Characteristics and 2-year outcomes of dabigatran treatment in patients with heart failure and atrial fibrillation: GLORIA-AF

Aims This study aimed to describe baseline characteristics of patients with atrial fibrillation (AF) at risk of stroke with and without history of heart failure (HF) and report 2-year outcomes in the dabigatran-treated subset of a prospective, global, observational study (GLORIA-AF).Methods and results Newly diagnosed patients with AF and CHA(2)DS(2)-VASc score >= 1 were consecutively enrolled. Baseline characteristics were assessed by the presence or absence of HF diagnosis at enrolment. Incidence rates for outcomes in dabigatran-treated patients were estimated with and without standardization by stroke (excluding HF component) and bleeding risk scores. A total of 15 308 eligible patients were enrolled, including 15 154 with known HF status; of these, 3679 (24.0%) had been diagnosed with HF, 11 475 (75.0%) had not. Among 4873 dabigatran-treated patients, 1169 (24.0%) had HF, and 3658 (75.1%) did not; the risk of stroke was high (CHA(2)DS(2)-VASc score >= 2) for 94.3% of patients with HF and 85.8% without, while 6.0% and 7.0%, respectively, had a high bleeding risk (HAS-BLED >= 3). Incidence rates of all-cause death in dabigatran-treated patients with and without HF, standardized for CHA(2)DS(2)-VASc and HAS-BLED scores, were 4.76 vs. 1.80 per 100 patient years (py), with roughly comparable rates of stroke (0.82 vs. 0.60 per 100 py) and major bleeding (1.20 vs. 0.92 per 100 py).Conclusions Patients with AF and history of HF may have greater disease burden at AF diagnosis and increased mortality rates vs. patients without HF. Stroke and major bleeding rates were roughly comparable between groups confirming the long-term safety and effectiveness of dabigatran in patients with HF.Thrombosis and Hemostasi

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (n(DM) = 178,691, n(noDM) = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes <sup>1</sup> . Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel <sup>2</sup> ) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries