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.
IMPORTANCE: Atrial fibrillation (AF) is the most common arrhythmia affecting 1% of the population. Young individuals with AF have a strong genetic association with the disease, but the mechanisms ...remain incompletely understood. OBJECTIVE: To perform large-scale whole-genome sequencing to identify genetic variants related to AF. DESIGN, SETTING, AND PARTICIPANTS: The National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine Program includes longitudinal and cohort studies that underwent high-depth whole-genome sequencing between 2014 and 2017 in 18 526 individuals from the United States, Mexico, Puerto Rico, Costa Rica, Barbados, and Samoa. This case-control study included 2781 patients with early-onset AF from 9 studies and identified 4959 controls of European ancestry from the remaining participants. Results were replicated in the UK Biobank (346 546 participants) and the MyCode Study (42 782 participants). EXPOSURES: Loss-of-function (LOF) variants in genes at AF loci and common genetic variation across the whole genome. MAIN OUTCOMES AND MEASURES: Early-onset AF (defined as AF onset in persons <66 years of age). Due to multiple testing, the significance threshold for the rare variant analysis was P = 4.55 × 10−3. RESULTS: Among 2781 participants with early-onset AF (the case group), 72.1% were men, and the mean (SD) age of AF onset was 48.7 (10.2) years. Participants underwent whole-genome sequencing at a mean depth of 37.8 fold and mean genome coverage of 99.1%. At least 1 LOF variant in TTN, the gene encoding the sarcomeric protein titin, was present in 2.1% of case participants compared with 1.1% in control participants (odds ratio OR, 1.76 95% CI, 1.04-2.97). The proportion of individuals with early-onset AF who carried a LOF variant in TTN increased with an earlier age of AF onset (P value for trend, 4.92 × 10−4), and 6.5% of individuals with AF onset prior to age 30 carried a TTN LOF variant (OR, 5.94 95% CI, 2.64-13.35; P = 1.65 × 10−5). The association between TTN LOF variants and AF was replicated in an independent study of 1582 patients with early-onset AF (cases) and 41 200 control participants (OR, 2.16 95% CI, 1.19-3.92; P = .01). CONCLUSIONS AND RELEVANCE: In a case-control study, there was a statistically significant association between an LOF variant in the TTN gene and early-onset AF, with the variant present in a small percentage of participants with early-onset AF (the case group). Further research is necessary to understand whether this is a causal relationship.
Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of ...rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
BACKGROUND:The relationship between cholesterol levels and risk of venous thromboembolism (VTE) is uncertain. We set out to determine the effect of PCSK9 (proprotein convertase subtilisin/kexin type ...9) inhibition on the risk of VTE, explore potential mechanisms, and examine the efficacy in subgroups with clinically and genetically defined risk.
METHODS:We performed a post hoc analysis of the FOURIER trial (Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk) testing whether evolocumab reduces the risk of VTE events (deep venous thrombosis or pulmonary embolism). Data from FOURIER and ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment with Alirocumab) were then combined in a meta-analysis to assess the class effect of PCSK9 inhibition on the risk of VTE. We also analyzed baseline lipids in FOURIER to investigate potential mechanisms explaining the reduction in VTE with evolocumab. Last, an exploratory genetic analysis was performed in FOURIER to determine whether a VTE polygenic risk score could identify high-risk patients who would derive the greatest VTE reduction from evolocumab.
RESULTS:In FOURIER, the hazard ratio (HR) for VTE with evolocumab was 0.71 (95% CI, 0.50–1.00; P=0.05), with no effect in the 1st year (HR, 0.96 95% CI, 0.57–1.62) but a 46% reduction (HR, 0.54 95% CI, 0.33–0.88; P=0.014) beyond 1 year. A meta-analysis of FOURIER and ODYSSEY OUTCOMES demonstrated a 31% relative risk reduction in VTE with PCSK9 inhibition (HR, 0.69 95% CI, 0.53–0.90; P=0.007). There was no relation between baseline low-density lipoprotein cholesterol levels and magnitude of VTE risk reduction. In contrast, in patients with higher baseline lipoprotein(a) (Lpa) levels, evolocumab reduced Lp(a) by 33 nmol/L and risk of VTE by 48% (HR, 0.52 95% CI, 0.30–0.89; P=0.017), whereas, in patients with lower baseline Lp(a) levels, evolocumab reduced Lp(a) by only 7 nmol/L and had no effect on VTE risk (Pinteraction 0.087 for HR; Pheterogeneity 0.037 for absolute risk reduction). Modeled as a continuous variable, there was a significant interaction between baseline Lp(a) concentration and magnitude of VTE risk reduction (Pinteraction=0.04). A polygenic risk score identified patients who were at >2-fold increased risk for VTE and who derived greater relative (Pinteraction=0.04) and absolute VTE reduction (Pheterogeneity=0.009) in comparison with those without high genetic risk.
