Asthma exacerbations: predisposing factors and prediction rules

Longitudinal association of exclusive and dual use of cigarettes and cigars with asthma exacerbation among US adults: a cohort study

BACKGROUND

Cigar use among adults in the United States has remained relatively stable in the past decade and occupies a growing part of the tobacco marketplace as cigarette use has declined. While studies have established the detrimental respiratory health effects of cigarette use, the effects of cigar use need further characterization. In this study, we evaluate the prospective association between cigar use, with or without cigarettes, and asthma exacerbation.

METHODS

We used data from Waves 1-5 (2013-2019) of the Population Assessment of Tobacco and Health Study to run generalized estimating equation models examining the association between time-varying, one-wave-lagged cigarette and cigar use and self-reported asthma exacerbation among US adults (18+). We defined our exposure as non-established (reference), former, exclusive cigarette, exclusive cigar, and dual use. We defined an asthma exacerbation event as a reported asthma attack in the past 12 months necessitating oral or injected steroid medication or asthma symptoms disrupting sleep at least once a week in the past 30 days. We adjusted for age, sex, race and ethnicity, household income, health insurance, established electronic nicotine delivery systems use, cigarette pack-years, secondhand smoke exposure, obesity, and baseline asthma exacerbation.

RESULTS

Exclusive cigarette use (incidence rate ratio (IRR): 1.26, 95% confidence interval (CI): 1.03-1.54) and dual use (IRR: 1.41, 95% CI: 1.08-1.85) were associated with a higher rate of asthma exacerbation compared to non-established use, while former use (IRR: 1.01, 95% CI: 0.80-1.28) and exclusive cigar use (IRR: 0.70, 95% CI: 0.42-1.17) were not.

CONCLUSION

We found no association between exclusive cigar use and self-reported asthma exacerbation. However, exclusive cigarette use and dual cigarette and cigar use were associated with higher incidence rates of self-reported asthma exacerbation compared to non-established use. Studies should evaluate strategies to improve cigarette and cigar smoking cessation among adults with asthma who continue to smoke.

Development of a risk prediction model to predict the risk of hospitalization due to exacerbated asthma among adult asthma patients in a lower middle-income country

BACKGROUND

Asthma patients experience higher rates of hospitalizations due to exacerbations leaving a considerable clinical and economic burden on the healthcare system. The use of a simple, risk prediction tool offers a low-cost mechanism to identify these high-risk asthma patients for specialized care. The study aimed to develop and validate a risk prediction model to identify high-risk asthma patients for hospitalization due to exacerbations.

METHODS

Hospital-based, case-control study was carried out among 466 asthma patients aged ≥ 20 years recruited from four tertiary care hospitals in a district of Sri Lanka to identify risk factors for asthma-related hospitalizations. Patients (n = 116) hospitalized due to an exacerbation with respiratory rate > 30/min, pulse rate > 120 bpm, O2 saturation (on air) < 90% on admission, selected consecutively from medical wards; controls (n = 350;1:3 ratio) randomly selected from asthma/medical clinics. Data was collected via a pre-tested Interviewer-Administered Questionnaire (IAQ). Logistic Regression (LR) analyses were performed to develop the model with consensus from an expert panel. A second case-control study was carried out to assess the criterion validity of the new model recruiting 158 cases and 101 controls from the same hospitals. Data was collected using an IAQ based on the newly developed risk prediction model.

RESULTS

The developed model consisted of ten predictors with an Area Under the Curve (AUC) of 0.83 (95% CI: 0.78 to 0.88, P < 0.001), sensitivity 69.0%, specificity 86.1%, positive predictive value (PPV) 88.6%, negative predictive value (NPV) 63.9%. Positive and negative likelihood ratios were 4.9 and 0.3, respectively.

CONCLUSIONS

The newly developed model was proven valid to identify adult asthma patients who are at risk of hospitalization due to exacerbations. It is recommended as a simple, low-cost tool for identifying and prioritizing high-risk asthma patients for specialized care.

Asthma exacerbations during the pandemic: Time to rethink clinical markers

Background

Reductions in asthma exacerbations during the coronavirus disease 2019 (COVID-19) pandemic may have an impact on clinical trial enrollment and outcomes.

Objective

Our aim was to review clinical studies and reports evaluating asthma exacerbations before and during the COVID-19 pandemic.

Methods

We reviewed clinical studies conducted with biologics over the past decade that evaluated asthma exacerbations as the primary end point. We also reviewed recent clinical reports evaluating asthma exacerbations during the COVID-19 pandemic.

Results

We showed that studies requiring at least 2 exacerbations in the prior year resulted in a higher number of exacerbations on study in the placebo arm, and conversely, those studies in which exacerbations were not required for entering the study failed to meet the primary end point. This result confirmed that history of prior exacerbations is a good maker to predict future exacerbations. In addition, a review of the literature confirmed a reduction of asthma exacerbations during the COVID-19 pandemic. The data presented are descriptive; no formal statistics were used.

Conclusion

Because of the COVID-19 pandemic, historical exacerbations may no longer be the best predictor for exacerbations in a clinical trial or clinical practice. Other clinical markers associated with exacerbations, such as blood eosinophil count and fractional exhaled nitric oxide level, should be considered for enrollment in clinical studies assessing asthma exacerbations.

Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis

Background

Asthma and chronic obstructive pulmonary disease (COPD) impose a heavy burden on health care. Approximately one-fourth of patients with asthma and patients with COPD are prone to exacerbations, which can be greatly reduced by preventive care via integrated disease management that has a limited service capacity. To do this well, a predictive model for proneness to exacerbation is required, but no such model exists. It would be suboptimal to build such models using the current model building approach for asthma and COPD, which has 2 gaps due to rarely factoring in temporal features showing early health changes and general directions. First, existing models for other asthma and COPD outcomes rarely use more advanced temporal features, such as the slope of the number of days to albuterol refill, and are inaccurate. Second, existing models seldom show the reason a patient is deemed high risk and the potential interventions to reduce the risk, making already occupied clinicians expend more time on chart review and overlook suitable interventions. Regular automatic explanation methods cannot deal with temporal data and address this issue well.

Objective

To enable more patients with asthma and patients with COPD to obtain suitable and timely care to avoid exacerbations, we aim to implement comprehensible computational methods to accurately predict proneness to exacerbation and recommend customized interventions.

Methods

We will use temporal features to accurately predict proneness to exacerbation, automatically find modifiable temporal risk factors for every high-risk patient, and assess the impact of actionable warnings on clinicians’ decisions to use integrated disease management to prevent proneness to exacerbation.

Results

We have obtained most of the clinical and administrative data of patients with asthma from 3 prominent American health care systems. We are retrieving other clinical and administrative data, mostly of patients with COPD, needed for the study. We intend to complete the study in 6 years.

Conclusions

Our results will help make asthma and COPD care more proactive, effective, and efficient, improving outcomes and saving resources.

International Registered Report Identifier (IRRID)

PRR1-10.2196/27065

Developing a Model to Predict Hospital Encounters for Asthma in Asthmatic Patients: Secondary Analysis

Background

As a major chronic disease, asthma causes many emergency department (ED) visits and hospitalizations each year. Predictive modeling is a key technology to prospectively identify high-risk asthmatic patients and enroll them in care management for preventive care to reduce future hospital encounters, including inpatient stays and ED visits. However, existing models for predicting hospital encounters in asthmatic patients are inaccurate. Usually, they miss over half of the patients who will incur future hospital encounters and incorrectly classify many others who will not. This makes it difficult to match the limited resources of care management to the patients who will incur future hospital encounters, increasing health care costs and degrading patient outcomes.

Objective

The goal of this study was to develop a more accurate model for predicting hospital encounters in asthmatic patients.

Methods

Secondary analysis of 334,564 data instances from Intermountain Healthcare from 2005 to 2018 was conducted to build a machine learning classification model to predict the hospital encounters for asthma in the following year in asthmatic patients. The patient cohort included all asthmatic patients who resided in Utah or Idaho and visited Intermountain Healthcare facilities during 2005 to 2018. A total of 235 candidate features were considered for model building.

