Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study

Area of Science:

• Pulmonology
• Immunology
• Genetics

Background:

• Asthma exhibits varying severity and complex disease mechanisms.
• Previous asthma stratification studies lacked validation in independent cohorts.
• Defining stable, clinically useful asthma phenotypes is crucial for targeted treatment.

Purpose of the Study:

• To define and validate clinically driven asthma phenotypes.
• To utilize two independent severe asthma cohorts, ADEPT and U-BIOPRED.
• To assess the stability and reproducibility of identified phenotypes.

Main Methods:

• Fuzzy partition-around-medoid clustering applied to ADEPT and U-BIOPRED data.
• Development of cluster classification probability models.
• Application of models to longitudinal ADEPT and U-BIOPRED datasets.
• Definition of Type-2 inflammation phenotypes based on gene expression in endobronchial biopsies.

Main Results:

• Four distinct asthma phenotypes identified in the ADEPT cohort with unique clinical and biomarker profiles.
• Phenotypes characterized by severity, lung function, inflammatory profiles (Type-2, eosinophilic, neutrophilic), and reversibility.
• Identified phenotypes demonstrated good longitudinal stability.
• Phenotypes were successfully reproduced with high classification probability in U-BIOPRED cohorts.

Conclusions:

• Four clinically validated, easy-to-assess asthma phenotypes were defined.
• These phenotypes exhibit distinct biological and clinical characteristics.
• Understanding these phenotypes aids in addressing unmet needs and developing tailored asthma therapies.