Comprehensive Cluster Analysis for COPD Including Systemic and Airway Inflammatory Markers

Chronic obstructive pulmonary disease (COPD) is a complex, multidimensional and heterogeneous disease. The main purpose of the present study was to identify clinical phenotypes through cluster nalysis in adults suffering from COPD. A retrospective study was conducted on 178 COPD patients in stable state recruited from ambulatory care at University hospital of Liege. All patients were above 40 years, had a smoking history of more than 20 pack years, post bronchodilator FEV1/FVC <70% and denied any history of asthma before 40 years. In this study, the patients were described by a total of 84 mixed sets of variables with some missing values. Hierarchical clustering on principal components (HCPC) was applied on multiple imputation. In the final step, patients were classified into homogeneous distinct groups by consensus clustering. Three different clusters, which shared similar smoking history were found. Cluster 1 included men with moderate airway obstruction (n¼67) while cluster 2 comprised men who were exacerbation-prone, with severe airflow limitation and intense granulocytic airway and neutrophilic systemic inflammation (n¼56). Cluster 3 essentially included women with moderate airway obstruction (n¼55). All clusters had a low rate of bacterial colonization (5%), a low median FeNO value (<20 ppb) and a very low sensitization rate toward common aeroallergens (0-5%). CAT score did not differ between clusters. Including markers of systemic airway inflammation and atopy and applying a comprehensive cluster analysis we provide here evidence for 3 clusters markedly shaped by sex, airway obstruction and neutrophilic inflammation but not by symptoms and T2 biomarkers

Are type-2 biomarkers of any help in asthma diagnosis?

Peer reviewe

Revisiting differences between atopic and non-atopic asthmatics: When age is shaping airway inflammatory profile

BACKGROUND: Atopic asthma is one of the most common asthma phenotypes and is generally opposed to the non-atopic counterpart. There have been very few large-scale studies comparing atopic and non-atopic asthmatics in terms of systemic and airway inflammation across the age spectrum. METHODS: Here, we have undertaken a retrospective study investigating 1626 patients (924 atopic and 702 non-atopic asthmatics) recruited from our university asthma clinic who underwent extensive clinical investigations including induced sputum. Atopy was defined by any positive specific IgE to common aeroallergens (>0,35 kU/L). We performed direct comparisons between the groups and sought to appreciate the influence of age on the airway and systemic inflammatory components. The study was approved by the ethics committee of the University Hospital of Liege (Ref. 2016/276). Informed consents were obtained from healthy subjects. RESULTS: Atopic asthmatics were younger (P < .001), had a higher male/female ratio (P < .001), an earlier disease onset (P < .001) and a greater proportion of treated rhinitis (P < .001) while non-atopic asthmatics had greater smoke exposure (P < .001), lower FEV(1)/FVC ratio (P = .01) and diffusing capacity (P < .001). There was no difference between the 2 groups regarding FEV(1) (% predicted), asthma control, asthma quality of life and exacerbations in the previous 12 months. Regarding inflammation, atopic patients had higher FeNO levels (median = 28 ppb, P < .001), were more eosinophilic both in blood (median = 2.8%, P < .001) and in sputum (median = 2.2%, P < .001) while non-atopic patients displayed greater blood (median = 57%, P = .01) and sputum (median = 58.8%, P = .01) neutrophilic inflammation. However, stratifying patients by age showed that non-atopic asthmatics above 50 years old became equally eosinophilic in the sputum (P = .07), but not in the blood, as compared to atopic patients. Likewise, FeNO rose in non-atopic patients after 50 years old but remained, however, lower than in atopic patients. CONCLUSIONS: We conclude that, while sharing many features, atopic group still differentiates from non-atopic asthmatics by demographics, functional and inflammatory profiles. When atopic asthmatics showed a constant eosinophilic pattern across the age spectrum, non-atopic asthmatics were found to be neutrophilic before the age of 50 but eosinophilic above 50 years old

A clustering analysis of eosinophilic asthmatics: Two clusters with sharp differences in atopic status and disease severity.

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Predictors of change in asthma-related quality of life: a longitudinal real-life study in adult asthmatics.

