Identifying adult asthma phenotypes using a clustering approach

Primary Care Asthma Attack Prediction Models for Adults: A Systematic Review of Reported Methodologies and Outcomes

Prognostic models hold great potential for predicting asthma exacerbations, providing opportunities for early intervention, and are a popular area of current research. However, it is unclear how models should be compared and contrasted, given their differences in both design and performance, particularly with a view to potential implementation in routine practice. This systematic review aimed to identify novel predictive models of asthma attacks in adults and compare differences in construction related to populations, outcome definitions, prediction time horizons, algorithms, validation, and performance estimation. Twenty-five studies were identified for comparison, with varying definitions of asthma attacks and prediction event time horizons ranging from 15 days to 30 months. The most commonly used algorithm was logistic regression (20/25 studies); however, none of the six which tested multiple algorithms identified it as highest performing algorithm. The effect of various study design characteristics on performance was evaluated in order to provide context to the limitations of highly performing models. Models used a variety of constructs, which affected both their performance and their viability for implementation in routine practice. Consultation with stakeholders is necessary to identify priorities for model refinement and to create a benchmark of acceptable performance for implementation in clinical practice.

Cytotoxic CD4+ tissue-resident memory T cells are associated with asthma severity

BACKGROUND

Patients with severe uncontrolled asthma represent a distinct endotype with persistent airway inflammation and remodeling that is refractory to corticosteroid treatment. CD4+ TH2 cells play a central role in orchestrating asthma pathogenesis, and biologic therapies targeting their cytokine pathways have had promising outcomes. However, not all patients respond well to such treatment, and their effects are not always durable nor reverse airway remodeling. This observation raises the possibility that other CD4+ T cell subsets and their effector molecules may drive airway inflammation and remodeling.

METHODS

We performed single-cell transcriptome analysis of >50,000 airway CD4+ T cells isolated from bronchoalveolar lavage samples from 30 patients with mild and severe asthma.

FINDINGS

We observed striking heterogeneity in the nature of CD4+ T cells present in asthmatics' airways, with tissue-resident memory T (TRM) cells making a dominant contribution. Notably, in severe asthmatics, a subset of CD4+ TRM cells (CD103-expressing) was significantly increased, comprising nearly 65% of all CD4+ T cells in the airways of male patients with severe asthma when compared to mild asthma (13%). This subset was enriched for transcripts linked to T cell receptor activation (HLA-DRB1, HLA-DPA1) and cytotoxicity (GZMB, GZMA) and, following stimulation, expressed high levels of transcripts encoding for pro-inflammatory non-TH2 cytokines (CCL3, CCL4, CCL5, TNF, LIGHT) that could fuel persistent airway inflammation and remodeling.

CONCLUSIONS

Our findings indicate the need to look beyond the traditional T2 model of severe asthma to better understand the heterogeneity of this disease.

FUNDING

This research was funded by the NIH.

Cluster Analysis of Finnish Population-Based Adult-Onset Asthma Patients

BACKGROUND

Phenotypes of adult asthma have been identified in previous studies but rarely in population-based settings.

OBJECTIVE

To identify clusters of adult-onset asthma in a Finnish population-based study on subjects born before 1967.

METHODS

We used population-based data from 1350 asthmatics with adult-onset asthma (Adult Asthma in Finland) from Finnish national registers. Twenty-eight covariates were selected based on literature. The number of covariates was reduced by using factor analysis before cluster analysis.

RESULTS

Five clusters (CLU1-CLU5) were identified, 3 clusters with late-onset adult asthma (onset ≥40 years) and 2 clusters with onset at earlier adulthood (<40 years). Subjects in CLU1 (n = 666) had late-onset asthma and were nonobese, symptomatic, and predominantly female with few respiratory infections during childhood. CLU2 (n = 36) consisted of subjects who had earlier-onset asthma, were predominantly female, obese with allergic asthma, and had recurrent respiratory infections. Subjects in CLU3 (n = 75) were nonobese, older, and predominantly men with late-onset asthma, smoking history, comorbidities, severe asthma, least allergic diseases, low education, many siblings, and childhood in rural areas. CLU4 (n = 218) was a late-onset cluster consisting of obese females with comorbidities, asthma symptoms, and low education level. Subjects in CLU5 (n = 260) had earlier onset asthma, were nonobese, and predominantly allergic females.

CONCLUSIONS

Our population-based adult-onset asthma clusters take into account several critical factors such as obesity and smoking, and identified clusters that partially overlap with clusters identified in clinical settings. Results give us a more profound understanding of adult-onset asthma phenotypes and support personalized management.

A review of the pathophysiology and the role of ion channels on bronchial asthma

Asthma is one of the main non-communicable chronic diseases and affects a huge portion of the population. It is a multifactorial disease, classified into several phenotypes, being the allergic the most frequent. The pathophysiological mechanism of asthma involves a Th2-type immune response, with high concentrations of allergen-specific immunoglobulin E, eosinophilia, hyperreactivity and airway remodeling. These mechanisms are orchestrated by intracellular signaling from effector cells, such as lymphocytes and eosinophils. Ion channels play a fundamental role in maintaining the inflammatory response on asthma. In particular, transient receptor potential (TRP), stock-operated Ca2+ channels (SOCs), Ca2+-activated K+ channels (IKCa and BKCa), calcium-activated chloride channel (TMEM16A), cystic fibrosis transmembrane conductance regulator (CFTR), piezo-type mechanosensitive ion channel component 1 (PIEZO1) and purinergic P2X receptor (P2X). The recognition of the participation of these channels in the pathological process of asthma is important, as they become pharmacological targets for the discovery of new drugs and/or pharmacological tools that effectively help the pharmacotherapeutic follow-up of this disease, as well as the more specific mechanisms involved in worsening asthma.

A population-based study exploring phenotypic clusters and clinical outcomes in stroke using unsupervised machine learning approach

Individuals developing stroke have varying clinical characteristics, demographic, and biochemical profiles. This heterogeneity in phenotypic characteristics can impact on cardiovascular disease (CVD) morbidity and mortality outcomes. This study uses a novel clustering approach to stratify individuals with incident stroke into phenotypic clusters and evaluates the differential burden of recurrent stroke and other cardiovascular outcomes. We used linked clinical data from primary care, hospitalisations, and death records in the UK. A data-driven clustering analysis (kamila algorithm) was used in 48,114 patients aged ≥ 18 years with incident stroke, from 1-Jan-1998 to 31-Dec-2017 and no prior history of serious vascular events. Cox proportional hazards regression was used to estimate hazard ratios (HRs) for subsequent adverse outcomes, for each of the generated clusters. Adverse outcomes included coronary heart disease (CHD), recurrent stroke, peripheral vascular disease (PVD), heart failure, CVD-related and all-cause mortality. Four distinct phenotypes with varying underlying clinical characteristics were identified in patients with incident stroke. Compared with cluster 1 (n = 5,201, 10.8%), the risk of composite recurrent stroke and CVD-related mortality was higher in the other 3 clusters (cluster 2 [n = 18,655, 38.8%]: hazard ratio [HR], 1.07; 95% CI, 1.02-1.12; cluster 3 [n = 10,244, 21.3%]: HR, 1.20; 95% CI, 1.14-1.26; and cluster 4 [n = 14,014, 29.1%]: HR, 1.44; 95% CI: 1.37-1.50). Similar trends in risk were observed for composite recurrent stroke and all-cause mortality outcome, and subsequent recurrent stroke outcome. However, results were not consistent for subsequent risk in CHD, PVD, heart failure, CVD-related mortality, and all-cause mortality. In this proof of principle study, we demonstrated how a heterogenous population of patients with incident stroke can be stratified into four relatively homogenous phenotypes with differential risk of recurrent and major cardiovascular outcomes. This offers an opportunity to revisit the stratification of care for patients with incident stroke to improve patient outcomes.

Ciliary dyskinesia in severe asthma is not affected by chronic mucus hypersecretion

Chronic mucus hypersecretion (CMH) is linked to increased asthma severity. Ciliary dyskinesia is present in severe asthma but CMH was not associated with a worse ciliary dysfunction, suggesting another mechanism to explain chronic cough and phlegm. https://bit.ly/3JNUgGr.

