Publications of our Scientists

Atrial fibrillation (AF) is a major public health problem, associated with increased risks of heart failure, stroke, dementia, and mortality. The treatment of AF involves multiple potential approaches, all of which presently have significant limitations. Over the past 20 years, tremendous advances have been made in understanding the pathophysiological determinants of AF. The present narrative review article aims to address selected issues that are highly relevant to clinically important questions in AF pathophysiology by reviewing insights from both experimental observations and complementary clinical investigations. Issues that we address include ) introduction and mechanistic concepts; ) the mechanistic basis for the crucial role of the pulmonary veins in AF; ) the progressive natural history of AF; ) the nature and mechanisms of secondary AF; ) AF and heart failure with reduced ejection fraction; ) AF and heart failure with preserved ejection fraction; ) AF burden: importance and mechanistic determinants; and ) the clinical importance of better understanding AF pathophysiology, leveraging new physiological knowledge and technologies to improve AF prevention. We consider in detail changes in ion channel and transporter function, the importance of inflammatory signaling, and the contribution of changes in tissue structure and composition in the development of AF-promoting atrial cardiomyopathy. The developments in our understanding of AF pathophysiology have been enormous and have produced many new conceptual and therapeutic opportunities, along with a wide range of important new questions. To capitalize on these opportunities and address the new questions that have emerged will require substantial additional investigation.

Atrial fibrillation (AF) may progress from paroxysmal AF (PAF) to more persistent forms, but the underlaying mechanisms are not well understood. The aim of this study was to assess the association between atherosclerosis and AF progression in patients with PAF.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) have gained interest as a pharmacological model but their immaturity leads to uncertainty regarding translation. We studied the key player in maintaining ionic homeostasis, the Na/K-ATPase (NKA), in hiPSC-CM.

Infection with the severe acute respiratory syndrome coronavirus-2 (SARSCoV-2), the virus which causes the corona virus disease-2019 (COVID-19) has substantial evidence that patients with pre-existing coronary artery disease (CAD) have an increased risk of serious illness, adverse coronary events, and mortality following infection. The COVID-CT registry will assess whether COVID-19 alters progression of coronary atherosclerotic plaque in patients with previously defined anatomic CAD on coronary computed tomographic angiography (CCTA). Mediators and covariates such as disease severity, inflammation, and neighborhood deprivation will also be assessed.

Polygenic scores can improve atrial fibrillation risk prediction. However, limited accuracy and cross-ancestry transferability hinder clinical translation. Here, we explore several ensemble approaches to generate ancestry-optimized polygenic scores, with development in diverse participants from the All of Us Research Program, BioBank Japan, and three additional cohorts. Our ancestry-specific multi-trait approach particularly improves prediction in South-Asian (odds-ratio/standard deviation 1.5-1.8; area under curve 0.60-0.64; relative R² +71%), Admixed-American (1.5; 0.60; +34%) and African ancestry groups (1.4; 0.57; +56%). Nevertheless, performance remains highest in European and East-Asian ancestries (1.8-2.2; 0.65-0.68), where >50% of SNP-heritability is explained. Improved risk stratification is also observed at the extremes, identifying European and East-Asian ancestry individuals with risk comparable to rare TTN variants (e.g., 6-11% with >4-fold odds). Finally, our scores improve incident risk prediction alongside clinical models. Together, we show that our ancestry-tailored multi-trait polygenic scores advance atrial fibrillation risk prediction and stratification, providing an equitable foundation for implementation.

The combined prevalence of heart failure (HF) with coronary atherosclerosis is frequent and often causally linked. The aim of this review is to elucidate whether lipid lowering drugs (LLDs) are useful in this context. The role of LLDs is interesting in two ways: incidence of HF patients treated with LLD versus outcomes in patients with a history of HF. Rosuvastatin and alirocumab have been tested in outcome trials specifically on patients with HF, the results are neutral since no benefit arose. To the contrary, use of statins in individuals without HF at baseline has been demonstrated to weakly but significantly reduce the incidence of HF. Overall, there is no notion that statins or other LLD are harmful in patients with HF. We will discuss the contribution of systemic inflammation and consider ischaemic versus non-ischaemic HF. We conclude that in contrast to other comorbidities like e.g. type 2 diabetes mellitus (T2DM), in HF we face a below-than-average efficacy of LLDs in terms of reducing hard cardiovascular endpoints.

Ischemic heart disease remains a leading global cause of death. We investigated the cardioprotective effects of the selective cluster of differentiation-36 receptor (CD36) modulator azapeptide MPE-298 in a mouse model of myocardial ischemia-reperfusion. Given before reperfusion, a single intravenous dose of azapeptide MPE-298 reduced infarct size by 44% of the area-at-risk and transiently decreased left ventricular long-chain fatty acids (LCFA) accumulation, independently of saturation status. Metabolomic profiling identified changes in amino acids that may fuel the tricarboxylic acid cycle and provide substrates for glutathione-dependent antioxidant defense. Gene expression analysis showed transient modulation of oxidative stress and inflammation-associated genes in both heart and adipose tissue. Thus, we conclude that modulation of CD36 by azapeptide MPE-298 exhibits therapeutic potential for treating acute myocardial ischemia and reperfusion by supporting metabolic recovery and limiting excess LCFA uptake.

Rare-variant association studies typically perform gene-level tests in which coding variants are filtered (or 'masked') and aggregated based on functional annotation and allele frequency. Through a systematic literature review, we cataloged 664 masks used across 234 studies and found that masking strategies (that is, sets of masks) rarely repeat across studies and are rarely justified. To quantify their impact on association results, we applied all previously employed strategies to 54 traits within 189,947 UK Biobank exomes. Here we find that the number of significant associations greatly depends on the masking strategy (ranging from 58 to 2,523 associations), which is a key reason for the modest overlap (<30%) of associations between separate published analyses of this dataset. We empirically determine masking strategies with high discovery power for low-frequency and rare variant gene-level associations across numerous datasets and traits, and we use these to explore the impact of other factors on burden test results. These findings offer a baseline strategy in burden tests to increase study power and replicability, addressing one source of inconsistency in previous studies.

Out-of-hospital cardiac arrest (OHCA) is a public health burden with the majority occurring in the general population for whom there is no firm strategy to predict risk.

Despite significant advances in heart failure (HF) management, mortality and readmission rates remain persistently high. Low adherence has been recognised as a contributing factor, although supporting data remain limited. Objective: This study aimed to evaluate the impact of medication adherence on outcome following a HF hospitalisation. Patients who were discharged after HF hospitalisation were included in the study from a national multicentre HF cohort, and their records were matched with the National Healthcare System database, which includes all health-related claims and clinical events. Adherence to beta blockers, renin-angiotensin system inhibitors, and mineralocorticoid receptor antagonists were measured using the proportion of days covered (PDC). Low adherence was defined by PDC < 80% for at least one of the three HF drug classes. We then analysed the relationship between the PDC and outcome during a two-year follow-up period. A total of 448 patients (median age: 73 years; 67% male; mean ejection fraction: 40%) were included. Of these patients, 152 (34%) were classified as having low adherence. The two-year mortality rate was comparable between the two groups (16.9% vs. 19.1% in adherent and low-adherent groups, respectively, = 0.6). However, the rates of all-cause and HF rehospitalisations at two years were lower in the adherent group than in the group with low adherence (85.9% vs. 92.8%, ≤ 0.01; 48.5% vs. 58.2%, = 0.04, respectively). : In patients discharged after acute HF, low adherence to HF drugs is frequent and worsens outcome, particularly the risk of rehospitalisation.

