The investigation of asthma phenotypes

Identification of bronchiolitis profiles in Italian children through the application of latent class analysis

BACKGROUND

Bronchiolitis is the primary infection of the lower respiratory tract in children under 2 years of age. Although it is generally considered a single nosological entity, recent studies suggested remarkable clinical heterogeneity. To date, no studies have identified classes of children with bronchiolitis within the Italian population. This study aimed to identify discrete profiles of Italian children hospitalized with bronchiolitis using a clustering approach and to compare findings with those obtained in international cohorts.

METHODS

This was a retrospective single-centre study conducted on children aged ≤2 years hospitalised with bronchiolitis (n = 401) at the Department of Infectious Diseases and the University Department of General Pediatrics in "Giovanni Di Cristina" Pediatric Hospital of Palermo, Italy, between November 2012 and May 2019. Bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical characteristics at admission and viral aetiology.

RESULTS

Three profiles were identified. Class 1 (49%) was composed of 45% male children; all children were aged ≤6 months at hospitalization; 77% were infected with RSV; 100% had respiratory distress, 11% had apnea and none had cough. Class 2 (77%) was mainly composed of male subjects (51%); 19% were aged > 6 months at admission; 37% were infected with RSV; 12% had respiratory distress, 5% had apnea and 90% had cough. Class 3 (19%) included the largest proportion of male subjects (94%) and was mostly composed of children aged > 6 months at the time of admission (68%); 70% had cough, 12% showed respiratory distress and none presented with apnoea. Children in Class 1 were more frequently born near the epidemic season (p = 0.028); breastfeeding duration was significantly longer for children in Class 3 (p = 0.004).

CONCLUSIONS

The study identified distinct clinical profiles of bronchiolitis by a clustering approach in a single-centre study of children hospitalised for bronchiolitis in Italy. The three bronchiolitis profiles share some similarities with those identified in international studies using the same statistical approach. These findings may help to increase the understanding of the phenotypic variability that typically characterizes bronchiolitis, with relevant implications for future research.

G Protein-Coupled Receptors in Asthma Therapy: Pharmacology and Drug Action

Asthma is a heterogeneous inflammatory disease of the airways that is associated with airway hyperresponsiveness and airflow limitation. Although asthma was once simply categorized as atopic or nonatopic, emerging analyses over the last few decades have revealed a variety of asthma endotypes that are attributed to numerous pathophysiological mechanisms. The classification of asthma by endotype is primarily routed in different profiles of airway inflammation that contribute to bronchoconstriction. Many asthma therapeutics target G protein-coupled receptors (GPCRs), which either enhance bronchodilation or prevent bronchoconstriction. Short-acting and long-acting β 2-agonists are widely used bronchodilators that signal through the activation of the β 2-adrenergic receptor. Short-acting and long-acting antagonists of muscarinic acetylcholine receptors are used to reduce bronchoconstriction by blocking the action of acetylcholine. Leukotriene antagonists that block the signaling of cysteinyl leukotriene receptor 1 are used as an add-on therapy to reduce bronchoconstriction and inflammation induced by cysteinyl leukotrienes. A number of GPCR-targeting asthma drug candidates are also in different stages of development. Among them, antagonists of prostaglandin D2 receptor 2 have advanced into phase III clinical trials. Others, including antagonists of the adenosine A2B receptor and the histamine H4 receptor, are in early stages of clinical investigation. In the past decade, significant research advancements in pharmacology, cell biology, structural biology, and molecular physiology have greatly deepened our understanding of the therapeutic roles of GPCRs in asthma and drug action on these GPCRs. This review summarizes our current understanding of GPCR signaling and pharmacology in the context of asthma treatment. SIGNIFICANCE STATEMENT: Although current treatment methods for asthma are effective for a majority of asthma patients, there are still a large number of patients with poorly controlled asthma who may experience asthma exacerbations. This review summarizes current asthma treatment methods and our understanding of signaling and pharmacology of G protein-coupled receptors (GPCRs) in asthma therapy, and discusses controversies regarding the use of GPCR drugs and new opportunities in developing GPCR-targeting therapeutics for the treatment of asthma.