Results

The model achieved an area under the receiver operating characteristic curve of 0.859 (95% CI 0.846-0.871). When the cutoff threshold for conducting binary classification was set at the top 10.00% (1926/19,256) of asthmatic patients with the highest predicted risk, the model reached an accuracy of 90.31% (17,391/19,256; 95% CI 89.86-90.70), a sensitivity of 53.7% (436/812; 95% CI 50.12-57.18), and a specificity of 91.93% (16,955/18,444; 95% CI 91.54-92.31). To steer future research on this topic, we pinpointed several potential improvements to our model.

Conclusions

Our model improves the state of the art for predicting hospital encounters for asthma in asthmatic patients. After further refinement, the model could be integrated into a decision support tool to guide asthma care management allocation.

International Registered Report Identifier (IRRID)

RR2-10.2196/resprot.5039

Genetic Signatures of Acute Asthma Exacerbation Related With Ineffective Response to Corticosteroid

Purpose

Acute exacerbation (AE) is an important domain of asthma management and may be related with ineffective response to corticosteroid. This study aimed to find mechanisms of AE using genome-wide gene expression profiles of blood cells from asthmatics and its perturbation by in vitro dexamethasone (Dex)-treatment.

Methods

We utilized lymphoblastoid B cells from 107 childhood asthmatics and peripheral blood mononuclear cells from 29 adult asthmatics who were treated with inhaled corticosteroids. We searched for a preserved co-expression gene module significantly associated with the AE rate in both cohorts and measured expression changes of genes belong to this module after Dex-treatment.

Results

We identified a preserved module composed of 77 genes. Among them, expressions of 2 genes (EIF2AK2 and NOL11) decreased significantly after Dex-treatment in both cohorts. EIF2AK2, a key gene acting antiviral defense mechanism, showed significantly higher expressions in asthmatics with AE. The protein repair pathway was enriched significantly in 64 genes which belong to the preserved module but showed no expression differences after Dex-treatment in both cohorts. Among them, MSRA and MSRB2 may play key roles by controlling oxidative stress.

Conclusions

Many genes belong to the AE rate-associated and preserved module identified in blood cells from childhood and adults asthmatics showed no expression changes after in vitro Dex-treatment. These findings suggest that we may need alternative treatment options to corticosteroids to prevent AE. EIF2AK2, MSRA and MSRB2 expressions on blood cells may help us select AE-susceptible asthmatics and adjust treatments to prevent AE.

Susceptibility to exacerbations in Black adults with asthma

OBJECTIVE

Exacerbations account for much of the morbidity in asthma. In a large intervention study, we sought to test the hypothesis that a Black adult exacerbation-prone phenotype - a group of Black people with asthma who are at high risk of repeat exacerbation within one year - exists in asthma independent of clinical control.

METHODS

We analyzed exacerbation risk factors in 536 self-identified Black Americans with asthma eligible for, or on, Step 3 National Asthma Education and Prevention Program (NAEPP) therapy who participated in a randomized 6-18 month trial of tiotropium versus long acting beta agonist as add-on therapy to inhaled corticosteroids. Exacerbations were defined as events treated by oral or systemic corticosteroids. Clinical control was assessed by a validated asthma control questionnaire (ACQ5).

RESULTS

Exacerbations became more likely with loss of clinical control. The mean baseline ACQs for exacerbators and non-exacerbators were 2.41 and 1.91, respectively (p < 0.001). The strongest independent factor associated with exacerbations across all ACQ levels was an exacerbation in the preceding year (adjusted OR 3.26; p < 0.001). The severity of prior exacerbations did not correlate with the likelihood of a future exacerbation. Lower baseline FEV1/FVC was also associated with increased risk of exacerbations.

CONCLUSIONS

Even though exacerbations increase with loss of clinical control, an exacerbation susceptibility phenotype exists in Black adults with asthma, independent of clinical control. This phenotype requires precision therapeutic targeting.

