Atrial fibrillation (AF) affects over 33 million individuals worldwide1 and has a complex heritability.2 We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Biosensors, Aarhus University Hospital, and participating sites.

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death.1,2 Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups.3–7 To further define the genetic basis of atrial fibrillation, we performed large-scale, multi-racial meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 18,398 individuals with atrial fibrillation and 91,536 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,806 cases and 132,612 referents. We identified 12 novel genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate new potential targets for drug discovery.8

MD; for the Nordic-Baltic PCI Study GroupBackground-It is unknown whether the preferred 1-stent bifurcation stenting approach with stenting of the main vessel (MV) and optional side branch stenting using drug-eluting stents should be finalized by a kissing balloon dilatation (FKBD). Therefore, we compared strategies of MV stenting with and without FKBD. Methods and Results-We randomized 477 patients with a bifurcation lesion to FKBD (nϭ238) or no FKBD (nϭ239) after MV stenting. The primary end point was major adverse cardiac events: cardiac death, non-procedure-related index lesion myocardial infarction, target lesion revascularization, or stent thrombosis within 6 months. The 6-month major adverse cardiac event rates were 2.1% and 2.5% (Pϭ1.00) in the FKBD and no-FKBD groups, respectively. Procedure and fluoroscopy times were longer and more contrast media was needed in the FKBD group than in the no-FKBD group. Three hundred twenty-six patients had a quantitative coronary assessment. At 8 months, the rate of binary (re)stenosis in the entire bifurcation lesion (MV and side branch) was 11.0% versus 17.3% (Pϭ0.11), in the MV was 3.1% versus 2.5% (Pϭ0.68), and in the side branch was 7.9% versus 15.4% (Pϭ0.039) in the FKBD versus no-FKBD groups, respectively. In patients with true bifurcation lesions, the side branch restenosis rate was 7.6% versus 20.0% (Pϭ0.024) in the FKBD and no-FKBD groups, respectively. Conclusions-MV

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (−0.74