Multi-dimensional phenotyping: towards a new taxonomy for airway disease

Cluster Analysis of World Trade Center Related Lower Airway Diseases

ABSTRACT

Introduction: Cluster analysis can classify without a priori assumptions the heterogeneous chronic lower airway diseases found in former workers at the World Trade Center (WTC) disaster site. Methods: We selected the first available chest computed tomography scan with quantitative computed tomography measurements on 311 former WTC workers with complete clinical, and spirometric data from their closest surveillance visit. We performed a nonhierarchical iterative algorithm K-prototype cluster analysis, using gap measure. Results: A five-cluster solution was most satisfactory. Cluster 5 had the healthiest individuals. In cluster 4, smoking was most prevalent and intense but there was scant evidence of respiratory disease. Cluster 3 had symptomatic subjects with reduced forced vital capacity impairment (low FVC). Clusters 1 and 2 had less dyspneic subjects, but more functional and quantitative computed tomography evidence of chronic obstructive pulmonary disease (COPD) in cluster 1, or low FVC in cluster 2. Clusters 1 and 4 had the highest proportion of rapid first-second forced expiratory volume decliners. Conclusions: Cluster analysis confirms low FVC and COPD/pre-COPD as distinctive chronic lower airway disease phenotypes on long-term surveillance of the WTC workers.

Pediatric and adult asthma clinical phenotypes: a real world, big data study based on acute exacerbations

INTRODUCTION

Asthma is a heterogeneous disease with a range of observable phenotypes. To date, the characterization of asthma phenotypes is mostly limited to allergic versus non-allergic disease. Therefore, the aim of this big data study was to computationally derive asthma subtypes from the OneFlorida Clinical Research Consortium.

METHODS

We obtained data from 2012-2020 from the OneFlorida Clinical Research Consortium. Longitudinal data for patients greater than two years of age who met inclusion criteria for an asthma exacerbation based on International Classification of Diseases codes. We used matrix factorization to extract information and K-means clustering to derive subtypes. The distributions of demographics, comorbidities, and medications were compared using Chi-square statistics.

RESULTS

A total of 39,807 pediatric patients and 23,883 adult patients met inclusion criteria. We identified five distinct pediatric subtypes and four distinct adult subtypes. Pediatric subtype P1 had the highest proportion of black patients, but the lowest use of inhaled corticosteroids and allergy medications. Subtype P2 had a predominance of patients with gastroesophageal reflux disease, whereas P3 had a predominance of patients with allergic disorders. Adult subtype A2 was the most severe and all patients were on biologic agents. Most of subtype A3 patients were not taking controller medications, whereas most patients (>90%) in subtypes A2 and A4 were taking corticosteroids and allergy medications.

CONCLUSION

We found five distinct pediatric asthma subtypes and four distinct adult asthma subtypes. Future work should externally validate these subtypes and characterize response to treatment by subtype to better guide clinical treatment of asthma.

Treatable Traits in Airway Disease: From Theory to Practice

Chronic airway diseases such as asthma and chronic obstructive pulmonary disease are prevalent and complex conditions that often coexist in the same patient. To address this complexity in clinical practice, and to move forward toward personalized and precision medicine of airway diseases, a strategy based on the identification and treatment of so-called "treatable traits" (TTs) has been proposed. A TT is a recognizable phenotypic or endotypic characteristic that can be assessed and successfully targeted by therapy to improve a clinical outcome in a patient with airway disease. Importantly, TTs can coexist in the same patient, so they are not mutually exclusive. The TT strategy proposes to investigate in each individual patient with chronic airway disease the number and type of TTs present and to treat each of them according to guideline recommendations. This strategy is agnostic (ie, independent) to the traditional diagnostic labels (asthma, chronic obstructive pulmonary disease), so it can be applied to any patient with airway disease. Currently, there is firm evidence supporting the adequacy and validity of the TT strategy. Here, we review the current state of the art of this topic, first by presenting its theoretical background and then by discussing how to best implement it in clinical practice.

Clinical phenotypes of chronic cough categorised by cluster analysis

BACKGROUND

Chronic cough is a heterogeneous disease with various aetiologies that are difficult to determine. Our study aimed to categorise the phenotypes of chronic cough.

METHODS

Adult patients with chronic cough were assessed based on the characteristics and severity of their cough using the COugh Assessment Test (COAT) and the Korean version of the Leicester Cough Questionnaire. A cluster analysis was performed using the K-prototype, and the variables to be included were determined using a correlation network.

RESULTS

In total, 255 participants were included in the analysis. Based on the correlation network, age, score for each item, and total COAT score were selected for the cluster analysis. Four clusters were identified and characterised as follows: 1) elderly with mild cough, 2) middle-aged with less severe cough, 3) relatively male-predominant youth with severe cough, and 4) female-predominant elderly with severe cough. All clusters had distinct demographic and symptomatic characteristics and underlying causes.

CONCLUSIONS

Cluster analysis of age, score for each item, and total COAT score identified 4 distinct phenotypes of chronic cough with significant differences in the aetiologies. Subgrouping patients with chronic cough into homogenous phenotypes could provide a stratified medical approach for individualising diagnostic and therapeutic strategies.

Validation of Clinical COPD Phenotypes for Prognosis of Long-Term Mortality in Swedish and Dutch Cohorts

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable mortality risk. The aim of our investigation was to validate a simple clinical algorithm for long-term mortality previously proposed by Burgel et al. in 2017. Subjects with COPD from two cohorts, the Swedish PRAXIS study (n = 784, mean age (standard deviation (SD)) 64.0 years (7.5), 42% males) and the Rotterdam Study (n = 735, mean age (SD) 72 years (9.2), 57% males), were included. Five clinical clusters were derived from baseline data on age, body mass index, dyspnoea grade, pulmonary function and comorbidity (cardiovascular disease/diabetes). Cox models were used to study associations with 9-year mortality. The distribution of clinical clusters (1-5) was 29%/45%/8%/6%/12% in the PRAXIS study and 23%/26%/36%/0%/15% in the Rotterdam Study. The cumulative proportion of deaths at the 9-year follow-up was highest in clusters 1 (65%) and 4 (72%), and lowest in cluster 5 (10%) in the PRAXIS study. In the Rotterdam Study, cluster 1 (44%) had the highest cumulative mortality and cluster 5 (5%) the lowest. Compared with cluster 5, the meta-analysed age- and sex-adjusted hazard ratio (95% confidence interval) for cluster 1 was 6.37 (3.94-10.32) and those for clusters 2 and 3 were 2.61 (1.58-4.32) and 3.06 (1.82-5.13), respectively. Burgel's clinical clusters can be used to predict long-term mortality risk. Clusters 1 and 4 are associated with the poorest prognosis, cluster 5 with the best prognosis and clusters 2 and 3 with intermediate prognosis in two independent cohorts from Sweden and the Netherlands.

