNO), a biomarker of airway inflammation, is associated with asthma at school age.

METHODS

At baseline, IgE and eosinophils were measured in the blood, and FeNO was measured offline in 391 children aged 3-47 months with lower airway symptoms. We developed an asthma predictive index (API) including high FeNO as major criterion. At follow-up, primary outcome was physician-diagnosed asthma based on standardized interviews in those children reaching school age (n = 166).

RESULTS

FeNO was significantly elevated in those children with later asthma (68/166) as compared to children not developing asthma. Median (IQR) FeNO was 10.5 (6.6-17.2) vs. 7.4 (5.3-10.3) ppb. Per 5 ppb FeNO increase, the odds ratio (95% CI) for asthma increased by 2.44 (1.61-3.70) without changing when adjusting for confounders. Using the new API, children scored at risk had 58.0% probability for later asthma, whereas the negative predictive value was 78.2%, which was comparable to the classical API.

CONCLUSIONS

In this cohort of high-risk preschool children, elevated FeNO is associated with increased risk for school-age asthma. The new API including FeNO identifies children at risk of later asthma comparably to the classical API, but does not require blood sampling.

Advances in pediatric asthma in 2012: moving toward asthma prevention

Last year's "Advances in pediatric asthma: moving forward" concluded the following: "Now is also the time to utilize information recorded in electronic medical records to develop innovative disease management plans that will track asthma over time and enable timely decisions on interventions in order to maintain control that can lead to disease remission and prevention." This year's summary will focus on recent advances in pediatric asthma on modifying disease activity, preventing asthma exacerbations, managing severe asthma, and risk factors for predicting and managing early asthma, as indicated in Journal of Allergy and Clinical Immunology publications in 2012. Recent reports continue to shed light on methods to improve asthma management through steps to assess disease activity, tools to standardize outcome measures in asthma, genetic markers that predict risk for asthma and appropriate treatment, and interventions that alter the early presentation of asthma to prevent progression. We are well on our way to creating a pathway around wellness in asthma care and also to use new tools to predict the risk for asthma and take steps to not only prevent asthma exacerbations but also to prevent the early manifestations of the disease and thus prevent its evolution to severe asthma.