Scalable risk stratification for ischemic stroke remains an unmet need.

Atrial fibrillation (AF) increases cardiovascular risk in patients with chronic kidney disease (CKD). The safety and efficacy of early rhythm control (ERC) in patients with CKD is not fully established.

Biomarkers have the potential to improve risk prediction beyond clinical characteristics. We examined the association of four emerging cardiovascular biomarkers (angiopoietin 2 [Angpt2], bone morphogenetic protein 10 [BMP10], fibroblast growth factor 23 [FGF23], insulin-like growth factor binding protein 7 [IGFBP7]) in comparison with N-terminal pro B-type natriuretic peptide (NTproBNP) across the disease course of atrial fibrillation (AF).

Obesity and type 2 diabetes (T2D) are metabolic diseases with shared pathophysiology. Traditional polygenic risk scores (PRSs) have focused on these conditions individually, yet the single-disease approach falls short in capturing the full dimension of metabolic dysfunction. We derived a biologically enriched metabolic PRS (MetPRS), a composite score that uses multi-ancestry genome-wide association studies of 20 metabolic traits from over 8.5 million individuals. MetPRS, optimized to predict obesity (O-MetPRS) and T2D (D-MetPRS), outperformed existing PRSs in predicting obesity and T2D across six ancestries. O-MetPRS and D-MetPRS effectively identify individuals at high risk for metabolic multimorbidity and predict clinical outcomes, including GLP-1 receptor agonist initiation. O-MetPRS and D-MetPRS showed an ∼2-fold increased risk of GLP-1 receptor agonist initiation for the top decile versus the middle quintile. The biologically enriched MetPRS has the potential to add an extra layer of information to disease prediction and management approaches for metabolic diseases.

Heart failure with preserved ejection fraction (HFpEF) is a poorly understood, multisystem disease with high morbidity and mortality. To improve understanding of its pathobiology, we analyzed single-nucleus RNA sequencing in human HFpEF myocardium versus controls.

In atrial fibrillation (AF), few studies have focused on the influence of the mode of restoration of sinus rhythm (SR) on cardiac cavities remodelling, especially after spontaneous restoration.

Cardiac graft rejection and allograft vasculopathy (CAV) are major causes of morbidity and mortality in heart transplant (HT) patients. While endomyocardial biopsy and invasive coronary angiography remain diagnostic gold standards, their invasiveness highlights the need for safer, noninvasive alternatives. Cardiac computed tomography (CT) has emerged as a promising modality for evaluating both coronary and myocardial status.

Circadian regulation of metabolism is an important factor in metabolic health, yet the role of rhythmic metabolites in Type 2 diabetes development remains poorly understood. This study investigated associations between circulating rhythmic metabolites and incident Type 2 diabetes risk and evaluated causal relationships using two-sample Mendelian randomisation.

Leukocyte telomere length (LTL) is associated with multiple conditions, including cardiovascular diseases and neoplasms, yet their differential associations across diverse individuals are largely unknown. We estimated LTL from blood-derived whole-genome sequences in the All of Us research program (n = 242,494) with diverse ancestries across the USA. LTL was associated with lifestyle, socioeconomic status, biomarkers, cardiometabolic diseases and neoplasms, with heterogeneity across genetic ancestries and sexes. Geographical analysis revealed that significantly longer LTL clustered in the West Coast and Central Midwest, while significantly shorter LTL clustered in the Southeast in the USA. Genome-wide association studies and meta-analyses with the UK Biobank (n = 679,972) found 234 nonoverlapping loci, of which 37 were novel. We identified six novel loci unique to non-European-like populations and one specific to women. Rare variant analysis uncovered nine novel genes, providing new functional insights. Our study highlighted underappreciated contextual heterogeneities of phenomic and genomic associations with LTL.

ECG-based artificial intelligence may enable efficient prediction of incident heart failure (HF) risk to facilitate preventive efforts. Prior models are proprietary, with modest or inconsistent accuracy. We sought to develop and validate a generalizable and publicly available convolutional neural network to predict incident HF using the 12-lead ECG waveform (ECG-to-HF [ECG2HF]).

Despite recent advances in cardiovascular pharmacotherapy, prevention and treatment of many cardiovascular diseases remain limited with a clear need for more effective and safer pharmacological strategies. Here, we summarize the most relevant advances in cardiovascular pharmacotherapy in 2025, including the approval of four new drugs (aficamten, etripamil, lerodalcibep, and plozasiran), the label expansions for five already approved drugs, and the results of major randomized clinical trials with already approved drugs, including those that met the prespecified primary endpoints (positive trials) representing new pharmacological options for cardiovascular diseases, those with neutral or negative results which did not confirm the primary endpoints and the withdrawal from the U.S. market of Andexanet-alfa for safety concerns. Finally, we present the most promising experimental cardiovascular drugs currently being investigated in ongoing phase 2 and 3 clinical trials.

Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot that is both a sensor and a modulator of myocardial biology and changes its composition in response to paracrine signals from the myocardium. We hypothesized that radiomic characterization of EAT from routine coronary computed tomographic angiography (CCTA) can noninvasively capture this adverse remodeling and enable early heart failure (HF) risk stratification.

Atrial fibrillation and the risk of its lethal complications are propelled by fibrosis, which induces electrical heterogeneity and gives rise to reentry circuits. Atrial TREM2 macrophages secrete osteopontin (encoded by Spp1), a matricellular signaling protein that engenders fibrosis, inflammation, and atrial fibrillation. Here we developed an antibody-siRNA conjugate (ARC) drug candidate to silence Spp1. The ARC relies on an anti-TREM2 antibody for delivering Spp1-targeted siRNA to a pathogenic macrophage subset that expands in human atrial fibrillation. The ARC preferentially targeted atrial TREM2 macrophages with limited uptake by other immune or stromal cells of the heart. We observed efficient silencing of the target gene in human myocardium and in mice, where it reduced pro-fibrotic fibroblast activation and atrial fibrosis. Four weeks of systemic ARC treatment suppressed inducible atrial fibrillation in mice exposed to clinically prevalent risk factors. These results suggest that macrophage subset targeting offers a viable immunomodulatory strategy for atrial fibrillation.