Computational phenotyping of obstructive airway diseases: protocol for a systematic review

BACKGROUND

Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim to perform a systematic review of studies using computational approaches to phenotype obstructive airway diseases in children and adults.

METHODS AND ANALYSIS

We will search PubMed, Embase, Scopus, Web of Science, and Google Scholar for papers published between 2010 and 2020. Conferences proceedings, reference list of included papers, and experts will form additional sources of literature. We will include observational epidemiological studies that used a computational approach to derive phenotypes of chronic airway diseases, whether in a general population or in a clinical setting. Two reviewers will independently screen the retrieved studies for eligibility, extract relevant data, and perform quality appraisal of included studies. A third reviewer will arbitrate any disagreements in these processes. Quality appraisal of the studies will be undertaken using the Effective Public Health Practice Project quality assessment tool. We will use summary tables to describe the included studies. We will narratively synthesize the generated evidence, providing critical assessment of the populations, variables, and computational approaches used in deriving the phenotypes across studies CONCLUSION: As progress continues to be made in the area of computational phenotyping of chronic obstructive airway diseases, this systematic review, the first on this topic, will provide the state of the art on the field and highlight important perspectives for future works.

ETHICS AND DISSEMINATION

No ethical approval is needed for this work is based only on the published literature and does not involve collection of any primary or human data.

REGISTRATION AND REPORTING

SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020164898.

Cluster analysis categorizes five phenotypes of pulmonary tuberculosis

Tuberculosis (TB) has a heterogeneous phenotype, which makes it challenging to diagnose. Our study aimed to identify TB phenotypes through cluster analysis and compare their initial symptomatic, microbiological and radiographic characteristics. We systemically collected data of notified TB patients notified in Korea and constructed a prospective, observational cohort database. Cluster analysis was performed using K-means clustering, and the variables to be included were determined by correlation network. A total of 4,370 subjects with pulmonary TB were enrolled in the study. Based on the correlation network, age and body mass index (BMI) were selected for the cluster analysis. Five clusters were identified and characterised as follows: (1) middle-aged overweight male dominance, (2) young-aged relatively female dominance without comorbidities, (3) middle-aged underweight male dominance, (4) overweight elderly with comorbidities and (5) underweight elderly with comorbidities. All clusters had distinct demographic and symptomatic characteristics. Initial microbiologic burdens and radiographic features also varied, including the presence of cavities and bilateral infiltration, which reflect TB-related severity. Cluster analysis of age and BMI identified five phenotypes of pulmonary TB with significant differences at initial clinical presentations. Further studies are necessary to validate our results and to assess their clinical implications.

Unravelling the mechanisms driving multimorbidity in COPD to develop holistic approaches to patient-centred care

COPD is a major cause of morbidity and mortality worldwide. Multimorbidity is common in COPD patients and a key modifiable factor, which requires timely identification and targeted holistic management strategies to improve outcomes and reduce the burden of disease.We discuss the use of integrative approaches, such as cluster analysis and network-based theory, to understand the common and novel pathobiological mechanisms underlying COPD and comorbid disease, which are likely to be key to informing new management strategies.Furthermore, we discuss the current understanding of mechanistic drivers to multimorbidity in COPD, including hypotheses such as multimorbidity as a result of shared common exposure to noxious stimuli (e.g. tobacco smoke), or as a consequence of loss of function following the development of pulmonary disease. In addition, we explore the links to pulmonary disease processes such as systemic overspill of pulmonary inflammation, immune cell priming within the inflamed COPD lung and targeted messengers such as extracellular vesicles as a result of local damage as a cause for multimorbidity in COPD.Finally, we focus on current and new management strategies which may target these underlying mechanisms, with the aim of holistic, patient-centred treatment rather than single disease management.

Allergic fungal airways disease (AFAD): an under-recognised asthma endotype

The term allergic fungal airways disease has a liberal definition based on IgE sensitisation to thermotolerant fungi and evidence of fungal-related lung damage. It arose from a body of work looking into the role of fungi in asthma. Historically fungi were considered a rare complication of asthma, exemplified by allergic bronchopulmonary aspergillosis; however, there is a significant proportion of individuals with Aspergillus fumigatus sensitisation who do not meet these criteria, who are at high risk for the development of lung damage. The fungi that play a role in asthma can be divided into two groups; those that can grow at body temperature referred to as thermotolerant, which are capable of both infection and allergy, and those that cannot but can still act as allergens in IgE sensitised individuals. Sensitisation to thermotolerant filamentous fungi (Aspergillus and Penicillium), and not non-thermotolerant fungi (Alternaria and Cladosporium) is associated with lower lung function and radiological abnormalities (bronchiectasis, tree-in-bud, fleeting shadows, collapse/consolidation and fibrosis). For antifungals to play a role in treatment, the focus should be on fungi capable of growing in the airways thereby causing a persistent chronic allergenic stimulus and releasing tissue damaging proteases and other enzymes which may disrupt the airway epithelial barrier and cause mucosal damage and airway remodelling. All patients with IgE sensitisation to thermotolerant fungi in the context of asthma and other airway disease are at risk of progressive lung damage, and as such should be monitored closely.

New Perspectives in the Diagnosis and Management of Allergic Fungal Airway Disease

Allergy to airway-colonising, thermotolerant, filamentous fungi represents a distinct eosinophilic endotype of often severe lung disease. This endotype, which particularly affects adult asthma, but also complicates other airway diseases and sometimes occurs de novo, has a heterogeneous presentation ranging from severe eosinophilic asthma to lobar collapse. Its hallmark is lung damage, characterised by fixed airflow obstruction (FAO), bronchiectasis and lung fibrosis. It has a number of monikers including severe asthma with fungal sensitisation (SAFS) and allergic bronchopulmonary aspergillosis/mycosis (ABPA/M), but these exclusive terms constitute only sub-sets of the condition. In order to capture the full extent of the syndrome we prefer the inclusive term allergic fungal airway disease (AFAD), the criteria for which are IgE sensitisation to relevant fungi in association with airway disease. The primary fungus involved is Aspergillus fumigatus, but a number of other thermotolerant species from several genera have been implicated. The unifying mechanism involves germination of inhaled fungal spores in the lung in the context of IgE sensitisation, leading to a persistent and vigorous eosinophilic inflammatory response in association with release of fungal proteases. Most allergenic fungi, including Alternaria and Cladosporium species, are not thermotolerant and cannot germinate in the airways so only act as aeroallergens and do not cause AFAD. Studies of the airway mycobiome have shown that A. fumigatus colonises the normal as much as the asthmatic airway, suggesting it is the tendency to become IgE-sensitised that is the critical triggering factor for AFAD rather than colonisation per se. Treatment is aimed at preventing exacerbations with glucocorticoids and increasingly by the use of anti-T2 biological therapies. Anti-fungal therapy has a limited place in management, but is an effective treatment for fungal bronchitis which complicates AFAD in about 10% of cases.

