Faculty, Staff and Student Publications
Language
English
Publication Date
5-1-2025
Journal
JACC: Advances
DOI
10.1016/j.jacadv.2025.101743
PMID
40447339
PMCID
PMC12235483
PubMedCentral® Posted Date
5-28-2025
PubMedCentral® Full Text Version
Post-print
Abstract
Background: Thoracic aortic dissection is a life-threatening condition that often occurs in the presence of aortic dilation. However, currently there are limited clinical risk factors beyond aortic diameter (AoD) used to determine individual-level dissection risk.
Objectives: The purpose of this study was to determine whether common variant genetics can be used to improve identification of individuals most at risk for dissection.
Methods: A genome-wide association study (GWAS)-by-subtraction was performed to characterize the diameter-independent genetics of thoracic aortic dissection by subtracting a GWAS of AoD from a GWAS of thoracic aortic aneurysm and dissection. A polygenic risk score (PRS) was calculated using the PRS-Continuous Shrinkage statistical package and applied to Penn Medicine BioBank participants. Statistical analysis was performed in R version 4.3.2.
Results: We identified 43 genetic risk loci associated with dissection and derived a "Dissection-PRS" from our GWAS-by-subtraction. In the Penn Medicine BioBank, the Dissection-PRS associated with prevalent dissection (OR: 2.13 per 1 SD increase in Dissection-PRS; 95% CI: 1.91-2.39; P < 0.001). When adjusting for risk factors including AoD, the association of the Dissection-PRS with prevalent dissection was attenuated but remained statistically robust (OR: 1.62 per 1 SD increase in PRS; 95% CI: 1.36-1.94; P < 0.001). The addition of the PRS to a model containing age, sex, and clinical risk factors substantially improved model discrimination (base model area under the receiver operator characteristic curve = 0.676; 95% CI: 0.651-0.702; with addition of PRS area under the receiver operator characteristic curve = 0.723; 95% CI: 0.702-0.744).
Conclusions: A common-variant PRS can predict aortic dissection in a diverse population.
Keywords
aortic dilation, polygenic risk, predictive modeling, thoracic aortic dissection
Published Open-Access
yes
Recommended Citation
DePaolo, John; Zamirpour, Siavash; Abramowitz, Sarah; et al., "Predicting Thoracic Aortic Dissection in a Diverse Biobank Using a Polygenic Risk Score" (2025). Faculty, Staff and Student Publications. 6269.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6269
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