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

Adult patients with an exacerbation of asthma and a higher risk for pulmonary embolism: a cluster analysis

OBJECTIVE

Current literature acknowledges the complexity of exacerbation triggers in patients with asthma. We studied the clinical heterogeneity of patients with asthma exacerbation suspected of having pulmonary embolism using cluster analysis and compared the clusters regarding of the risks for pulmonary embolism.

METHODS

In a secondary analysis of a dataset from the University of Florida, USA, individuals who experienced asthma exacerbation between June 2011 and October 2018 were included. All patients had undergone pulmonary CT angiography. Overall, 18 variables consisting of demographic, clinical, comorbidity, and therapeutic characteristics were used to cluster patients. The clusters were then profiled and compared in the percentages of pulmonary embolism.

RESULTS

In total, 758 patients (226; 29.8% men) with an exacerbation of asthma were included in the analysis. The frequency of a confirmed pulmonary embolism was 145 (19.1%). Two distinct clusters were identified with a statistically significant difference in pulmonary embolism [p < 0.001, odds ratio (95%CI)=2.24 (1.55, 3.24)]. We developed a high-performance classifier to profile the low- and high-risk clusters (area under the curve = 0.923, positive likelihood ratio = 20.2). The three top important variables discriminating the two clusters were age, heart rate, and body mass index. Older age, lower heart rate, higher body mass index, black race, and positive medical history (including atrial fibrillation) were more frequent in the high-risk group. Despite the higher percentage of women in the high-risk group, the sex ratios were not significantly different between the clusters.

CONCLUSION

There are two clusters in patients with an exacerbation of asthma with different prognoses percentages of pulmonary embolism. The clusters can be well identified based on patient characteristics.

Metabotyping: a tool for identifying subgroups for tailored nutrition advice

Diet-related diseases are the leading cause of death globally and strategies to tailor effective nutrition advice are required. Personalised nutrition advice is increasingly recognised as more effective than population-level advice to improve dietary intake and health outcomes. A potential tool to deliver personalised nutrition advice is metabotyping which groups individuals into homogeneous subgroups (metabotypes) using metabolic profiles. In summary, metabotyping has been successfully employed in human nutrition research to identify subgroups of individuals with differential responses to dietary challenges and interventions and diet–disease associations. The suitability of metabotyping to identify clinically relevant subgroups is corroborated by other fields such as diabetes research where metabolic profiling has been intensely used to identify subgroups of patients that display patterns of disease progression and complications. However, there is a paucity of studies examining the efficacy of the approach to improve dietary intake and health parameters. While the application of metabotypes to tailor and deliver nutrition advice is very promising, further evidence from randomised controlled trials is necessary for further development and acceptance of the approach.

Long-term air pollution exposure, greenspace and health-related quality of life in the ECRHS study

BACKGROUND

Associations of long-term exposure to air pollution and greenspace with health-related quality of life (HRQOL) are poorly studied and few studies have accounted for asthma-rhinitis status.

OBJECTIVE

To assess the associations of air pollution and greenspace with HRQOL and whether asthma and/or rhinitis modify these associations.

METHODS

The study was based on the participants in the second (2000-2002, n = 6542) and third (2011-2013, n = 3686) waves of the European Community Respiratory Health Survey (ECRHS) including 19 centres. The mean follow-up time was 11.3 years. HRQOL was assessed by the SF-36 Physical and Mental Component Summary scores (PCS and MCS). NO₂, PM_2.5 and PM₁₀ annual concentrations were estimated at the residential address from existing land-use regression models. Greenspace around the residential address was estimated by the (i) mean of the Normalized Difference Vegetation Index (NDVI) and by the (ii) presence of green spaces within a 300 m buffer. Associations of each exposure variable with PCS and MCS were assessed by mixed linear regression models, accounting for the multicentre design and repeated data, and adjusting for potential confounders. Analyses were stratified by asthma-rhinitis status.

RESULTS

The mean (SD) age of the ECRHS-II and III participants was 43 (7.1) and 54 (7.2) years, respectively, and 48 % were men. Higher NO₂, PM_2.5 and PM₁₀ concentrations were associated with lower MCS (regression coefficients [95%CI] for one unit increase in the inter-quartile range of exposures were -0.69 [-1.23; -0.15], -1.79 [-2.88; -0.70], -1.80 [-2.98; -0.62] respectively). Higher NDVI and presence of forests were associated with higher MCS. No consistent associations were observed for PCS. Similar association patterns were observed regardless of asthma-rhinitis status.