Cohort profile: the West Sweden Asthma Study (WSAS): a multidisciplinary population-based longitudinal study of asthma, allergy and respiratory conditions in adults

PURPOSE

The West Sweden Asthma Study (WSAS) is a population-representative longitudinal study established to: (1) generate data on prevalence trends, incidence and remission of asthma, allergy and respiratory conditions, (2) elucidate on the risk and prognostic factors associated with these diseases, (3) characterise clinically relevant phenotypes of these diseases and (4) catalyse relevant mechanistic, genomic, genetic and translational investigations.

PARTICIPANTS

WSAS comprised of randomly selected individuals aged 16 to 75 years who are followed up longitudinally. The first stage involved a questionnaire survey (>42 000 participants) and was undertaken in 2008 and 2016. A random sample (about 8000) of participants in the initial survey undergoes extensive clinical investigations every 8 to 10 years (first investigations in 2009 to 2012, second wave currently ongoing). Measurements undertaken at the clinical investigations involve structured interviews, self-completed questionnaire on personality traits, physical measurements and extensive biological samples.

FINDINGS TO DATE

Some of our key findings have shown a 54% increase in the use of asthma medications between the 1990s and 2000s, primarily driven by a five-fold increase in the use of inhaled corticosteroids. About 36% of asthmatics expressed at least one sign of severe asthma indicator, with differential lung performance, inflammation and allergic sensitisation among asthmatics with different signs of severe asthma. Multi-symptom asthmatics were at greater risk of having indicators of severe asthma. In all adults, being raised on a farm was associated with a decreased risk of allergic sensitisation, rhinitis and eczema, but not asthma. However, among adolescents (ie, those 16 to 20 years of age), being raised on a farm decreased the risk of asthma. Personality traits were associated with both beliefs of asthma medication and adherence to treatment.

FUTURE PLANS

Follow-up of the cohort is being undertaken every 8 to 10 years. The repeated clinical examinations will take place in 2019 to 2022. The cohort data are currently being linked to routine Swedish healthcare registers for a continuous follow-up. Mechanistic, genomic, genetic and translational investigations are ongoing.

Data-driven adult asthma phenotypes based on clinical characteristics are associated with asthma outcomes twenty years later

BACKGROUND

Research based on cluster analyses led to the identification of particular phenotypes confirming phenotypic heterogeneity of asthma. The long-term clinical course of asthma phenotypes defined by clustering analysis remains unknown, although it is a key aspect to underpin their clinical relevance. We aimed to estimate risk of poor asthma events between asthma clusters identified 20 years earlier.

METHODS

The study relied on two cohorts of adults with asthma with 20-year follow-up, ECRHS (European Community Respiratory Health Survey) and EGEA (Epidemiological study on Genetics and Environment of Asthma). Regression models were used to compare asthma characteristics (current asthma, asthma exacerbations, asthma control, quality of life, and FEV₁ ) at follow-up and the course of FEV₁  between seven cluster-based asthma phenotypes identified 20 years earlier.

RESULTS

The analysis included 1325 adults with ever asthma. For each asthma characteristic assessed at follow-up, the risk for adverse outcomes differed significantly between the seven asthma clusters identified at baseline. As compared with the mildest asthma phenotype, ORs (95% CI) for asthma exacerbations varied from 0.9 (0.4 to 2.0) to 4.0 (2.0 to 7.8) and the regression estimates (95% CI) for FEV₁ % predicted varied from 0.6 (-3.5 to 4.6) to -9.9 (-14.2 to -5.5) between clusters. Change in FEV₁ over time did not differ significantly across clusters.

CONCLUSION

Our findings show that the long-term risk for poor asthma outcomes differed between comprehensive adult asthma phenotypes identified 20 years earlier, and suggest a strong tracking of asthma activity and impaired lung function over time.

