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
- oral anticoagulants
- left atrial
- left atrial appendage
- genome wide analysis
- direct oral anticoagulants
- systematic review
- copy number
- heart failure
- percutaneous coronary intervention
- immune response
- dna methylation
- endothelial cells
- single cell
- end stage renal disease
- newly diagnosed
- gene expression
- high glucose
- randomized controlled trial
- prognostic factors
- risk assessment
- machine learning
- toll like receptor
- genome wide identification
- mitral valve
- blood brain barrier
- data analysis
- big data
- deep learning
- patient reported