Sequencing in over 50,000 cases identifies coding and structural variation underlying atrial fibrillation risk.

Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B.

Meta-analysis of genome-wide associations and polygenic risk prediction for atrial fibrillation in more than 180,000 cases.

Atrial fibrillation (AF) is the most common heart rhythm abnormality and is a leading cause of heart failure and stroke. This large-scale meta-analysis of genome-wide association studies increased the power to detect single-nucleotide variant associations and found more than 350 AF-associated genetic loci. We identified candidate genes related to muscle contractility, cardiac muscle development and cell-cell communication at 139 loci.

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.

The impact of common and rare genetic variants on bradyarrhythmia development.

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively.

Transcriptional profile of the rat cardiovascular system at single-cell resolution.

We sought to characterize cellular composition across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We performed single-nucleus RNA sequencing (snRNA-seq) in 78 samples in 10 distinct regions, including the four chambers of the heart, ventricular septum, sinoatrial node, atrioventricular node, aorta, pulmonary artery, and pulmonary veins, which produced 505,835 nuclei. We identified 26 distinct cell types and additional subtypes, with different cellular composition across cardiac regions and tissue-specific transcription for each cell type.

Culturally responsive strategies and practical considerations for live tissue studies in Māori participant cohorts.

Introduction: Indigenous communities globally are inequitably affected by non-communicable diseases such as cancer and coronary artery disease. Increased focus on personalized medicine approaches for the treatment of these diseases offers opportunities to improve the health of Indigenous people. Conversely, poorly implemented approaches pose increased risk of further exacerbating current inequities in health outcomes for Indigenous peoples.

Large-scale single-nuclei profiling identifies role for ATRNL1 in atrial fibrillation.

Atrial fibrillation (AF) is the most common sustained arrhythmia in humans, yet the molecular basis of AF remains incompletely understood. To determine the cell type-specific transcriptional changes underlying AF, we perform single-nucleus RNA-seq (snRNA-seq) on left atrial (LA) samples from patients with AF and controls. From more than 175,000 nuclei we find that only cardiomyocytes (CMs) and macrophages (MΦs) have a significant number of differentially expressed genes in patients with AF.

Martian atmospheric hydrogen and deuterium: Seasonal changes and paradigm for escape to space.

Mars' water history is fundamental to understanding Earth-like planet evolution. Water escapes to space as atoms, and hydrogen atoms escape faster than deuterium giving an increase in the residual D/H ratio. The present ratio reflects the total water Mars has lost.

Venus water loss is dominated by HCO dissociative recombination.

Despite its Earth-like size and source material, Venus is extremely dry, indicating near-total water loss to space by means of hydrogen outflow from an ancient, steam-dominated atmosphere. Such hydrodynamic escape likely removed most of an initial Earth-like 3-km global equivalent layer (GEL) of water but cannot deplete the atmosphere to the observed 3-cm GEL because it shuts down below about 10-100 m GEL. To complete Venus water loss, and to produce the observed bulk atmospheric enrichment in deuterium of about 120 times Earth, nonthermal H escape mechanisms still operating today are required.

Transcriptional profile of the rat cardiovascular system at single cell resolution.

Background: Despite the critical role of the cardiovascular system, our understanding of its cellular and transcriptional diversity remains limited. We therefore sought to characterize the cellular composition, phenotypes, molecular pathways, and communication networks between cell types at the tissue and sub-tissue level across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We obtained high quality tissue samples under controlled conditions that reveal a level of cellular detail so far inaccessible in human studies.

Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender.

Droplet-based single-cell assays, including single-cell RNA sequencing (scRNA-seq), single-nucleus RNA sequencing (snRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), generate considerable background noise counts, the hallmark of which is nonzero counts in cell-free droplets and off-target gene expression in unexpected cell types. Such systematic background noise can lead to batch effects and spurious differential gene expression results. Here we develop a deep generative model based on the phenomenology of noise generation in droplet-based assays.

Transfer learning enables predictions in network biology.

Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding and computer vision by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology.

The Genetic Determinants of Aortic Distention.

Background: As the largest conduit vessel, the aorta is responsible for the conversion of phasic systolic inflow from ventricular ejection into more continuous peripheral blood delivery. Systolic distention and diastolic recoil conserve energy and are enabled by the specialized composition of the aortic extracellular matrix. Aortic distensibility decreases with age and vascular disease.

Plasma extracellular vesicle transcriptome as a dynamic liquid biopsy in acute heart failure.

Background: Acute decompensation is associated with increased mortality in heart failure (HF) patients, though the underlying etiology remains unclear. Extracellular vesicles (EVs) and their cargo may mark specific cardiovascular physiologic states. We hypothesized that EV transcriptomic cargo, including long non-coding RNAs (lncRNAs) and mRNAs, is dynamic from the decompensated to recompensated HF state, reflecting molecular pathways relevant to adverse remodeling.

Single-nucleus RNA sequencing in ischemic cardiomyopathy reveals common transcriptional profile underlying end-stage heart failure.

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.

Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease.

Background: A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene () are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia.

Methods: To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls.

Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta.

Background: Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue.

Methods: Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm.

Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer's disease.

For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.

Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy.

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts, but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts.