Deep learning enables genetic analysis of the human thoracic aorta
Open accessPublished version of a preprint
Abstract
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 × 10-20). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.
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The AFAP1 locus was recently associated with descending thoracic aorta diameter by GWAS.
“This locus was recently associated with descending thoracic aorta diameter by GWAS33.”
From Integrative genomic analyses identify candidate causal genes for calcific aortic valve stenosis involving tissue-specific regulation (2024) · cites this paper as [33]
The Results section (‘GWAS of thoracic aortic diameter’; page unavailable) reports 47 loci associated with descending aortic diameter, but the passages retrieved from our copy do not identify AFAP1 as one of them. Searches for AFAP1 and for the descending-aorta locus table did not establish the claimed locus-specific association. (LLM, conf=0.70)
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References 104 · Cited by 210
- Authors
- Pirruccello, J. P., Chaffin, M. D., Chou, E. L., Fleming, S. J., Lin, H., Nekoui, M., Khurshid, S., Friedman, S. F., Bick, A. G., Arduini, A., Weng, L.-C., Choi, S. H., Akkad, A.-D., Batra, P., Tucker, N. R., Hall, A. W., Roselli, C., Benjamin, E. J., Vellarikkal, S. K., Gupta, R. M., Stegmann, C. M., Juric, D., Stone, J. R., Vasan, R. S., Ho, J. E., Hoffmann, U., Lubitz, S. A., Philippakis, A. A., Lindsay, M. E., & Ellinor, P. T.
- Affiliations
- Broad Institute (US)
- Massachusetts General Hospital (US)
- Boston University (US)
- Masonic Medical Research Laboratory (US)
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Corresponding author
- Ellinor, Patrick T.
- ORCID
- Pirruccello, James P.
- Chaffin, Mark D.
- Chou, Elizabeth L.
- Fleming, Stephen J.
- Lin, Honghuang
- Nekoui, Mahan
- Khurshid, Shaan
- Bick, Alexander G.
- Arduini, Alessandro
- Weng, Lu-Chen
- Choi, Seung Hoan
- Akkad, Amer-Denis
- Batra, Puneet
- Tucker, Nathan R.
- Hall, Amelia W.
- Roselli, Carolina
- Benjamin, Emelia J.
- Vellarikkal, Shamsudheen K.
- Gupta, Rajat M.
- Stegmann, Christian M.
- Juric, Dejan
- Stone, James R.
- Vasan, Ramachandran S.
- Ho, Jennifer E.
- Hoffmann, Udo
- Lubitz, Steven A.
- Philippakis, Anthony A.
- Lindsay, Mark E.
- Ellinor, Patrick T.
- Venue
- Nature Genetics
- Published
- 2021-11-26
- Volume
- 54
- Issue
- 1
- Pages
- 40-51
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC8758523
- OpenAlex
- W3216026604
- Cited by
- 210
- References
- 104
- Citations by year
- 2026: 37 · 2025: 43 · 2024: 47 · 2023: 41 · 2022: 33 · 2021: 8 · 2020: 1
- FWCI
- 18.50
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- Fondation Leducq (14CVD01)
- U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (1RO1HL092577, R01HL128914, K24HL105780, T32HL007208, 5K01HL140187, 2R01HL092577, 1R01HL141434, R01HL134893, R01HL140224, 1R01HL139731)
- American Heart Association (Strategically Focused Research Networks, 18SFRN34110082)
- John S LaDue Memorial Fellowship
- Career Award for Medical Scientists from the Burroughs Wellcome Fund
- The Fredman Fellowship for Aortic DiseaseThe Toomey Fund for Aortic Dissection Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Aortic Disease and Treatment Approaches
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Connective tissue disorders research
- Keywords
- thoracic aorta, aortic diameter, thoracic aortic aneurysm, aortic dissection, ascending aorta, descending aorta, cardiac magnetic resonance imaging, deep learning, genome-wide association study, transcriptome-wide association study, rare variant burden, polygenic risk score, UK Biobank, genetic loci
- MeSH terms
- Biological Variation, Population, Deep Learning, Adult, Aged, Aorta, Thoracic, Aortic Aneurysm, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Quantitative Trait Loci, Genome-Wide Association Study, Transcriptome
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