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) have proven beneficial in chronic heart failure (HF) across a wide range of left ventricular ejection fractions (LVEFs). Emerging data suggests that these benefits may extend to acute HF decompensation through enhanced decongestion. To investigate changes in N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels according to SGLT2i use among patients hospitalized for acute HF decompensation. In this prospective cohort study, consecutive patients hospitalized for HF decompensation were enrolled. Demographics, comorbidities, and cardiovascular risk factors were recorded. Participants were classified into three groups: Group 1-No SGLT2i use or discontinuation; Group 2-Prior SGLT2i use and continuation; Group 3-SGLT2i-naïve with initiation during hospitalization. NT-proBNP was measured on admission and discharge. A total of 159 patients (median age 79 years, 64.8% male) were included. Group 1 patients exhibited negligible changes in NT-proBNP, whereas those continuing or newly initiating SGLT2i demonstrated significant reductions (absolute change: 506 [8792] pg/mL vs. -5610 [9461] pg/mL vs. -3602 [4409] pg/mL, = 0.001, percentage change: -2.1 [63.4]% vs. -30.3 [39.0]% vs. -38.3 [41.5]%, = 0.001). Multivariable regression confirmed that SGLT2i continuation or initiation independently predicted greater NT-proBNP reduction. NT-proBNP levels were significantly reduced among patients with decompensated HF treated with SGLT2i, with the greatest reduction in treatment-naïve patients. These findings highlight the potential role of SGLT2i even during acute HF hospitalization.

Screening for atrial fibrillation (AF) may lead to earlier detection and initiation of preventive measures. Current AF screening approaches using a guideline age-based threshold of ≥65 years have shown limited yield.

Cardiovascular diseases are a leading cause of morbidity and mortality in SLE. In this target population, epicardial adipose tissue (EAT) volume is increased, but its determinants and roles are poorly understood. This study aimed to assess the circulating metabolomic and lipidomic signatures associated with EAT in SLE.

Excess adiposity, most commonly indexed through body mass index (BMI), is strongly associated with the development of heart failure (HF). Weight loss therapies improve outcomes in patients with obesity and HF with preserved left ventricular ejection fraction (LVEF), but their effects in HF with reduced LVEF remain unclear.

Sudden cardiac death (SCD) causes 4 to 5 million deaths each year globally. Electrical vortices (tornadoes or rotors) are the origin of ventricular fibrillation (VF), which often causes SCD. Cardiac electrical vortices have complex dynamics and have been shown in many mammalian species. During VF, the heart fails to contract suitably and is unable to pump blood. Once VF is initiated, drug treatments are ineffective and even make things worse. The only effective treatment is electrical shock to the ventricles. Our current understanding of VF mechanisms is fragmentary, hindering the development of personalized therapies. Yet recent insights into the roles of the most critical sarcolemmal ion channels in VF in controlling the excitation-recovery process provide hope. Substantial evidence indicates that the molecular interplay between the main cardiac sodium channel (Na1.5) and the strong inward-rectifier potassium current (Kir2.1) controls cardiac excitability, wave propagation velocity, and rotor formation, as well as rotor stability and frequency during VF. Studies at the cellular, molecular, and ion channel levels are helping us understand how rotors generate the turbulence that characterizes VF, providing insights into how to prevent their initiation and identifying new therapeutic targets to avert premature death.

Cardiometabolic disorders like obesity and diabetes are closely linked with activated coagulation and inflammatory and immune signalling, leading to increased risk of thromboembolism and stroke. In this review, we elaborate recent clinical and basic science insights into the causal and bidirectional links between thrombo-inflammation-settings of activated coagulation and inflammation-and cardiometabolic disease. We discuss how metabolic disorders provide early triggers for a procoagulant state, notably endothelial dysfunction, platelet hyper-reactivity and an imbalance between procoagulant and fibrinolytic signals, and how the interplay with inflammation and immune signalling affects cardiac and adipose tissues and ultimately clinical outcome. We discuss possible sex differences and highlight candidate biomarker signatures that could improve timely detection of thrombo-inflammation, and review the recent evidence and remaining challenges of currently available therapeutic strategies.

Effects of sedentary behavior across the spectrum of future disease, including cardiovascular-kidney-metabolic (CKM) syndrome-related conditions, are poorly understood.

Peak oxygen consumption (peak VO), the gold standard measure of cardiorespiratory fitness, may identify women at high risk for pregnancy-related cardiovascular (CV) complications, but ascertainment is not widely scalable. We previously developed and validated a deep learning model to estimate peak VO from the resting 12-lead electrocardiogram (ECG).

Polygenic risk scores (PRS) stratify inherited cardiovascular risk, but their path to clinical implementation remains unclear.

The identification of reliable biomarkers for atrial fibrillation (AF) recurrence post-catheter ablation remains a clinical challenge. This study aimed to identify circulating microRNAs (miRNAs) associated with post-ablation AF recurrence and examine their underlying molecular pathways using an integrative translational approach.

ObjectiveThis study aimed to identify distinct cardiovascular risk phenotypes in systemic lupus erythematosus (SLE) using an unsupervised cluster analysis, and to compare the risk of incident cardiovascular events and subclinical atherosclerosis progression in the identified subgroups.MethodsConsecutive SLE patients who underwent a comprehensive cardiovascular risk assessment at the French National Referral Center for SLE between 2014 and 2024 were retrospectively included. An unsupervised analysis was performed using a hierarchical clustering algorithm on clinical, biological and imaging variables. Incident atherosclerotic cardiovascular disease (ASCVD) event rates, follow-up coronary artery calcium (CAC) scores and annualized CAC progression rates were compared across the identified clusters.ResultsA total of 226 patients were included (91% females, 45 ± 13 years). Three clusters were identified. Cluster 1 ( = 123) included young female patients with very few traditional cardiovascular risk factors, normal body-mass index (BMI) and low CAC scores. Cluster 2 ( = 78) included older female patients with a longstanding SLE course, high low-density lipoprotein levels and increased CAC scores. Cluster 3 ( = 25) included middle-aged male and female patients with frequent diabetes mellitus, increased BMI, triglycerides levels, epicardial adipose tissue volume and CAC scores. Overall, incident ASCVD events rates, follow-up CAC scores and annualized CAC progression rates significantly differed between the three clusters (C3>C2>C1, all P < .01). A post-clustering decision tree identified age, diabetes mellitus, and epicardial adipose tissue volume as key determinants of cluster membership.ConclusionSLE cardiovascular risk profiles encompass three subgroups with distinct cardiometabolic phenotypes and risk of incident cardiovascular events.

The management of angiographically intermediate coronary lesions (AICLs) remains challenging. Although current guidelines recommend physiological assessment to guide treatment decisions, residual atherothrombotic risk related to vulnerable plaque morphology may persist in deferred non-culprit lesions (NCLs). We performed a systematic review and meta-analysis to evaluate the prognostic impact of high-risk plaque morphology and impaired physiology in untreated NCLs.

Major adverse cardiovascular events (MACE)-cardiovascular (CV) death, nonfatal myocardial infarction (MI), and nonfatal stroke-are highly relevant clinical outcomes. In global randomized trials, medical records review by a physician clinical events committee (CEC) is the conventional standard for adjudicating MACE but is labor intensive. Automated adjudication with the use of artificial intelligence (AI) could reduce cost and improve reproducibility.

Coronary computed tomography angiography (CCTA) enables a non-invasive, comprehensive assessment of coronary artery disease, and artificial intelligence (AI) offers the potential to improve CCTA image interpretation. This study aimed to evaluate the performance of an AI-powered method for automatic plaque quantification from CCTA, with optical coherence tomography (OCT) as reference standard.

