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Omic Risk Scores are Associated with COPD-related Traits Across Three Cohorts
Iain R Konigsberg1, Luciana B Vargas1, Katherine A Pratte2
1Department of Biomedical Informatics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Background:
Chronic obstructive pulmonary disease (COPD) exhibits marked heterogeneity in lung function decline, mortality, exacerbations, and other disease-related outcomes. Omic risk scores (ORS) estimate the cumulative contribution of omics, such as the transcriptome, proteome, and metabolome, to a particular trait. This study evaluates the predictive value of ORS for COPD-related traits in both smoking-enriched and general population cohorts.
Methods:
ORS were developed and tested in 3,339 participants of Genetic Epidemiology of COPD (COPDGene) with blood RNA-sequencing, proteomic, and metabolomic. Single- and multi-omic risk scores were trained 24 cross-sectional and five longitudinal traits using 80% of the data, focusing on disease severity, exacerbations, and traits from spirometry and computed tomography scans. Multivariable models were used to test ORS associations with outcomes in remaining COPDGene participants and externally validated in SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) (n = 2,177) and Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,000).
Results:
In the COPDGene testing set, 69 of 72 single-omic ORS showed significant associations with 24 cross-sectional traits (adjusted p-value < 0·05). One of 15 longitudinal ORS was associated with changes in trait values between COPDGene visits. Significant associations were observed for all 38 cross-sectional ORS tested in SPIROMICS and for 16 of 24 in MESA. Proteomic and metabolomic risk scores generally displayed stronger associations than transcriptomic scores.
Discussion:
Blood-based ORS can predict cross-sectional and future COPD-related traits in both smoking-enriched and general population cohorts.
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