Longitudinal Asthma Phenotypes from Childhood to Middle-Age: A Population-based Cohort Study

Rationale: Asthma is a heterogeneous condition, and longitudinal phenotyping may provide new insights into the origins and outcomes of the disease. Objectives: We aimed to characterize the longitudinal phenotypes of asthma between the first and sixth decades of life in a population-based cohort study. Methods: Respiratory questionnaires were collected at seven time points in the TAHS (Tasmanian Longitudinal Health Study) when participants were aged 7, 13, 18, 32, 43, 50, and 53 years. Current-asthma and ever-asthma status was determined at each time point, and group-based trajectory modeling was used to characterize distinct longitudinal phenotypes. Linear and logistic regression models were fitted to investigate associations of the longitudinal phenotypes with childhood factors and adult outcomes. Measurements and Main Results: Of 8,583 original participants, 1,506 had reported ever asthma. Five longitudinal asthma phenotypes were identified: early-onset adolescent-remitting (40%), early-onset adult-remitting (11%), early-onset persistent (9%), late-onset remitting (13%), and late-onset persistent (27%). All phenotypes were associated with chronic obstructive pulmonary disease at age 53 years, except for late-onset remitting asthma (odds ratios: early-onset adolescent-remitting, 2.00 [95% confidence interval (CI), 1.13-3.56]; early-onset adult-remitting, 3.61 [95% CI, 1.30-10.02]; early-onset persistent, 8.73 [95% CI, 4.10-18.55]; and late-onset persistent, 6.69 [95% CI, 3.81-11.73]). Late-onset persistent asthma was associated with the greatest comorbidity at age 53 years, with increased risk of mental health disorders and cardiovascular risk factors. Conclusions: Five longitudinal asthma phenotypes were identified between the first and sixth decades of life, including two novel remitting phenotypes. We found differential effects of these phenotypes on risk of chronic obstructive pulmonary disease and nonrespiratory comorbidities in middle age.

Mechanisms underlying corticosteroid resistance in patients with asthma: a review of current knowledge

INTRODUCTION

Corticosteroids are the most cost-effective anti-inflammatory drugs available for the treatment of asthma. Despite their effectiveness, several asthmatic patients have corticosteroid resistance or insensitivity and exhibit a poor response. Corticosteroid insensitivity implies a poor prognosis due to challenges in finding alternative therapeutic options for asthma.

AREAS COVERED

In this review, we describe asthma phenotypes and endotypes, as well as their differential responsiveness to corticosteroids. In addition, we describe the mechanism of action of corticosteroids underlying their regulation of the expression of glucocorticoid receptors (GRs) and their anti-inflammatory effects. Furthermore, we summarize the mechanistic evidence underlying corticosteroid-insensitive asthma, which is mainly related to changes in GR gene expression, structure, and post-transcriptional modifications. Finally, various pharmacological strategies designed to reverse corticosteroid insensitivity are discussed.

EXPERT OPINION

Corticosteroid insensitivity is influenced by the asthma phenotype, endotype, and severity, and serves as an indication for biological therapy. The molecular mechanisms underlying corticosteroid-insensitive asthma have been used to develop targeted therapeutic strategies. However, the lack of clinical trials prevents the clinical application of these treatments.

Development of a new HISCL automated CXCL9 immunoassay

C-X-C motif chemokine ligand 9 (CXCL9), a candidate biomarker, reflects type 1 (T1) inflammation pathology. Here, we report the analytical performance and clinical characteristics of a new CXCL9 reagent for a fully automated immunoassay device. We evaluated the limits of blank, detection, and quantitation (LoQ) along with other efficacy parameters, and the ability of the assay to report patient health, COVID-19 status, and the presence of asthma and/or interstitial lung diseases (ILDs). The coefficient of variation for 5-day total precision using two instruments was 7% across two controls, serum, and plasma panels. LoQ of 2.2 pg/mL suggested the efficacy of the assay in detecting T1 inflammation in plasma or serum; no cross-reactivity or interference was observed. We identified high serum CXCL9 levels in samples from patients with acute COVID-19 infections (n = 57), chronic bird-related hypersensitivity pneumonitis (n = 61), asthma (n = 194), and ILDs (n = 84) compared to healthy individuals (< 39.0 pg/mL). Furthermore, CXCL9 levels increased with age in asthma patients, and an opposite trend was observed for T2 inflammatory factors. These results suggest the utility of the automated CXCL9 immunoassay for measuring CXCL9 in clinical samples and reflect its role in T1 inflammation.

Subtypes of Adult-Onset Asthma at the Time of Diagnosis: A Latent Class Analysis

INTRODUCTION

Only a few previous studies have investigated the subtypes of adult-onset asthma. No previous study has assessed whether these subtypes are different between men and women, or whether these subtypes have different risk factors.

METHODS

We applied latent class analyses to the Finnish Environment and Asthma Study population, including 520 new cases of adult-onset asthma. We formed subtypes separately between women and men and analyzed the following determinants as potential predictors for these subtypes: age, body mass index, smoking, and parental asthma.

RESULTS

Among women, the subtypes identified were: 1. Moderate asthma, 2. Cough-variant asthma, 3. Eosinophilic asthma, 4. Allergic asthma, and 5. Difficult asthma. Among men, the subtypes were: 1. Mild asthma, 2. Moderate asthma, 3. Allergic asthma, and 4. Difficult asthma. Three of the subtypes were similar among women and men: Moderate, Allergic, and Difficult asthma. In addition, women had two distinct subtypes: Cough-variant asthma, and Eosinophilic asthma. These subtypes had different risk factor profiles, e.g., heredity was important for Eosinophilic and Allergic asthma (RR for Both parents having asthma in Eosinophilic 3.55 (1.09 to 11.62)). Furthermore, smoking increased the risk of Moderate asthma among women (RR for former smoking 2.21 (1.19 to 4.11)) and Difficult asthma among men but had little influence on Allergic or Cough-variant asthma. Conclusion: This is an original investigation of the subtypes of adult-onset asthma identified at the time of diagnosis. These subtypes differ between women and men, and these subtypes have different risk factor profiles. These findings have both clinical and public health importance for the etiology, prognosis, and treatment of adult-onset asthma.

Clinical Phenotypes of Immediate First-Dose Reactions to mRNA COVID-19: A Multicenter Latent Class Analysis

BACKGROUND

Although immediate potentially allergic reactions have been reported after dose 1 of mRNA coronavirus disease 2019 (COVID-19) vaccines, comprehensively defined subtypes have not been clearly distinguished.

OBJECTIVE

To define distinct clinical phenotypes of immediate reactions after dose 1 of mRNA COVID-19 vaccination, and to assess the relation of clinical phenotype to mRNA COVID-19 vaccine second dose tolerance.

METHODS

This retrospective study included patients with 1 or more potentially allergic symptoms or signs within 4 hours of receiving dose 1 of an mRNA COVID-19 vaccine and assessed by allergy/immunology specialists from 5 U.S. academic medical centers (January-June 2021). We used latent class analysis-an unbiased, machine-learning modeling method-to define novel clinical phenotypes. We assessed demographic, clinical, and reaction characteristics associated with phenotype membership. Using log-binomial regression, we assessed the relation between phenotype membership and second dose tolerance, defined as either no symptoms or mild, self-limited symptoms resolving with antihistamines alone. A sensitivity analysis considered second dose tolerance as objective signs only.

RESULTS

We identified 265 patients with dose-1 immediate reactions with 3 phenotype clusters: (1) Limited or Predominantly Cutaneous, (2) Sensory, and (3) Systemic. A total of 223 patients (84%) received a second dose and 200 (90%) tolerated their second dose. Sensory cluster (all patients had the symptom of numbness or tingling) was associated with a higher likelihood of second dose intolerance, but this finding did not persist when accounting for objective signs.

CONCLUSIONS

Three novel clinical phenotypes of immediate-onset reactions after dose 1 of mRNA COVID-19 vaccines were identified using latent class analysis: (1) Limited or Predominantly Cutaneous, (2) Sensory, and (3) Systemic. Whereas these clinical phenotypes may indicate differential mechanistic etiologies or associations with subsequent dose tolerance, most individuals proceeding to their second dose tolerated it.

Classifications of moderate to severe asthma phenotypes in Japan and analysis of serum biomarkers: A Nationwide Cohort Study in Japan (NHOM Asthma Study)

BACKGROUND

Asthma is a heterogeneous disease, and phenotyping can facilitate understanding of disease pathogenesis and direct appropriate asthma treatment. This nationwide cohort study aimed to phenotype asthma patients in Japan and identify potential biomarkers to classify the phenotypes.

METHODS

Adult asthma patients (n = 1925) from 27 national hospitals in Japan were enrolled and divided into Global Initiative for Asthma (GINA) steps 4 or 5 (GINA 4, 5) and GINA Steps 1, 2, or 3 (GINA 1-3) for therapy. Clinical data and questionnaires were collected. Biomarker levels among GINA 4, 5 patients were measured. Ward's minimum variance hierarchical clustering method and tree analysis were performed for phenotyping. Analysis of variance, the Kruskal-Wallis, and chi-square tests were used to compare cluster differences.

RESULTS

The following five clusters were identified: 1) late-onset, old, less-atopic; 2) late-onset, old, eosinophilic, low FEV₁; 3) early-onset, long-duration, atopic, poorly controlled; 4) early-onset, young, female-dominant, atopic; and 5) female-dominant, T1/T2-mixed, most severe. Age of onset, disease duration, blood eosinophils and neutrophils, asthma control questionnaire Sum 6, number of controllers, FEV₁, body mass index (BMI), and hypertension were the phenotype-classifying variables determined by tree analysis that assigned 79.5% to the appropriate cluster. Among the cytokines measured, IL-1RA, YKL40/CHI3L1, IP-10/CXCL10, RANTES/CCL5, and TIMP-1 were useful biomarkers for classifying GINA 4, 5 phenotypes.

CONCLUSIONS

Five distinct phenotypes were identified for moderate to severe asthma and may be classified using clinical and molecular variables (Registered in UMIN-CTR; UMIN000027776.).

Exposome Profiles and Asthma among French Adults

Rationale: Although previous studies in environmental epidemiology focused on single or a few exposures, a holistic approach combining multiple preventable risk factors is needed to tackle the etiology of multifactorial diseases such as asthma. Objectives: To investigate the association between combined socioeconomic, external environment, early-life environment, and lifestyle-anthropometric factors and asthma phenotypes. Methods: A total of 20,833 adults from the French NutriNet-Santé cohort were included (mean age, 56.2 yr; SD, 13.2; 72% women). The validated asthma symptom score (continuous) and asthma control (never asthma, controlled asthma, and uncontrolled asthma) were considered. The exposome (n = 87 factors) covered four domains: socioeconomic, external environment, early-life environment, and lifestyle-anthropometric. Cluster-based analyses were performed within each exposome domain, and the identified profiles were studied in association to asthma outcomes in negative binomial (asthma symptom score) or multinomial logistic (asthma control) regression models. Measurements and Main Results: In total, 5,546 (27%) individuals had an asthma symptom score ⩾1, and 1,206 (6%) and 194 (1%) had controlled and uncontrolled asthma, respectively. Three early-life exposure profiles ("high passive smoking-own dogs," "poor birth parameters-daycare attendance-city center," or "⩾2 siblings-breastfed" compared with "farm-pet owner-molds-low passive smoking") and one lifestyle-anthropometric profile ("unhealthy diet-high smoking-overweight" compared with "healthy diet-nonsmoker-thin") were associated with more asthma symptoms and uncontrolled asthma. Conclusions: This large-scale exposome-based study revealed early-life and lifestyle exposure profiles that were at risk for asthma in adults. Our findings support the importance of multiinterventional programs for the primary and secondary prevention of asthma, including control of specific early-life risk factors and promotion of a healthy lifestyle in adulthood.

Determinants of Severe Asthma - A Long-Term Cohort Study in Northern Sweden

Background

Risk factors for severe asthma are not well described. The aim was to identify clinical characteristics and risk factors at study entry that are associated with severe asthma at follow-up in a long-term prospective population-based cohort study of adults with asthma.

Methods

Between 1986 and 2001, 2055 adults with asthma were identified by clinical examinations of population-based samples in northern Sweden. During 2012-2014, n = 1006 (71% of invited) were still alive, residing in the study area and participated in a follow-up, of which 40 were identified as having severe asthma according to ERS/ATS, 131 according to GINA, while 875 had other asthma. The mean follow-up time was 18.7 years.

Results

Obesity at study entry and adult-onset asthma were associated with severe asthma at follow-up. While severe asthma was more common in those with adult-onset asthma in both men and women, the association with obesity was observed in women only. Sensitization to mites and moulds, but not to other allergens, as well as NSAID-related respiratory symptoms was more common in severe asthma than in other asthma. Participants with severe asthma at follow-up had lower FEV₁, more pronounced FEV₁ reversibility, and more wheeze, dyspnea and nighttime awakenings already at study entry than those with other asthma.

Conclusion

Adult-onset asthma is an important risk factor for development of severe asthma in adults, and obesity increased the risk among women. The high burden of respiratory symptoms already at study entry also indicate long-term associations with development of severe asthma.

The new era of add-on asthma treatments: where do we stand?

Globally, a small proportion (5–12%) of asthma patients are estimated to have severe disease. However, severe asthma accounts for disproportionately high healthcare resource utilization. The Global Initiative for Asthma (GINA) management committee recommends treating patients with asthma with inhaled corticosteroids plus long-acting β₂-agonists and, when needed, adding a long-acting muscarinic receptor antagonist or biologic agent. Five biologics, targeting different effectors in the type 2 inflammatory pathway, are approved for asthma treatment. However, biologics have not been compared against each other or add-on inhaled therapies in head-to-head clinical trials. As a result, their positioning versus that of current and anticipated small-molecule strategies is largely unknown. Furthermore, with the emergence of biomarkers for predicting response to biologics, a more personalized treatment approach—currently lacking with inhaled therapies—may be possible. To gain perspective, we reviewed recent advances in asthma pathophysiology, phenotypes, and biomarkers; the place of biologics in the management and personalized treatment of severe asthma; and the future of biologics and small-molecule drugs. We propose an algorithm for the stepwise treatment of severe asthma based on recommendations in the GINA strategy document that accounts for the broad range of phenotypes targeted by inhaled therapies and the specificity of biologics. In the future, both biologics and small molecules will continue to play key roles in the individualized treatment of severe asthma. However, as targeted therapies, their application will continue to be focused on patients with certain phenotypes who meet the specific criteria for use as identified in pivotal clinical trials.

Trajectories of asthma and allergy symptoms from childhood to adulthood

BACKGROUND

Phenotypes of asthma and allergic diseases are mainly studied separately for children and adults. To explore the role of adolescence and young adulthood, we investigated symptom trajectories at the transition from childhood into adulthood.

METHODS

Latent class analysis (LCA) was conducted in a population initially recruited for the German arm of Phase II of the International Study of Asthma and Allergies in Childhood and followed-up three times until their early 30s (N=2267). Indicators included in LCA were 12-month prevalences of symptoms of wheeze, rhinoconjunctivitis, and eczema. Latent classes were further characterised regarding important traits such as skin prick tests. Logistic regression models were used to investigate associations with environmental determinants such as smoking and occupational exposures.

RESULTS

Six latent classes were identified: an asymptomatic one as well as three with single and two with co-occurring symptoms. All trajectories essentially established between baseline assessment at around 10 years and the first follow-up at around 17 years. Probabilities for symptoms increased from childhood to adolescence, especially for wheeze-related latent classes, while they remained constant in adulthood. Wheeze-related latent classes were also positively associated with exposures during adolescence (e.g. active smoking).

CONCLUSION

Distinct trajectories of asthma and allergy symptoms establish from childhood through adolescence and stabilize during early adulthood. This pattern was most notable in wheeze-related latent classes which also showed the strongest positive associations with environmental exposures in adolescence/young adulthood. Therefore, not only childhood but also adolescence is relevant for disease development and offers considerable potential for prevention and health promotion.

Asthma phenotype: Clinical, physiological, and biochemical profiles of North Indian patients

Background and Objectives:

Asthma is a common, chronic and heterogeneous disease with various phenotypes. The clinical phenotypes has aided in revealing the genetic heterogeneity, provide education, life style advice and novel biological treatments. The few common factors associated with phenotypes are smoking, rhinitis and obesity. The present study was thus planned to analyse and correlate the clinical, physiological, biochemical and serological parameters of asthma and to study the phenotypic characteristics in different asthmatic.