Atrial fibrillation (AF) is characterized by a heterogeneous presentation of symptoms. AF ablation reduces symptom burden. However, persistent symptoms following AF ablation are common independently of AF recurrence.

Stressor-associated atrial fibrillation (AF) refers to new-onset AF that occurs with a reversible, acute stressor. Identifying individuals at highest risk for AF recurrence is essential to guide management. Although clinical factors have shown limited value, the utility of contemporary artificial intelligence (AI)-enabled models using the 12-lead ECG to estimate recurrence risk remains unknown.

As the global population ages, identifying risk factors for age-related diseases, such as COPD, is crucial for public health. Mosaic loss of Y chromosome (mLOY) in blood cells is an age-related somatic mosaicism event, but its relationship with pulmonary health remains undercharacterized.

Cardiovascular diseases (CVD) remain a major global health challenge. Early markers of disease initiation and progression are urgently needed. We, and others, have previously shown changes in the gut microbiome in association with metabolic and CVD. Here, we demonstrate that gut microbiome-related changes can be detected in association with subclinical variations in heart and kidney function. Markers related to gut microbial metabolism of aromatic amino acids, phenylalanine and tyrosine, associate with circulating pro-atrial natriuretic peptide and estimated glomerular filtration rate in a metabolically healthy European population. Observational and genetic evidence further identify microbiome-related metabolites as mediators of this gut microbiome-kidney axis, with their baseline levels associating with incident CVD in an external Canadian population. Altogether, our work suggests that the gut microbiome interacts with the cardiorenal axis and participates in an interorgan crosstalk affecting host physiology and risk of CVD.

Artificial intelligence (AI) is reshaping cardiovascular imaging, transforming it from a set of diagnostic tests into powerful tools of precision medicine. This review traces this evolution through the lens of Thomas Lewis's legacy of clinical science, which championed the integration of physiology, experimentation and patient care. Modern AI fulfils that perspective by extracting biological information from routine imaging and linking it with molecular data to reveal mechanisms of disease, forecast outcomes and personalise therapy. An illustrative example of this translational pathway is the Fat Attenuation Index (FAI) score and AI-Risk model. The FAI Score is a new image analysis method that measures coronary inflammation from routine coronary CT angiograms (CCTA) by analysing the CT attenuation gradients within pericoronary adipose tissue in a standardised way, with strong value in predicting future cardiovascular events. The AI Risk model is a prognostic algorithm that integrates FAI Score, metrics of the extent of coronary plaque (by incorporating the Duke score) and clinical risk factors, to generate an accurate prediction of an individual's risk for a cardiovascular event, which is used clinically for risk stratification and decision making. Emerging big data-driven fields such as radiotranscriptomics, merging imaging data with multidimensional biological profiles, enable non-invasive 'molecular biopsies' that accelerate precision cardiology. Alongside these advances, the review addresses the ethical, regulatory and environmental challenges of AI deployment. Ultimately, AI is the current version of Lewis's perspective of translation: physiology shown in pixels, algorithms turning biology into care and discovery reaching its highest goal, which is to improve patient outcomes.

Multiple germline and somatic genomic factors are associated with risk of coronary artery disease, but there is no single measure of risk that integrates all information from a DNA sample. To address this gap, we develop an integrated genomic model that includes six germline and somatic genetic drivers for coronary artery disease, including polygenic risk score, genetically-proxied proteomic/metabolomic risk scores, and clonal hematopoiesis of indeterminate potential. We evaluated its predictive power in the UK Biobank (N = 391,536), and validate it using data from the TOPMed program (N = 34,177). The 10-year coronary artery disease risk based on the integrated genomic model profile ranges from 1.1% to 15.5% in the UK Biobank and from 3.8% to 33.0% in TOPMed, with a more pronounced gradient in males than females. The integrated genomic model captures the cumulative effect of multiple genetic drivers, identifying individuals at high risk for coronary artery disease despite lacking any single high-risk genetic factor, as well as individuals at low risk despite carrying known high-risk factors. In middle age, the integrated genomic model augments the performance of the Pooled Cohort Equations, a clinical risk calculator for coronary artery disease. While the integrated genomic model yields only modest incremental predictive value over polygenic risk score at the population level, it identifies approximately 13% of high-risk individuals not detected by polygenic risk score alone.

Proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9is) have emerged as a promising class of medications, primarily recognized for inducing potent cholesterol-lowering effects. In addition to the established role of these inhibitors in reducing low-density lipoprotein cholesterol levels, recent studies suggest that PCSK9is may also modify coronary atherosclerotic plaques. Therefore, this meta-analysis aimed to comprehensively synthesize data from relevant clinical studies and trials investigating the effects of PCSK9is on coronary atherosclerotic plaque characteristics.

To evaluate the performance of open-weight and proprietary LLMs, with and without Retrieval-Augmented Generation (RAG), on cardiology board-style questions and benchmark them against the human average. We tested 14 LLMs (6 open-weight, 8 proprietary) on 449 multiple-choice questions from the American College of Cardiology Self-Assessment Program (ACCSAP). Accuracy was measured as percent correct. RAG was implemented using a knowledge base of 123 guideline and textbook documents. The open-weight model DeepSeek R1 achieved the highest accuracy at 86.9% (95% CI: 83.4-89.7%), outperforming proprietary models and the human average of 78%. GPT 4o (80.9%, 95% CI: 77.0-84.2%) and the commercial platform OpenEvidence (81.3%, 95% CI: 77.4-84.7%) demonstrated similar performance. A positive correlation between model size and performance was observed within model families, but across families, substantial variability persisted among models with similar parameter counts. After RAG, all models improved, and open-weight models like Mistral Large 2 (78.0%, 95% CI: 73.9-81.5) performed comparably to proprietary alternatives like GPT 4o. Large language models (LLMs) are increasingly integrated into clinical workflows, yet their performance in cardiovascular medicine remains insufficiently evaluated. Open-weight models can match or exceed proprietary systems in cardiovascular knowledge, with RAG particularly beneficial for smaller models. Given their transparency, configurability, and potential for local deployment, open-weight models, strategically augmented, represent viable, lower-cost alternatives for clinical applications. Open-weight LLMs demonstrate competency in cardiovascular medicine comparable to or exceeding that of proprietary models, with and without RAG depending on the model.

This study investigated the genetic diversity of Griffon Vultures (Gyps fulvus) from two South - East European, and seven Mediterranean countries and islands, including Spain, which hosts the largest European population. Our sample, comprising 249 newly generated plus 92 public D-loop sequences, is the largest dataset so far analyzed for this species. We identified 14 novel haplotypes, with Hpt-A being predominant across populations. Exclusive haplotypes have been identified in the populations from Spain, Serbia, Israel, Croatia, and Sardinia, suggesting them as worthy of targeted conservation programs to preserve such haplotypes. Principal coordinate analysis identified a big cluster composed of populations from continental Europe and the Aegean islands that were clearly differentiated from Western Mediterranean and Middle East populations. This structure would suggest the Serbian population is potentially a good source for restocking efforts in the Eastern Mediterranean. In addition, results indicated that historical restocking actions with Spanish individuals have significantly influenced genetic composition in the insular population of Sardinia, and provided evidence consistent with possible hybridization between Griffon and Rüppell's Vultures (Gyps rueppellii) in Spain. This raises concerns about the use of non-genotyped Spanish individuals for restocking in populations like the Eastern Mediterranean ones, where contact zones between the two species have never been reported.

