Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma

Area of Science:

• Pulmonology and Respiratory Medicine
• Clinical Immunology
• Biostatistics

Background:

• Bronchial asthma is a complex, heterogeneous respiratory disease with various underlying pathological mechanisms.
• Recognizing distinct asthma subtypes is crucial for effective management and treatment strategies.

Purpose of the Study:

• To employ cluster analysis for identifying phenotypes in moderate to severe bronchial asthma.
• To compare clinical, physiological, immunological, and inflammatory data across identified asthma clusters.

Main Methods:

• Cluster analysis (two-step, hierarchical, k-mean) was applied to data from 40 adult asthma patients.
• Data included clinical assessment, spirometry, fractional exhaled nitric oxide, blood eosinophils, IgE, and periostin levels.

Main Results:

• Four distinct asthma clusters were identified: late-onset non-atopic with impaired lung function, late-onset atopic, late-onset aspirin-sensitive eosinophilic, and early-onset atopic.
• Key differentiating variables included age of onset, disease duration, atopy, smoking, eosinophil count, NSAID hypersensitivity, FEV1/FVC, and symptom severity.

Conclusions:

• The study confirms the heterogeneity of bronchial asthma.
• Cluster analysis is a valuable tool for phenotyping asthma and guiding personalized treatment approaches.