CONCLUSION

European adults who resided at places with higher air pollution and lower greenspace were more likely to have lower mental component of HRQOL. Asthma or rhinitis status did not modify these associations.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

IMPACT

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

Longitudinal follow-up of the asthma status in a French-Canadian cohort

Asthma affects 340 million people worldwide and varies in time. Twenty years ago, in Canada, the Saguenay–Lac-Saint-Jean asthma family cohort was created to study the genetic and environmental components of asthma. This study is a follow-up of 125 participants of this cohort to explore the appearance, persistence, and progression of asthma over 10–20 years. Participants answered a clinical standardized questionnaire. Lung function was assessed (forced expiratory volume in 1 s, forced vital capacity, bronchial reversibility, and methacholine bronchoprovocation), skin allergy testing was performed, blood samples were obtained (immunoglobulin E, white blood cell counts) and phenotypes were compared between recruitment and follow-up. From the participants without asthma at recruitment, 12% developed a phenotype of adult-onset asthma with the presence of risk factors, such as atopy, high body mass index, and exposure to smoking. A decrease of PC₂₀ values in this group was observed and a decrease in the FEV₁/FVC ratio in all groups. Also, 7% of individuals with asthma at recruitment developed chronic obstructive pulmonary disease, presenting risk factors at recruitment, such as moderate-to-severe bronchial hyperresponsiveness, exposure to smoking, and asthma. This study allowed a better interpretation of the evolution of asthma. Fine phenotypic characterization is the first step for meaningful genetic and epigenetic studies.

Outcome-Oriented Deep Temporal Phenotyping of Disease Progression

Chronic diseases evolve slowly throughout a patient's lifetime creating heterogeneous progression patterns that make clinical outcomes remarkably varied across individual patients. A tool capable of identifying temporal phenotypes based on the patients different progression patterns and clinical outcomes would allow clinicians to better forecast disease progression by recognizing a group of similar past patients, and to better design treatment guidelines that are tailored to specific phenotypes. To build such a tool, we propose a deep learning approach, which we refer to as outcome-oriented deep temporal phenotyping (ODTP), to identify temporal phenotypes of disease progression considering what type of clinical outcomes will occur and when based on the longitudinal observations. More specifically, we model clinical outcomes throughout a patient's longitudinal observations via time-to-event (TTE) processes whose conditional intensity functions are estimated as non-linear functions using a recurrent neural network. Temporal phenotyping of disease progression is carried out by our novel loss function that is specifically designed to learn discrete latent representations that best characterize the underlying TTE processes. The key insight here is that learning such discrete representations groups progression patterns considering the similarity in expected clinical outcomes, and thus naturally provides outcome-oriented temporal phenotypes. We demonstrate the power of ODTP by applying it to a real-world heterogeneous cohort of 11 779 stage III breast cancer patients from the U.K. National Cancer Registration and Analysis Service. The experiments show that ODTP identifies temporal phenotypes that are strongly associated with the future clinical outcomes and achieves significant gain on the homogeneity and heterogeneity measures over existing methods. Furthermore, we are able to identify the key driving factors that lead to transitions between phenotypes which can be translated into actionable information to support better clinical decision-making.

Atopic respiratory diseases and IgE sensitization are associated with leukocyte subset concentrations in 14,440 blood donors

BACKGROUND AND AIMS

Allergic rhinitis (AR), allergic conjunctivitis (AC), and asthma are characterized by activation of the immune system. The aim of this study was to explore the long-term association between AR, AC, asthma, and specific immunoglobulin E (IgE) and blood platelet and leukocyte differential counts.

MATERIAL AND METHODS

In the Danish Blood Donor Study, 14,440 participants from Central Denmark Region had platelet and leukocyte differential counts available and completed a questionnaire regarding AR, AC, and asthma. Of these participants, 8485 were tested for IgE to inhalation allergens.

RESULTS

The prevalence of AR, AC, asthma, and IgE sensitization was 19%, 15%, 9%, and 29%, respectively. AR, AC, asthma, wheeze, and IgE sensitization was associated with increased blood eosinophil concentration even in IgE sensitized participants who did not report any allergy or asthma. The strongest associations were observed for participants with current disease. We found no differences in eosinophil concentration between months without symptoms and months with symptoms of AR and asthma.

CONCLUSION

AR, AC, asthma, wheezing, and IgE sensitization to inhalation allergens are associated with increased eosinophil concentration. This may reflect a persistent inflammation even in periods without symptomatic disease.

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.

Combinations of self-reported rhinitis, conjunctivitis, and asthma predicts IgE sensitization in more than 25,000 Danes

Background

Allergic rhinitis (AR), allergic conjunctivitis (AC), and asthma composing multiple phenotypes and improved understanding of these phenotypes and their respective risk factors are needed.

Objectives

The objective of this study was to define the prevalence of AR, AC, and asthma and their association with allergen‐specific immunoglobulin E (sIgE) sensitization in a large cohort of blood donors and identify risk factors.

Methods

From the nationwide population‐based Danish Blood Donor Study, 52,976 participants completed an electronic questionnaire including AR, AC, asthma, allergic predisposition, and childhood residence. Of these, 25,257 were additionally tested for sIgE to inhalation allergens (Phadiatop).

Results

The prevalence of sIgE sensitization, AR, AC, and asthma was 30%, 19%, 15%, and 9%, respectively. The youngest birth cohorts had the highest prevalence of sIgE sensitization and symptoms of asthma, AR, and AC, and for asthma, they apparently experienced symptoms at an earlier age. The sIgE sensitization was positively associated with male sex. The sIgE seroprevalence was higher in participants with both AR and AC (ARC) than in participants with either AR or AC. Allergic predisposition and sIgE sensitization increased the risk of the diseases, while farm upbringing was associated with reduced prevalence of ARC, however, only in sIgE sensitized participants.

Conclusion

Birth year, childhood residence, sIgE sensitization, and allergic predisposition were associated with asthma, AR, and AC prevalence. Individuals with self‐reported ARC represent a primarily sIgE‐positive phenotype, while those with either AR or AC represent more diverse phenotypes.

Machine learning in asthma research: moving toward a more integrated approach

Introduction: Big data are reshaping the future of medicine. The growing availability and increasing complexity of data have favored the adoption of modern analytical and computational methodologies in every area of medicine. Over the past decades, asthma research has been characterized by a shift in the way studies are conducted and data are analyzed. Motivated by the assumptions that 'data will speak for themselves', hypothesis-driven approaches have been replaced by data-driven hypotheses-generating methods to explore hidden patterns and underlying mechanisms. However, even with all the advancement in technologies and the new important insight that we gained to understand and characterize asthma heterogeneity, very few research findings have been translated into clinically actionable solutions.Areas covered: To investigate some of the fundamental analytical approaches adopted in the current literature and appraise their impact and usefulness in medicine, we conducted a bibliometric analysis of big data analytics in asthma research in the past 50 years.Expert opinion: No single data source or methodology can uncover the complexity of human health and disease. To fully capitalize on the potential of 'big data', we will have to embrace the collaborative science and encourage the creation of integrated cross-disciplinary teams brought together around technological advances.

Phenotype-Guided Asthma Therapy: An Alternative Approach to Guidelines

Despite recent advances in therapy, a substantial proportion of asthmatics remain not well controlled. The classical stepwise approach to pharmacological therapy in adult asthma recommends that treatment is progressively stepped up by increasing the inhaled corticosteroid (ICS) dose or by adding another controller medication- to achieve symptom control and reduce the risk of exacerbations, and stepped down after a period of control. In general, asthma guideline recommendations do not reflect that there are significant differences between ICS in terms of potency. Moreover, they do not consider efficacy and safety separately, incorrectly assuming that "low" and "high" dose categories inevitably correspond with low and high risk of systemic effects. Another point of criticism is the fact that guidelines do not take into account the inflammatory profile of the patient, although substantial groups of patients with mild and moderate asthma have little evidence of "T2-high" inflammation, and by extension are likely to show a poor response to ICS treatment. On the other hand, the latest version of the Global Initiative for Asthma (GINA) equally recommends regular ICS and ICS/formoterol as needed to prevent exacerbations in step 2 patients, without taking into consideration that the therapeutic objectives (exacerbations, symptoms) may differ between individual patients and that different goals may warrant distinct treatment strategies. In this review, we bring to the table several controversial issues concerning asthma treatment and suggest an alternative proposal that takes into consideration the potential side effects of high ICS doses, the patient's inflammatory profile and the therapeutic goals to be achieved.