Physiological parameters of mental health predict the emergence of post-traumatic stress symptoms in physicians treating COVID-19 patients

Lack of established knowledge and treatment strategies, and change in work environment, may altogether critically affect the mental health and functioning of physicians treating COVID-19 patients. Thus, we examined whether treating COVID-19 patients affect the physicians' mental health differently compared with physicians treating non-COVID-19 patients. In this cohort study, an association was blindly computed between physiologically measured anxiety and attention vigilance (collected from 1 May 2014 to 31 May 31 2016) and self-reports of anxiety, mental health aspects, and sleep quality (collected from 20 April to 30 June 2020, and analyzed from 1 July to 1 September 2020), of 91 physicians treating COVID-19 or non-COVID-19 patients. As a priori hypothesized, physicians treating COVID-19 patients showed a relative elevation in both physiological measures of anxiety (95% CI: 2317.69-2453.44 versus 1982.32-2068.46; P < 0.001) and attention vigilance (95% CI: 29.85-34.97 versus 22.84-26.61; P < 0.001), compared with their colleagues treating non-COVID-19 patients. At least 3 months into the pandemic, physicians treating COVID-19 patients reported high anxiety and low quality of sleep. Machine learning showed clustering to the COVID-19 and non-COVID-19 subgroups with a high correlation mainly between physiological and self-reported anxiety, and between physiologically measured anxiety and sleep duration. To conclude, the pattern of attention vigilance, heightened anxiety, and reduced sleep quality findings point the need for mental intervention aimed at those physicians susceptible to develop post-traumatic stress symptoms, owing to the consequences of fighting at the forefront of the COVID-19 pandemic.

Asthma-COPD overlap: current understanding and the utility of experimental models

Pathological features of both asthma and COPD coexist in some patients and this is termed asthma-COPD overlap (ACO). ACO is heterogeneous and patients exhibit various combinations of asthma and COPD features, making it difficult to characterise the underlying pathogenic mechanisms. There are no controlled studies that define effective therapies for ACO, which arises from the lack of international consensus on the definition and diagnostic criteria for ACO, as well as scant in vitro and in vivo data. There remain unmet needs for experimental models of ACO that accurately recapitulate the hallmark features of ACO in patients. The development and interrogation of such models will identify underlying disease-causing mechanisms, as well as enabling the identification of novel therapeutic targets and providing a platform for assessing new ACO therapies. Here, we review the current understanding of the clinical features of ACO and highlight the approaches that are best suited for developing representative experimental models of ACO.

Understanding the pathogenesis of asthma-COPD overlap is critical for improving therapeutic approaches. We present current knowledge on asthma-COPD overlap and the requirements for developing an optimal animal model of disease.https://bit.ly/3lsjyvm

Chronic obstructive pulmonary disease phenotypes: imprint on pharmacological and non-pharmacological therapy

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease associated with significant morbidity and mortality. Over the past few years, there has been cumulating interest in describing this heterogeneity and using this information to group patients into different COPD phenotypes. The term phenotype is defined as single or combination of disease attributes that describe differences between individuals with COPD as they relate to clinically meaningful outcomes. It describes also the physical appearance or biochemical characteristics which result from the genotype-environment interaction. Furthermore, it clearly identifies subgroups with a significant impact in the prognosis. Recently, approaches to COPD phenotyping have been significantly enhanced in tandem with developments in understanding the disease’s various pathological, clinical and genetic features. This knowledge inspired the researchers to investigate more tailored therapeutic strategies that could not only give a more potent effect but also help to avoid the traditional therapy’s undesirable side effects. Eventually, it could be said that the phenotypic approach to COPD in the last decade had a huge impact on daily practice and management delivered to COPD patients. In this review, we highlight the impact of pharmacological and non-pharmacological treatment options on COPD outcomes, using a personalized treatment strategy based on different phenotypes.

COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda

Chronic Obstructive Pulmonary Disease (COPD) is a highly heterogeneous condition projected to become the third leading cause of death worldwide by 2030. To better characterize this condition, clinicians have classified patients sharing certain symptomatic characteristics, such as symptom intensity and history of exacerbations, into distinct phenotypes. In recent years, the growing use of machine learning algorithms, and cluster analysis in particular, has promised to advance this classification through the integration of additional patient characteristics, including comorbidities, biomarkers, and genomic information. This combination would allow researchers to more reliably identify new COPD phenotypes, as well as better characterize existing ones, with the aim of improving diagnosis and developing novel treatments. Here, we systematically review the last decade of research progress, which uses cluster analysis to identify COPD phenotypes. Collectively, we provide a systematized account of the extant evidence, describe the strengths and weaknesses of the main methods used, identify gaps in the literature, and suggest recommendations for future research.

Cluster Analysis: A New Approach for Identification of Underlying Risk Factors and Demographic Features of First Trimester Pregnancy Women

Thyroid pathology is reported internationally in 5-10% of all pregnancies. The overall aim of this research was to determine the prevalence of hypothyroidism and risk factors during the first trimester screening in a Mexican patients sample. We included the records of 306 patients who attended a prenatal control consultation between January 2016 and December 2017 at the Women's Institute in Monterrey, Mexico. The studied sample had homogeneous demographic characteristics in terms of age, weight, height, BMI (body mass index) and number of pregnancies. The presence of at least one of the risk factors for thyroid disease was observed in 39.2% of the sample. Two and three clusters were identified, in which patients varied considerably among risk factors, symptoms and pregnancy complications. Compared to Cluster 0, one or more symptoms or signs of hypothyroidism occurred, while Cluster 1 was characterized by healthier patients. When three clusters were used, Cluster 2 had a higher TSH (thyroid stimulating hormone) value and pregnancy complications. There were no significant differences in perinatal variables. In addition, high TSH levels in first trimester pregnancy are characterized by pregnancy complications and decreased newborn weight. Our findings underline the high degree of disease heterogeneity with existing pregnant hypothyroid patients and the need to improve the phenotyping of the syndrome in the Mexican population.

A comparison of diagnostic consistency for asthma-chronic obstructive pulmonary disease overlap and clinical characteristics study

BACKGROUND

The diagnostic criteria for asthma-chronic obstructive pulmonary disease overlap have not been unified. Different studies have used different criteria, and this has led to diagnostic inconsistencies.

METHODS

We collected data of patients who were older than 40 years and hospitalised because of chronic bronchial diseases. One hundred and seventy-one patients were included in this study. We compared seven different diagnostic criteria, examined their consistency, and analysed differences among groups classified with each set.

RESULTS

The prevalence of ACO ranged between 7.02 and 27.49% depending on the criteria applied. The patients who met the Soler-Cataluna et al. criteria also met the GesEPOC criteria. Rhee has proposed the strictest diagnostic criteria; hence, the number of patients who met these criteria was the smallest, and those patients also met the diagnostic criteria proposed by the other studies. We found that applying the different sets of criteria did not lead to the selection of the same population, while there were no statistical differences in age, disease duration, allergens, and inflammatory markers.