There is a lack of robust comparative data between limus drug-coated balloons (DCBs) versus paclitaxel-coated balloons (PCBs) on their efficacy and safety in treating in-stent restenosis (ISR).

We investigated the role of Lgi3-4 proteins in cardiac electrophysiology, with a specific focus on IKur, and their potential contribution to the pathophysiology of atrial fibrillation (AF).

Atrial fibrillation (AF) is conventionally classified as paroxysmal or persistent. AF burden might better reflect response to rhythm-control interventions. This study evaluated the association between estimated pre-procedural time spent in AF and recurrences after AF ablation, compared with conventional AF classification.

Following cold exposure, brown adipose tissue (BAT) generates heat through uncoupling protein 1-mediated thermogenesis. Intracellular lipolysis, mediated by neutral lipases, provides nonesterified fatty acids that fuel BAT mitochondrial respiration and uncoupling. In the present review, we provide current knowledge on the neuroendocrine control of intracellular lipolysis in brown adipocytes and discuss how the intracellular lipolytic machinery is important for the thermogenic activity of BAT. We also examine the importance of glycerolipid cycling and white adipose tissue (WAT) lipolysis in cold-induced thermogenesis. We discuss recent evidence suggesting a significant role for other organs, such as the liver and cardiovascular system, in nonshivering thermogenesis. Beyond BAT, interorgan glycerolipid cycling between WAT and lean organs may contribute significantly to whole-body thermogenic responses.

The triglyceride-glucose (TyG) index and its obesity-related derivatives have emerged as surrogate markers of insulin resistance associated with cardiovascular outcomes. However, whether these indicators influence atrial fibrillation (AF) risk through cardiac structural and functional remodeling remains unclear.

Coronary computed tomography angiography (CTA)-derived fractional flow reserve (FFR) serves as a gatekeeper to invasive coronary angiography (ICA), but its accuracy depends on image quality of the scan. Photon-counting coronary computed tomography angiography (PCCTA) technology enables spectral standard resolution (SR) and ultrahigh resolution (UHR) imaging.

The prevalence of obesity and cardiovascular-kidney-metabolic (CKM) syndrome continues to rise. Indications for novel CKM therapies, including glucagonlike peptide 1 receptor agonists (GLP-1RAs), sodium-glucose cotransporter-2 inhibitors (SGLT2is), and nonsteroidal mineralocorticoid antagonists (nsMRAs) continue to expand, yet the proportion of adults meeting expanded indications, including for multiple medications remains unclear.

Ambient air pollution has been linked to atrial fibrillation (AF), yet the underlying metabolic mechanisms remain poorly understood.

Nonmyocytes may contribute to regional adaptive changes during persistent atrial fibrillation (PsAF), favoring its perpetuation. We aimed to investigate the differential features of fibroblast and macrophage populations within individual-specific atrial regions associated with PsAF maintenance.

Perivascular adipose tissue (PVAT) is a metabolically active tissue that influences vascular function through paracrine signaling of adipokines. Pathologically altered PVAT is associated with proinflammatory, pro-oxidative, and proatherogenic signaling in coronary vessels, and consequently contributes to the pathophysiological mechanisms underlying atherosclerosis. Bidirectional cross talk from inflamed vasculature can also induce phenotypic changes in the PVAT that can be detected noninvasively with cross-sectional imaging. Imaging modalities like computed tomography are readily available in clinical settings, and PVAT characterization with Fat Attenuation Index has emerged as a valuable prognostic tool that quantifies coronary inflammation. This article reviews the imaging, quantification, and novel radiotranscriptomic analysis of PVAT. We also describe how these could integrate into artificial intelligence-enabled risk-prediction models for personalizing medical therapy guided by an individual's inflammatory risk, and how this approach already changes clinical management in healthcare systems where it has been adopted.

Chronic, unresolved inflammation, and immune system activation contribute to the development and progression of human cardiovascular disease. Specialized proresolving mediators (SPMs), primarily the lipoxins and resolvins, demonstrate potent inflammation-resolving effects. SPMs bind to their respective G protein-coupled receptors (GPCRs) to transduce intracellular events and exert proresolving actions. Given the importance of immune cells in the cardiovascular system, the involvement of nonimmune cardiac cell-types in chronic cardiac inflammation, and the inflammation-resolving effects of SPMs, SPM-GPCR interactions may present efficacious new therapeutic targets for heart disease. In this review, we discuss the mechanisms potentially underlying these GPCR-mediated responses. We begin by providing a brief overview of SPM biosynthesis and the GPCRs implicated in SPM signaling. We then discuss literature demonstrating protective effects of SPMs in models of heart disease. We look in detail at the pharmacology of SPM-GPCR interactions, with a primary focus on formyl peptide receptor 2, GPR32, GPR18, and chemerin receptor 1. We then consider SPM-GPCR downstream signaling pathways in various cell models, including heterologous cell systems overexpressing human SPM-GPCR constructs, SPM-GPCR interactions in endogenous immune cells and effects in nonimmune cell types of the heart including cardiomyocytes, cardiac fibroblasts, endothelial cells, and vascular smooth muscle cells. We end by considering knowledge gaps and discussing future directions in SPM-GPCR interaction research. SPM-GPCR signaling networks and actions vary widely in different cell-types and disease contexts, and knowledge of the detailed pharmacology in the heart is quite limited, so extensive additional work on SPM-GPCR signaling is needed to capitalize on the rich therapeutic potential. SIGNIFICANCE STATEMENT: Inflammation resolution is a critical process in cardiac healing after injury or disease. Understanding of the pharmacology and G protein-coupled receptor-dependent signaling mechanisms of inflammation-resolving molecules in the heart is limited, heavily dependent on cell type, and sometimes conflicting. The knowledge gained about these signaling mechanisms in more basic cell systems can be used to facilitate future investigation of how these molecules work within the diverse cardiac cellular milieu as potential targeted therapeutics for heart disease.

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Coronary artery disease (CAD) polygenic risk scores (PRS) may identify individuals at elevated genetic risk "flying under the radar" in contemporary practice. The aims of the PROACT (Polygenic Risk Based Detection and Treatment of Subclinical Coronary Atherosclerosis) trials are to prospectively identify these individuals, quantify subclinical coronary plaque, and slow its progression with pharmacologic interventions.

We performed an individual patient data analysis of COMBINE AF to assess differences in 14 clinically relevant outcomes between patients with paroxysmal (PAF) vs. non-PAF.

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is a major contributor to stroke, heart failure, and mortality worldwide. Although AF affects both men and women at a similar rate, accumulating experimental and clinical evidence indicates that its underlying mechanisms, disease progression, and treatment responses differ by sex. However, current antiarrhythmic drug development and clinical management of AF remains largely sex neutral, likely contributing to limited efficacy and increased adverse effects. To address this gap, we developed a computational drug-screening pipeline based on experimentally constrained, sex-specific human atrial cardiomyocyte models to predict and evaluate sex-specific pharmacological strategies for AF. The pipeline integrates multivariable regression with mechanistic modeling to systematically test multi-target combinations of ion channel inhibitors and Ca handling modulators and identify interventions that reduce arrhythmia vulnerability by restoring sex-specific electrophysiological and Ca handling properties toward normal sinus rhythm (nSR). Application of this approach revealed a greater number of successful inhibitory drug combinations in males than in females. In males, optimal recovery to nSR primarily required inhibition of Na and K channels to prolong repolarization and refractoriness, increase Ca transient amplitude (CaT), and reduce susceptibility to action potential duration (APD) alternans. In females, modulation of Ca-related pathways was additionally required to suppress delayed afterdepolarizations (DADs). Forward single-cell simulations confirmed the predictions of the drug-analysis pipeline, demonstrating recovery of APD, CaT, and arrhythmia vulnerability indices without introducing instabilities. Importantly, extension of these interventions to two-dimensional atrial tissue simulations demonstrated that sex-specific drug strategies reduce vulnerability to triggered activity, while suppression of reentry was most effective when combined with partial recovery of cell-cell coupling. Our results establish a multiscale computational pipeline for identifying sex-informed, multi-target antiarrhythmic therapies, amenable to experimental validation and translation to the clinic.

Physical activity is a key modifiable determinant of health, yet current guidelines primarily emphasize moderate-to-vigorous physical activity and provide limited guidance on other actionable dimensions such as daily step count and sedentary time. The growing availability of wearables enables high-resolution measurement of these metrics and assessment of their associations with clinical outcomes.

Stressor-associated atrial fibrillation (AF), defined as newly diagnosed AF in the setting of a reversible physiological stressor, is common. However, risk factors, outcomes, and current management practices remain poorly understood.

Up to 50% of patients presenting with ST-elevation myocardial infarction (STEMI) have multivessel coronary artery disease (CAD). Randomized trials suggest that complete revascularization improves outcomes, but the mechanism and identification of patients who benefit remain unclear. This study aims to assess the association between blood and coronary imaging biomarkers and clinical events, to identify patient-, vessel-, and lesion-specific risk in STEMI patients with bystander disease.

Aging is one of the most significant risk factors for the development of atrial fibrillation, and given our aging population, this is likely to present a major public health challenge in the coming years. Although the specific mechanisms underlying this association remain poorly understood, several biological processes including fibrosis, DNA damage, chromatin remodeling, amyloid deposition, mitochondrial dysfunction, and inflammation have been implicated in the structural and functional deterioration that leads to the development of atrial fibrillation. Herein, we review work from the last several years that has contributed to our understanding of the link between aging and atrial fibrillation with a focus on the basic pathophysiological mechanisms. We also outline areas for future research aimed at better characterizing this complex relationship.

Metabolic dysfunction-associated steatotic liver disease (MASLD) spans from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH) and can progress to cirrhosis or hepatocellular carcinoma. Despite its prevalence, effective therapies are lacking. Recent genome-wide association studies identified a common missense variant (rs2642438) in the Mitochondrial Amidoxime Reducing Component 1 (MTARC1) gene that protects against liver cirrhosis without increasing cardiovascular disease risk. Biochemical and disease risk signatures associated with carriers of this missense variant also aligned with those of a known loss-of-function MTARC1 variant, suggesting mARC1 inhibition as a potential MASLD treatment.

Understanding how rare genetic variants influence complex traits remains a major challenge, particularly when these variants lie in noncoding regions of the genome. The effects of variants within candidate cis-regulatory elements (cCREs) often depend on the cell type, making interpretation difficult. Here we introduce cellSTAAR, which integrates whole-genome sequencing data with single-cell assay for transposase-accessible chromatin using sequencing data to capture variability in chromatin accessibility across cell types via the construction of cell-type-specific functional annotations and regulatory elements. To reflect the uncertainty in cCRE-gene linking, cellSTAAR uses a comprehensive strategy to link cCREs to their target genes. We applied cellSTAAR to data from the Trans-Omics for Precision Medicine consortium (n ≈ 60,000) and replicated our findings using the UK Biobank (n ≈ 190,000). Across four lipid traits, cellSTAAR improved the detection of biologically meaningful associations and enhanced biological interpretability. These results demonstrate the potential of cell-type-aware approaches to boost discovery in rare variant whole-genome sequencing association studies.

Cyclic adenosine monophosphate (cAMP) is a critical second messenger in cardiomyocytes, regulating essential cellular functions. Upon G-protein-coupled receptor stimulation, adenylyl cyclase (AC) synthesizes cAMP, which phosphodiesterase (PDE) enzymes subsequently degrade. Recent studies challenge the traditional view of uniform cAMP signaling, revealing nanodomain-specific regulation within cardiomyocytes. This localized cAMP signaling modulates key Ca-handling proteins, including ryanodine receptor type-2 (RyR2), through channel-bound protein kinases and PDEs. Additionally, nucleoside-diphosphate kinases (NDPKs), particularly NDPK-C, contribute to cAMP synthesis and RyR2 regulation. Elevated NDPK-C levels in failing hearts correlate with increased cAMP levels, enhanced sarcoplasmic reticulum Ca release, and cardiac arrhythmias. Furthermore, cAMP influences the expression of Ca-handling proteins. This review examines the mechanisms governing cAMP levels in the sarcoplasmic reticulum nanodomain and their role in regulating RyR2 function in healthy and diseased hearts.

Optimal outcomes for patients with cardiac arrhythmias can be achieved through multimodal therapy including lifestyle support, medication, and interventions. Planning of these therapy concepts requires a detailed understanding of phenotypes, responses to therapies, and outcomes.

Atrial fibrillation (AF) is associated with an increased risk of stroke and hypercoagulability. Coagulation factors mediate remodeling processes via protease-activated receptors (PARs) in various organs.We evaluated whether inhibition of factor Xa (FXa) via rivaroxaban protects against atrial structural remodeling in goats with persistent AF and explored FXa and thrombin hypertrophic effect on human iPSC-derived cardiomyocytes (hiPSC-CMs).Three groups of goats were tested: CTRL AF (control AF,  = 10), RIVA AF (rivaroxaban treatment during AF,  = 11), and SHAM (no AF,  = 10). Pacing-induced AF was maintained for 16 weeks. AF stability, hemodynamics, and AF complexity were assessed. Atrial samples were collected for histological and gene expression analyses. hiPSC-CM were stimulated with PAR-1 agonist TRAP14, FXa, or thrombin with and without their inhibitors. Pro-hypertrophic and pro-inflammatory gene expression was assessed by qRT-PCR after 24 hours.Rivaroxaban inhibited thrombin generation in RIVA AF goats (baseline: 249 ± 42 nM vs. final: 69 ± 33 nM). Sixteen weeks of AF induced atrial myocyte hypertrophy in CTRL AF (13.5 µm [95% CI: 12.9, 14.0] vs. SHAM: 12.5 µm [95% CI: 12.0, 13.0]) and pro-hypertrophic (NPPA: fourfold; NPPB: 22-fold) and pro-fibrotic (COL1A1: threefold) gene expression. Rivaroxaban fully prevented hypertrophy (12.2 µm [95% CI: 11.7, 12.7]) and downregulated inflammatory signaling without altering hemodynamics and AF stability. In hiPSC-CM, thrombin and TRAP14 induced overexpression of the pro-hypertrophic genes NPPA and NPPB. The PAR1 antagonist, SCH79797, prevented thrombin-induced NPPA and NPPB upregulation.Prolonged rivaroxaban treatment reduces thrombin generation, preventing AF-induced atrial myocyte hypertrophy through inhibition of PAR-1 signaling.