Advances and recent developments in asthma in 2020

In this review, we discuss recent publications on asthma and review the studies that have reported on the different aspects of the prevalence, risk factors and prevention, mechanisms, diagnosis, and treatment of asthma. Many risk and protective factors and molecular mechanisms are involved in the development of asthma. Emerging concepts and challenges in implementing the exposome paradigm and its application in allergic diseases and asthma are reviewed, including genetic and epigenetic factors, microbial dysbiosis, and environmental exposure, particularly to indoor and outdoor substances. The most relevant experimental studies further advancing the understanding of molecular and immune mechanisms with potential new targets for the development of therapeutics are discussed. A reliable diagnosis of asthma, disease endotyping, and monitoring its severity are of great importance in the management of asthma. Correct evaluation and management of asthma comorbidity/multimorbidity, including interaction with asthma phenotypes and its value for the precision medicine approach and validation of predictive biomarkers, are further detailed. Novel approaches and strategies in asthma treatment linked to mechanisms and endotypes of asthma, particularly biologicals, are critically appraised. Finally, due to the recent pandemics and its impact on patient management, we discuss the challenges, relationships, and molecular mechanisms between asthma, allergies, SARS-CoV-2, and COVID-19.

Phenotypes and endotypes of adult asthma: Moving toward precision medicine

Asthma is a chronic inflammatory disease of the airways that is challenging to dissect into subgroups because of the heterogeneity present across the spectrum of the disease. Efforts to subclassify asthma using advanced computational methods have identified a number of different phenotypes that suggest that multiple pathobiologically driven clusters of disease exist. The main phenotypes that have been identified include (1) early-onset allergic asthma, (2) early-onset allergic moderate-to-severe remodeled asthma, (3) late-onset nonallergic eosinophilic asthma, and (4) late-onset nonallergic noneosinophilic asthma. Subgroups of these phenotypes also exist but have not been as consistently identified. Advances in our understanding of the diverse immunologic perturbations that drive airway inflammation are consistent with clinical traits associated with these phenotypes and their response to biologic therapies. This has improved the clinician's approach to characterizing asthmatic patients in the clinic. Being able to define asthma endotypes using clinical characteristics and biomarkers will move physicians toward even more personalized management of asthma and precision-based care in the future. Here we will review the most prominent phenotypes and immunologic advances that suggest these disease subtypes represent asthma endotypes.

Needs for Systems Approaches to Better Treat Individuals With Severe Asthma: Predicting Phenotypes and Responses to Treatments

Asthma is a frequent heterogeneous multifactorial chronic disease whose severe forms remain largely uncontrolled despite the availability of many drugs and educational therapy. Several phenotypes and endotypes of severe asthma have been described over the last two decades. Typical type-2-immunity-driven asthma remains the most frequent phenotype, and several targeted therapies have been developed and are now available. On the contrary, non-type-2 immunity-driven severe asthma is less understood and still requires efficient innovative therapies. A personalized approach would allow improving asthma control with the help of robust biomarkers able to predict phenotypes/endotypes, exacerbations, response to targeted treatments and, in the future, possible curative options. Some data from large multicenter cohorts have emerged in recent years, especially in transcriptomics. These data have to be integrated and reproduced longitudinally to provide a systems approach for asthma care. In this focused review, the needs for such an approach and the available data will be reviewed as well as the next steps for achieving personalized medicine in asthma.

Asthma Case Cluster during Renovation of a Water-Damaged and Toxic Building

BACKGROUND

An association between fungal exposure at work and asthma onset has been shown, but a causal relationship between them has not beTanle en established.

METHODS

The study describes an asthma cluster in workers in a building under renovation. Before renovation the work site had significant water damage, technical deficiencies, and ventilation problems. Worker protection was insufficient during renovation. In the building, toxicity was determined from dust as well as from cultured dust. Toxicity analysis was conducted in vitro using the boar spermatozoa motility assay.

RESULTS

During the 8-month renovation period, among 290 workers, 21 (7.2%) experienced new-onset asthma (9 women, 42.9%; 12 men, 57.1%; median age, 43 years (range, 30-60 years)). At the renovation site, they had been exposed to areas where remarkable toxicity was demonstrated in vitro. One year later, 13 (61.9%) of them still had moderate disease, and three (14.8%) had severe disease. Most patients had a poor response to inhaled corticosteroids.

CONCLUSIONS

This study documents a clear temporal association between occupational exposure during renovation of a water-damaged building and a cluster of 21 new occupational asthma cases. In addition, dust and cultured dust from their work spaces showed remarkable toxicity based on inhibition of boar sperm motility in vitro.