Omalizumab for Severe Asthma: Beyond Allergic Asthma

Different subsets of asthma patients may be recognized according to the exposure trigger and the frequency and severity of clinical signs and symptoms. Regarding the exposure trigger, generally asthma can be classified as allergic (or atopic) and nonallergic (or nonatopic). Allergic and nonallergic asthma are distinguished by the presence or absence of clinical allergic reaction and in vitro IgE response to specific aeroallergens. The mechanisms of allergic asthma have been extensively studied with major advances in the last two decades. Nonallergic asthma is characterized by its apparent independence from allergen exposure and sensitization and a higher degree of severity, but little is known regarding the underlying mechanisms. Clinically, allergic and nonallergic asthma are virtually indistinguishable in exacerbations, although exacerbation following allergen exposure is typical of allergic asthma. Although they both show several distinct clinical phenotypes and different biomarkers, there are no ideal biomarkers to stratify asthma phenotypes and guide therapy in clinical practice. Nevertheless, some biomarkers may be helpful to select subsets of atopic patients which might benefit from biologic agents, such as omalizumab. Patients with severe asthma, uncontrolled besides optimal treatment, notwithstanding nonatopic, may also benefit from omalizumab therapy, although currently there are no randomized double-blind placebo controlled clinical trials to support this suggestion. However, omalizumab discontinuation according to each patient's response to therapy and pharmacoeconomical analysis are questions that remain to be answered.

African ancestry is associated with cluster-based childhood asthma subphenotypes

BACKGROUND

Childhood asthma is a syndrome composed of heterogeneous phenotypes; furthermore, intrinsic biologic variation among racial/ethnic populations suggests possible genetic ancestry variation in childhood asthma. The objective of the study is to identify clinically homogeneous asthma subphenotypes in a diverse sample of asthmatic children and to assess subphenotype-specific genetic ancestry in African-American asthmatic children.

METHODS

A total of 1211 asthmatic children including 813 in the Childhood Asthma Management Program and 398 in the Childhood Asthma Research and Education program were studied. Unsupervised cluster analysis on clinical phenotypes was conducted to identify homogeneous subphenotypes. Subphenotype-specific genetic ancestry was estimated for 167 African-American asthmatic children. Genetic ancestry association with subphenotypes/clinical phenotypes were determined.

RESULTS

Three distinct subphenotypes were identified: a moderate atopic dermatitis (AD) group with negative skin prick test (SPT) and preserved lung function; a high AD group with positive SPT and airway hyperresponsiveness; and a low AD group with positive SPT and lower lung function. African ancestry at asthma genome-wide association study (GWAS) SNPs differed between subphenotypes (64, 89, and 94% for the three subphenotypes, respectively) and was inversely correlated with AD; each additional 10% increase in African ancestry was associated with 1.5 fold higher in IgE and 6.3 higher odds of positive SPT (all p-values < 0.0001).

CONCLUSIONS

By conducting phenotype-based cluster analysis and assessing subphenotype-specific genetic ancestry, we were able to identify homogeneous subphenotypes for childhood asthma that showed significant variation in genetic ancestry of African-American asthmatic children. This finding demonstrates the utility of these complementary approaches to understand and refine childhood asthma subphenotypes and enable more targeted therapy.

Patterns of cleaning product exposures using a novel clustering approach for data with correlated variables

PURPOSE

Clustering methods may be useful in epidemiology to better characterize exposures and account for their multidimensional aspects. In this context, application of clustering models allowing for highly dependent variables is of particular interest. We aimed to characterize patterns of domestic exposure to cleaning products using a novel clustering model allowing for highly dependent variables.

METHODS

To identify domestic cleaning patterns in a large population of French women, we used a mixture model of dependency blocks. This novel approach specifically models within-class dependencies, and is an alternative to the latent class model, which assumes conditional independence. Analyses were conducted in 19,398 participants of the E3N study (women aged 61-88 years) who completed a questionnaire regarding household cleaning habits.

RESULTS

Seven classes were identified, which differed with the frequency of cleaning tasks (e.g., dusting/sweeping/hoovering) and use of specific products (e.g., bleach, sprays). The model also grouped the variables into conditionally independent blocks, providing a summary of the main dependencies among the variables.

