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AORTA Gene Score for Ascending Aortic Dilation
Quick Takes
- Incorporating both an aortic polygenic score and clinical covariates improved estimation of ascending aortic diameter and identification of aortic dilation as compared to a clinical model built with the same nongenetic covariates.
- Furthermore, adding genetic covariates was also more informative for risk of adverse thoracic aortic events including thoracic aortic dissection and aneurysm.
- These data support integrating genetic information into a clinical model to improve estimation of ascending aortic diameter, the identification of individuals with thoracic aortic dilation, and estimation of risk of adverse thoracic aortic events including thoracic aortic dissection.
Study Questions:
Does incorporating polygenic risk into a clinical model improve estimation of ascending aortic diameter and the ascertainment of aneurysm as well as thoracic aortic dissection beyond clinical factors alone?
Methods:
The investigators built aortic diameter estimation models with a 1.1 million-variant polygenic score (AORTA Gene) and without it. Models were validated internally in 4,394 UK Biobank participants and externally in 5,469 individuals from Mass General Brigham (MGB) Biobank, 1,298 from the Framingham Heart Study (FHS), and 610 from All of Us. Model fit for adverse thoracic aortic events was compared in 401,453 UK Biobank and 164,789 All of Us participants. The primary outcome was correlation between the scores and ascending aortic diameter using linear models, expressed as R2 (variance explained). Secondary outcomes in the imaging cohorts included tests of calibration and performance for identifying ascending aortic diameter ≥4.0 cm.
Results:
AORTA Gene explained more of the variance in thoracic aortic diameter compared to clinical factors alone: 39.5% (95% confidence interval [CI], 37.3%–41.8%) vs. 29.3% (27.0%–31.5%) in UK Biobank, 36.5% (34.4%–38.5%) vs. 32.5% (30.4%–34.5%) in MGB, 41.8% (37.7%–45.9%) vs. 33.0% (28.9%–37.2%) in FHS, and 34.9% (28.8%–41.0%) vs. 28.9% (22.9%–35.0%) in All of Us. AORTA Gene had a greater area under the receiver operating characteristic curve for identifying diameter ≥4 cm: 0.836 vs. 0.776 (p < 0.0001) in UK Biobank, 0.808 vs. 0.767 in MGB (p < 0.0001), 0.856 vs. 0.818 in FHS (p < 0.0001), and 0.827 vs. 0.791 (p = 0.0078) in All of Us. AORTA Gene was more informative for adverse thoracic aortic events in UK Biobank (p = 0.0042) and All of Us (p = 0.049).
Conclusions:
The authors report that a comprehensive model incorporating polygenic information and clinical risk factors explained 34.9%–41.8% of the variation in ascending aortic diameter, improving the identification of ascending aortic dilation and adverse thoracic aortic events compared to clinical risk factors.
Perspective:
This study reports that incorporating both an aortic polygenic score and clinical covariates improved estimation of ascending aortic diameter and identification of aortic dilation as compared to a clinical model built with the same nongenetic covariates. Furthermore, adding genetic covariates was also more informative for risk of adverse thoracic aortic events including thoracic aortic dissection and aneurysm diagnoses in the UK Biobank and All of Us participants. These data support integrating genetic information into a clinical model to improve estimation of ascending aortic diameter, the identification of individuals with thoracic aortic dilation, and estimation of risk of adverse thoracic aortic events including thoracic aortic dissection.
Clinical Topics: Arrhythmias and Clinical EP, Vascular Medicine, Genetic Arrhythmic Conditions, Prevention
Keywords: Aneurysm, Dissecting, Aorta, Thoracic, Genetics, Risk
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