CONCLUSIONS

The diagnostic criteria of ACO have not been unified, which hinders the design and progress of clinical studies that would investigate the ACO phenotypes and underlying mechanisms.

Primary care risk stratification in COPD using routinely collected data: a secondary data analysis

Most clinical contacts with chronic obstructive pulmonary disease (COPD) patients take place in primary care, presenting opportunity for proactive clinical management. Electronic health records could be used to risk stratify diagnosed patients in this setting, but may be limited by poor data quality or completeness. We developed a risk stratification database algorithm using the DOSE index (Dyspnoea, Obstruction, Smoking and Exacerbation) with routinely collected primary care data, aiming to calculate up to three repeated risk scores per patient over five years, each separated by at least one year. Among 10,393 patients with diagnosed COPD, sufficient primary care data were present to calculate at least one risk score for 77.4%, and the maximum of three risk scores for 50.6%. Linked secondary care data revealed primary care under-recording of hospital exacerbations, which translated to a slight, non-significant cohort average risk score reduction, and an understated risk group allocation for less than 1% of patients. Algorithmic calculation of the DOSE index is possible using primary care data, and appears robust to the absence of linked secondary care data, if unavailable. The DOSE index appears a simple and practical means of incorporating risk stratification into the routine primary care of COPD patients, but further research is needed to evaluate its clinical utility in this setting. Although secondary analysis of routinely collected primary care data could benefit clinicians, patients and the health system, standardised data collection and improved data quality and completeness are also needed.

COPD overdiagnosis in primary care: a UK observational study of consistency of airflow obstruction

Chronic obstructive pulmonary disease (COPD) is heterogeneous, but persistent airflow obstruction (AFO) is fundamental to diagnosis. We studied AFO consistency from initial diagnosis and explored factors associated with absent or inconsistent AFO. This was a retrospective observational study using patient-anonymised routine individual data in Care and Health Information Analytics (CHIA) database. Identifying a prevalent COPD cohort based on diagnostic codes in primary care records, we used serial ratios of forced expiratory volume in 1 s to forced vital capacity (FEV1/FVC%) from time of initial COPD diagnosis to assign patients to one of three AFO categories, according to whether all (persistent), some (variable) or none (absent) were <70%. We described respiratory prescriptions over 3 years (2011-2013) and used multivariable logistic regression to estimate odds of absent or variable AFO and potential predictors. We identified 14,378 patients with diagnosed COPD (mean ± SD age 68.8 ± 10.7 years), median (IQR) COPD duration of 60 (25,103) months. FEV1/FVC% was recorded in 12,491 (86.9%) patients: median (IQR) 5 (3, 7) measurements. Six thousand five hundred and fifty (52.4%) had persistent AFO, 4507 (36.1%) variable AFO and 1434 (11.5%) absent AFO. Being female, never smoking, having higher BMI or more comorbidities significantly predicted absent and variable AFO. Despite absent AFO, 57% received long-acting bronchodilators and 60% inhaled corticosteroids (50% and 49%, respectively, in those without asthma). In all, 13.1% of patients diagnosed with COPD had unrecorded FEV1/FVC%; 11.5% had absent AFO on repeated measurements, yet many received inhalers likely to be ineffective. Such prescribing is not evidence based and the true cause of symptoms may have been missed.

Analysis of two questionnaires on quality of life of Chronic Obstructive Pulmonary Disease patients

Objective:

to evaluate the efficacy of quality of life questionnaires St. George Respiratory Questionnaire and Chronic Obstructive Pulmonary Disease Assessment Test in patients with chronic obstructive pulmonary disease based on correlation and agreement analyses, and identify the most effective tool to assess their quality of life.

Method:

cross-sectional cohort study with patients hospitalized in a Spanish hospital for exacerbation of chronic obstructive pulmonary disease. Health-related quality of life was assessed with both questionnaires. The correlation and the agreement between the questionnaires were analyzed, as well as the internal consistency. Associations were established between the clinical variables and the results of the questionnaire.

Results:

one hundred and fifty-six patients participated in the study. The scales had a correlation and agreement between them and high internal consistency. A higher sensitivity of the Chronic Obstructive Pulmonary Disease Assessment Test was observed for the presence of cough and expectoration.

Conclusion:

the questionnaires have similar reliability and validity to measure the quality of life in patients with acute chronic obstructive pulmonary disease, and the Chronic Obstructive Pulmonary Disease Assessment Test is more sensitive to detect cough and expectoration and requires a shorter time to be completed.

Intensity and temporal patterns of physical activity and cardiovascular disease risk in midlife

Physical activity (PA) and sedentary time (SED) are associated with the risk of cardiovascular disease (CVD), but the temporal patterns of these behaviors most beneficial for cardiovascular health remain unknown. We aimed to identify the intensity and temporal patterns of PA and SED measured continuously by an accelerometer and their relationship with CVD risk. At the age of 46 years, 4582 members (1916 men; 2666 women) of the Northern Finland Birth Cohort 1966 study underwent continuous measurement of PA with Polar Active (Polar Electro, Finland) accelerometers for one week. X-means clustering was applied based on 10 min average MET (metabolic equivalent) values during the measurement period. Ten-year risk of CVD was estimated using the Framingham risk model. Most of the participants had low risk for CVD. Four distinct PA clusters were identified that were well differentiable by the intensity and temporal patterns of activity (inactive, evening active, moderately active, very active). A significant difference in 10-year CVD risk across the clusters was found in men (p = 0.028) and women (p < 0.001). Higher levels of HDL cholesterol were found in more active clusters compared to less active clusters (p < 0.001) in both genders. In women total cholesterol was lower in the moderately active cluster compared to the inactive and evening active clusters (p = 0.001). Four distinct PA clusters were recognized based on accelerometer data and X-means clustering. A significant difference in CVD risk across the clusters was found in both genders. These results can be used in developing and promoting CVD prevention strategies.

COPD classification models and mortality prediction capacity

Objective

Our aim was to assess the impact of comorbidities on existing COPD prognosis scores.

Patients and methods

A total of 543 patients with COPD (FEV₁ <80% and FEV₁/FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index.

Results

Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV₁% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLD_ABCD, GOLD₂₀₁₇ and cluster analysis for predicting mortality, cluster system was found to be superior compared with GOLD₂₀₁₇ (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001).

Conclusion

Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortality.

Clinical profile of predefined asthma phenotypes in a large cohort of UK primary care patients (Clinical Practice Research Datalink)

BACKGROUND

Distinct asthma phenotypes have previously been suggested, including benign asthma, atopic asthma and obese non-eosinophilic asthma. This study aims to establish if these phenotypes can be identified using data recorded in primary care clinical records and reports on patient characteristics and exacerbation frequency.

METHODS

A population-based cohort study identified 193,999 asthma patients in UK primary care from 2007 to 2017. We used linked primary and secondary care data from the Clinical Practice Research Datalink, Hospital Episode Statistics and Office for National Statistics. Patients were classified into predefined phenotypes or included in an asthma "not otherwise specified" (NOS) group. We used negative binomial regression to calculate the exacerbation rates and adjusted rate ratios. Rate ratios were further stratified by asthma treatment step.