CONCLUSIONS

The mixture model of dependency blocks, a useful alternative to the latent class model, may have broader application in epidemiology, in particular, in the context of exposome research and growing need for data-reduction methods.

Moving toward consensus on diagnosis and management of severe asthma in children

Children with severe asthma continue to experience symptoms despite long-term treatment with high doses of corticosteroids. Moreover, the heterogeneous nature of asthma and the presence of several phenotypes have limited our ability to develop an optimized management strategy for these patients. Adequate management of severe asthma in children necessitates a detailed understanding of what makes asthma difficult to control, knowledge of the causal factors, review of diagnosis for accurate identification of pediatric patients with severe asthma and a precise definition of the phenotypes to be able to better target the therapy. Advancement in all these aspects is likely to improve childhood asthma treatment in the future. Although our understanding of severe pediatric asthma has grown in recent years, there remains a lack of consensus and clarity around critical aspects of this condition. This review attempts to present a harmonized view on the definition of severe asthma in the pediatric age group, identification of phenotypes and diagnosis, the inflammatory cascade, pharmacological and non-pharmacological treatment strategies, considerations for follow-up and referral to specialists, and disease prevention strategies.

Moving toward consensus on diagnosis and management of severe asthma in adults

Asthma is a considerable health problem with an increasing global prevalence. The burden of severe asthma is expected to notably increase in the following years. Some misleading concepts that sometimes appear in the literature can drive the physician responsible for a patient's management to make incorrect decisions. Furthermore, some of the concepts that appear in the literature and in the guidelines may not be clear to understand, follow or adapt to regional and local realities. This could again drive the physicians responsible for a patient's management to make incorrect clinical judgments. In this article, we review the definition, prevalence and immunopathology of severe asthma, describe the asthma phenotypes, clinical features and comorbidities, the diagnosis of severe asthma and personalized asthma treatment. At the end, we offer a treatment approach based on literature publications, personalized medicine and marketed biologic treatment options.

Pediatric Asthma and the Indoor Microbial Environment

The global increase in the prevalence of asthma has been related to several risk factors; many of them linked to the "westernization" process and the characteristics of the indoor microbial environment during early life may play an important role. Living in moisture damaged homes contributes to the exacerbation and development of asthma. However, living in homes with a rich variety and high levels of microbes (e.g., traditional farming environments) may confer protection. While the results of previous research are rather consistent when it comes to observation/report of indoor moisture damage or when comparing farming versus non-farming homes, when actual measures targeting indoor microbial exposure are included, the picture becomes less clear and the associations appear inconsistent. This may partly be due to limitations of sampling and measurement techniques that make comparisons difficult and provide an incomplete picture of the indoor microbial environment and in particular also human exposure. In this regard, new generation sequencing techniques represent a potential revolution in better understanding the impact of the indoor microbiome on human health.

Defining Phenotypes in Diabetic Nephropathy: a novel approach using a cross-sectional analysis of a single centre cohort

The global increase in Diabetes Mellitus (DM) has led to an increase in DM-Chronic Kidney Disease (DM-CKD). In this cross-sectional observational study we aimed to define phenotypes for patients with DM-CKD that in future may be used to individualise treatment We report 4 DM-CKD phenotypes in 220 patients recruited from Imperial College NHS Trust clinics from 2004–2012. A robust principal component analysis (PCA) was used to statistically determine clusters with phenotypically different patients. 163 patients with complete data sets were analysed: 77 with CKD and 86 with DM-CKD. Four different clusters were identified. Phenotypes 1 and 2 are entirely composed of patients with DM-CKD and phenotypes 3 and 4 are predominantly CKD (non-DM-CKD). Phenotype 1 depicts a cardiovascular phenotype; phenotype 2: microvascular complications with advanced DM-CKD; phenotype 3: advanced CKD with less anaemia, lower weight and HbA1c; phenotype 4: hypercholesteraemic, younger, less severe CKD. We are the first group to describe different phenotypes in DM-CKD using a PCA approach. Identification of phenotypic groups illustrates the differences and similarities that occur under the umbrella term of DM-CKD providing an opportunity to study phenotypes within these groups thereby facilitating development of precision/personalised targeted medicine.

