Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk ...factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.
BACKGROUND:The cells that form the arterial wall contribute to multiple vascular diseases. The extent of cellular heterogeneity within these populations has not been fully characterized. Recent ...advances in single-cell RNA-sequencing make it possible to identify and characterize cellular subpopulations.
METHODS:We validate a method for generating a droplet-based single-cell atlas of gene expression in a normal blood vessel. Enzymatic dissociation of 4 whole mouse aortas was followed by single-cell sequencing of >10 000 cells.
RESULTS:Clustering analysis of gene expression from aortic cells identified 10 populations of cells representing each of the main arterial cell typesfibroblasts, vascular smooth muscle cells, endothelial cells (ECs), and immune cells, including monocytes, macrophages, and lymphocytes. The most significant cellular heterogeneity was seen in the 3 distinct EC populations. Gene set enrichment analysis of these EC subpopulations identified a lymphatic EC cluster and 2 other populations more specialized in lipoprotein handling, angiogenesis, and extracellular matrix production. These subpopulations persist and exhibit similar changes in gene expression in response to a Western diet. Immunofluorescence for Vcam1 and Cd36 demonstrates regional heterogeneity in EC populations throughout the aorta.
CONCLUSIONS:We present a comprehensive single-cell atlas of all cells in the aorta. By integrating expression from >1900 genes per cell, we are better able to characterize cellular heterogeneity compared with conventional approaches. Gene expression signatures identify cell subpopulations with vascular disease–relevant functions.
Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased morbidity. As the population ages and the prevalence of AF continues to rise, the socioeconomic consequences of ...AF will become increasingly burdensome. Although there are well-defined clinical risk factors for AF, a significant heritable component is also recognized. To identify the molecular basis for the heritability of AF, investigators have used a combination of classical Mendelian genetics, candidate gene screening, and genome-wide association studies. However, these avenues have, as yet, failed to define the majority of the heritability of AF. The goal of this review is to describe the results from both candidate gene and genome-wide studies, as well as to outline potential future avenues for creating a more complete understanding of AF genetics. Ultimately, a more comprehensive view of the genetic underpinnings for AF will lead to the identification of novel molecular pathways and improved risk prediction of this complex arrhythmia.
BACKGROUND:The human heart requires a complex ensemble of specialized cell types to perform its essential function. A greater knowledge of the intricate cellular milieu of the heart is critical to ...increase our understanding of cardiac homeostasis and pathology. As recent advances in low-input RNA sequencing have allowed definitions of cellular transcriptomes at single-cell resolution at scale, we have applied these approaches to assess the cellular and transcriptional diversity of the nonfailing human heart.
METHODS:Microfluidic encapsulation and barcoding was used to perform single nuclear RNA sequencing with samples from 7 human donors, selected for their absence of overt cardiac disease. Individual nuclear transcriptomes were then clustered based on transcriptional profiles of highly variable genes. These clusters were used as the basis for between-chamber and between-sex differential gene expression analyses and intersection with genetic and pharmacologic data.
RESULTS:We sequenced the transcriptomes of 287 269 single cardiac nuclei, revealing 9 major cell types and 20 subclusters of cell types within the human heart. Cellular subclasses include 2 distinct groups of resident macrophages, 4 endothelial subtypes, and 2 fibroblast subsets. Comparisons of cellular transcriptomes by cardiac chamber or sex reveal diversity not only in cardiomyocyte transcriptional programs but also in subtypes involved in extracellular matrix remodeling and vascularization. Using genetic association data, we identified strong enrichment for the role of cell subtypes in cardiac traits and diseases. Intersection of our data set with genes on cardiac clinical testing panels and the druggable genome reveals striking patterns of cellular specificity.
CONCLUSIONS:Using large-scale single nuclei RNA sequencing, we defined the transcriptional and cellular diversity in the normal human heart. Our identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases.
Organ-specific functions of tissue-resident macrophages in the steady-state heart are unknown. Here, we show that cardiac macrophages facilitate electrical conduction through the distal ...atrioventricular node, where conducting cells densely intersperse with elongated macrophages expressing connexin 43. When coupled to spontaneously beating cardiomyocytes via connexin-43-containing gap junctions, cardiac macrophages have a negative resting membrane potential and depolarize in synchrony with cardiomyocytes. Conversely, macrophages render the resting membrane potential of cardiomyocytes more positive and, according to computational modeling, accelerate their repolarization. Photostimulation of channelrhodopsin-2-expressing macrophages improves atrioventricular conduction, whereas conditional deletion of connexin 43 in macrophages and congenital lack of macrophages delay atrioventricular conduction. In the Cd11bDTR mouse, macrophage ablation induces progressive atrioventricular block. These observations implicate macrophages in normal and aberrant cardiac conduction.
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•Tissue-resident macrophages abound in the mouse and human AV nodes•Connexin 43 connects macrophages with cardiomyocytes•Macrophages modulate the electrical activity of cardiomyocytes•Macrophages assist normal AV nodal conduction
Heart-resident macrophages directly modulate the electrical properties of cardiomyocytes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Genetic variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many ...variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.
Summary Background Comprehensive long-term data on atrial fibrillation trends in men and women are scant. We aimed to provide such data through analysis of the Framingham cohort over 50 years. ...Methods We investigated trends in incidence, prevalence, and risk factors for atrial fibrillation and its association with stroke and mortality after onset in 9511 participants enrolled in the Framingham Heart Study between 1958 and 2007. We analysed trends within 10 year groups (1958–67, 1968–77, 1978–87, 1988–97, and 1998–2007), stratified by sex. Findings During 50 years of observation (202 417 person-years), 1544 cases of new-onset atrial fibrillation occurred (of whom 723 47% were women). Between 1958–67 and 1998–2007, age-adjusted prevalence of atrial fibrillation quadrupled from 20·4 to 96·2 cases per 1000 person-years in men and from 13·7 to 49·4 cases per 1000 person-years in women; age-adjusted incidence increased from 3·7 to 13·4 new cases per 1000 person-years in men and from 2·5 to 8·6 new cases per 1000 person-years in women (ptrend <0·0001 for all comparisons). For atrial fibrillation diagnosed by electrocardiograph (ECG) during routine Framingham examinations, age-adjusted prevalence per 1000 person-years increased (12·6 in 1958–67 to 25·7 in 1998–2007 in men, ptrend =0·0007; 8·1 to 11·8 in women, ptrend =0·009). However, age-adjusted incidence of atrial fibrillation by Framingham Heart Study ECGs did not change significantly with time. Although the prevalence of most risk factors changed over time, their associated hazards for atrial fibrillation changed little. Multivariable-adjusted proportional hazards models revealed a 74% (95% CI 50–86%) decrease in stroke (hazards ratio HR 3·77, 95% CI 1·98–7·20 in 1958–1967 compared with 1998–2007; ptrend =0·0001) and a 25% (95% CI −3–46%) decrease in mortality (HR 1·34, 95% CI 0·97–1·86 in 1958–1967 compared with 1998–2007; ptrend =0·003) in 20 years following atrial fibrillation onset. Interpretation Trends of increased incidence and prevalence of atrial fibrillation in the community were probably partly due to enhanced surveillance. Measures are needed to enhance early detection of atrial fibrillation, through increased awareness coupled with targeted screening programmes and risk factor-specific prevention. Funding NIH, NHLBI, NINDS, Deutsche Forschungsgemeinschaft.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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