Development and Validation of Personalized Prediction to Estimate Future Risk of Severe Exacerbations and Uncontrolled Asthma in Patients with Asthma, Using Clinical Parameters and Early Treatment Response

BACKGROUND

Current level of asthma control can be easily assessed by validated instruments, but it is currently difficult to assess individuals' level of future risk.

OBJECTIVE

Develop, and validate, a risk prediction score for level of future risk, including patient characteristics and information on early treatment response.

METHODS

We used data of 304 adult patients with asthma from a 12-month primary care randomized controlled trial with 3-monthly assessments. With logistic regression we modeled the association between the level of future risk and patient characteristics including early treatment response. Future risk was defined as Asthma Control Questionnaire (ACQ) score of 1.5 or more at 12 months or the experience of at least 1 exacerbation during the final 6 months. We developed a risk prediction score on the basis of regression coefficients.

RESULTS

Performance of the risk prediction score improved, taking into account data on early treatment response (area under receiver-operating curve [AUROC] = 0.84) compared with a model containing only baseline characteristics (AUROC = 0.78). The score includes 6 easy-to-obtain predictors: sex, ACQ score and exacerbations in the previous year at baseline and at first follow-up, and smoking status and exacerbations in the previous 3 months (indicating early treatment response). External validation yielded an AUROC of 0.77. The risk prediction score classified patients into 3 risk groups: low (absolute risk, 11.7%), intermediate (47.0%), and high (72.7%).

CONCLUSIONS

We developed and externally validated a risk prediction score, quantifying both level of current asthma control and the guideline-defined future risk. Patients' individual risk can now be estimated in an easy way, as proposed but not specified, by asthma management guidelines.

Exacerbations in Adults with Asthma: A Systematic Review and External Validation of Prediction Models

BACKGROUND

Several prediction models assessing future risk of exacerbations in adult patients with asthma have been published. Applicability of these models is uncertain because their predictive performance has often not been assessed beyond the population in which they were derived.

OBJECTIVE

This study aimed to identify and critically appraise prediction models for asthma exacerbations and validate them in 2 clinically distinct populations.

METHODS

PubMed and EMBASE were searched to April 2017 for reports describing adult asthma populations in which multivariable models were constructed to predict exacerbations during any time frame. After critical appraisal, the models' predictive performances were assessed in a primary and a secondary care population for author-defined exacerbations and for American Thoracic Society/European Respiratory Society-defined severe exacerbations.

RESULTS

We found 12 reports from which 24 prediction models were evaluated. Three predictors (previous health care utilization, symptoms, and spirometry values) were retained in most models. Assessment was hampered by suboptimal methodology and reporting, and by differences in exacerbation outcomes. Discrimination (area under the receiver-operating characteristic curve [c-statistic]) of models for author-defined exacerbations was better in the primary care population (mean, 0.71) than in the secondary care population (mean, 0.60) and similar (0.65 and 0.62, respectively) for American Thoracic Society/European Respiratory Society-defined severe exacerbations. Model calibration was generally poor, but consistent between the 2 populations.

CONCLUSIONS

The preservation of 3 predictors in models derived from variable populations and the fairly consistent predictive properties of most models in 2 distinct validation populations suggest the feasibility of a generalizable model predicting severe exacerbations. Nevertheless, improvement of the models is warranted because predictive performances are below the desired level.

Respiratory Viruses and Asthma

Asthma remains the most prevalent chronic respiratory disorder, affecting people of all ages. The relationship between respiratory virus infection and asthma has long been recognized, though remains incompletely understood. In this article, we will address key issues around this relationship. These will include the crucial role virus infection plays in early life, as a potential risk factor for the development of asthma and lung disease. We will assess the impact that virus infection has on those with established asthma as a trigger for acute disease and how this may influence asthma throughout life. Finally, we will explore the complex interaction that occurs between the airway and the immune responses that make those with asthma so susceptible to the effects of virus infection.

Impact of periodontal treatment on hospitalization for adverse respiratory events in asthmatic adults: A propensity-matched cohort study

BACKGROUND

Periodontal disease is prevalent in asthmatics, but it is unclear whether periodontal treatment plays a role in adverse respiratory events in these patients. We evaluated risk of hospitalization for adverse respiratory events (acute exacerbation, pneumonia, and acute respiratory failure) and mortality in asthmatic adults with and without periodontal treatment.

METHODS

We used National Health Insurance (NHI) claims data of Taiwan to identify 4771 asthmatic adults with periodontal disease who underwent periodontal treatment during 2000-2006. The control group consisted of asthmatic adults without periodontal disease at a 1:1 ratio matched by the propensity score. Both groups were followed up for 5years to estimate the risk of hospitalization for adverse respiratory events and mortality.

RESULTS

Compared with controls, the periodontal treatment group had lower overall incidence of hospitalization for adverse respiratory events [5.41 vs. 6.07 per 100 person-years, 95% confidence interval (CI)=0.78-0.92] and intensive care unit admissions (1.14 vs. 1.25 per 100 person-years, 95% CI=0.79-0.99). In addition, the all-cause mortality rate was significantly lower in the periodontal treatment group than in the control group during the follow-up period (1.86 vs. 2.79 per 100 person-years, 95% CI=0.59-0.71).

CONCLUSION

Asthmatic adults who underwent periodontal treatment were at lower risk of hospitalization for adverse respiratory events and mortality than those without periodontal disease. Asthmatic adults should adopt more precautionary oral hygiene and ensure that they undergo regular periodontal health checkups.

Genetic Signatures of Asthma Exacerbation

Asthma exacerbation (AE) usually denotes worsening of asthma symptoms that requires intense management to prevent further deterioration. AE has been reported to correlate with clinical and demographic factors, such as race, gender, and treatment compliance as well as environmental factors, such as viral infection, smoking, and air pollution. In addition, recent observations suggest that there are likely to be genetic factors specific to AE. Understanding genetic factors specific to AE is essential to develop therapy tailored for exacerbation-prone asthma. Here, we summarize the results of studies involving genetic risk factors for AE. To simplify and enhance understanding, we reviewed the studies according to the following categories: hypothesis-driven approaches, hypothesis-free approaches, gene-environment interactions, and pharmacogenetics.

Rhinovirus-induced asthma exacerbations and risk populations

PURPOSE OF REVIEW

This article discusses recent findings into the mechanisms that determine how viruses trigger asthma exacerbations.

RECENT FINDINGS

Substantial progress has been made in our understanding of the pathogenesis of virus-induced asthma exacerbations. This includes new insights into the role of bacteria, the regulation of interferon responses, and the discovery of innate immune pathways that link viral infections with allergic inflammation. Progress has also been made in elucidating the genetic risk factors for asthma exacerbations, most notably the contribution of the ORMDL3/GSDMB locus on 17q, the mechanisms underlying the farming effect, and the discovery that CDHR3 binds to rhinovirus species C.

SUMMARY

Asthma exacerbations are heterogeneous conditions that involve the complex interplay between environmental exposures and innate and adaptive immune function in genetically predisposed individuals. Recent insights into the interrelationships between these factors provide new opportunities for therapeutic intervention.

Factors Affecting Recovery Time of Pulmonary Function in Hospitalized Patients With Acute Asthma Exacerbations

Purpose

Prolonged recovery time of pulmonary function after an asthma exacerbation is a significant burden on asthmatics, and management of these patients needs to be improved. The aim of this study was to evaluate factors associated with a longer recovery time of pulmonary function among asthmatic patients hospitalized due to a severe asthma exacerbation.

Methods

We retrospectively reviewed the medical records of 89 patients who were admitted for the management of acute asthma exacerbations. The recovery time of pulmonary function was defined as the time from the date each patient initially received treatment for asthma exacerbations to the date the patient reached his or her previous best FEV1% value. We investigated the influence of various clinical and laboratory factors on the recovery time.

Results

The median recovery time of the patients was 1.7 weeks. Multiple linear regression analysis revealed that using regular inhaled corticosteroids (ICS) before an acute exacerbation of asthma and concurrent with viral infection at admission were associated with the prolonged recovery time of pulmonary function.

