Multi-trait polygenic scores for COPD and COPD exacerbations implicate druggable proteins

BACKGROUND. To construct multi-trait polygenic scores (PRS) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validate their performance in diverse cohorts, and identify PRS-related proteins for potential therapeutic targeting. METHODS. PRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRS multi ) in COPDGene non-Hispanic white participants (n=6,647). Associations of PRS multi with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n=2,466), ECLIPSE (n=1,858), MassGeneral Brigham Biobank (n=15,152), and All of Us (n=118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRS multi and were validated with proteomic data in COPDGene (n=5,173) and UK Biobank (n=5,012). RESULTS. PRSmix+ selected 7 traits for PRS multi . In multivariable models, PRS multi was associated with COPD status (meta-analysis random effects (RE) OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE beta 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRS multi outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRS that were also validated with measured protein levels in COPDGene and UK biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS. Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION. COPDGene: NCT00608764; ECLIPSE: NCT00292552.