Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction.
Kazuo MiyazawaShefali S VermaMasamichi ItoZhaonan ZouMasayuki KubotaSeitaro NomuraHiroshi MatsunagaSatoshi KoyamaHirotaka IekiMasato AkiyamaYoshinao KoikeRyo KurosawaHiroki YoshidaKouichi OzakiYoshihiro Onouchinull nullAtsushi TakahashiKoichi MatsudaYoshinori MurakamiHiroyuki AburataniMichiaki KuboYukihide MomozawaChikashi C TeraoShinya OkiHiroshi AkazawaYoichiro KamataniIssei KomuroPublished in: Nature genetics (2023)
Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9,826 cases among 150,272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77,690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrated ERRg as having a key role in the transcriptional regulation of AF-associated genes. A polygenic risk score derived from the cross-ancestry meta-analysis predicted increased risks of cardiovascular and stroke mortalities and segregated individuals with cardioembolic stroke in undiagnosed AF patients. Our results provide new biological and clinical insights into AF genetics and suggest their potential for clinical applications.
Keyphrases
- atrial fibrillation
- genome wide association study
- genome wide
- catheter ablation
- left atrial
- oral anticoagulants
- left atrial appendage
- direct oral anticoagulants
- genome wide analysis
- heart failure
- copy number
- systematic review
- immune response
- end stage renal disease
- dna methylation
- percutaneous coronary intervention
- rna seq
- gene expression
- newly diagnosed
- chronic kidney disease
- ejection fraction
- single cell
- peritoneal dialysis
- human health
- high glucose
- left ventricular
- toll like receptor
- acute coronary syndrome
- coronary artery disease
- genome wide identification
- deep learning
- meta analyses
- inflammatory response
- oxidative stress
- transcription factor
- patient reported outcomes
- electronic health record
- stress induced