CONCLUSIONS:PCSK9 inhibition significantly reduces the risk of VTE. Lp(a) reduction may be an important mediator of this effect, a finding of particular interest given the ongoing development of potent Lp(a) inhibitors.
Congenital heart diseases often involve maldevelopment of the evolutionarily recent right heart chamber. To gain insight into right heart structure and function, we fine-tuned deep learning models to ...recognize the right atrium, right ventricle and pulmonary artery, measuring right heart structures in 40,000 individuals from the UK Biobank with magnetic resonance imaging. Genome-wide association studies identified 130 distinct loci associated with at least one right heart measurement, of which 72 were not associated with left heart structures. Loci were found near genes previously linked with congenital heart disease, including NKX2-5, TBX5/TBX3, WNT9B and GATA4. A genome-wide polygenic predictor of right ventricular ejection fraction was associated with incident dilated cardiomyopathy (hazard ratio, 1.33 per standard deviation; P = 7.1 × 10
) and remained significant after accounting for a left ventricular polygenic score. Harnessing deep learning to perform large-scale cardiac phenotyping, our results yield insights into the genetic determinants of right heart structure and function.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
BACKGROUND—Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke.
METHODS—To determine ...whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in five prospective studies comprising 18,919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic 40%) and 3,028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P-values ranging from <1x10 to <1x10 in a prior independent genetic association study.
RESULTS—Incident AF occurred in 1,032 (5.5%) individuals. AF genetic risk scores were associated with new-onset AF after adjusting for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95%CI, 1.13-1.46; P=1.5x10) to 1.67 (25 variants; 95%CI, 1.47-1.90; P=9.3x10). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629-0.811; maximum ΔC statistic from clinical score alone, 0.009-0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95%CI, 1.39-4.58; P=2.7x10). The effect persisted after excluding individuals (n=70) with known AF (odds ratio, 2.25; 95%CI, 1.20-4.40; P=0.01).
CONCLUSIONS—Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors, though offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms.
BACKGROUND:Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic ...susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF.
METHODS:Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation.
RESULTS:Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger (P<0.001) and had fewer clinical risk factors for AF (P=0.001). Persistent AF (hazard ratio HR, 1.39 95% CI, 1.22–1.58; P<0.001), left atrial size (per cmHR, 1.32 95% CI, 1.19–1.46; P<0.001), and left ventricular ejection fraction (per 10%HR, 0.88 95% CI, 0.80–0.97; P=0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 95% CI, 0.99–1.18; P=0.07), which became less significant in multivariable analysis (HR, 1.06 95% CI, 0.98–1.15; P=0.13).
CONCLUSIONS:Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.
Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.
We assessed the contribution ...of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability,
) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated
using a variance components method with variants having a minor allele frequency ≥1%. We evaluated
in age, sex, and genomic strata of interest. The
for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.
Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that further genetic discovery, with an emphasis on common variation, is warranted to understand the causal genetic basis of AF.
Atrial fibrillation (AF) is a morbid and heritable arrhythmia. Over 35 genes have been reported to underlie AF, most of which were described in small candidate gene association studies. Replication ...remains lacking for most, and therefore the contribution of coding variation to AF susceptibility remains poorly understood. We examined whole exome sequencing data in a large community-based sample of 1,734 individuals with and 9,423 without AF from the Framingham Heart Study, Cardiovascular Health Study, Atherosclerosis Risk in Communities Study, and NHLBI-GO Exome Sequencing Project and meta-analyzed the results. We also examined whether genetic variation was enriched in suspected AF genes (N = 37) in AF cases versus controls. The mean age ranged from 59 to 73 years; 8,656 (78%) were of European ancestry. None of the 99,404 common variants evaluated was significantly associated after adjusting for multiple testing. Among the most significantly associated variants was a common (allele frequency = 86%) missense variant in SYNPO2L (rs3812629, p.Pro707Leu, odds ratio 1.27, 95% confidence interval 1.13-1.43, P = 6.6x10-5) which lies at a known AF susceptibility locus and is in linkage disequilibrium with a top marker from prior analyses at the locus. We did not observe significant associations between rare variants and AF in gene-based tests. Individuals with AF did not display any statistically significant enrichment for common or rare coding variation in previously implicated AF genes. In conclusion, we did not observe associations between coding genetic variants and AF, suggesting that large-effect coding variation is not the predominant mechanism underlying AF. A coding variant in SYNPO2L requires further evaluation to determine whether it is causally related to AF. Efforts to identify biologically meaningful coding variation underlying AF may require large sample sizes or populations enriched for large genetic effects.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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