RESULTS

In our cohort, 3.9% of patients were categorized as benign asthma, 28.6% atopic asthma and 4.8% obese non-eosinophilic asthma. About 62.7% of patients were asthma NOS, including asthma NOS without treatment (10.4%), only on short-acting beta agonist (6.1%) and on maintenance treatment (46.2%). Crude severe exacerbation rates per 1,000 person-years were lowest for benign asthma (106.8 [95% CI: 101.2-112.3]) and highest for obese non-eosinophilic asthma (469.0 [451.7-486.2]). Incidence rate ratios for all phenotype groups decreased when stratified by treatment step but remained raised compared to benign asthma.

CONCLUSION

Established phenotypes can be identified in a general asthma population, although many patients did not fit into the specific phenotypes which we studied. Phenotyping patients and knowledge of asthma treatment step could help anticipate clinical course and therefore could aid clinical management but is only possible in a minority of primary care patients based on current phenotypes and electronic health records (EHRs).

The overlap between bronchiectasis and chronic airway diseases: state of the art and future directions

Bronchiectasis is a clinical and radiological diagnosis associated with cough, sputum production and recurrent respiratory infections. The clinical presentation inevitably overlaps with other respiratory disorders such as asthma and chronic obstructive pulmonary disease (COPD). In addition, 4-72% of patients with severe COPD are found to have radiological bronchiectasis on computed tomography, with similar frequencies (20-30%) now being reported in cohorts with severe or uncontrolled asthma. Co-diagnosis of bronchiectasis with another airway disease is associated with increased lung inflammation, frequent exacerbations, worse lung function and higher mortality. In addition, many patients with all three disorders have chronic rhinosinusitis and upper airway disease, resulting in a complex "mixed airway" phenotype.The management of asthma, bronchiectasis, COPD and upper airway diseases has traditionally been outlined in separate guidelines for each individual disorder. Recognition that the majority of patients have one or more overlapping pathologies requires that we re-evaluate how we treat airway disease. The concept of treatable traits promotes a holistic, pathophysiology-based approach to treatment rather than a syndromic approach and may be more appropriate for patients with overlapping features.Here, we review the current clinical definition, diagnosis, management and future directions for the overlap between bronchiectasis and other airway diseases.

Phenotypes of childhood wheeze in Japanese children: A group-based trajectory analysis

BACKGROUND

Exploring patterns of childhood wheeze may help to clarify the etiology and prognosis of respiratory diseases. The purpose of this study was to classify phenotypes of wheezing in children up to 9 years of age in Japan and to evaluate the individual and environmental risk factors for these phenotypes.

METHODS

Wheeze was evaluated at approximately 1-year intervals based on the mothers' recollection of their child's wheezing or whistling in the chest during the preceding 12 months. The children were aged 1-9 years. In total, 1116 children who had at least five measures of wheezing at all nine time points were used for identifying trajectories. Trajectories were identified with group-based trajectory analysis. A multinomial logit model was built to evaluate the relationships between phenotypes and risk factors.

RESULTS

Five typical trajectories were identified. The probability of group membership was 43.7%, 32.2%, 6.2%, 8.6%, and 9.2% for the never/infrequent wheeze, transient early wheeze, school-age-onset wheeze, early-childhood-onset remitting wheeze, and persistent wheeze trajectories, respectively. Infant tobacco exposure increased the odds of membership in the transient early wheeze trajectory compared to the never/infrequent wheeze trajectory.

CONCLUSIONS

Using the group-based trajectory modeling approach, we identified five trajectories of childhood wheeze development in a Japanese population. The trajectories shown here are based on formal statistical modeling rather than on subjective classification, and an assessment of its precision suggested that the model has high assignment accuracy.

Treatable traits of chronic airways disease

PURPOSE OF REVIEW

To describe the rationale on which the treatable traits approach to the management of airways disease is based and the issues that need to be considered for its implementation in clinical practice.

RECENT FINDINGS

In clinical practice, treatable traits can be classified according to both endotypes and phenotypes, broadly grouped within pulmonary, extrapulmonary, environmental and behavioural factors. Specific investigations and treatments are undertaken for each of the traits rather than a 'one size fits all' stepwise approach to pharmacological treatment which currently represents the core of asthma and chronic obstructive pulmonary disease (COPD) guidelines. Although there is strong evidence of the benefit of the treatable traits approach to specific traits in asthma and/or COPD, there is uncertainty regarding the preferred method of implementation, efficacy and cost-effectiveness of multidimensional intervention programmes in clinical practice. It is likely that 'master protocols' for randomized controlled trials will be required to evaluate such multiple interventions in broad populations of patients with airways disease.

SUMMARY

Current evidence suggests that the precision medicine approach based on the identification and treatment of treatable traits is preferable to a 'one-size-fits-all' stepwise approach to the treatment of airways disease, although high-quality evidence to guide the practical application of this multidimensional management strategy is now required. VIDEO ABSTRACT.

COPD stands for complex obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) has extensively been reported as a complex disease affecting patients' health beyond the lungs with a variety of intra- and extrapulmonary components and considerable variability between individuals. This review discusses the assessment of this complexity and underlines the importance of transdisciplinary management programmes addressing the physical, emotional and social health of the individual patient.COPD management is challenging and requires advanced, sophisticated strategies meeting the patient's individual needs. Due to the heterogeneity and complexity of the disease leading to non-linear and consequently poorly predictable treatment responses, multidimensional patient profiling is crucial to identify the right COPD patient for the right treatment. Current methods are often restricted to general, well-known and commonly used assessments neglecting potentially relevant (interactions between) individual, unique "traits" to finally ensure personalised treatment. Dynamic, personalised and holistic approaches are needed to tackle this multifaceted disease and to ensure personalised medicine and value-based healthcare.

African ancestry is associated with cluster-based childhood asthma subphenotypes

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Integral Health Status-Based Cluster Analysis in Moderate-Severe COPD Patients Identifies Three Clinical Phenotypes: Relevant for Treatment As Usual and Pulmonary Rehabilitation

PURPOSE

The purposes of the study are to identify clinical phenotypes that reflect the level of adaptation to the disease and to examine whether these clinical phenotypes respond differently to treatment as usual (TAU) and pulmonary rehabilitation (PR), the latter with its strong emphasis on improving adaptation.

METHODS

Clusters were identified by a cluster analysis using data on many subdomains of the four domains of health status (HS) (physiological functioning, functional impairment, symptoms and quality of life) in 160 outpatients with chronic obstructive pulmonary disease (COPD) receiving TAU. By discriminant analysis in the TAU sample, all 459 PR patients could be assigned to one of the identified clusters. The effect of TAU and PR on HS was examined with paired t tests.

