Two phenothypes of severe asthma identified by cluster analysis

O. Kharevich (Minsk, Belarus), I. Lapteva (Minsk, Belarus), E. Lapteva (Minsk, Belarus)

Source: International Congress 2018 – Clinical markers of asthma
Session: Clinical markers of asthma
Session type: Thematic Poster
Number: 3996
Disease area: Airway diseases

Congress or journal article abstractE-poster

Abstract

In the recent years the attention of researchers has been focused on identifying approaches to the differentiation of asthma phenotypes, which is especially important in the case of severe asthma (SA).

The aim of the study was to identify SA phenotypes.

Methods. Hierarchical cluster analysis was used to identify asthma phenotypes in 63 patients with SA.

Results. The most adequate model was obtained using a combination of such parameters as allergic status, frequency of exacerbations, postbronchodilator  FEV1 and mean variability of PEF. Two phenotypes of SA were identified in this model. 38 patients with predominantly nonallergic asthma and severe airway obstruction were assigned to cluster 1 (phenotype of SA with irreversible airway obstruction), and 25 patients with predominantly allergic asthma, high frequency of exacerbations and significant PEF variability, but with less pronounced airway obstruction - to cluster 2 (phenotype of severe labile asthma).

The patients from cluster 1 demonstrated the presence of lung hyperinflation (higher RV/TLC than in cluster 2: 140,7 (125,3-161,6) %pred vs 121,7 (117,0-133,8) %pred, ?=0,005). Sputum neutrophil count was higher in cluster 1 than in cluster 2 (28 (22-31)% vs 18 (17-24)%, ?=0,005). Level of neutrophils in sputum in this group correlated with FEV1/FVC (rs=-0,69, p=0,009), that may indicate the involvement of neutrophilic inflammation in the development of irreversible obstruction. The serum level of IL-8 (which is known to be a chemoattractant for neutrophils) was higher in cluster 1 than in cluster 2 (57 (25-101) pg/ml vs 15 (10-55) pg/ml, p=0,015).

Conclusion. The possibility of identification of two distinct phenotypes of SA using cluster analysis was demonstrated.



Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
O. Kharevich (Minsk, Belarus), I. Lapteva (Minsk, Belarus), E. Lapteva (Minsk, Belarus). Two phenothypes of severe asthma identified by cluster analysis. 3996

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.


Related content which might interest you:
Identification of asthma phenotypes using cluster analysis
Source: International Congress 2018 – Exploring the importance of daily physical activity in chronic respiratory disease
Year: 2018

Cluster analysis to identify phenotypes in COPD
Source: Annual Congress 2009 - Quality of life and symptoms in COPD
Year: 2009

Cluster analysis and clinical asthma phenotypes
Source: Annual Congress 2013 –Severe asthma: moving from phenotyping to endotyping
Year: 2013


Analysis of phenotypes in a group of severe asthma
Source: International Congress 2019 – Immunopathological mechanisms of lung disease
Year: 2019

Identification of asthma clusters in two independent Korean adult asthma cohorts
Source: Eur Respir J 2013; 41: 1308-1314
Year: 2013



Two novel, severe asthma phenotypes identified during childhood using a clustering approach
Source: Eur Respir J 2012; 40: 55-60
Year: 2012



Identification of clinical phenotypes using cluster analyses in COPD patients
Source: International Congress 2019 – Phenotypes and comorbidities of airway diseases
Year: 2019


Cluster analysis of severe life-threatening asthma: identification of a distinct phenotype characterized by high serum eosinophils
Source: International Congress 2017 – Monitoring asthma control
Year: 2017


Identifying adult asthma phenotypes using a clustering approach
Source: Eur Respir J 2011; 38: 310-317
Year: 2011



Clinical COPD phenotypes identified by cluster analysis: validation with mortality
Source: Eur Respir J 2012; 40: 495-496
Year: 2012


Cluster analysis identifies distinct clinical phenotypes with poor treatment responsiveness in asthma.
Source: International Congress 2018 – Asthma: clinical screening tools
Year: 2018


Phenotypes of adult-onset asthma by cluster analysis
Source: Annual Congress 2012 - Phenotypes and mechanisms of treatment of asthma
Year: 2012

Scores of asthma and asthma severity reveal new regions of linkage in EGEA study families
Source: Eur Respir J 2007; 30: 253-259
Year: 2007



Distinguishing phenotypes of childhood wheeze and cough using latent class analysis
Source: Eur Respir J 2008; 31: 974-981
Year: 2008



Cluster analysis revealed differences on quality of life and susceptibility to exacerbation between subpopulations of smokers including COPD
Source: Annual Congress 2011 - COPD diagnosis
Year: 2011


Defining the clinical clusters of severe asthma within UBIOPRED
Source: International Congress 2015 – Fingerprinting severe asthma
Year: 2015



Urinary metabolomics-profiling of the U-BIOPRED asthma study identified biochemical clusters associated with asthma severity
Source: Virtual Congress 2020 – Phenotypes of obstructive diseases
Year: 2020


Longitudinal validation of clinical COPD phenotypes identified by cluster analysis
Source: Annual Congress 2011 - COPD diagnosis
Year: 2011

Distinct clinical phenotypes of airways disease defined by cluster analysis
Source: Eur Respir J 2009; 34: 812-818
Year: 2009



Latent class analyses used to study phenotypes in severe COPD with exacerbation. A pilot study
Source: Annual Congress 2010 - Epidemiological data for smoking control
Year: 2010