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.

Asthma phenotypes in children and stratified pharmacological treatment regimens

INTRODUCTION

Asthma is the most common inflammatory disease in childhood. The interaction of genetic, environmental and host factors may contribute to the development of childhood asthma and defines its progress, including persistence and severity. Until now, various classifications of childhood asthma phenotypes have been suggested based on patient's age during onset of symptoms, type of inflammatory cells, response to treatment and disease severity. Many efforts have been carried out to identify childhood asthma phenotypes and to clarify which are the risk factors that define asthma prediction and the response to therapy. The identification of asthma phenotypes has not only prognostic but also therapeutic role. However, the classification of asthma phenotypes is complex due to the heterogeneity of the disease. Areas covered: The current childhood asthma phenotypes and the new therapeutic strategies for each phenotype are reviewed. Expert commentary: There are multiple phenotypes in childhood asthma and it is crucial to define them before the initiation of personalized treatment. Both the therapeutic strategy and monitoring should follow the recent guidelines.

Characteristics and outcomes of older adults with long-standing versus late-onset asthma

OBJECTIVE

To examine the effect of age of onset on clinical characteristics and outcomes in a cohort of older patients with long-standing (LSA) and late-onset asthma (LOA).

METHODS

In all, 452 patients 60 years of age and older with persistent asthma were recruited. We defined LOA as asthma developing at age 40 or later and LSA as developing before age 40. We compared airway obstruction as assessed by spirometry, as well as asthma control using the Asthma Control Questionnaire (ACQ), quality of life using the Mini Asthma Quality of Life Questionnaire (AQLQ), and asthma-related emergency department visits and hospitalizations among patients with LSA vs. LOA.

RESULTS

Patients with LOA, were less likely to have FEV₁ <70% of predicted (23% vs. 40%, p = 0.0002), to have FEV₁/FVC<0.7 (27% vs. 38%, p = 0.01), or to have been intubated in the past (5% vs. 14%, p = 0.0007), and were also less likely to report a history of allergic conditions (64% vs 76%, p = 0.007). There was no significant difference in the level of asthma control, quality of life, or health care utilization.

CONCLUSIONS

Older adults with LOA have different clinical and physiological characteristics and outcomes compared to those with LSA. Some of these differences may represent sequelae of longstanding disease, however LOA may also represent a different clinical phenotype that could influence management approaches.

A clustering approach to identify severe bronchiolitis profiles in children

OBJECTIVE

Although bronchiolitis is generally considered a single disease, recent studies suggest heterogeneity. We aimed to identify severe bronchiolitis profiles using a clustering approach.

METHODS

We analysed data from two prospective, multicentre cohorts of children younger than 2 years hospitalised with bronchiolitis, one in the USA (2007-2010 winter seasons, n=2207) and one in Finland (2008-2010 winter seasons, n=408). Severe bronchiolitis profiles were determined by latent class analysis, classifying children based on clinical factors and viral aetiology.

RESULTS

In the US study, four profiles were identified. Profile A (12%) was characterised by history of wheezing and eczema, wheezing at the emergency department (ED) presentation and rhinovirus infection. Profile B (36%) included children with wheezing at the ED presentation, but, in contrast to profile A, most did not have history of wheezing or eczema; this profile had the largest probability of respiratory syncytial virus infection. Profile C (34%) was the most severely ill group, with longer hospital stay and moderate-to-severe retractions. Profile D (17%) had the least severe illness, including non-wheezing children with shorter length of stay. Two of these profiles (A and D) were replicated in the Finnish cohort; a third group ('BC') included Finnish children with characteristics of profiles B and/or C in the US population.