Right ventricular-pulmonary artery (RVPA) coupling is an emerging prognostic marker in cardiovascular disease, but its predictive value in patients undergoing mitral transcatheter edge-to-edge repair (MTEER) remains uncertain.

Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are heart muscle diseases with largely opposing structural and functional phenotypes. Yet, both may lead to the same devastating outcomes of advanced heart failure and life-threatening arrhythmias. Using genome-wide association data from 9,365 DCM cases, 5,900 HCM cases, and over 1.2 million controls, we show that DCM and HCM are largely inversely associated across multiple genomic levels. Modeling both disorders as opposing genetic entities, in case-case GWAS approaches, we identify 100 loci (17 novel) underlying the cardiomyopathy spectrum. Several loci map to potential therapeutic targets (e.g., , ), and polygenic risk scores derived from these data show strong discrimination between DCM and HCM patients in external datasets (AUC 0.78-0.84; AUPRC ~ 0.85). The pervasive opposing associations suggest that cardiomyocyte-directed therapies may often have opposite effects in DCM versus HCM. Nevertheless, a shared-effect analysis reveals a single locus - near the calcium-buffering gene - and also identifies a concordant genomic component associated with cardiometabolic health and extracardiac risk factors. By leveraging the shared and opposing genetic mechanisms of DCM and HCM, our work defines the genomic architecture of major cardiomyopathy subtypes and suggests new directions for therapeutics and precision medicine in heart failure.

Atrial cardiomyopathy (AtCM) is increasingly recognized as an important substrate for atrial fibrillation (AF). This study aimed to examine potential markers and risk factors of AtCM, and associations with incident AF, heart failure (HF), and stroke.

Ischaemic heart disease shows important differences between men and women, requiring an understanding of sex and gender dissimilarities to improve outcomes. This Scientific Statement provides an updated review of the current knowledge from risk factors to prognosis. It discusses the unequal impact of certain traditional risk factors between men and women, along with additional factors, such as hormonal changes and treatments (including those for transgender people and cancer), pregnancy-related complications, and autoimmune diseases, which contribute to the sex-specific risk profiles. Moreover, it outlines functional and structural sex differences in the pathophysiology (e.g. coronary atheroma plaques and burden, coronary dissection, vasospasm, and microvascular disease) with women being more prone to microvascular disease and endothelial dysfunction, while paradoxically experiencing less severe myocardial ischaemia at similar levels of coronary stenosis. The document further addresses the evaluation of diagnostic tools, which often have a male-centric bias, resulting in underdiagnosis in women who also tend to receive less guideline-recommended treatment. Additionally, women can have different responses and side effects to various preventive and therapeutic treatments, potentially contributing to the worse prognosis documented in acute coronary syndromes with obstructive coronary artery disease, particularly at a young age. Considering all these sex and gender differences and the low enrolment of women in randomized controlled trials, questions arise regarding the optimal treatment for women. Addressing sex differences requires conducting sex-specific research to close the knowledge gap. Overall, the Scientific Statement highlights all relevant sex- and gender-specific dissimilarities to advance clinical practice and identify directions for future research to improve guideline recommendations for equitable care.

Cardiovascular diseases remain the leading cause of mortality worldwide, driven by complex, multiscale mechanisms that span molecular, cellular and organ-level dysfunction. Effective therapeutic strategies therefore require integrative approaches that link fundamental biology to translational applications. The 8 UC Davis CardioVascular Symposium gathered experts in ion channel biophysics, Ca signalling, arrhythmia mechanisms and cardiovascular physiology to discuss recent advances and define emerging priorities. This white paper synthesizes the key themes and consensus points that emerged, highlighting progress in two core domains: (1) advances in cardiovascular electrophysiology and arrhythmia mechanisms, and (2) spatiotemporal dynamics of Ca signalling in cardiac and vascular function and remodelling. We also identify conceptual and technical challenges that must be addressed to accelerate therapeutic discovery and emphasize cross-cutting opportunities where experimental and computational approaches can converge. By integrating ion channel biology and Ca signalling mechanisms across scales, this work outlines new directions for advancing cardiovascular research and treatment.

The dynamic, heterogeneous nature of atrial fibrillation (AF) episodes and poor symptom-rhythm correlation make early AF detection challenging. The optimal screening strategy for early AF detection and its role in stroke prevention are unknown.

Exercise may lead to disease progression and higher risk of sudden death in individuals with genetic cardiomyopathies, but the effects of exercise among individuals carrying a cardiomyopathy-associated variant without clinical manifestations (G+P-) are unclear.

Pulmonary vein isolation (PVI) is the cornerstone of atrial fibrillation (AF) ablation, but recurrences are frequent. Ablating AF sources beyond PVI may prevent re-initiations. This proof-of-principle in silico study compares a novel source-based ablation approach to conventional strategies in preventing AF re-initiation.

Lp(a) (lipoprotein[a]) is associated with cardiovascular disease, but neither the causal nature nor the underlying mechanisms are fully documented. This study investigated whether Lp(a) triggers atherogenesis by dysregulating vascular redox-sensitive inflammatory state.

The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10) and Mass General Brigham Biobank (HR = 2.76, P = 7.8 × 10). Using Mendelian randomization, we found evidence supporting a potential causal role for Lp(a) and LDL on aortic valve function. These findings have implications for the early pathogenesis of aortic stenosis and suggest modifiable pathways as targets for preventive therapy.

People with HIV (PWH) and undetectable virus experience elevated cardiovascular risk independent of traditional risk factors. Vascular inflammation may contribute to this residual risk. The perivascular fat attenuation index (FAI), derived from coronary computed tomography angiography (CCTA), is a biomarker of coronary inflammation. Lipoprotein(a) [Lp(a)] carries oxidized phospholipids that may promote inflammation. Statins have demonstrated cardiovascular benefit in PWH, including pleiotropic anti-inflammatory effects. This study assessed the associations of Lp(a) and of statin use with coronary inflammation (FAI) in men with HIV (MWH).