Methods:

This was a prospective observational study of 120 patients with 30 each in BA-rhinitis, BA, BA-obesity and BA smoker phenotypes. All the enrolled patients were assessed by SGRQ, Mini-AQLQ, GINA with ACE, chest X ray, Spirometry, SPT against common aero-allergens, FENO, hsCRP, vitamin-D, IgE, and Interleukins (IL) including IL-5, IL-6, IL-8, IL-13, IL-17 and IL-33. The mentioned profiles of each phenotype correlated and characterized among different phenotypes.

Results:

The majority of patients 78(65%) were female with mean BMI of 24.07±4.73kg/m². Majority of the patient in BA and BA-rhinitis phenotype are in mild severity and young compared to majority in BA-obesity and BA-smoker are moderate to severe severity with older. (p<0.001) The SPT and FENO level were highest among BA-rhinitis phenotype with significant difference among phenotypes. (p<0.001) Similarly the most of inflammatory markers were significantly different in various phenotypes. The FEV1 showed correlation with most of parameters with statistically significant correlation with IL-5, IL-8 and FENO.

Conclusion:

The majority of parameters were significantly different among various phenotypes. We advise to phenotypic classification of asthma whenever possible for better management and quality of life.

Regulation and Function of Interferon-Lambda (IFNλ) and Its Receptor in Asthma

Asthma is a chronic respiratory disease affecting people of all ages, especially children, worldwide. Origins of asthma are suggested to be placed in early life with heterogeneous clinical presentation, severity and pathophysiology. Exacerbations of asthma disease can be triggered by many factors, including viral respiratory tract infections. Rhinovirus (RV) induced respiratory infections are the predominant cause of the common cold and also play a crucial role in asthma development and exacerbations. Rhinovirus mainly replicates in epithelial cells lining the upper and lower respiratory tract. Type III interferons, also known as interferon-lambda (IFNλ), are potent immune mediators of resolution of infectious diseases but they are known to be involved in autoimmune diseases as well. The protective role of type III IFNs in antiviral, antibacterial, antifungal and antiprotozoal functions is of major importance for our innate immune system. The IFNλ receptor (IFNλR) is expressed in selected types of cells like epithelial cells, thus orchestrating a specific immune response at the site of viruses and bacteria entry into the body. In asthma, IFNλ restricts the development of TH2 cells, which are induced in the airways of asthmatic patients. Several studies described type III IFNs as the predominant type of interferon increased after infection caused by respiratory viruses. It efficiently reduces viral replication, viral spread into the lungs and viral transmission from infected to naive individuals. Several reports showed that bronchial epithelial cells from asthmatic subjects have a deficient response of type III interferon after RV infection ex vivo. Toll like Receptors (TLRs) recognize pathogen-associated molecular patterns (PAMPs) expressed on infectious agents, and induce the development of antiviral and antibacterial immunity. We recently discovered that activation of TLR7/8 resulted in enhanced IFNλ receptor mRNA expression in PBMCs of healthy and asthmatic children, opening new therapeutic frontiers for rhinovirus-induced asthma. This article reviews the recent advances of the literature on the regulated expression of type III Interferons and their receptor in association with rhinovirus infection in asthmatic subjects.

Characterizing Inflammatory Cell Asthma Associated Phenotypes in Dental Health Workers Using Cytokine Profiling

Cytokines elicit a pro-inflammatory response by modifying the airway microenvironment in patients with acute or chronic asthma. The expression pattern of several distinct cytokines could be a useful discriminator in asthma. This study aimed to identify asthma subject groupings based on common inflammatory patterns and to determine the relationship between these identified patterns and asthma-associated clinical indices. A sub-group of 76 dental healthcare workers (HCWs) identified from a larger cross-sectional study of 454 dental HCWs in five dental institutions were evaluated further. A self-administered questionnaire elicited the health and employment history of subjects. Sera were analyzed for atopic status, latex sensitization, and 12 cytokines (IL-1β, 3, 4, 5, 6, 7, 8, 10, 12p70, eotaxin, GM-CSF, TNF-α). Pre and post-bronchodilator spirometry was performed on all HCWs. Data clustering and factor analysis were used to identify inflammatory cluster patterns of cytokines. Associations between the cytokine cluster groupings and relevant asthma-associated clinical indices were determined using multivariate logistic regression. The classification of asthma subtype based on cytokine patterns demonstrated both eosinophilic and neutrophilic inflammatory responses. Four phenotypically distinct subgroups relating to the severity of inflammation (acute or chronic) of the cell types were identified. Cytokine determinants for the neutrophilic subtype included IL-1β, 6, 8, 10, 12p70, and TNF-α whereas for the eosinophilic subtype these included IL-3, 4, 5, 7, eotaxin, and GM-CSF. The multivariate models showed a significant association between work-related chest symptoms and all four inflammatory patterns. However, stronger associations were observed for the acute neutrophilic (OR = 6.00, p < 0.05) compared to acute and chronic eosinophilic responses (OR = 4.30, p < 0.05; OR = 4.93, p < 0.05), respectively. Subjects with airway obstruction were more likely to have a mixed cellular infiltrate. The odds of work-exacerbated asthma were increased in acute or chronic eosinophilia (OR = 7.75 and 8.12; p < 0.05), respectively as well as with acute neutrophilia (OR = 6) sub-type. This study demonstrated that neutrophilic inflammatory cell asthma phenotypes coexist with eosinophilic inflammatory phenotypes suggesting a possible dual pathway for asthma in dental health workers, probably due to mixed exposures to high molecular weight (e.g., latex) and low molecular weight (e.g., acrylates) agents.

Bayesian approaches to variable selection in mixture models with application to disease clustering

In biomedical research, cluster analysis is often performed to identify patient subgroups based on patients' characteristics or traits. In the model-based clustering for identifying patient subgroups, mixture models have played a fundamental role in modeling. While there is an increasing interest in using mixture modeling for identifying patient subgroups, little work has been done in selecting the predictors that are associated with the class assignment. In this study, we develop and compare two approaches to perform variable selection in the context of a mixture model to identify important predictors that are associated with the class assignment. These two approaches are the one-step approach and the stepwise approach. The former refers to an approach in which clustering and variable selection are performed simultaneously in one overall model, whereas the latter refers to an approach in which clustering and variable selection are performed in two sequential steps. We considered both shrinkage prior and spike-and-slab prior to select the importance of variables. Markov chain Monte Carlo algorithms are developed to estimate the posterior distribution of the model parameters. Practical applications and simulation studies are carried out to evaluate the clustering and variable selection performance of the proposed models.

Clustering of asthma and related comorbidities and their association with maternal health during pregnancy: evidence from an Australian birth cohort

Background

The population-based classification of asthma severity is varied and needs further classification. This study identified clusters of asthma and related comorbidities of Australian children aged 12–13 years; determined health outcome differences among clusters; and investigated the associations between maternal asthma and other health conditions during pregnancy and the children’s clustered groups.

Methods

Participants were 1777 children in the birth cohort of the Longitudinal Study of Australian Children (LSAC) who participated in the Health CheckPoint survey and the LSAC 7th Wave. A latent class analysis (LCA) was conducted to identify clusters of children afflicted with eight diseases, such as asthma (ever diagnosed or current), wheezing, eczema, sleep problem/snoring/breathing problem, general health status, having any health condition and food allergy. Multinomial logistic regression was used to investigate the association between maternal asthma or other health conditions and LCA clusters.

Results

The study identified four clusters: (i) had asthma – currently healthy (11.0%), (ii) never asthmatic & healthy (64.9%), (iii) early-onset asthmatic or allergic (10.7%), and (iv) asthmatic unhealthy (13.4%). The asthmatic unhealthy cluster was in poor health in terms of health-related quality of life, general wellbeing and lung functions compared to other clusters. Children whose mothers had asthma during pregnancy were 3.31 times (OR 3.31, 95% CI: 2.06–5.30) more likely to be in the asthmatic unhealthy cluster than children whose mothers were non-asthmatic during pregnancy.

Conclusion

Using LCA analysis, this study improved a classification strategy for children with asthma and related morbidities to identify the most vulnerable groups within a population-based sample.