RESULTS

Three distinct phenotypes were identified in the TAU sample. Two types were labelled adapted: phenotype 1 (moderate COPD-low impact on HS, n = 53) and phenotype 3 (severe COPD-moderate impact on HS, n = 73). One type was labelled non-adapted: phenotype 2 (moderate COPD-high impact on HS, n = 34). After 1-year TAU, the integral health status of all patients did not improve in any subdomain. In contrast, at the end of PR, significant improvements in HS were found in all three phenotypes especially the non-adapted.

CONCLUSIONS

Different phenotypes exist in COPD that are based on behavioural aspects (i.e. the level of adaptation to the disease). Non-adapted patient responds better to treatments with a strong emphasis on improving adaptation by learning the patient better self-management skills. Knowing to which clinical phenotype a patient belongs helps to optimize patient-tailored treatment.

Phenotypes of symptomatic airways disease in China and New Zealand

It is uncertain whether phenotypes of asthma and chronic obstructive pulmonary disease (COPD) vary between populations with different genetic and environmental characteristics. Here, our objective was to compare the phenotypes of airways disease in two separate populations.This was a cross-sectional observational study in adult populations from New Zealand and China. Participants aged 40-75 years who reported wheeze and breathlessness in the last 12 months were randomly selected from the general population and underwent detailed characterisation. Complete data for cluster analysis were available for 345 participants. Hierarchical cluster analysis was undertaken, based on 12 variables: forced expiratory volume in 1 s (FEV₁), FEV₁/forced vital capacity ratio, bronchodilator reversibility, peak expiratory flow variability, transfer coefficient of the lung for carbon monoxide, exhaled nitric oxide fraction, total IgE, C-reactive protein, age of symptom onset, body mass index, health status and cigarette smoke exposure.Cluster analysis of the combined dataset described five phenotypes: "severe late-onset asthma/COPD overlap group", "moderately severe early-onset asthma/COPD overlap group", "moderate to severe asthma group with type 2 predominant disease", and two groups with minimal airflow obstruction, differentiated by age of onset. Separate analyses by country showed similar patterns; however, a distinct obese/comorbid group was observed in the New Zealand population.Cluster analysis of adults with symptomatic airways disease suggests the presence of similar asthma/COPD overlap phenotypes within populations with different genetic and environmental characteristics, and an obese/comorbid phenotype in a Western population.

Heterogeneity of respiratory disease in children and young adults with sickle cell disease

To detect and characterise different phenotypes of respiratory disease in children and young adults with sickle cell disease (SCD), 11 lung function and haematological biomarkers were analysed using k-means cluster analysis in a cohort of 114 subjects with SCD aged between 5 and 27 years. Three clusters were detected: cluster 1 had elevated pulmonary capillary blood volume, mixed obstructive/restrictive lung disease, hypoxia and moderately severe anaemia; cluster 2 were older patients with restrictive lung disease; and cluster 3 were younger patients with obstructive lung disease, elevated serum lactate dehydrogenase and bronchodilator reversibility. These results may inform more personalised management strategies to improve outcomes.

What does endotyping mean for treatment in chronic obstructive pulmonary disease?

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease, both at the clinical and biological level. However, COPD is still diagnosed and treated according to simple clinical measures (level of airflow limitation, symptoms, and frequency of previous exacerbations). To address this clinical and biological complexity and to move towards precision medicine in COPD, we need to integrate (bioinformatics) and interpret (clinical science) the vast amount of high-throughput information that existing technology provides (systems biology and network medicine) so diagnosis, stratification, and treatment of patients with COPD can occur on the basis of their pathobiological mechanism (ie, endotypes). Therefore, this Series paper discusses a possible new taxonomy of COPD, the role of endotypes and associated biomarkers and phenotypes, the gaps (and opportunities) in existing knowledge of COPD pathobiology, how systems biology and network medicine can improve understanding of the disease and help to identify relevant endotypes and their specific biomarkers, and how endotypes and their biomarkers can improve the precision, effectiveness, and safety of the treatment of patients with COPD.

Diagnosing eosinophilic asthma using a multivariate prediction model based on blood granulocyte responsiveness

BACKGROUND

The identification of inflammatory asthma phenotypes, using sputum analysis, has proven its value in diagnosis and disease monitoring. However due to technical limitations of sputum analysis, there is a strong need for fast and noninvasive diagnostics. This study included the activation state of eosinophils and neutrophils in peripheral blood to phenotype and monitor asthma.

OBJECTIVES

To (i) construct a multivariable model using the activation state of blood granulocytes, (ii) compare its diagnostic value with sputum eosinophilia as gold standard and (iii) validate the model in an independent patient cohort.

METHODS

Clinical parameters, activation of blood granulocytes and sputum characteristics were assessed in 115 adult patients with asthma (training cohort/Utrecht) and 34 patients (validation cohort/Oxford).

RESULTS

The combination of blood eosinophil count, fractional exhaled nitric oxide, Asthma Control Questionnaire, medication use, nasal polyposis, aspirin sensitivity and neutrophil/eosinophil responsiveness upon stimulation with formyl-methionyl-leucyl phenylalanine was found to identify sputum eosinophilia with 90.5% sensitivity and 91.5% specificity in the training cohort and with 77% sensitivity and 71% specificity in the validation cohort (relatively high percentage on oral corticosteroids [OCS]).

CONCLUSIONS

The proposed prediction model identifies eosinophilic asthma without the need for sputum induction. The model forms a noninvasive and externally validated test to assess eosinophilic asthma in patients not on OCS.

Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients

Grading of essential hypertension according to blood pressure (BP) level may not adequately reflect clinical heterogeneity of hypertensive patients. This study was carried out to explore clinical phenotypes in essential hypertensive patients using cluster analysis. This study recruited 513 hypertensive patients and evaluated BP variations with ambulatory blood pressure monitoring. Four distinct hypertension groups were identified using cluster analysis: (1) younger male smokers with relatively high BP had the most severe carotid plaque thickness but no coronary artery disease (CAD); (2) older women with relatively low diastolic BP had more diabetes; (3) non-smokers with a low systolic BP level had neither diabetes nor CAD; (4) hypertensive patients with BP reverse dipping were most likely to have CAD but had least severe carotid plaque thickness. In binary logistic analysis, reverse dipping was significantly associated with prevalence of CAD. Cluster analysis was shown to be a feasible approach for investigating the heterogeneity of essential hypertension in clinical studies. BP reverse dipping might be valuable for prediction of CAD in hypertensive patients when compared with carotid plaque thickness. However, large-scale prospective trials with more information of plaque morphology are necessary to further compare the predicative power between BP dipping pattern and carotid plaque.

