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.

Population-Scale Studies of Protein S Abnormalities and Thrombosis.

Importance: Clinical decision-making in thrombotic disorders is impeded by long-standing uncertainty regarding the magnitude of venous and arterial thrombosis risk associated with low protein S. Population-scale multiomic datasets offer an unprecedented opportunity to answer questions regarding the epidemiology and clinical impacts of protein S deficiency.

Objective: To evaluate the risk associated with protein S deficiency across multiple thrombosis phenotypes.

Endothelial cell-related genetic variants identify LDL cholesterol-sensitive individuals who derive greater benefit from aggressive lipid lowering.

The role of endothelial cell (EC) dysfunction in contributing to an individual's susceptibility to coronary atherosclerosis and how low-density lipoprotein cholesterol (LDL-C) concentrations might modify this relationship have not been previously studied. Here, from an examination of genome-wide significant single nucleotide polymorphisms associated with coronary artery disease (CAD), we identified variants with effects on EC function and constructed a 35 single nucleotide polymorphism polygenic risk score comprising these EC-specific variants (EC PRS). The association of the EC PRS with the risk of incident cardiovascular disease was tested in 3 cohorts: a primary prevention population in the UK Biobank (UKBB; n = 348,967); a primary prevention cohort from a trial that tested a statin (JUPITER, n = 8,749); and a secondary prevention cohort that tested a PCSK9 inhibitor (FOURIER, n = 14,298).

A deep learning digital biomarker to detect hypertension and stratify cardiovascular risk from the electrocardiogram.

Hypertension is a major risk factor for cardiovascular disease (CVD), yet blood pressure is measured intermittently and under suboptimal conditions. We developed a deep learning model to identify hypertension and stratify risk of CVD using 12-lead electrocardiogram waveforms. HTN-AI was trained to detect hypertension using 752,415 electrocardiograms from 103,405 adults at Massachusetts General Hospital.

Impact of a clinical atrial fibrillation risk estimation tool on cardiac rhythm monitor utilization following acute ischemic stroke: A prepost clinical trial.

Background: Detection of undiagnosed atrial fibrillation (AF) after ischemic stroke through extended cardiac monitoring is important for preventing recurrent stroke. We evaluated whether a tool that displays clinically predicted AF risk to clinicians caring for stroke patients was associated with the use of extended cardiac monitoring.

Methods: We prospectively included hospitalized ischemic stroke patients without known AF in a preintervention (October 2018 - June 2019) and intervention period (March 11, 2021 - March 10, 2022).

Contemporary Burden of Cardiovascular Disease in Pregnancy: Insights from a Real-World Pregnancy Electronic Health Record Cohort.

Importance: Cardiovascular disease (CVD) is the leading cause of maternal morbidity and mortality, however the contemporary burden and secular trends in pregnancy-related CV complications are not well characterized.

Objective: We sought to examine contemporary trends in prevalence of maternal cardiometabolic comorbidities and established CVD, as well as future pregnancy-related CV complications across a large multi-institutional health system.

Design: Retrospective analysis of longitudinal electronic health record (EHR)-based cohort of pregnancies.

"Weekend Warrior" Physical Activity and Adipose Tissue Deposition.

Background: Attaining guideline-recommended levels of physical activity is associated with substantially lower risk of cardiometabolic diseases.

Objectives: Although physical activity commonly follows a weekend warrior pattern, in which most moderate-to-vigorous physical activity is concentrated in 1 to 2 days rather than spread more evenly across the week (regular), the effects of activity pattern on imaging-based biomarkers of cardiometabolic health are unknown.

Methods: We analyzed 17,146 UK Biobank participants who wore accelerometers for 1 week, and later underwent cardiac magnetic resonance imaging.

Predicting Atrial Fibrillation After Stroke by Combining Polygenic Risk Scores and Clinical Features.

Since treatment with anticoagulants can prevent recurrent strokes, identification of patients at risk for incident AF after stroke is crucial. We aimed to investigate whether the addition of AF polygenic risk scores (PRS) to existing clinical risk predictors could improve prediction of AF after stroke. Patients diagnosed with ischemic stroke at Massachusetts General Hospital between 2003-2017 were included.

Genomic Drivers of Coronary Artery Disease and Risk of Future Outcomes After Coronary Angiography.

Importance: Disease characteristics of genetically mediated coronary artery disease (CAD) on coronary angiography and the association of genomic risk with outcomes after coronary angiography are not well understood.

Objective: To assess the angiographic characteristics and risk of post-coronary angiography outcomes of patients with genomic drivers of CAD: familial hypercholesterolemia (FH), high polygenic risk score (PRS), and clonal hematopoiesis of indeterminate potential (CHIP).

Design, Setting, And Participants: A retrospective cohort study of 3518 Mass General Brigham Biobank participants with genomic information who underwent coronary angiography was conducted between July 18, 2000, and August 1, 2023.

Genetic Predisposition to Low-Density Lipoprotein Cholesterol and Incident Type 2 Diabetes.

Importance: Treatment to lower high levels of low-density lipoprotein cholesterol (LDL-C) reduces incident coronary artery disease (CAD) risk but modestly increases the risk for incident type 2 diabetes (T2D). The extent to which genetic factors across the cholesterol spectrum are associated with incident T2D is not well understood.

Objective: To investigate the association of genetic predisposition to increased LDL-C levels with incident T2D risk.

Unsupervised deep learning of electrocardiograms enables scalable human disease profiling.

The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated associations between ECG encodings and ~1,600 Phecode-based diseases in three datasets separate from model development, and meta-analyzed the results.

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.

Type 2 diabetes genetic risk and incident diabetes across diabetes risk enhancers.

Aims: To evaluate the predictive value of a contemporary type 2 diabetes (T2D) polygenic score (PGS) in detecting incident diabetes across a range of diabetes risk factors.

Materials And Methods: We analysed participants in the Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk (FOURIER) trial (ClinicalTrials.gov, number NCT0176463), which compared the efficacy of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor evolocumab versus placebo in lowering cardiovascular outcomes in participants with stable atherosclerotic cardiovascular disease and LDL cholesterol levels of 70 mg/dL (1.

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.