Different Phenotypes in Asthma: Clinical Findings and Experimental Animal Models

Asthma is a respiratory allergic disease presenting a high prevalence worldwide, and it is responsible for several complications throughout life, including death. Fortunately, asthma is no longer recognized as a unique manifestation but as a very heterogenic manifestation. Its phenotypes and endotypes are known, respectively, as pathologic and molecular features that might not be directly associated with each other. The increasing number of studies covering this issue has brought significant insights and knowledge that are constantly expanding. In this review, we intended to summarize this new information obtained from clinical studies, which not only allowed for the creation of patient clusters by means of personalized medicine and a deeper molecular evaluation, but also created a connection with data obtained from experimental models, especially murine models. We gathered information regarding sensitization and trigger and emphasizing the most relevant phenotypes and endotypes, such as Th2-^high asthma and Th2-^low asthma, which included smoking and obesity-related asthma and mixed and paucigranulocytic asthma, not only in physiopathology and the clinic but also in how these phenotypes can be determined with relative similarity using murine models. We also further investigated how clinical studies have been treating patients using newly developed drugs focusing on specific biomarkers that are more relevant according to the patient's clinical manifestation of the disease.

Air pollution-related asthma profiles among children/adolescents: A multi-group latent class analysis

BACKGROUND

This study aimed to investigate the asthma profile among children/adolescents and the relationship of the prevalence of air pollution profiles using latent class analysis (LCA).

OBJECTIVES

In this cross-sectional study, a case rural community was selected in an industrial area, and two rural control communities were selected in unexposed areas.

METHODS

Hourly concentrations of PM₁₀, SO₂, NO_2, and total volatile organic compounds were obtained from the records of a fixed air quality monitoring station, and the concentrations of benzene, toluene, xylenes styrene were measured during six campaigns. Asthma data was collected using the International Study of Asthma and Allergies in Childhood in 7-18 years old children/adolescents. The modeling was conducted using LCA.

RESULTS

A higher amount of air pollution indices were observed in the case than both control communities. LCA divided the participants into three clusters; "healthy" (92.8%), "moderate" (2.8%), and "severe" (4.4%). A higher probability of severe asthma (6.8%) was observed in the case than control communities (2.6% and 1.8%). Additionally, after adjusting for possible confounders, the odds of asthma was lower in the control communities than the case in both moderate and sever classes (Odds Ratios in the range of 0.135-0.697).

CONCLUSIONS

This study indicates asthma profiles of children/adolescents and the higher prevalence of severe class in the area, explaining the possible effect of air pollution.

Risk factors for severe adult-onset asthma: a multi-factor approach

BACKGROUND

The aim was to identify risk factors for severe adult-onset asthma.

METHODS

We used data from a population-based sample (Adult Asthma in Finland) of 1350 patients with adult-onset asthma (age range 31-93 years) from Finnish national registers. Severe asthma was defined as self-reported severe asthma and asthma symptoms causing much harm and regular impairment and ≥ 1 oral corticosteroid course/year or regular oral corticosteroids or waking up in the night due to asthma symptoms/wheezing ≥ a few times/month. Sixteen covariates covering several domains (personal characteristics, education, lifestyle, early-life factors, asthma characteristics and multiple morbidities) were selected based on the literature and were studied in association with severe asthma using logistic regressions.

RESULTS

The study population included 100 (7.4%) individuals with severe asthma. In a univariate analysis, severe asthma was associated with male sex, age, a low education level, no professional training, ever smoking, ≥ 2 siblings, ≥ 1 chronic comorbidity and non-steroidal anti-inflammatory drug (NSAID)-exacerbated respiratory disease (NERD) (p < 0.05), and trends for association (p < 0.2) were observed for severe childhood infection, the presence of chronic rhinosinusitis with nasal polyps, and being the 1st child. The 10 variables (being a 1st child was removed due to multicollinearity) were thus entered in a multivariate regression model, and severe asthma was significantly associated with male sex (OR [95% CI] = 1.96 [1.16-3.30]), ever smoking (1.98 [1.11-3.52]), chronic comorbidities (2.68 [1.35-5.31]), NERD (3.29 [1.75-6.19]), and ≥ 2 siblings (2.51 [1.17-5.41]). There was a dose-response effect of the total sum of these five factors on severe asthma (OR [95% CI] = 2.30 [1.81-2.93] for each one-unit increase in the score).

CONCLUSIONS

Male sex, smoking, NERD, comorbidities, and ≥ 2 siblings were independent risk factors for self-reported severe asthma. The effects of these factors seem to be cumulative; each additional risk factor gradually increases the risk of severe asthma.

Mepolizumab effectiveness in patients with severe eosinophilic asthma and co-presence of bronchiectasis: A real-world retrospective pilot study

BACKGROUND

The association of bronchiectasis (BE) in patients with severe eosinophilic asthma (SEA) is quite frequent. Mepolizumab is a well-recognized treatment for SEA; we aim to evaluate its effectiveness in SEA patients with and without BE in real-life.

METHODS

We performed a single-center retrospective pilot study, including patients with SEA treated with mepolizumab for one year. Asthma control test (ACT), lung function, annual exacerbations rate, oral corticosteroid dosage, FeNO, chronic mucous secretions, blood and sputum eosinophils were recorded at baseline and after 6 and 12 months.

RESULTS

we included 32 patients (mean age: 52.3 ± 10, 59% female). 50% showed co-presence of bronchiectasis, (SEA + BE). Significant improvements were found in ACT [(13.8 ± 4.6 to 20.7 ± 4.1, p = 0.0009) and (13 ± 4.8 to 20.7 ± 4.6, p = 0.0003)], annual exacerbations rate [from 7 (4-12) to 0 (0.00-0.75) and from 8 (4-12) to 0 (0-1), p < 0.0001], and blood eosinophils count [748 cells/μL (400-1250) vs. 84 cells/μL (52.5-100), and from 691 cells/μL (405-798) vs. 60 cells/μL (41-105), p < 0.0001] in SEA and SEA + BE group respectively, already after 6 months of treatment. A reduction in daily oral corticosteroids intake at 12 months was shown [from 15 mg (0-25) to 0 mg (0-0), p = 0.003 and from 8.8 mg (0-25) to 0 mg (0-0) (p = 0.01)] in both SEA and SEA + BE, respectively. Similar results were found, comparing SEA + BE patients based on the severity of bronchiectasis.

CONCLUSIONS

Mepolizumab effectively improves asthma symptoms control, reducing annual exacerbations and corticosteroid intake in all patients with SEA, even in the subgroup with coexisting bronchiectasis, independently of their severity.

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.

Allergic Endotypes and Phenotypes of Asthma

Allergic asthma is defined as asthma associated with sensitization to aeroallergens, which leads to asthma symptoms and airway inflammation. Allergic asthma is the most common asthma phenotype. The onset of allergic asthma is most often in childhood and is usually accompanied by other comorbidities including atopic dermatitis and allergic rhinitis. It is often persistent although there is a wide variation in disease severity. It is a T_H2-driven process. Biomarkers have been identified to distinguish patients with allergic asthma, particularly serum IgE levels, tests to indicate sensitization to aeroallergens such as specific IgE or skin prick test positivity, blood and sputum eosinophil levels, fraction of exhaled nitric oxide, and periostin. Treatments for allergic asthma include environmental control measures, allergen immunotherapy, and glucocorticoids. Biologics, targeting the T_H2 pathway, have been shown to be effective in the treatment of allergic asthma.

Profile of exposures and lung function in adults with asthma: An exposome approach in the EGEA study

BACKGROUND

Environmental research on multifactorial health outcomes calls for exposome approaches able to assess the joint effect of multiple exposures.

OBJECTIVE

Our aim was to identify profiles of exposure to lifestyle/environmental factors associated with lung function in adults with asthma using a cluster-based approach.

METHODS

We used data from 599 adults of the Epidemiological study on the Genetics and Environment of Asthma, bronchial hyperresponsiveness and atopy (EGEA) (mean age 39.0 years, 52% men) who ever had asthma. Exposures to 53 lifestyle/environmental factors were assessed by questionnaires or geographic information systems-based models. A two-step approach was developed: 1) exposome dimension reduction by selecting factors showing association with forced expiratory volume in 1 s (FEV₁) (p < 0.20) in an exposome-wide association study (ExWAS), 2) clustering analysis using the supervised Bayesian Profile Regression (sBPR) to group individuals according to FEV₁ level and to their profile of exposure to a reduced set of uncorrelated exposures (each paired correlation<0.70) identified in step 1.