Chronic obstructive pulmonary disease phenotypes using cluster analysis of electronic medical records

Chronic obstructive pulmonary disease is a heterogeneous disease. In this retrospective study, we hypothesize that it is possible to identify clinically relevant phenotypes by applying clustering methods to electronic medical records. We included all the patients >40 years with a diagnosis of chronic obstructive pulmonary disease admitted to the University of New Mexico Hospital between 1 January 2011 and 1 May 2014. We collected admissions, demographics, comorbidities, severity markers and treatments. A total of 3144 patients met the inclusion criteria: 46 percent were >65 years and 52 percent were males. The median Charlson score was 2 (interquartile range: 1-4) and the most frequent comorbidities were depression (36%), congestive heart failure (25%), obesity (19%), cancer (19%) and mild liver disease (18%). Using the sphere exclusion method, nine clusters were obtained: depression-chronic obstructive pulmonary disease, coronary artery disease-chronic obstructive pulmonary disease, cerebrovascular disease-chronic obstructive pulmonary disease, malignancy-chronic obstructive pulmonary disease, advanced malignancy-chronic obstructive pulmonary disease, diabetes mellitus-chronic kidney disease-chronic obstructive pulmonary disease, young age-few comorbidities-high readmission rates-chronic obstructive pulmonary disease, atopy-chronic obstructive pulmonary disease, and advanced disease-chronic obstructive pulmonary disease. These clusters will need to be validated prospectively.

A Systematic Review of the Prevalence and Pattern of Imaging Defined Post-TB Lung Disease

Background

Tuberculosis is an important risk factor for chronic respiratory disease in resource poor settings. The persistence of abnormal spirometry and symptoms after treatment are well described, but the structural abnormalities underlying these changes remain poorly defined, limiting our ability to phenotype post-TB lung disease in to meaningful categories for clinical management, prognostication, and ongoing research. The relationship between post-TB lung damage and patient-centred outcomes including functional impairment, respiratory symptoms, and health related quality of life also remains unclear.

Methods

We performed a systematic literature review to determine the prevalence and pattern of imaging-defined lung pathology in adults after medical treatment for pleural, miliary, or pulmonary TB disease. Data were collected on study characteristics, and the modality, timing, and findings of thoracic imaging. The proportion of studies relating imaging findings to spirometry results and patient morbidity was recorded. Study quality was assessed using a modified Newcastle-Ottowa score. (Prospero Registration number CRD42015027958)

Results

We identified 37 eligible studies. The principle features seen on CXR were cavitation (8.3–83.7%), bronchiectasis (4.3–11.2%), and fibrosis (25.0–70.4%), but prevalence was highly variable. CT imaging identified a wider range of residual abnormalities than CXR, including nodules (25.0–55.8%), consolidation (3.7–19.2%), and emphysema (15.0–45.0%). The prevalence of cavitation was generally lower (7.4–34.6%) and bronchiectasis higher (35.0–86.0%) on CT vs. CXR imaging. A paucity of prospective data, and data from HIV-infected adults and sub-Saharan Africa (sSA) was noted. Few studies related structural damage to physiological impairment, respiratory symptoms, or patient morbidity.

Conclusions

Post-TB structural lung pathology is common. Prospective data are required to determine the evolution of this lung damage and its associated morbidity over time. Further data are required from HIV-infected groups and those living in sSA.

Real-life effectiveness of omalizumab in severe allergic asthma above the recommended dosing range criteria

BACKGROUND

Omalizumab (Xolair) dosing in severe allergic asthma is based on serum IgE and bodyweight. In Australia, patients eligible for omalizumab but exceeding recommended ranges for IgE (30-1500 IU/mL) and bodyweight (30-150 kg) may still receive a ceiling dose of 750 mg/4 weeks. About 62% of patients receiving government-subsidized omalizumab are enrolled in the Australian Xolair Registry (AXR).

OBJECTIVES

To determine whether AXR participants above the recommended dosing ranges benefit from omalizumab and to compare their response to within-range participants.

METHODS

Data were stratified according to dose range status (above-range or within-range). Further sub-analyses were conducted according to the reason for being above the dosing range (IgE only vs. IgE and weight).

RESULTS

Data for 179 participants were analysed. About 55 (31%) were above recommended dosing criteria; other characteristics were similar to within-range participants. Above-range participants had higher baseline IgE [812 (IQR 632, 1747) IU/mL vs. 209 (IQR 134, 306) IU/mL] and received higher doses of omalizumab [750 (IQR 650, 750) mg] compared to within-range participants [450 (IQR, 300, 600) mg]. At 6 months, improvements in Juniper 5-item Asthma Control Questionnaire (ACQ-5, 3.61 down to 2.01 for above-range, 3.47 down to 1.93 for within-range, P < 0.0001 for both) and Asthma Quality of Life Questionnaire (AQLQ mean score (3.22 up to 4.41 for above-range, 3.71 up to 4.88 for within-range, P < 0.0001) were observed in both groups. Forced expiratory volume in one second (FEV₁ ) improved among above-range participants. There was no difference in response between above-range and within-range participants. Above-range participants due to either IgE alone or IgE and weight had similar improvements in ACQ-5, AQLQ and FEV₁ .

CONCLUSIONS AND CLINICAL RELEVANCE

Patients with severe allergic asthma above recommended dosing criteria for omalizumab have significantly improved symptom control, quality of life and lung function to a similar degree to within-range participants, achieved without dose escalation above 750 mg.

Clinical phenotypes of obstructive airway diseases in an outpatient population

BACKGROUND AND OBJECTIVES

Historically, obstructive airway diseases such as asthma and COPD are classified as different diseases. Although the definitions are clearly described, classification of patients into these traditional, clinical disease entity can be difficult. Recent evidence that there are complex, overlapping phenotypes of obstructive lung disease. Our aim was to capture clinical phenotypes of obstructive diseases through the use of cluster analysis in a representative patient population at a common Dutch pulmonary outpatient clinic. Clinical physiological and cellular/ molecular markers were used in the analysis.

METHODS

To carry out the cluster analysis, an imputed dataset was created from a random sample of 191 adult patients chosen from a pulmonary outpatient clinic. The selection criteria from the sample included patients with a doctor's diagnosis for asthma or COPD. Detailed assessment of patient pulmonary function, blood eosinophil counts, allergic sensitisation and smoking history was collected.

RESULTS

We observed four distinct clusters with different clinical characteristics of obstructive lung diseases. Cluster 1: patients with a history of extensive cigarette smoking, airway obstruction without signs of emphysema; cluster 2: patients with features of the emphysematous type of COPD; cluster 3: patients with characteristics of allergic asthma; cluster 4: patients with features suggesting an overlap syndrome of atopic asthma and COPD.

CONCLUSION

Four phenotypes of obstructive lung disease were identified amongst patients clinically labelled as asthma or COPD. These findings emphasize the concept that there are different phenotypes of obstructive lung diseases, including overlapping and complementary disease entities. These phenotypes of chronic airways disease can serve to tailor disease management.

