Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Background Short and long sleep duration have been linked with poorer cognitive outcomes, but it remains unclear whether these associations are causal. Methods We conducted the first Mendelian randomization (MR) study with 77 single-nucleotide polymorphisms (SNPs) for sleep duration using individual-participant data from the UK Biobank cohort (N = 395 803) and summary statistics from the International Genomics of Alzheimer’s Project (N cases/controls = 17 008/37 154) to investigate the potential impact of sleep duration on cognitive outcomes. Results Linear MR suggested that each additional hour/day of sleep was associated with 1% [95% confidence interval (CI) = 0–2%; P = 0.008] slower reaction time and 3% more errors in visual-memory test (95% CI = 0–6%; P = 0.05). There was little evidence to support associations of increased sleep duration with decline in visual memory [odds ratio (OR) per additional hour/day of sleep = 1.10 (95% CI = 0.76–1.57); P = 0.62], decline in reaction time [OR = 1.28 (95% CI = 0.49–3.35); P = 0.61], all-cause dementia [OR = 1.19 (95% CI = 0.65–2.19); P = 0.57] or Alzheimer’s disease risk [OR = 0.89 (95% CI = 0.67–1.18); P = 0.41]. Non-linear MR suggested that both short and long sleep duration were associated with poorer visual memory (P for non-linearity = 3.44e–9) and reaction time (P for non-linearity = 6.66e–16). Conclusions Linear increase in sleep duration has a small negative effect on reaction time and visual memory, but the true association might be non-linear, with evidence of associations for both short and long sleep duration. These findings suggest that sleep duration may represent a potential causal pathway for cognition.

The inner surfaces of the human heart are covered by a complex network of muscular strands that is thought to be a vestige of embryonic development. 1,2 The function of these trabeculae in adults and their genetic architecture are unknown. To investigate this we performed a genome-wide association study using fractal analysis of trabecular morphology as an image-derived phenotype in 18,096 UK Biobank participants. We identified 16 significant loci containing genes associated with haemodynamic phenotypes and regulation of cytoskeletal arborisation. 3,4 Using biomechanical simulations and human observational data, we demonstrate that trabecular morphology is an important determinant of cardiac performance. Through genetic association studies with cardiac disease phenotypes and Mendelian randomisation, we find a causal relationship between trabecular morphology and cardiovascular disease risk. These findings suggest an unexpected role for myocardial trabeculae in the function of the adult heart, identify conserved pathways that regulate structural complexity, and reveal their influence on susceptibility to disease. MainThe chambers of the mature human heart have a complex inner surface whose function is unknown. Unlike the smooth endothelium of the great vessels, the endocardial surfaces of both ventricles are lined by a fenestrated network of muscular trabeculae which extend into the cavity. Their embryological development is driven by highly-conserved signalling pathways involving the endocardium-myocardium and extra-cellular matrix that regulate myocardial proliferation during cardiac morphogenesis. 2,[5][6][7][8][9] 1 Cell lineage tracing suggests that trabeculae have a molecular and developmental identity which is distinct from the compact myocardium. 10 The high surface area of trabeculae enables nutrient and oxygen diffusion from blood pool to myocardium before the coronary circulation is established. 1 Trabeculae are also vital to formation of the conduction system. 11 Theoretical analyses have proposed that their complex structure may contribute to efficient intra-ventricular flow patterns. 12-14 While hypertrabeculation is observed as a feature of some genetically-characterised cardiomyopathies, 15 the physiological function of trabeculae in adult hearts, their genetic architecture, and potential role in common disease have not been determined.The distinguishing trait of trabeculae is their branching morphology and the degree of such biological complexity in the heart can be quantified by fractal dimension (FD) analysis of cardiac magnetic resonance (CMR) imaging. 8 In a replicated genomewide association study (GWAS), using FD as an image-derived phenotype, we identify loci linked with trabecular morphology. Knockout models of loci-associated genes showed a marked decrease in trabecular complexity. Using biomechanical modelling and human observational data, we find a causal relationship between myocardial trabeculation and ventricular performance, with Mendelian randomisation showing that reduced trabecula...

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Background-There is debate concerning whether an aneurysmal ascending aorta should be replaced when associated with a dysfunctioning aortic valve that is to be replaced. To examine this issue, we divided the patients by type of aortic valve dysfunction-either aortic stenosis (AS) or pure aortic regurgitation (AR)-something not previously undertaken. Methods and Results-Of 122 patients with ascending aortic aneurysm (unassociated with aortitis or acute dissection), the aortic valve was congenitally malformed (unicuspid or bicuspid) in 58 (98%) of the 59 AS patients, and in 38 (60%) of the 63 pure AR patients. Ascending aortic medial elastic fiber loss (EFL) (graded 0 to 4ϩ) was zero or 1ϩ in 53 (90%) of the AS patients, in 20 (53%) of the 38 AR patients with bicuspid valves, and in all 12 AR patients with tricuspid valves unassociated with the Marfan syndrome. An unadjusted analysis showed that, among the 96 patients with congenitally malformed valves, the 38 AR patients had a significantly higher likelihood of 2ϩ to 4ϩ EFL than the 58 AS patients (crude odds ratio: 8.78; 95% confidence interval: 2.95, 28.13). Conclusions-These data strongly suggest that the type of aortic valve dysfunction-AS versus pure AR-is very helpful in predicting loss of aortic medial elastic fibers in patients with ascending aortic aneurysms and aortic valve disease. (Circulation. 2011;123:896-903.)

Background: Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets. Methods: We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of four population-based studies, comprising a total of 3,019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization (MR), using cis -protein quantitative loci genetic instruments identified from genome-wide association studies (GWAS) in over 30,000 individuals. To improve the precision of causal estimates, we implemented an MR model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and MR models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait MR analysis. Results: 44/90 proteins were positively associated with risk of incident HF (P < 6.0 x 10-4). Among these, eight proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23) and MMP-12 (Matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1. Conclusions: We identified 44 circulating proteins that were associated with incident HF, of which eight showed evidence of a causal relationship and seven were druggable, including adrenomedullin which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.

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