Key result
The AORTA Gene model, incorporating a polygenic score, explained 39.9% of the variance in thoracic aortic diameter compared to 29.2% for clinical factors alone in the UK Biobank.
Why the study?
Thoracic aortic disease is a major cause of morbidity and mortality with heritable diameter risk, prompting evaluation of polygenic prediction.
Does a polygenic prediction score improve the detection of thoracic aortic aneurysm compared to clinical factors alone?
Observational (n=57,316)
Yes
Does a polygenic prediction score improve the detection of thoracic aortic aneurysm compared to clinical factors alone?
Absolute Event Rate: 39.9% vs 29.2%
p-value: p=2.6E-551
The addition of a polygenic score to clinical risk factors significantly improves the prediction of ascending thoracic aortic diameter and the detection of aortic aneurysms ≥4cm.
Polygenic scores may enhance aortic aneurysm detection beyond clinical factors alone; leaves open prospective validation before practice change.
Background Thoracic aortic disease is an important cause of morbidity and mortality in the US, and aortic diameter is a heritable contributor to risk. Could a polygenic prediction of ascending aortic diameter improve detection of aortic aneurysm? Methods Deep learning was used to measure ascending thoracic aortic diameter in 49,939 UK Biobank participants. A genome-wide association study (GWAS) was conducted in 39,524 participants and leveraged to build a 1.1 million-variant polygenic score with PRScs-auto . Aortic diameter prediction models were built with the polygenic score (“AORTA Gene”) and without it. The models were tested in a held-out set of 4,962 UK Biobank participants and externally validated in 5,469 participants from Mass General Brigham Biobank (MGB), 1,298 from the Framingham Heart Study (FHS), and 610 participants from All of Us . Results In each test set, the AORTA Gene model explained more of the variance in thoracic aortic diameter compared to clinical factors alone: 39.9% (95% CI 37.8-42.0%) vs 29.2% (95% CI 27.1-31.4%) in UK Biobank, 36.5% (95% CI 34.4-38.5%) vs 32.5% (95% CI 30.4-34.5%) in MGB, 41.8% (95% CI 37.7-45.9%) vs 33.0% (95% CI 28.9-37.2%) in FHS, and 34.9% (95% CI 28.8-41.0%) vs 28.9% (95% CI 22.9-35.0%) in All of Us . AORTA Gene had a greater AUROC for identifying diameter ≥4cm in each test set: 0.834 vs 0.765 (P=7.3E-10) in UK Biobank, 0.808 vs 0.767 in MGB (P=4.5E-12), 0.856 vs 0.818 in FHS (P=8.5E-05), and 0.827 vs 0.791 (P=7.8E-03) in All of Us . Conclusions Genetic information improved estimation of thoracic aortic diameter when added to clinical risk factors. Larger and more diverse cohorts will be needed to develop more powerful and equitable scores.
No takes yet. Share an insight, caveat, or question.
Pirruccello et al. (2023) conducted an observational in Thoracic aortic aneurysm (n=57,316). AORTA Gene model (polygenic score plus clinical factors) vs. Clinical factors alone (AORTA Score) was evaluated on Variance explained (R2) in ascending aortic diameter (95% CI 37.8-42.0, p=2.6E-551). The AORTA Gene model, incorporating a polygenic score, explained 39.9% of the variance in thoracic aortic diameter compared to 29.2% for clinical factors alone in the UK Biobank.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: