Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.
Nat Genet
; 56(7): 1412-1419, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38862854
ABSTRACT
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Doença da Artéria Coronariana
/
Predisposição Genética para Doença
/
Aprendizado de Máquina
Limite:
Female
/
Humans
Idioma:
En
Revista:
Nat Genet
Assunto da revista:
GENETICA MEDICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos