Pathogenic Cardiomyopathy-Associated Gene Variants and Prognosis in Atrial Fibrillation: Results in 18,000 Clinical Trial Participants.

Background: Genetic variants in cardiomyopathy genes are associated with risk of atrial fibrillation (AF), although data on clinical outcomes for AF patients with such variants remain sparse.

Objectives: We aimed to study the prognostic implication of rare cardiomyopathy-associated pathogenic variants (CMP-PLP) in AF patients from large, well-phenotyped clinical trials.

Methods: CMP-PLP carriers were identified using exome sequencing in 5 multinational trials from the Thrombolysis in Myocardial Infarction study group (ENGAGE AF, FOURIER, SAVOR, PEGASUS, and DECLARE), with replication in the EAST-AFNET-4 trial.

Coagulation factor XII haploinsufficiency is protective against venous thromboembolism in a population-scale multidimensional analysis.

Coagulation factor XII has been identified as a potential drug target that could prevent thrombosis without increasing the risk of bleeding. However, human data to support the development of factor XII-directed therapeutics are lacking. To assess the role of factor XII in venous thromboembolism, we examine genetic variation in the coding region of the F12 locus across 703,745 participants in the UK Biobank and NIH All of Us biorepositories.

A Polygenic Risk Score to Predict Incident Heart Failure Across the Spectrum of Cardiovascular Risk.

Background: The clinical utility of a heart failure (HF) polygenic risk score (PRS) is uncertain.

Objectives: The purpose of this study was to investigate the ability of an HF PRS to predict new-onset HF in individuals across the spectrum of cardiovascular risk.

Methods: An HF PRS (>1 million single nucleotide variations) was used to stratify individuals from 7 clinical studies to low (quintile [Q] 1), intermediate (Q2-Q4), or high (Q5) genetic risk.

ACE inhibition increases Alzheimer's disease risk by promoting tau phosphorylation.

Reportedly, over 60% of individuals in the USA aged 65 or older take antihypertensive medications, making it crucial to evaluate their potential impact on dementia. Alzheimer's disease (AD), the most prevalent form of dementia, develops insidiously over decades, effectively precluding clinical trials of antihypertensive drug effects on AD risk. Through a triangulation approach integrating large-scale human genetics, population-based study, and rigorous experimental models, we identified that angiotensin-converting enzyme (ACE) inhibitors were associated with increased AD risk, with no significant associations observed for other antihypertensive classes, including angiotensin II receptor blockers and calcium channel blockers.

Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease.

Background: Coronary artery disease (CAD) results in substantial morbidity and mortality.

Objectives: The purpose of this study was to develop a deep learning model to detect CAD defined using diagnostic codes ("ECG2CAD") and identify people at risk for adverse events using electrocardiograms (ECGs) in a primary care setting.

Methods: ECG2CAD was trained on 764,670 ECGs representing 137,199 individuals at Massachusetts General Hospital (MGH).

Polygenic prediction of body mass index and obesity through the life course and across ancestries.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.

Genomics reveals eleven obesity endotypes with distinct biological and phenotypic signatures.

Obesity, a leading global risk factor for cardiometabolic conditions, arises from multifaceted and biologically complex mechanisms. To elucidate the full-dimensional genetic architecture underlying obesity, we conducted a multi-trait, multi-ancestry, genome-wide association study (GWAS) by combining genetic data on anthropometric traits (body mass index, waist circumference, waist-to-hip ratio, and hip circumference) from >2 million ancestrally diverse participants. We identified 743 significant loci, including 86 previously unreported loci, representing a 13% increase in locus discovery.

Machine Learning-Based Plasma Protein Risk Score Improves Atrial Fibrillation Prediction Over Clinical and Genomic Models.

Background: Clinical factors discriminate incident atrial fibrillation (AF) risk with moderate accuracy, with only modest improvement after incorporation of polygenic risk scores. Whether emerging large-scale proteomic profiling can augment AF risk estimation is unknown.

Methods: In the UK Biobank cohort, we derived and validated a machine learning model to predict incident AF risk using serum proteins (Pro-AF).

Identifying a Heterogeneous Effect of Atrial Fibrillation Screening in Older Adults: A Secondary Analysis of the VITAL-AF Trial.

Background: One-time atrial fibrillation (AF) screening trials in older adults have produced mixed results. In a secondary analysis of the VITAL-AF trial, we aimed to identify a subset of people in whom such screening is effective, using effect-based and risk-based approaches.

Methods: The VITAL-AF trial was a cluster-randomized trial of 1-time, 30-second single-lead ECG screening during primary care visits.

Rare genetic variation in PTPRB is associated with central serous chorioretinopathy, varicose veins and glaucoma.

Central serous chorioretinopathy is an eye disease characterized by fluid buildup under the central retina whose etiology is not well understood. Abnormal choroidal veins in central serous chorioretinopathy patients have been shown to have similarities with varicose veins. To identify potential mechanisms, we analyzed genotype data from 1,477 patients and 455,449 controls in FinnGen.

Timing and trajectory of BCR::ABL1-driven chronic myeloid leukaemia.

Mutation of some genes drives uncontrolled cell proliferation and cancer. The Philadelphia chromosome in chronic myeloid leukaemia (CML) provided the very first such genetic link to cancer. However, little is known about the trajectory to CML, the rate of BCR::ABL1 clonal expansion and how this affects disease.

New Threshold for Defining Mild Aortic Stenosis Derived From Velocity-Encoded MRI in 60,000 Individuals.

Background: Mild aortic stenosis (AS) is associated with adverse outcomes but is incompletely defined.

Objectives: The purpose of this study was to examine the epidemiology of AV function measured without clinical indications.

Methods: We developed a deep learning model to measure aortic valve (AV) area, peak velocity, and mean gradient in velocity-encoded cardiac magnetic resonance imaging in 62,902 UK Biobank participants.

Single cell transcriptomic analyses of human heart failure with preserved ejection fraction.

Background: Heart failure with preserved ejection fraction (HFpEF) is a poorly understood, multi-system disease with high morbidity and mortality. To improve our understanding of its underlying biology, we used single-nucleus RNA sequencing (snRNA-seq) to characterize cell-specific gene expression patterns in human HFpEF myocardium.

Methods: Septal myocardial biopsies (2-3 mg) from 30 HFpEF patients and 29 non-failing donor controls were analyzed using the 10X Genomics platform, with nuclei isolated from combined samples (6 patients/pool).

A 3D Genome Atlas of Genetic Variants and Their Pathological Effects in Cancer.

The hierarchical organization of the eukaryotic genome is crucial for nuclear activities and cellular development. Genetic aberrations can disrupt this 3D genomic architecture, potentially driving oncogenesis. However, current research often lacks a comprehensive perspective, focusing on specific mutation types and singular 3D structural levels.

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.

Background: Because treatment with anticoagulants can prevent recurrent strokes, identification of patients at risk for incident atrial fibrillation (AF) after stroke is crucial. We aimed to investigate whether the addition of AF polygenic risk scores (PRSs) to existing clinical risk predictors could improve prediction of AF after stroke.

Methods: Patients diagnosed with ischemic stroke at the Massachusetts General Hospital between 2003 and 2017 were included.