期刊
NATURE GENETICS
卷 54, 期 1, 页码 40-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s41588-021-00962-4
关键词
-
资金
- Fondation Leducq [14CVD01]
- National Institutes of Health [1R01HL092577, R01HL128914, K24HL105780, R01HL134893, R01HL140224, 5K01HL140187, T32HL007208, 2R01HL092577, 1R01HL141434, 2U54HL120163, 1R01HL139731, K08HL159346]
- American Heart Association [18SFRN34110082, 18SFRN34250007]
- John S LaDue Memorial Fellowship
- Sarnoff Scholar Award
- Burroughs Wellcome Fund
- Fredman Fellowship for Aortic Disease
- Toomey Fund for Aortic Dissection Research
- Susan Eid Tumor Heterogeneity Initiative
Genome-wide association analyses identified variants associated with thoracic aortic diameter and polygenic score for ascending aortic diameter was correlated with a diagnosis of thoracic aortic aneurysm. Enlargement or aneurysm of the aorta predisposes to dissection, and a deep learning model along with genome-wide association studies successfully identified loci associated with ascending and descending thoracic aortic diameter, highlighting the potential for rapidly defining quantitative traits with deep learning in biomedical images.
Genome-wide association analyses identify variants associated with thoracic aortic diameter. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in independent samples. 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 x 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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据