New Publication: Targeted Proteomics and Machine Learning Predict CRS Endotypes

We are excited to share our latest publication in the Journal of Allergy and Clinical Immunology (JACI), where our team applied proteomic profiling and machine learning to classify endotypes of Chronic Rhinosinusitis (CRS).This study represents an important step toward personalized medicine for chronic respiratory diseases.

CRS is a highly complex condition, particularly challenging to treat in severe subtypes such as NSAID-Exacerbated RespiratoryDisease (N-ERD). By moving beyond symptom-based assessment and focusing on molecular-level analysis, we identified distinct proteomic signatures and potential novel biomarkers in nasal and serum samples. Using machine learning, we were able to pinpoint protein patterns that distinguish patient subgroups, opening the door to more tailored treatment strategies.

Our findings provide new hope for patients with severe CRS, supporting the development of improved diagnostics and targeted therapies.

We would like to thank all co-authors and GSK for their invaluable contributions.

To make our work more accessible, we also created a comic-style version oft he study, illustrated by Sara Miranda.

📄 Read the full article here: https://doi.org/10.1016/j.jaci.2025.08.025