Sputum Transcriptomic Analysis and Clustering Reveals Insight Into Asthma Heterogeneity

Area of Science:

• Pulmonary Medicine
• Genomics
• Inflammation Research

Background:

• Asthma is a complex disease with diverse underlying inflammatory mechanisms.
• Current classifications may not fully capture asthma heterogeneity.
• Understanding molecular profiles is crucial for targeted therapies.

Purpose of the Study:

• To investigate transcriptomic profiles in adult asthma patients.
• To associate these profiles with inflammation, airway damage, and lung function.
• To identify distinct asthma endotypes beyond the traditional type 2/non-type 2 classification.

Main Methods:

• Bulk RNA-sequencing was performed on sputum samples from 56 adult asthma patients.
• Unsupervised clustering was used to subgroup patients.
• Sputum cytokine mRNA levels and airway damage markers were analyzed.

Main Results:

• Three distinct asthma clusters emerged from transcriptomic analysis.
• Cluster 1: Pauci-granulocytic asthma with upregulated oxidative stress and downregulated TLR signaling.
• Cluster 2: Associated with type 2 inflammation, elevated eosinophils, epithelial damage, and allergy.
• Cluster 3: Characterized by worse lung function, increased neutrophils, and elevated calprotectin.

Conclusions:

• Transcriptomic profiling identified three novel asthma clusters.
• These clusters offer a more nuanced understanding of asthma heterogeneity.
• Findings bridge the gap between classical type 2 and non-type 2 asthma classifications.