RESULTS

The ExWAS identified 21 factors showing suggestive association with FEV₁ (none significant when controlling for multiple tests). The sBPR conducted on 15 uncorrelated exposures identified in step 1, revealed 3 clusters composed of 30, 115 and 454 individuals with a mean ± SD FEV₁(%pred) of 79% ± 21, 90% ± 19 and 93% ± 16, respectively. Cluster 1 was composed of individuals with heavy smoking, poor diet, higher outdoor humidity and proximity to traffic, while cluster 2 and 3 included individuals with moderate/low levels of exposure to these factors.

DISCUSSION

This exposome study identified a specific profile of joint lifestyle and environmental factors, associated with a low FEV₁ in adults with asthma. None of the exposures revealed significant association when considered independently.

Long-Term Follow-Up of Cluster-Based Diisocyanate Asthma Phenotypes

BACKGROUND

Data on the outcome of occupational asthma (OA) are heterogeneous.

OBJECTIVE

To assess the impact of being part of a specific cluster at diagnosis on the long-term outcome of diisocyanate-induced OA.

METHODS

We collected data from 56 patients who had a diagnosis of OA confirmed by a positive specific inhalation challenge. Patients sensitized to toluene diisocyanate were allocated to cluster 1 or 2 based on a tree analysis, using the 3 variables relevant for cluster segregation identified in a previous study: age, body mass index, and forced expiratory volume in 1 second/forced vital capacity at diagnosis. Patients sensitized to methylene diisocyanate were allocated to cluster 3, as in previous study. We defined OA remission when a patient had met a total of 3 criteria: no asthma symptoms and no antiasthma therapy for the last year, as well as having normal lung function.

RESULTS

At follow-up, 16 patients showed OA remission. They exhibited better lung function, less bronchial hyperreactivity, as well as younger age at diagnosis. Twenty-eight patients were allocated to cluster 1, 10 to cluster 2, and 18 to cluster 3. The percentage of patients with OA remission was higher in cluster 2 (50% vs 25% in cluster 1 and 22.5% in cluster 3), although the difference was not statistically significant (P = .2789).

CONCLUSIONS

Age at diagnosis was a strong predictor of OA remission. The outcome of diisocyanate OA tended to be more favorable for patients with toluene diisocyanate OA allocated in cluster 2, but this finding needs to be validated by further data.

A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods

Classification of asthma phenotypes has a potentially relevant impact on the clinical management of the disease. Methods for statistical classification without a priori assumptions (data-driven approaches) may contribute to developing a better comprehension of trait heterogeneity in disease phenotyping. This study aimed to summarize and characterize asthma phenotypes derived by data-driven methods. We performed a systematic review using three scientific databases, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. We included studies reporting adult asthma phenotypes derived by data-driven methods using easily accessible variables in clinical practice. Two independent reviewers assessed studies. The methodological quality of included primary studies was assessed using the ROBINS-I tool. We retrieved 7446 results and included 68 studies of which 65% (n = 44) used data from specialized centers and 53% (n = 36) evaluated the consistency of phenotypes. The most frequent data-driven method was hierarchical cluster analysis (n = 19). Three major asthma-related domains of easily measurable clinical variables used for phenotyping were identified: personal (n = 49), functional (n = 48) and clinical (n = 47). The identified asthma phenotypes varied according to the sample’s characteristics, variables included in the model, and data availability. Overall, the most frequent phenotypes were related to atopy, gender, and severe disease. This review shows a large variability of asthma phenotypes derived from data-driven methods. Further research should include more population-based samples and assess longitudinal consistency of data-driven phenotypes.

The Hygiene Hypothesis and New Perspectives-Current Challenges Meeting an Old Postulate

During its 30 years history, the Hygiene Hypothesis has shown itself to be adaptable whenever it has been challenged by new scientific developments and this is a still a continuously ongoing process. In this regard, the mini review aims to discuss some selected new developments in relation to their impact on further fine-tuning and expansion of the Hygiene Hypothesis. This will include the role of recently discovered classes of innate and adaptive immune cells that challenges the old Th1/Th2 paradigm, the applicability of the Hygiene Hypothesis to newly identified allergy/asthma phenotypes with diverse underlying pathomechanistic endotypes, and the increasing knowledge derived from epigenetic studies that leads to better understanding of mechanisms involved in the translation of environmental impacts on biological systems. Further, we discuss in brief the expansion of the Hygiene Hypothesis to other disease areas like psychiatric disorders and cancer and conclude that the continuously developing Hygiene Hypothesis may provide a more generalized explanation for health burden in highly industrialized countries also relation to global changes.

Combined unsupervised-supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea

Unsupervised clustering models have been widely used for multimetric phenotyping of complex and heterogeneous diseases such as diabetes and obstructive sleep apnea (OSA) to more precisely characterize the disease beyond simplistic conventional diagnosis standards. However, the number of clusters and key phenotypic features have been subjectively selected, reducing the reliability of the phenotyping results. Here, to minimize such subjective decisions for highly confident phenotyping, we develop a multimetric phenotyping framework by combining supervised and unsupervised machine learning. This clusters 2277 OSA patients to six phenotypes based on their multidimensional polysomnography (PSG) data. Importantly, these new phenotypes show statistically different comorbidity development for OSA-related cardio-neuro-metabolic diseases, unlike the conventional single-metric apnea–hypopnea index-based phenotypes. Furthermore, the key features of highly comorbid phenotypes were identified through supervised learning rather than subjective choice. These results can also be used to automatically phenotype new patients and predict their comorbidity risks solely based on their PSG data. The phenotyping framework based on the combination of unsupervised and supervised machine learning methods can also be applied to other complex, heterogeneous diseases for phenotyping patients and identifying important features for high-risk phenotypes.

Practitioner's Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls

Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the application of latent class analysis in the fields of critical care, respiratory medicine, and beyond. In this review, we present a brief overview of the principles behind latent class analysis. Furthermore, in a stepwise manner, we outline the key processes necessary to perform latent class analysis including some of the challenges and pitfalls faced at each of these steps. The review provides a one-stop shop for investigators seeking to apply latent class analysis to their data.

Rapid and remarkable effectiveness of benralizumab for treating severe bronchial asthma with intractable eosinophilic rhinosinusitis and eosinophilic otitis media: A case report

Severe bronchial asthma is a challenging disorder to treat and can impair quality of life (QOL) under conventional therapeutic modalities. We report the case of a 52-year-old woman with severe asthma associated with eosinophilic chronic rhinosinusitis (ECRS) and eosinophilic otitis media (EOM). Although the patient was treated with a full dose of inhaled corticosteroid, leukotriene receptor antagonist (LTRA), theophylline, burst use of oral corticosteroids (OCS), her asthmatic condition aggravated, disrupting her daily life. ECRS and EOM symptoms were also getting worse despite treatment with topical application of corticosteroids to the nose and ears, LTRA, and occasional use of OCS. In addition to asthmatic symptom, the patient always suffered from intractable nasal obstruction and hearing disturbance, which contributed to the heavily impaired QOL. However, the administration of benralizumab showed rapid and remarkable improvement not only in her asthmatic conditions but also in the symptoms of ECRS and EOM within a month. These results suggest that the use of benralizumab for the treatment of severe asthma with intractable ECRS and EOM should be considered when the patient's QOL is severely deteriorated.

Endotypes identified by cluster analysis in asthmatics and non-asthmatics and their clinical characteristics at follow-up: the case-control EGEA study

Background

Identifying relevant asthma endotypes may be the first step towards improving asthma management. We aimed identifying respiratory endotypes in adults using a cluster analysis and to compare their clinical characteristics at follow-up.

Methods

The analysis was performed separately among current asthmatics (CA, n=402) and never asthmatics (NA, n=666) from the first follow-up of the French EGEA study (EGEA2). Cluster analysis jointly considered 4 demographic, 22 clinical/functional (respiratory symptoms, asthma treatments, lung function) and four blood biological (allergy-related, inflammation-related and oxidative stress-related biomarkers) characteristics at EGEA2. The clinical characteristics at follow-up (EGEA3) were compared according to the endotype identified at EGEA2.