Conclusions

The prolonged recovery time of pulmonary function after a severe asthma exacerbation was not shown to be directly associated with poor adherence to ICS. Therefore the results indicate that an unknown subtype of asthma may be associated with the prolonged recovery of pulmonary function time after an acute exacerbation of asthma despite regular ICS use. Further prospective studies to investigate factors affecting the recovery time of pulmonary function after an asthma exacerbation are warranted.

Clinically relevant outcome measures for new therapies of asthma using pharmaceutical and biologic agents

PURPOSE OF REVIEW

To determine the benefits of new asthma drugs or therapies, they should be assessed with regard to their effects on relevant clinical outcomes.

RECENT FINDINGS

The most frequently used outcomes have been symptoms, rescue medication needs and pulmonary function tests, although others such as quality of life, exacerbations and impairment of activities have also been identified as important ones. Improvements in our understanding of basic mechanisms of asthma have led to the development of new sets of outcomes including inflammatory markers and a rapidly increasing number of biomarkers, which however require validation, and assessment of their clinical usefulness. Many studies have not only looked at induced sputum cell differentials or FENO to phenotype asthma but also as treatment efficacy markers. Periostin is considered a marker of TH2-induced airway inflammation and a predictor of response to drugs such as anti-IL13 and omalizumab, although at the individual level, such prediction remains imperfect.

SUMMARY

There is a need to develop new markers of activity of the disease, with a prognostic value with regard to the benefits of new treatments.

Asthma Is Associated With a Subsequent Risk of Peripheral Artery Disease: A Longitudinal Population-Based Study

Asthma has been associated with the atherosclerosis risk, but not clear of peripheral artery disease (PAD). We attempted to examine the risk of PAD in patients with asthma.From the insurance claims data of Taiwan, we identified 28,158 newly diagnosed asthma patients in 2000 to 2005 and 56,316 persons without asthma randomly selected into the comparison cohort, frequency matched by sex, age, and the date of diagnosis. Both cohorts were followed up until the end of 2011 to estimate the incident PAD. Adjusted hazard ratios (aHRs) of PAD were estimated using the Cox proportional hazards model after controlling for sex, age, and comorbidities.The incidence of PAD was 1.46 times higher in the asthma cohort than in the comparison cohort, with an aHR of 1.34 [95% confidence interval (CI) = 1.24-1.45]. Incidence of PAD was higher in men, the aged, and those with comorbidities in both cohorts. The aHRs of PAD remained significant for the asthma cohort in all subgroups of sex, age, and the presence of comorbidity. The aHRs of PAD were 14.1 (95% CI = 8.18-24.5) in asthma patients with multiple emergency visits and 22.3 (95% CI = 15.6-31.9) for those with multiple hospitalizations.Although smoking is a potential confounding factor, this study suggests patients with asthma have a significantly higher risk of developing PAD than the general population. The results also support the notion that poor control of asthma status is a key factor in subsequent PAD development.

CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies

BACKGROUND

Asthma exacerbations are a major cause of morbidity and medical cost.

OBJECTIVE

The objective of this study was to identify genetic predictors of exacerbations in asthmatic subjects.

METHODS

We performed a genome-wide association study meta-analysis of acute asthma exacerbation in 2 pediatric clinical trials: the Childhood Asthma Management Program (n = 581) and the Childhood Asthma Research and Education (n = 205) network. Acute asthma exacerbations were defined as treatment with a 5-day course of oral steroids. We obtained a replication cohort from Biobank of Vanderbilt University Medical Center (BioVU; n = 786), the Vanderbilt University electronic medical record-linked DNA biobank. We used CD4(+) lymphocyte genome-wide mRNA expression profiling to identify associations of top single nucleotide polymorphisms with mRNA abundance of nearby genes.

