Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation
- PMID: 39324273
- PMCID: PMC11540195
- DOI: 10.1161/CIRCGEN.123.004512
Polygenic Scoring for Detection of Ascending Thoracic Aortic Dilation
Abstract
Background: Ascending thoracic aortic dilation is a complex heritable trait that involves modifiable and nonmodifiable risk factors. Polygenic scores (PGS) are increasingly used to assess risk for complex diseases. The degree to which a PGS can improve aortic diameter prediction in diverse populations is unknown. Presently, we tested whether adding a PGS to clinical prediction algorithms improves performance in a diverse biobank.
Methods: The analytic cohort comprised 6235 Penn Medicine Biobank participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a genome-wide association study of thoracic aortic diameter performed in the UK Biobank and were compared with the performance of the previously published aorta optimized regression for thoracic aneurysm (AORTA) score.
Results: Cohort participants had a median age of 61 years (IQR, 53-70) and a mean ascending aortic diameter of 3.36 cm (SD, 0.49). Fifty-five percent were male, and 33% were genetically similar to an African reference population. Compared with the AORTA score, which explained 30.6% (95% CI, 29.9%-31.4%) of the variance in aortic diameter, AORTA score+UK Biobank-derived PGS explained 33.1%, (95% CI, 32.3%-33.8%), the reweighted AORTA score explained 32.5% (95% CI, 31.8%-33.2%), and the reweighted AORTA score+UK Biobank-derived PGS explained 34.9% (95% CI, 34.2%-35.6%). When stratified by population, models including the UK Biobank-derived PGS consistently improved upon the clinical AORTA score among individuals genetically similar to a European reference population but conferred minimal improvement among individuals genetically similar to an African reference population. Comparable performance disparities were observed in models developed to discriminate cases/noncases of thoracic aortic dilation (≥4.0 cm).
Conclusions: We demonstrated that inclusion of a UK Biobank-derived PGS to the AORTA score confers a clinically meaningful improvement in model performance only among individuals genetically similar to European reference populations and may exacerbate existing health care disparities.
Keywords: Bayesian analysis; aortic dilation; polygenic risk score; statistical models; thoracic aorta.
Conflict of interest statement
Dr Levin receives research support to his institution from MyOme outside of this work. Dr Damrauer receives research support to his institution from RenalytixAI and in kind support from Novo Nordisk, both outside of this work. Dr Damrauer is named as a co-inventor on a government-owned US Patent application related to the use of genetic risk prediction for venous thromboembolic disease filed by the US Department of Veterans Affairs in accordance with Federal regulatory requirements.
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