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

Area of Science:

• Genetics and Genomics
• Pulmonary Medicine
• Precision Medicine

Background:

• Chronic obstructive pulmonary disease (COPD) poses a significant global health burden.
• Accurate prediction of COPD risk and exacerbations is crucial for effective management.
• Current predictive models may not fully capture the complex genetic and biological underpinnings of COPD.

Purpose of the Study:

• To develop and validate multi-trait polygenic scores (PRS) for predicting COPD and exacerbations.
• To identify PRS-associated proteins for potential therapeutic targeting in COPD.
• To assess the performance of multi-trait PRS compared to single-trait PRS.

Main Methods:

• Utilized PRSmix+, a multi-trait PRS framework, incorporating 7 traits into a composite PRS (PRS_multi).
• Validated PRS_multi in diverse prospective cohorts including COPDGene, ECLIPSE, All of Us, and UK Biobank.
• Integrated PRS with proteomic data to identify and validate PRS-related proteins, linking them to existing or investigational drugs.

Main Results:

• The composite PRS (PRS_multi) demonstrated significant associations with COPD status and exacerbation frequency across cohorts.
• PRS_multi outperformed traditional single-trait PRS in predictive accuracy.
• Identified 73 PRS-associated proteins, with 25 linked to druggable targets, including AGER, IL1RL1, and SCARF2.

Conclusions:

• Multi-trait PRS offers improved prediction of COPD and exacerbation risk.
• Integration of PRS with proteomic data successfully identifies novel, druggable therapeutic targets.
• This approach represents a promising strategy for advancing precision medicine in COPD management.