RESULTS

A locus in catenin (cadherin-associated protein), alpha 3 (CTNNA3), reached genome-wide significance (rs7915695, P = 2.19 × 10(-8); mean exacerbations, 6.05 for minor alleles vs 3.71 for homozygous major alleles). Among the 4 top single nucleotide polymorphisms replicated in BioVU, rs993312 in Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3D (SEMA3D) was significant (P = .0083) and displayed stronger association among African Americans (P = .0004 in BioVU [mean exacerbations, 3.91 vs 1.53]; P = .0089 in the Childhood Asthma Management Program [mean exacerbations, 6.0 vs 3.25]). CTNNA3 variants did not replicate in BioVU. A regulatory variant in the CTNNA3 locus was associated with CTNNA3 mRNA expression in CD4(+) cells from asthmatic patients (P = .00079). CTNNA3 appears to be active in the immune response, and SEMA3D has a plausible role in airway remodeling. We also provide a replication of a previous association of purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7), with asthma exacerbation.

CONCLUSIONS

We identified 2 loci associated with exacerbations through a genome-wide association study. CTNNA3 met genome-wide significance thresholds, and SEMA3D replicated in a clinical biobank database.

The role of macrophage IL-10/innate IFN interplay during virus-induced asthma

Activation through different signaling pathways results in two functionally different types of macrophages, the pro-inflammatory (M1) and the anti-inflammatory (M2). The polarization of macrophages toward the pro-inflammatory M1 phenotype is considered to be critical for efficient antiviral immune responses in the lung. Among the various cell types that are present in the asthmatic airways, macrophages have emerged as significant participants in disease pathogenesis, because of their activation during both the inflammatory and resolution phases, with an impact on disease progression. Polarized M1 and M2 macrophages are able to reversibly undergo functional redifferentiation into anti-inflammatory or pro-inflammatory macrophages, respectively, and therefore, macrophages mediate both processes. Recent studies have indicated a predominance of M2 macrophages in asthmatic airways. During a virus infection, it is likely that M2 macrophages would secrete higher amounts of the suppressor cytokine IL-10, and less innate IFNs. However, the interactions between IL-10 and innate IFNs during virus-induced exacerbations of asthma have not been well studied. The possible role of IL-10 as a therapy in allergic asthma has already been suggested, but the divergent roles of this suppressor molecule in the antiviral immune response raise concerns. This review attempts to shed light on macrophage IL-10-IFNs interactions and discusses the role of IL-10 in virus-induced asthma exacerbations. Whereas IL-10 is important in terminating pro-inflammatory and antiviral immune responses, the presence of this immune regulatory cytokine at the beginning of virus infection could impair the response to viruses and play a role in virus-induced asthma exacerbations.

Predicting phenotypes of asthma and eczema with machine learning

Background

There is increasing recognition that asthma and eczema are heterogeneous diseases. We investigated the predictive ability of a spectrum of machine learning methods to disambiguate clinical sub-groups of asthma, wheeze and eczema, using a large heterogeneous set of attributes in an unselected population. The aim was to identify to what extent such heterogeneous information can be combined to reveal specific clinical manifestations.

Methods

The study population comprised a cross-sectional sample of adults, and included representatives of the general population enriched by subjects with asthma. Linear and non-linear machine learning methods, from logistic regression to random forests, were fit on a large attribute set including demographic, clinical and laboratory features, genetic profiles and environmental exposures. Outcome of interest were asthma, wheeze and eczema encoded by different operational definitions. Model validation was performed via bootstrapping.

Results

The study population included 554 adults, 42% male, 38% previous or current smokers. Proportion of asthma, wheeze, and eczema diagnoses was 16.7%, 12.3%, and 21.7%, respectively. Models were fit on 223 non-genetic variables plus 215 single nucleotide polymorphisms. In general, non-linear models achieved higher sensitivity and specificity than other methods, especially for asthma and wheeze, less for eczema, with areas under receiver operating characteristic curve of 84%, 76% and 64%, respectively. Our findings confirm that allergen sensitisation and lung function characterise asthma better in combination than separately. The predictive ability of genetic markers alone is limited. For eczema, new predictors such as bio-impedance were discovered.

Conclusions

More usefully-complex modelling is the key to a better understanding of disease mechanisms and personalised healthcare: further advances are likely with the incorporation of more factors/attributes and longitudinal measures.