Omic Risk Scores are Associated with COPD-related Traits Across Three Cohorts

Area of Science:

• Pulmonary Medicine
• Genomics
• Biomarker Discovery

Background:

• Chronic obstructive pulmonary disease (COPD) is characterized by significant variability in disease progression and outcomes.
• Omic risk scores (ORS) integrate multi-omic data (transcriptome, proteome, metabolome) to quantify biological complexity related to traits.

Purpose of the Study:

• To assess the predictive capability of blood-based omic risk scores (ORS) for chronic obstructive pulmonary disease (COPD) related traits.
• To evaluate ORS performance in both smoking-enriched and general population cohorts.

Main Methods:

• Developed and tested single- and multi-omic risk scores using RNA-sequencing, proteomic, and metabolomic data from 3,339 COPDGene participants.
• Trained ORS on 24 cross-sectional and five longitudinal COPD traits, focusing on disease severity, exacerbations, spirometry, and CT scan metrics.
• Externally validated ORS in SPIROMICS (n=2,177) and MESA (n=1,000) cohorts using multivariable models.

Main Results:

• A high proportion of single-omic ORS (69/72) significantly associated with cross-sectional COPD traits in the COPDGene cohort.
• Proteomic and metabolomic ORS demonstrated stronger associations with COPD traits compared to transcriptomic ORS.
• All tested cross-sectional ORS showed significant associations in the SPIROMICS cohort, and a majority (16/24) in the MESA cohort.

Conclusions:

• Blood-based omic risk scores effectively predict current and future COPD-related traits.
• ORS demonstrate predictive utility across diverse populations, including smoking-enriched and general cohorts.
• These findings support the use of ORS for understanding and potentially managing COPD heterogeneity.