CONCLUSIONS

Several distinct clinical profiles (phenotypes) were identified by a clustering approach in two multicentre studies of children hospitalised for bronchiolitis. The observed heterogeneity has important implications for future research on the aetiology, management and long-term outcomes of bronchiolitis, such as future risk of childhood asthma.

Immunobiology of critical pediatric asthma

Asthma is a heterogeneous disease with numerous clinical phenotypes. Severe asthma constitutes about 10 % of all cases of asthma. There is significant geographic and regional variation in the incidence and severity of asthma. Other important factors include gender, ethnicity, living environment, lifestyle, socioeconomic class, and pathophysiology. These factors can often be identified as either genetic or environmental influences on asthma severity. The immune system derangements in severe asthma are poorly understood. Many molecules and cell types have been implicated in severe asthma, including neutrophils, airway epithelial cells, thymic stromal lymphopoietin, and even filaggrin. Recently, vitamin D has been thought to have a role in the severity of asthma. Aspirin exacerbated respiratory disease is an example of a phenotype that includes severe asthma as a feature. This suggests a role of leukotrienes or prostaglandins in the pathogenesis of severe asthma. Both the innate and adaptive immune system may play a role in the development of severe asthma. Besides filaggrin, other factors of the innate immune system, including TLR4 and TLR9 have been implicated in asthma. Airway epithelial cells possess pattern recognition receptors that recognize danger or pathogen-associated molecular patterns, and the result of binding of the ligand is the triggering of a signaling pathway that ultimately can lead to an activation of inflammatory mediators through the action of calcineurin and NF-κB. Components of the adaptive immune system, including TH2 and Th17 cells, have been implicated in the pathogenesis of asthma. The fact that so many molecules and cells may be variably involved in asthma patients, coupled with the presence of redundant pathways that lead to secretion of inflammatory mediators, make the development of effective drugs for the treatment of asthma extremely difficult. A better understanding of the heterogeneity and what drives this diversity on a genetic and epigenetic level will help to develop strategies for novel therapeutic agents or methods.

Clinical and epidemiologic phenotypes of childhood asthma

RATIONALE

Clinical and epidemiologic approaches have identified two distinct sets of classifications for asthma and wheeze phenotypes.

OBJECTIVES

To compare epidemiologic phenotype definitions identified by latent class analysis (LCA) with clinical phenotypes based on patient histories, diagnostic work-up, and treatment responses. To relate phenotypes to genetic and environmental determinants as well as diagnostic and treatment-related parameters.

METHODS

LCA was performed in an international multicenter birth cohort based on yearly questions about current wheeze until age 6 years. Associations of wheeze classes and clinical phenotypes with asthma-related characteristics such as atopy, lung function, fraction of exhaled nitric oxide, and medication use were calculated using regression models.

MEASUREMENTS AND MAIN RESULTS

LCA identified five classes, which verified the clinically defined wheeze phenotypes with high sensitivity and specificity; the respective receiver operating characteristics curves displayed an area under the curve ranging from 84% (frequent wheeze) to 85% (asthma diagnosis) and 87% (unremitting wheeze) to 97% (recurrent unremitting wheeze). Recurrent unremitting wheeze was the most specific and unremitting wheeze at least once the most sensitive definition. The latter identified a subgroup of children with decreased lung function, increased genetic risk, and in utero smoke exposure (ODDS RATIO, 2.03; 95% CONFIDENCE INTERVAL, 1.12-3.68; P = 0.0191), but without established asthma diagnosis and treatment.

CONCLUSIONS

Clinical phenotypes were well supported by LCA analysis. The hypothesis-free LCA phenotypes were a useful reference for comparing clinical phenotypes. Thereby, we identified children with clinically conspicuous but undiagnosed disease. Because of their high area under the curve values, clinical phenotypes such as (recurrent) unremitting wheeze emerged as promising alternative asthma definitions for epidemiologic studies.

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.

Ten-year follow-up of cluster-based asthma phenotypes in adults. A pooled analysis of three cohorts

RATIONALE

The temporal stability of adult asthma phenotypes identified using clustering methods has never been addressed. Longitudinal cluster-based methods may provide novel insights in the study of the natural history of asthma.