Eosinophilic airway inflammation: role in asthma and chronic obstructive pulmonary disease

The chronic lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are common affecting over 500 million people worldwide and causing substantial morbidity and mortality. Asthma is typically associated with Th2-mediated eosinophilic airway inflammation, in contrast to neutrophilic inflammation observed commonly in COPD. However, there is increasing evidence that the eosinophil might play an important role in 10-40% of patients with COPD. Consistently in both asthma and COPD a sputum eosinophilia is associated with a good response to corticosteroid therapy and tailored strategies aimed to normalize sputum eosinophils reduce exacerbation frequency and severity. Advances in our understanding of the multistep paradigm of eosinophil recruitment to the airway, and the consequence of eosinophilic inflammation, has led to the development of new therapies to target these molecular pathways. In this article we discuss the mechanisms of eosinophilic trafficking, the tools to assess eosinophilic airway inflammation in asthma and COPD during stable disease and exacerbations and review current and novel anti-eosinophilic treatments.

Biomarkers for precision medicine in airways disease

Chronic obstructive pulmonary disease (COPD) is a complex clinical entity. In contrast to previously limited diagnostic definitions, it is now apparent that COPD is a clinically and biologically heterogeneous disease process, overlapping with other airways diseases like chronic asthma. As such, symptomatic response to current standard treatment practices is variable. New clinical guidelines have been altered to reflect this, with the inclusion of symptoms and risk factors in diagnostic and management algorithms. However, as our understanding of COPD pathophysiology deepens, many novel physiological, cellular, proteomic, and genetic markers have been identified. Several have been observed to be independently predictive of distinct clinical disease patterns, which at present are not illustrated by conventional measurements of lung impairment. The potential use of these predictive biomarkers to stratify this diverse patient population could transform the care we offer. We should aim for precision medicine to optimize diagnosis and treatment choices and to monitor and improve clinical outcomes in this disease.

Phenome-Wide Association Studies: Embracing Complexity for Discovery

The inherent complexity of biological systems can be leveraged for a greater understanding of the impact of genetic architecture on outcomes, traits, and pharmacological response. The genome-wide association study (GWAS) approach has well-developed methods and relatively straight-forward methodologies; however, the bigger picture of the impact of genetic architecture on phenotypic outcome still remains to be elucidated even with an ever-growing number of GWAS performed. Greater consideration of the complexity of biological processes, using more data from the phenome, exposome, and diverse -omic resources, including considering the interplay of pleiotropy and genetic interactions, may provide additional leverage for making the most of the incredible wealth of information available for study. Here, we describe how incorporating greater complexity into analyses through the use of additional phenotypic data and widespread deployment of phenome-wide association studies may provide new insights into genetic factors influencing diseases, traits, and pharmacological response.

Asthma-COPD overlap 2015: now we are six

BACKGROUND

The overlap between asthma and COPD is increasingly recognised. This review examines the new insights, treatment and remaining knowledge gaps for asthma-COPD overlap.

METHOD

A systematic literature review of cluster analyses of asthma and COPD was performed. Articles from 2009 to the present dealing with prevalence, morbidity and treatment of asthma-COPD overlap were identified and reviewed.

RESULTS

Asthma-COPD overlap was consistently recognised in studies using a variety of different study designs and sampling. The prevalence was approximately 20% in patients with obstructive airways diseases. Asthma-COPD overlap was associated with increased morbidity and possibly an increased mortality and comorbidity. There was evidence of a heterogeneous pattern of airway inflammation that included eosinophilic (in adult asthma), neutrophilic or mixed patterns (in severe asthma and COPD). Systemic inflammation was present in asthma-COPD overlap and resembled that of COPD. Within asthma-COPD overlap, there is evidence of different subgroups, and recognition using bronchodilator responsiveness has not been successful. Guidelines generally recommend a serial approach to assessment, with treatment recommendations dominated by an asthma paradigm. Research is needed into key clinical features that impact outcome, mechanisms and treatment approaches in asthma-COPD overlap. Identifying and treating disease components by multidimensional assessment shows promise.

CONCLUSIONS

Asthma-COPD overlap has drawn attention to the significant heterogeneity that exists within obstructive airway diseases. It should be replaced by novel approaches that identify and manage the components of this heterogeneity, such as multidimensional assessment and treatment. Future research is needed to test these novel and personalised approaches.

Treatment responsiveness of phenotypes of symptomatic airways obstruction in adults

BACKGROUND

Asthma and chronic obstructive pulmonary disease (COPD) are heterogeneous disorders encompassing different phenotypes of airflow obstruction, which might differ in their response to treatment.

OBJECTIVE

The aim of this study was to determine distinct phenotypes comprising the syndromes of asthma and COPD and the treatment responsiveness of these phenotypes to inhaled β-agonist, antimuscarinic, and corticosteroid therapy.

METHODS

We undertook a cross-sectional study with 3 phases. In phase 1, 1,264 participants aged 18 to 75 years with self-reported current wheeze and breathlessness were identified from a random population sample of 16,459. In phase 2, 451 participants attended for detailed assessment, including responsiveness to inhaled salbutamol and ipratropium bromide. In phase 3, 168 steroid-naive participants were enrolled in a 12-week trial of inhaled budesonide. Cluster analysis was performed in 389 participants who completed phase 2 with full data. Treatment responsiveness was compared between phenotypes.

RESULTS

Cluster analysis identified 5 phenotypes: moderate-to-severe childhood-onset atopic asthma, asthma-COPD overlap, obese-comorbid, mild childhood-onset atopic asthma, and mild intermittent. Bronchodilation after salbutamol was equal to or greater than that after ipratropium for all phenotypes. The moderate-to-severe childhood-onset atopic asthma, asthma-COPD overlap, and obese-comorbid phenotypes had greater efficacy with inhaled corticosteroid treatment than the mild intermittent group.

CONCLUSION

Cluster analysis of adults with symptomatic airflow obstruction identifies 5 disease phenotypes, including asthma-COPD overlap and obese-comorbid phenotypes, and provides evidence that patients with the asthma-COPD overlap syndrome might benefit from inhaled corticosteroid therapy.

Synergy-COPD: a systems approach for understanding and managing chronic diseases

Chronic diseases (CD) are generating a dramatic societal burden worldwide that is expected to persist over the next decades. The challenges posed by the epidemics of CD have triggered a novel health paradigm with major consequences on the traditional concept of disease and with a profound impact on key aspects of healthcare systems. We hypothesized that the development of a systems approach to understand CD together with the generation of an ecosystem to transfer the acquired knowledge into the novel healthcare scenario may contribute to a cost-effective enhancement of health outcomes. To this end, we designed the Synergy-COPD project wherein the heterogeneity of chronic obstructive pulmonary disease (COPD) was addressed as a use case representative of CD. The current manuscript describes main features of the project design and the strategies put in place for its development, as well the expected outcomes during the project life-span. Moreover, the manuscript serves as introductory and unifying chapter of the different papers associated to the Supplement describing the characteristics, tools and the objectives of Synergy-COPD.

Chronic Obstructive Pulmonary Disease heterogeneity: challenges for health risk assessment, stratification and management

Background and hypothesis

Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics.

Objective and method

To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena.

Results

(1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering.

Conclusions

The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.