Cost-efficient approach for phenotyping cells in large cohorts and relating them with COPD clinical outcomes

In Canada, over 2 million people suffer from COPD, costing over $1.5 billion per year in direct expenditures. However, no existing therapy can reverse COPD’s disease progress. Alveolar macrophages (AMs) are the lungs’ dominant immune cells and perform critical functions, including fighting infection and tissue repair. Single-cell genomics technology can characterize AM phenotypes and reveal their roles in COPD. However, validating the relation between AM phenotypes and COPD clinical outcomes requires many patients, making the unscalable single-cell technology impractical to study such large cohorts. This issue motivated me to develop a cost-efficient approach to discover cell-phenotype biomarkers, using both high-resolution single-cell and low-cost bulk genomic technologies. I will develop novel statistical methods and software tools for this novel approach. The key deliverables are: 1) an experiment protocol, novel statistical methods, and the first software pipeline for cost-efficient deep-phenotyping of large clinical cohorts, to discover biomarkers for ANY diseases; 2) novel AM phenotype biomarkers as drug targets of immunotherapy for COPD or a genomics diagnostic test (medical device) to guide personalized COPD treatment.