peer reviewed("[en] PURPOSE: Asthma negatively impacts health-related quality of life (HRQL). The objective is to investigate the longitudinal relationship between HRQL in asthma and disease control, demographic and clinical objective parameters in an adult population in real-life settings. METHODS: We conducted a longitudinal study on adult asthmatics recruited from Liege University Hospital Asthma Clinic (Belgium) between 2011 and 2019. We selected those who had two visits and completed two patient-reported outcome measures (PROMs), the asthma control test (ACT) and the mini asthma quality of life questionnaire (AQLQ) (n = 290). AQLQ was the dependent variable. Demographic, functional and inflammatory characteristics, asthma control, and exacerbations were the independent variables. We applied generalized linear mixed models to identify the factors associated with change in AQLQ and its dimensions. RESULTS: Median (IQR) time interval between the two visits was 7 (5-19) months. Overall, median (IQR) global AQLQ increased from 4.1 (3-5.1) to 4.6 (3.4-5.9) (p < 0.0001). All AQLQ dimensions significantly improved, apart the environmental one. AQLQ improved in patients who had both step-up and step-down pharmacological treatment as well as in patients reporting no change between the two visits. The fitted models indicated that change in ACT was the main predictor of change in AQLQ (p < 0.0001). A rise in 3 units in ACT predicted an improvement of 0.5 AQLQ (AUC-ROC = 0.85; p < 0.0001). Change in BMI inversely impacted global AQLQ (p < 0.01) and its activity dimension (p < 0.0001). CONCLUSION: Asthma control and BMI are key predictors of asthma quality of life acting in an opposite direction. AQLQ may improve without step-up in the pharmacological treatment.","[en] ",""

Chronic infection with Chlamydia pneumoniae in asthma: a type-2 low infection related phenotype.

BACKGROUND: Chlamydia pneumoniae and Mycoplasma pneumoniae have been implicated in the pathogenesis of asthma and are responsible for chronic inflammation when host immune system fails to eradicate the bacteria. METHOD: We performed a prospective study on 410 patients who underwent a visit at the asthma clinic of CHU of Liege between June 2016 and June 2018 with serology testing for C. pneumoniae and M. pneumoniae. RESULTS: 65% of our asthmatic population had serum IgA and/or IgG towards C. pneumoniae, while only 12.6% had IgM and/or IgG against M. pneumoniae. Compared to seronegative asthmatics, asthmatics with IgA+ and IgG+ against C. pneumoniae were more often male and older with a higher proportion of patients with smoking history. They received higher doses of inhaled corticosteroids (ICS) and displayed lower FEV(1)/FVC ratio, higher RV/TLC ratio and lower conductance. They had higher levels of fibrinogen, though in the normal range and had lower sputum eosinophil counts. Patients with IgA- and IgG+ against C. pneumoniae were older and had higher blood monocyte counts and alpha-1-antitrypsin levels as compared to seronegative patients. Patients with IgM and/or IgG towards M. pneumoniae were more often males than seronegative asthmatics. In a subpopulation of 14 neutrophilic asthmatics with Chlamydia pneumoniae IgA + /IgG + treated with macrolides, we found a significant decrease in blood neutrophils and normalization of sputum neutrophil count but no effect on asthma quality of life and exacerbations. CONCLUSION: Positive Chlamydia serologic test is more common than positive Mycoplasma serology. Asthmatics with IgA and IgG against C. pneumoniae have more severe disease with increased airway obstruction, higher doses of ICS, more signs of air trapping and less type-2 inflammation.Peer reviewe

Predictors of asthma-related quality of life in a large cohort of asthmatics : A cross-sectional study in a secondary care center

peer reviewe

A primary ciliary dysfunction might be present in severe asthma

peer reviewe

Evidence for two clusters among non-eosinophilic asthmatics.

peer reviewed[en] BACKGROUND: Although asthma is often seen as an eosinophilic disease associated with atopy non eosinophilic asthmatics represent a substantial part of asthmatic population. OBJECTIVE: Here we have applied an unsupervised clustering method on a cohort of 588 non eosinophilic asthmatics (sputum eosinophils <3%) recruited from an asthma clinic of a secondary care center. METHODS: Our cluster analysis of the whole cohort identified two subgroups as cluster 1 (n=417) and cluster 2 (n=171). RESULTS: Cluster 1 consisted of a dominant female group with a late disease onset, a low proportion of atopy (24%) and a substantial smoking history (53%). In this cluster, treatment burden was low (<50% of ICS users), asthma control and quality of life was poor with median ACT, ACQ and AQLQ of 16 and 1,7 and 4,5 respectively whereas lung function was preserved with a median post bronchodilation FEV1 of 93% predicted. Cluster 2 was a dominant male group, almost exclusively composed of atopic patients (99%) with early disease onset and a moderate treatment burden (median ICS dose 800 µg/d equivalent beclomethasone). In cluster 2 asthma was partially controlled with median ACT and ACQ reaching 18 and 1.3 respectively and lung function well preserved with a median post bronchodilation 95% predicted. While systemic and airway neutrophilic inflammation was the dominant pattern in cluster 1, cluster 2 essentially comprised paucigranulocytic asthma with moderately elevated FeNO. CONCLUSION: Non eosinophilic asthma splits in two clusters distinguishing by disease onset, atopic status, smoking history, systemic and airway inflammation and disease control and quality of life