Cardiac imaging of aortic valve area from 26,142 UK Biobank participants reveal novel genetic associations and shared genetic comorbidity with multiple disease phenotypes
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Le résumé fourni par la source
ABSTRACT The aortic valve is an important determinant of cardiovascular physiology and anatomic location of common human diseases. From a sample of 26,142 European-ancestry participants, we estimated functional aortic valve area by planimetry from prospectively obtained cardiac MRI sequences of the aortic valve. A genome-wide association study of aortic valve area in these UK Biobank participants showed two significant associations indexed by rs71190365 (chr13:50764607, DLEU1, p =1.8×10 −9 ) and rs35991305 (chr12:94191968, CRADD, p =3.4×10 −8 ). From the GWAS findings we constructed a polygenic risk score for aortic valve area, which in a separate cohort of 311,728 individuals without imaging demonstrated that smaller aortic valve area is predictive of increased risk for aortic valve disease (Odds Ratio 0.88, p =2.3×10 −6 ). After excluding subjects with a medical diagnosis of aortic valve stenosis (remaining n=310,546 individuals), phenome-wide association of >10,000 traits showed multiple links between the polygenic score for aortic valve disease and key health-related comorbidities involving the cardiovascular system and autoimmune disease. Genetic correlation analysis supports a shared genetic etiology with between aortic valve size and birthweight along with other cardiovascular conditions. These results illustrate the use of automated phenotyping of cardiac imaging data from the general population to investigate the genetic etiology of aortic valve disease, perform clinical prediction, and uncover new clinical and genetic correlates of cardiac anatomy.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Cardiac imaging of aortic valve area from 26,142 UK Biobank participants reveal novel genetic associations and shared genetic comorbidity with multiple disease phenotypes
- Date Crossref
- 14/04/2020
- Éditeur
- openRxiv
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
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