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

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Developing multi-trait polygenic scores (PRS) enhances chronic obstructive pulmonary disease (COPD) prediction and identifies potential drug targets. This approach improves risk assessment for COPD and exacerbations.

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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 (PRSmulti).
  • Validated PRSmulti 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 (PRSmulti) demonstrated significant associations with COPD status and exacerbation frequency across cohorts.
  • PRSmulti 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.