Multi-Trait Polygenic Scores for COPD and COPD Exacerbations Implicate Druggable Proteins

  1. Chengyue Zhang
  2. Iain R. Konigsberg
  3. Yixuan He
  4. Jingzhou Zhang
  5. Tinashe Chikowore
  6. William B. Feldman
  7. Xiaowei Hu
  8. Yi Ding
  9. Bogdan Pasaniuc
  10. Diana Chang
  11. Qingwen Chen
  12. Jessica A. Lasky-Su
  13. Julian Hecker
  14. Martin D. Tobin
  15. Jing Chen
  16. Sean Kalra
  17. Katherine A. Pratte
  18. Hae Kyung Im
  19. Emily S. Wan
  20. Ani Manichaikul
  21. Edwin K. Silverman
  22. Russell P. Bowler
  23. Leslie A. Lange
  24. Victor E. Ortega
  25. Alicia R. Martin
  26. Michael H. Cho
  27. Matthew R. Moll
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Abstract

Objectives.

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.

Design

Prospective cohort studies.

Setting.

Genetic Epidemiology of COPD (COPDGene; 2007-present), Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE; 2005-2008), Mass General Brigham Biobank (MGBB; 2010-present), All of Us (2016-present), and UK Biobank (UKB; 2006-present).

Participants.

6,647 non-Hispanic White (NHW) and 2,466 African American (AA) participants from COPDGene; 1,858 participants from ECLIPSE; 118,566 from All of Us; 15,142 from MGBB with genetic data. 5,173 COPDGene and 5,012 UKB participants with proteomic data.

Main outcome measures.

COPD status (GOLD 2-4 vs. GOLD 0) and COPD exacerbation frequency.

Results.

PRSmix+, a multi-trait PRS framework, selected 7 traits for a composite PRS (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 AGER (RAGE), 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 .

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  1. Version published to 10.1101/2025.08.22.25334001 on medRxiv