OBJECTIVES

To compare the stability of cluster-based asthma phenotype structures a decade apart in adults and to address the individuals' phenotypic transition across these asthma phenotypes.

METHODS

The latent transition analysis was applied on longitudinal data (twice, 10 yr apart) from 3,320 adults with asthma who took part in the European Community Respiratory Health Survey, the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults, or the Epidemiological Study on Genetics and Environment of Asthma. Nine variables covering personal and phenotypic characteristics measured twice, 10 years apart, were simultaneously considered.

MEASUREMENTS AND MAIN RESULTS

Latent transition analysis identifies seven asthma phenotypes (prevalence range, 8.4-20.8%), mainly characterized by the level of asthma symptoms (low, moderate, high), the allergic status, and pulmonary function. Phenotypes observed 10 years apart showed strong similarities. The probability of membership in the same asthma phenotype at both times varied across phenotypes from 54 to 88%. Different transition patterns were observed across phenotypes. Transitions toward increased asthma symptoms were more frequently observed among nonallergic phenotypes as compared with allergic phenotypes. Results showed a strong stability of the allergic status over time.

CONCLUSIONS

Adult asthma phenotypes identified by a clustering approach, 10 years apart, were highly consistent. This study is the first to model the probabilities of transitioning over time between comprehensive asthma phenotypes.

Confounding with familial determinants affects the association between mode of delivery and childhood asthma medication - a national cohort study

Background

Mode of delivery may affect the risk of asthma but the findings have not been consistent and factors shared by siblings may confound the associations in previous studies.

Methods

The association between mode of delivery and dispensed inhaled corticosteroid (ICS) (a marker of asthma) was examined in a register based national cohort (n=199 837). A cohort analysis of all first born children aged 2-5 and 6-9 years was performed. An age-matched sibling-pair analysis was also performed to account for shared genetic and environmental risk factors.

Results

Analyses of first-borns demonstrated that elective caesarean section was associated with an increased risk of dispensed ICS in both 2-5 (adjusted odds ratio (aOR)=1.19, 95% confidence interval (CI) 1.09-1.29) and 6-9 (aOR=1.21, 1.09-1.34) age groups. In the sibling-pair analysis, the increased risk associated with elective caesarean section was confirmed in 2-5 year olds (aOR=1.22, 1.05-1.43) but not in 6-9 year olds (aOR=1.06, 0.78-1.44). Emergency caesarean section and vacuum extraction had some association with dispensed ICS in the analyses of first-borns but these associations were not confirmed in the sibling-pair analyses.

Conclusions

Confounding by familial factors affects the association between mode of delivery and dispensed ICS. Despite this confounding, there was some evidence that elective caesarean section contributed to a modestly increased risk of dispensed ICS but only up to five years of age.

Clinical asthma phenotypes and therapeutic responses

Asthma is a heterogeneous disease that means not all asthmatics respond to the same treatment. We hypothesize an approach to characterize asthma phenotypes based on symptomatology (shortness of breath (SOB), cough, and wheezy phenotypes) in correlation with airway inflammatory biomarkers and FEV1. We aimed to detect whether those clinical phenotypes have an impact on the response to asthma medications. Two hundred three asthmatic children were allocated randomly to receive either montelukast (5 mg at bed time) or fluticasone propionate (100 ug twice daily) for 8 consecutive weeks. Serum concentrations of IL-2Rs, ICAM-1, VCAM-1, total IgE, eosinophilic %, eosinophil cationic protein (ECP), and FEV1 were done before and after treatment to patients and once to controls. Children who have SOB were found to have higher levels of total sIgE, older age, and longer disease duration, and they responded to fluticasone alone. Cough group was found to have higher levels of eosinophilic % and sECP, younger age, shorter disease duration and responded to montelukast alone. Wheezy group showed mixed pattern and responded to both medications. Conclusion. Although there is variability in response to ICS and LTRAs, we did identify characteristics of patient that should guide the clinician in the choice of asthma medications.