Results

We identified five respiratory endotypes, three among CA and two among NA: CA1 (n=53) with active treated adult-onset asthma, poor lung function, chronic cough and phlegm and dyspnoea, high body mass index, and high blood neutrophil count and fluorescent oxidation products level; CA2 (n=219) with mild asthma and rhinitis; CA3 (n=130) with inactive/mild untreated allergic childhood-onset asthma, high frequency of current smokers and low frequency of attacks of breathlessness at rest, and high IgE level; NA1 (n=489) asymptomatic, and NA2 (n=177) with respiratory symptoms, high blood neutrophil and eosinophil counts. CA1 had poor asthma control and high leptin level, CA2 had hyper-responsiveness and high interleukin (IL)-1Ra, IL-5, IL-7, IL-8, IL-10, IL-13 and TNF-α levels, and NA2 had high leptin and C reactive protein levels. Ten years later, asthmatics in CA1 had worse clinical characteristics whereas those in CA3 had better respiratory outcomes than CA2; NA in NA2 had more respiratory symptoms and higher rate of incident asthma than those in NA1.

Conclusion

These results highlight the interest to jointly consider clinical and biological characteristics in cluster analyses to identify endotypes among adults with or without asthma.

Clinical entities, phenotypes, causation, and endotypes based on selected asthma publications

Patients with complex chronic disorders, such as asthma, present clinicians with important management problems. The identification of a clinical syndrome usually leads to the diagnosis of the disease entity. The next concern involves classification and a choice as to whether to use a few inclusive categories or multiple exclusive categories. Patients with asthma have multiple clinical syndromes, and these can be described as phenotypes. The use of cluster analysis allows investigators to identify phenotypes with less clinical bias. However, the identification of a particular phenotype does not necessarily provide much insight into the underlying pathogenesis. In asthma, the pathogenetic events are complex and multiple and require a classification based on endotypes. This difficulty introduces the idea of causation and models for causation. Asthma probably does not have a single universal necessary cause. However, it does have multiple sufficient component causes. Understanding these components and their interactions potentially leads to better treatment trials and more focused drug therapy. Clinicians need to identify asthmatic patients and classify them into particular phenotypes; they should also wonder about causation. Clinical investigators need to use these phenotypes to identify more homogenous groups of patients to study the underlying pathogenesis and establish endotypes. Focusing on causation can improve our understanding of disease entities, disease classification, and disease causation. This review outlines ideas relevant to causation in nearly all diseases.

Distinguishing Wheezing Phenotypes from Infancy to Adolescence. A Pooled Analysis of Five Birth Cohorts

Rationale: Pooling data from multiple cohorts and extending the time frame across childhood should minimize study-specific effects, enabling better characterization of childhood wheezing.

Objectives: To analyze wheezing patterns from early childhood to adolescence using combined data from five birth cohorts.

Methods: We used latent class analysis to derive wheeze phenotypes among 7,719 participants from five birth cohorts with complete report of wheeze at five time periods. We tested the associations of derived phenotypes with late asthma outcomes and lung function, and investigated the uncertainty in phenotype assignment.

Results: We identified five phenotypes: never/infrequent wheeze (52.1%), early onset preschool remitting (23.9%), early onset midchildhood remitting (9%), persistent (7.9%), and late-onset wheeze (7.1%). Compared with the never/infrequent wheeze, all phenotypes had higher odds of asthma and lower forced expiratory volume in 1 second and forced expiratory volume in 1 second/forced vital capacity in adolescence. The association with asthma was strongest for persistent wheeze (adjusted odds ratio, 56.54; 95% confidence interval, 43.75–73.06). We observed considerable within-class heterogeneity at the individual level, with 913 (12%) children having low membership probability (<0.60) of any phenotype. Class membership certainty was highest in persistent and never/infrequent, and lowest in late-onset wheeze (with 51% of participants having membership probabilities <0.80). Individual wheezing patterns were particularly heterogeneous in late-onset wheeze, whereas many children assigned to early onset preschool remitting class reported wheezing at later time points.

Conclusions: All wheeze phenotypes had significantly diminished lung function in school-age children, suggesting that the notion that early life episodic wheeze has a benign prognosis may not be true for a proportion of transient wheezers. We observed considerable within-phenotype heterogeneity in individual wheezing patterns.

New Perspectives on Difficult Asthma; Sex and Age of Asthma-Onset Based Phenotypes

BACKGROUND

Asthma is a diverse condition that differs with age and sex. However, it remains unclear how sex, age of asthma onset, and/or their interaction influence clinical expression of more problematic adult "difficult" asthma.

OBJECTIVES

To better understand the clinical features of difficult asthma within a real-world clinical setting using novel phenotypic classification, stratifying subjects by sex and age of asthma onset.

METHODS

Participants in a longitudinal difficult asthma clinical cohort study (Wessex AsThma CoHort of difficult asthma; WATCH), United Kingdom (n = 501), were stratified into 4 difficult asthma phenotypes based on sex and age of asthma onset (early <18 years or adult ≥18 years) and characterized in relation to clinical and pathophysiological features.

RESULTS

The cohort had more female participants (65%) but had similar proportions of participants with early- or adult-onset disease. Early-onset female disease was commonest (35%), highly atopic, with good spirometry and strong associations with some physical comorbidities but highest psychophysiologic comorbidities. Adult-onset females also had considerable psychophysiologic comorbidities and highest obesity, and were least atopic. Amongst male subjects, proportionately more had adult-onset disease. Early-onset male disease was rarest (14%) but associated with worst lung function, high smoking, atopy, and fungal sensitization. Despite shortest disease duration, adult-onset males had highest use of maintenance oral corticosteroid, poor lung function, and highest fractional exhaled nitrogen oxide in spite of highest smoking prevalence.

CONCLUSIONS

This study shows that sex, age of asthma onset, and their interactions influence different clinical manifestations of difficult asthma and identifies a greater risk for lung function loss and oral corticosteroid dependence associated with smoking in adult-onset male subjects.

Data-driven questionnaire-based cluster analysis of asthma in Swedish adults

The aim of this study was to identify asthma phenotypes through cluster analysis. Cluster analysis was performed using self-reported characteristics from a cohort of 1291 Swedish asthma patients. Disease burden was measured using the Asthma Control Test (ACT), the mini Asthma Quality of Life Questionnaire (mini-AQLQ), exacerbation frequency and asthma severity. Validation was performed in 748 individuals from the same geographical region. Three clusters; early onset predominantly female, adult onset predominantly female and adult onset predominantly male, were identified. Early onset predominantly female asthma had a higher burden of disease, the highest exacerbation frequency and use of inhaled corticosteroids. Adult onset predominantly male asthma had the highest mean score of ACT and mini-AQLQ, the lowest exacerbation frequency and higher proportion of subjects with mild asthma. These clusters, based on information from clinical questionnaire data, might be useful in primary care settings where the access to spirometry and biomarkers is limited.

Exploring the role of nerves in asthma; insights from the study of cough

Cough in asthma predicts disease severity, prognosis, and is a common and troublesome symptom. Cough is the archetypal airway neuronal reflex, yet little is understood about the underlying neuronal mechanisms. It is generally assumed that symptoms arise because of airway hyper-responsiveness and/or airway inflammation, but despite using inhaled corticosteroids and bronchodilators targeting these pathologies, a large proportion of patients have persistent coughing. This review focuses on the prevalence and impact of cough in asthma and explores data from pre-clinical and clinical studies which have explored neuronal mechanisms of cough and asthma. We present evidence to suggest patients with asthma have evidence of neuronal dysfunction, which is further heightened and exaggerated by both bronchoconstriction and airway eosinophilia. Identifying patients with excessive coughing with asthma may represent a neuro-phenotype and hence developing treatment for this symptom is important for reducing the burden of disease on patients' lives and currently represents a major unmet clinical need.

The Future of Asthma Care: Personalized Asthma Treatment

Although once considered a single disease entity, asthma is now known to be a complex inflammatory disease engaging a range of causal pathways. The most frequent forms of asthma are identified by sputum/blood eosinophilia and activation of type 2 inflammatory pathways involving interleukins-3, -4, -5, and granulocyte-macrophage colony-stimulating factor. The use of diagnostics that identify T2 engagement linked to the selective use of highly targeted biologics has opened up a new way of managing severe disease. Novel technologies, such as wearables and intelligent inhalers, enable real-time remote monitoring of asthma, creating a unique opportunity for personalized health care.

