Frequency of Electrocardiogram-Defined Cardiac Conduction Disorders in a Multi-Institutional Primary Care Cohort.

Background: Disorders affecting cardiac conduction are associated with substantial morbidity. Understanding the epidemiology and risk factors for conduction disorders may enable earlier diagnosis and preventive efforts.

Objectives: The purpose of this study was to quantify contemporary frequency and risk factors for electrocardiogram (ECG)-defined cardiac conduction disorders in a large multi-institutional primary care sample.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems.

Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity.

Importance: Epicardial and pericardial adipose tissue (EPAT) has been associated with cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease (CAD), but studies have been limited in sample size or drawn from selected populations. It has been suggested that the association between EPAT and cardiovascular disease could be mediated by local or paracrine effects.

Objective: To evaluate the association of EPAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of EPAT in a large population cohort.

Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias.

Background And Aims: Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutations, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias.

Methods: UK Biobank participants without prevalent arrhythmias were included.

The Cardiovascular Impact and Genetics of Pericardial Adiposity.

Background: While previous studies have reported associations of pericardial adipose tissue (PAT) with cardiovascular diseases such as atrial fibrillation and coronary artery disease, they have been limited in sample size or drawn from selected populations. Additionally, the genetic determinants of PAT remain largely unknown. We aimed to evaluate the association of PAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of PAT in a large population cohort.

Major cardiovascular events after COVID-19, event rates post-vaccination, antiviral or anti-inflammatory therapy, and temporal trends: Rationale and methodology of the CORONA-VTE-Network study.

Background: Coronavirus disease 2019 (COVID-19) is associated with excess risk of cardiovascular and thrombotic events in the early post-infection period and during convalescence. Despite the progress in our understanding of cardiovascular complications, uncertainty persists with respect to more recent event rates, temporal trends, association between vaccination status and outcomes, and findings within vulnerable subgroups such as older adults (aged 65 years or older), or those undergoing hemodialysis. Sex-informed findings, including results among pregnant and breastfeeding women, as well as adjusted comparisons between male and female adults are similarly understudied.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants.

Genetics of myocardial interstitial fibrosis in the human heart and association with disease.

Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis.

Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass.

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.

Machine Learning to Understand Genetic and Clinical Factors Associated With the Pulse Waveform Dicrotic Notch.

Background: Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease.

Methods: In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning.

Wearable accelerometer-derived physical activity and incident disease.

Physical activity is regarded as favorable to health but effects across the spectrum of human disease are poorly quantified. In contrast to self-reported measures, wearable accelerometers can provide more precise and reproducible activity quantification. Using wrist-worn accelerometry data from the UK Biobank prospective cohort study, we test associations between moderate-to-vigorous physical activity (MVPA) - both total MVPA minutes and whether MVPA is above a guideline-based threshold of ≥150 min/week-and incidence of 697 diseases using Cox proportional hazards models adjusted for age, sex, body mass index, smoking, Townsend Deprivation Index, educational attainment, diet quality, alcohol use, blood pressure, anti-hypertensive use.

Spatially Distinct Genetic Determinants of Aortic Dimensions Influence Risks of Aneurysm and Stenosis.

Background: The left ventricular outflow tract (LVOT) and ascending aorta are spatially complex, with distinct pathologies and embryologic origins. Prior work examined the genetics of thoracic aortic diameter in a single plane.

Objectives: We sought to elucidate the genetic basis for the diameter of the LVOT, aortic root, and ascending aorta.

LMNA Variants and Risk of Adult-Onset Cardiac Disease.

Background: Genetic variants in LMNA may cause cardiac disease, but population-level contributions of variants to cardiac disease burden are not well-characterized.

Objectives: We sought to determine the frequency and contribution of rare LMNA variants to cardiomyopathy and arrhythmia risk among ambulatory adults.

Methods: We included 185,990 UK Biobank participants with whole-exome sequencing.

Monogenic and Polygenic Contributions to QTc Prolongation in the Population.

Background: 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.

Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank.

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.