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.
Calmodulin (CaM) is a Ca2+-sensing protein that is highly conserved and ubiquitous in eukaryotes. In humans it is a locus of life-threatening cardiomyopathies. The primary function of CaM is to ...transduce Ca2+ concentration into cellular signals by binding to a wide range of target proteins in a Ca2+-dependent manner. We do not fully understand how CaM performs its role as a high-fidelity signal transducer for more than 300 target proteins, but diversity among its four Ca2+-binding sites, called EF-hands, may contribute to CaM’s functional versatility. We therefore looked at the conservation of CaM sequences over deep evolutionary time, focusing primarily on the four EF-hand motifs. Expanding on previous work, we found that CaM evolves slowly but that its evolutionary rate is substantially faster in fungi. We also found that the four EF-hands have distinguishing biophysical and structural properties that span eukaryotes. These results suggest that all eukaryotes require CaM to decode Ca2+ signals using four specialized EF-hands, each with specific, conserved traits. In addition, we provide an extensive map of sites associated with target proteins and with human disease and correlate these with evolutionary sequence diversity. Our comprehensive evolutionary analysis provides a basis for understanding the sequence space associated with CaM function and should help guide future work on the relationship between structure, function, and disease.
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, ...but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90
percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.
Genome-wide association studies have identified over 100 genetic loci for atrial fibrillation (AF); recent work described an association between loss-of-function (LOF) variants in
and early-onset AF.
...We sought to determine the contribution of rare and common genetic variation to AF risk in the general population.
The UK Biobank is a population-based study of 500 000 individuals including a subset with genome-wide genotyping and exome sequencing. In this case-control study, we included AF cases and controls of genetically determined white-European ancestry; analyses were performed using a logistic mixed-effects model adjusting for age, sex, the first 4 principal components of ancestry, empirical relationships, and case-control imbalance. An exome-wide, gene-based burden analysis was performed to examine the relationship between AF and rare, high-confidence LOF variants in genes with ≥10 LOF carriers. A polygenic risk score for AF was estimated using the LDpred algorithm. We then compared the contribution of AF polygenic risk score and LOF variants to AF risk.
The study included 1546 AF cases and 41 593 controls. In an analysis of 9099 genes with sufficient LOF variant carriers, a significant association between AF and rare LOF variants was observed in a single gene,
(odds ratio, 2.71,
=2.50×10
). The association with AF was more significant (odds ratio, 6.15,
=3.26×10
) when restricting to LOF variants located in exons highly expressed in cardiac tissue (
). Overall, 0.44% of individuals carried
variants, of whom 14% had AF. Among individuals in the highest 0.44% of the AF polygenic risk score only 9.3% had AF. In contrast, the AF polygenic risk score explained 4.7% of the variance in AF susceptibility, while
variants only accounted for 0.2%.
Both monogenic and polygenic factors contribute to AF risk in the general population. While rare
variants confer a substantial AF penetrance, the additive effect of many common variants explains a larger proportion of genetic susceptibility to AF.
Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending ...thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 × 10
). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.
Ischemic cardiomyopathy (ICM) is the leading cause of heart failure worldwide, yet the cellular and molecular signature of this disease is largely unclear. Using single-nucleus RNA sequencing ...(snRNA-seq) and integrated computational analyses, we profile the transcriptomes of over 99,000 human cardiac nuclei from the non-infarct region of the left ventricle of 7 ICM transplant recipients and 8 non-failing (NF) controls. We find the cellular composition of the ischemic heart is significantly altered, with decreased cardiomyocytes and increased proportions of lymphatic, angiogenic, and arterial endothelial cells in patients with ICM. We show that there is increased LAMININ signaling from endothelial cells to other cell types in ICM compared with NF. Finally, we find that the transcriptional changes that occur in ICM are similar to those in hypertrophic and dilated cardiomyopathies and that the mining of these combined datasets can identify druggable genes that could be used to target end-stage heart failure.
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•Cellular expression and composition are altered in ischemic cardiomyopathy•LAMININ signaling from endothelial cells to other cell types increases in disease•Cell-type transcriptional profiles converge across multiple cardiomyopathy subtypes•Potential druggable targets identified for end-stage heart failure
Simonson et al. compare non-failing and ischemic cardiomyopathy human left ventricles using snRNA-seq and identify an increase in lymphatic and angiogenic endothelial cells in disease. Transcriptionally, ischemic cardiomyopathy is similar to other cardiomyopathies. Gene targets from this shared expression profile could be explored for therapeutic benefit in end-stage heart failure.
Atrial fibrillation (AF) affects over 1% of the population and is a leading cause of stroke and heart failure in the elderly. A feared side effect of sodium channel blocker therapy, ventricular ...pro-arrhythmia, appears to be relatively rare in patients with AF. The biophysical reasons for this relative safety of sodium blockers are not known.
Our data demonstrates intrinsic differences between atrial and ventricular cardiac voltage-gated sodium currents (INa), leading to reduced maximum upstroke velocity of action potential and slower conduction, in left atria compared to ventricle. Reduced atrial INa is only detected at physiological membrane potentials and is driven by alterations in sodium channel biophysical properties and not by NaV1.5 protein expression. Flecainide displayed greater inhibition of atrial INa, greater reduction of maximum upstroke velocity of action potential, and slowed conduction in atrial cells and tissue.
Our work highlights differences in biophysical properties of sodium channels in left atria and ventricles and their response to flecainide. These differences can explain the relative safety of sodium channel blocker therapy in patients with atrial fibrillation.
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•Different sodium channel biophysical properties in atria and ventricles.•Left atrial tissue has slower conduction then left ventricle.•Flecainide is more effective at inhibiting atrial sodium channels.•Flecainide displays greater inhibition of atrial conduction compared to ventricles.
Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac ...transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.
Genome-wide association studies found that increased risk for atrial fibrillation (AF), the most common human heart arrhythmia, is associated with noncoding sequence variants located in proximity to ...PITX2. Cardiomyocyte-specific epigenomic and comparative genomics uncovered 2 AF-associated enhancers neighboring PITX2 with varying conservation in mice. Chromosome conformation capture experiments in mice revealed that the Pitx2c promoter directly contacted the AF-associated enhancer regions. CRISPR/Cas9-mediated deletion of a 20-kb topologically engaged enhancer led to reduced Pitx2c transcription and AF predisposition. Allele-specific chromatin immunoprecipitation sequencing on hybrid heterozygous enhancer knockout mice revealed that long-range interaction of an AF-associated region with the Pitx2c promoter was required for maintenance of the Pitx2c promoter chromatin state. Long-range looping was mediated by CCCTC-binding factor (CTCF), since genetic disruption of the intronic CTCF-binding site caused reduced Pitx2c expression, AF predisposition, and diminished active chromatin marks on Pitx2. AF risk variants located at 4q25 reside in genomic regions possessing long-range transcriptional regulatory functions directed at PITX2.
Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with ...unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population.
We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed.
Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc
=1.4 ms 95% CI, 1.3 to 1.5;
=1.1×10
). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms 95% CI, 7.4 to 14.4). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS).
QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.
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