Long-term air pollution exposure is associated with increased severity of rhinitis in 2 European cohorts

BACKGROUND

Very few studies have examined the association between long-term outdoor air pollution and rhinitis severity in adults.

OBJECTIVE

We sought to assess the cross-sectional association between individual long-term exposure to air pollution and severity of rhinitis.

METHODS

Participants with rhinitis from 2 multicenter European cohorts (Epidemiological Study on the Genetics and Environment on Asthma and the European Community Respiratory Health Survey) were included. Annual exposure to NO₂, PM₁₀, PM_2.5, and PM_coarse (calculated by subtracting PM_2.5 from PM₁₀) was estimated using land-use regression models derived from the European Study of Cohorts for Air Pollution Effects project, at the participants' residential address. The score of rhinitis severity (range, 0-12), based on intensity of disturbance due to symptoms reported by questionnaire, was categorized into low (reference), mild, moderate, and high severity. Polytomous logistic regression models with a random intercept for city were used.

RESULTS

A total of 1408 adults with rhinitis (mean age, 52 years; 46% men, 81% from the European Community Respiratory Health Survey) were included. The median (1st quartile-3rd quartile) score of rhinitis severity was 4 (2-6). Higher exposure to PM₁₀ was associated with higher rhinitis severity (adjusted odds ratio [95% CI] for a 10 μg/m³ increase in PM₁₀: for mild: 1.20 [0.88-1.64], moderate: 1.53 [1.07-2.19], and high severity: 1.72 [1.23-2.41]). Similar results were found for PM_2.5. Higher exposure to NO₂ was associated with an increased severity of rhinitis, with similar adjusted odds ratios whatever the level of severity. Adjusted odds ratios were higher among participants without allergic sensitization than among those with, but interaction was found only for NO_2. CONCLUSIONS: People with rhinitis who live in areas with higher levels of pollution are more likely to report more severe nasal symptoms. Further work is required to elucidate the mechanisms of this association.

Omics for the future in asthma

Asthma is a common, complex, multifaceted disease. It comprises multiple phenotypes, which might benefit from treatment with different types of innovative targeted therapies. Refining these phenotypes and understanding their underlying biological structure would help to apply precision medicine approaches. Using different omics methods, such as (epi)genomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, allowed to view and investigate asthma from diverse angles. Technological advancement led to a large increase in the application of omics studies in the asthma field. Although the use of omics technologies has reduced the gap between bench to bedside, several design and methodological challenges still need to be tackled before omics can be applied in asthma patient care. Collaborating under a centralized harmonized work frame (such as in consortia, under consistent methodologies) could help worldwide research teams to tackle these challenges. In this review, we discuss the transition of single biomarker research to multi-omics studies. In addition, we deliberate challenges such as the lack of standardization of sampling and analytical methodologies and validation of findings, which comes in between omics and personalized patient care. The future of omics in asthma is encouraging but not completely clear with some unanswered questions, which have not been adequately addressed before. Therefore, we highlight these questions and emphasize on the importance of fulfilling them.

Age-specific incidence of allergic and non-allergic asthma

Background

Onset of allergic asthma has a strong association with childhood but only a few studies have analyzed incidence of asthma from childhood to late adulthood in relation to allergy. The purpose of the study was to assess age-specific incidence of allergic and non-allergic asthma.

Methods

Questionnaires were sent to 8000 randomly selected recipients aged 20–69 years in Finland in 2016. The response rate was 52.3% (n = 4173). The questionnaire included questions on e.g. atopic status, asthma and age at asthma diagnosis. Asthma was classified allergic if also a physician-diagnosed allergic rhinitis was reported.

Results

The prevalence of physician-diagnosed asthma and allergic rhinitis were 11.2 and 17.8%, respectively. Of the 445 responders with physician-diagnosed asthma, 52% were classified as allergic and 48% as non-allergic. Median ages at diagnosis of allergic and non-allergic asthma were 19 and 35 years, respectively. Among subjects with asthma diagnosis at ages 0–9, 10–19, 20–29, 30–39, 40–49, 50–59 and 60–69 years, 70, 62, 58, 53, 38, 19 and 33%, respectively, were allergic. For non-allergic asthma, the incidence rate was lowest in children and young adults (0.7/1000/year). It increased after middle age and was highest in older age groups (2.4/1000/year in 50–59 years old).

Conclusions

The incidence of allergic asthma is highest in early childhood and steadily decreases with advancing age, while the incidence of non-allergic asthma is low until it peaks in late adulthood. After approximately 40 years of age, most of the new cases of asthma are non-allergic.

National Health and Wellness Survey exploratory cluster analysis of males 40-70 years old focused on erectile dysfunction and associated risk factors across the USA, Italy, Brazil and China

OBJECTIVES

Prior studies of erectile dysfunction (ED) tend to narrowly focus on relationships with specific comorbidities, rather than evaluating a more comprehensive array of risk factors and assessing naturalistic patterns among them. This study identifies natural clusters of male characteristics from a general population sample per country, quantifies ED dynamics in these profiles and compares profiles across the US, Italy, Brazil and China samples.

METHODS

National Health and Wellness Survey 2015 and 2016 patient-reported data on men aged 40-70 years (USA n = 15,652; Italy n = 2,521; Brazil n = 2,822; China n = 5,553) were analysed. Hierarchical agglomerative clustering identified clusters where predictors included demographics, health characteristics/behaviours, ED risk factors and provider visits in the past 6 months. Multinomial logistic regression assessed the independent utility of variables in predicting cluster membership, compared with the healthiest control cluster per country.

RESULTS

Different natural clusters were found across countries, with four clusters for the USA, Italy and China and three clusters for Brazil. Age, income, employment, health behaviours and ED risk factors predicted different cluster membership across countries. In the USA, Italy and Brazil, younger clusters were predicted by ED, unhealthy behaviours and ED risk factors. Unique cluster profiles were identified in China, with ED and ED risk factors (aside from hypertension) not predicting cluster membership, while socio-demographics and health behaviours were strongly predictive.

CONCLUSIONS

Natural cluster profiles revealed notable ED rates among adult males of age 40-70 in four different countries. Clusters were mainly predicted by unhealthy behaviours, ED risk factors and ED, regardless of level or presence of positive health characteristics and behaviours. This analysis identified meaningful subgroups of men with heightened ED risk factors, which can help healthcare providers to better recognise specific populations with the greatest need for intervention.

Obese- and allergic-related asthma phenotypes among children across the United States

OBJECTIVES

Pediatric asthma is heterogeneous with phenotypes that reflect differing underlying inflammation and pathophysiology. Little is known about the national prevalence of certain obesity- and allergy-related asthma phenotypes or associated characteristics. We therefore assessed the national prevalence, risk factors, and caregiver-reported severity of four asthma phenotypes: not-allergic-not-obese, allergic-not-obese, obese-not-allergic, and allergic-and-obese.

METHODS

We analyzed data from the 2007-2008 National Survey of Children's Health (NSCH) of 10-17 year-olds with caregiver-reported asthma. We described sociodemographic and health risk factors of each phenotype and then applied logistic and ordinal regression models to identify associated risk factors and level of severity of the phenotypes.

RESULTS

Among 4427 children with asthma in this NSCH cohort, the association between race and phenotype was statistically significant (p < 0.0001); white children with asthma were most likely to have allergic-not-obese asthma while black and Hispanic children with asthma were most likely to have the obese-nonallergic phenotype (p < 0.001). Attention-deficit disorder/attention-deficit hyperactivity disorder was more likely to be present in allergic-not-obese children (odds ratio (OR) 1.50, confidence interval (CI) 1.14-1.98, p = 0.004). The phenotype with the highest risk for more severe compared to mild asthma was the obese-and-allergic asthma phenotype (OR 3.34, CI 2.23-5.01, p < 0.001).

CONCLUSIONS

Allergic-not-obese asthma comprised half of our studied asthma phenotypes, while obesity-related asthma (with or without allergic components) comprised one-fifth of asthma phenotypes in this cohort representative of the US population. Children with both obese and allergic asthma are most likely to have severe asthma. Future management of childhood asthma might consider more tailoring of treatment and management plans based upon different childhood asthma phenotypes.