Coronary computed tomography angiography plays a pivotal role in the diagnosis, risk stratification, and treatment of patients with known or suspected coronary artery disease. However, conventional computed tomography (CT) technologies are limited by spatial resolution, artifact susceptibility, and radiation exposure. Photon-counting computed tomography (PCCT) introduces substantial technological improvements over conventional CT. This includes improved spatial and contrast resolution, energy discrimination, and reduction of various artifacts. As a result, PCCT enables superior coronary lumen and plaque evaluation, even in complex cases with severe calcification or smaller coronary stents. Beyond the coronary arteries, PCCT offers improved visualization of cardiac anatomy and myocardial tissue characterization with the potential to reduce downstream testing, improve diagnosis and treatment, and ultimately improve clinical outcomes. PCCT is poised to become the dominant technology for cardiovascular CT; however, challenges such as high costs, increased data demands, and a need for more validation, standardized image acquisition, and post-processing protocols remain. This review explores the technical principles of PCCT, its advantages over conventional CT, and its current and potential future applications in cardiac imaging, highlighting opportunities for future research.

 To assess the prognostic impact of both the frequency and timing of prior heart failure (HF) hospitalisations on outcomes in patients with reduced left ventricular ejection fraction (LVEF).

Aortic stenosis (AS) remains the most prevalent valvular heart disease worldwide and is increasingly managed through transcatheter aortic valve implantation (TAVI). With the 2025 ESC/EACTS Guidelines lowering the age threshold for TAVI to 70 years, the focus has shifted from short-term survival to lifetime management, necessitating rigorous evaluation of device durability, coronary access, and biological valve degeneration. This review synthesizes the latest evidence-based strategies for TAVI, contrasting randomized trial data with long-term registry findings. We critically analyze the hemodynamic trade-offs between self-expandable valves and balloon-expandable valves, particularly in patients with small aortic annuli, where SEVs demonstrate superior indexed effective orifice areas and reduced rates of patient-prosthesis mismatch (SMALL-TAVI registry). We further examine the expansion of indications into complex anatomical subsets, including bicuspid aortic valves (BIVOLUTX, STABILITY) and pure aortic regurgitation, where dedicated anchoring mechanisms are required to mitigate the risk of valve migration. Procedural optimization is addressed through the "minimalist" TAVI pathway (BENCHMARK registry), which emphasizes conscious sedation and ultrasound-guided vascular access to reduce length of stay without compromising safety. Finally, we discuss emerging biomarkers (MMP-3, osteopontin) and the role of epicardial adipose tissue as novel predictors of structural valve deterioration, signaling a potential shift toward biological modulation of valvular disease.

HER2-positive breast cancer patients receiving chemotherapy and targeted therapy (including anthracyclines and trastuzumab) face an elevated risk of cardiotoxicity, which can lead to long-term cardiovascular complications. Identifying predictive biomarkers is essential for early intervention. Circulating microRNAs (miRNAs), known regulators of gene expression and cardiovascular function, have emerged as potential indicators of cardiotoxicity. This study aims to evaluate the differential expression of circulating miRNAs in HER2-positive breast cancer patients undergoing chemotherapy and to assess their prognostic ability for therapy-induced cardiotoxicity using machine learning models. Forty-seven patients were assessed for cardiac toxicity at baseline and every 3 months, up to 15 months. Blood samples were collected at baseline. MiRNA expression profiling for 84 microRNAs was performed using the miRCURY LNA miRNA PCR Panel. Differential expression was calculated via the 2 method. The five most upregulated and five most downregulated miRNAs were further assessed using univariate logistic regression and receiver operating characteristic (ROC) analysis. Five machine learning models (Decision Tree, Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), k-Nearest Neighbors (KNN)) were developed to classify cardiotoxicity based on miRNA expression. Forty-five miRNAs showed significant differential expression between cardiac toxic and non-toxic groups. ROC analysis identified hsa-miR-155-5p (AUC 0.76, = 0.006) and hsa-miR-124-3p (AUC 0.75, = 0.007) as the strongest predictors. kNN, SVM, and RF models demonstrated high prognostic accuracy. The decision tree model identified hsa-miR-17-5p and hsa-miR-185-5p as key classifiers. SVM and RF highlighted additional miRNAs associated with cardiotoxicity (SVM: hsa-miR-143-3p, hsa-miR-133b, hsa-miR-145-5p, hsa-miR-185-5p, hsa-miR-199a-5p, RF: hsa-miR-185-5p, hsa-miR-145-5p, hsa-miR-17-5p, hsa-miR-144-3p, and hsa-miR-133a-3p). Performance metrics revealed that SVM, kNN, and RF models outperformed the decision tree in overall prognostic accuracy. Pathway enrichment analysis of top-ranked miRNAs demonstrated significant involvement in apoptosis, p53, MAPK, and focal adhesion pathways, all known to be implicated in chemotherapy-induced cardiac stress and remodeling. Circulating miRNAs show promise as biomarkers for predicting cardiotoxicity in breast cancer patients. Machine learning approaches may enhance miRNA-based risk stratification, enabling personalized monitoring and early cardioprotective interventions.

Here, we present a protocol to analyze endolysosomal (EL) proteins in goat atrial fibrillation (AF) tissue using a modified density-gradient, proteomic-based fractionation. This method separates organelles from tissue lysate, isolating sarcoplasmic reticulum, mitochondria (1.3 g/mL), and EL (1.04 g/mL) with minimal contamination. The protocol includes tissue isolation, homogenization, density-gradient processing, peptide analysis, data analysis, and protein network identification using discontinuous Percoll and sucrose gradients; it supports molecular and proteomic studies. For complete details on the use and execution of this protocol, please refer to Ayagama et al. and Ayagama et al..

Atrial fibrillation (AF) is a growing unmet medical need. To reduce its impact on patients' lives, improvements in stroke prevention therapy, treatment of concomitant conditions, and rhythm control therapy are actively developed: Innovations in anti-thrombotic agents, new anti-arrhythmic drugs (AADs), and novel interventional rhythm control therapies emerge alongside AF-reducing effects of general cardiometabolic therapies. Simple risk scores are slowly replaced by personalized AF risk estimation using quantifiable features. These developments were discussed by over 80 experts from academia and industry during the 10th Atrial Fibrillation NETwork /European Heart Rhythm Association consensus conference from 5 to 7 May 2025. The emerging consensus, described here, is multi-domain therapy combining stroke prevention, rhythm control, and therapy of concomitant cardiovascular conditions. This combines anti-coagulants, AADs, and AF ablation with old and new cardiometabolic drugs that can reduce AF risk, AF burden, and AF-related complications at scale. The paper furthermore describes quantitative traits that may enable a shift towards risk-driven therapy based on AF phenotypes. These can enable adjusted therapy strategies that are safe, accessible, and patient-centred. Applying modern data science and artificial intelligence methods to quantitative phenotypic and genetic features can further improve risk estimation and personalized therapy selection. At the same time, translational and clinical research into reversing the drivers of AF and into improved stroke prevention through new drugs and through combination therapies is needed. Together, these efforts offer pathways towards personalized, patient-centred, multi-modal, and accessible AF management that integrates rhythm control, stroke prevention, and therapy of concomitant conditions to bridge today's practical needs with tomorrow's therapeutic innovation.

Type 2 diabetes mellitus (T2D) is an established risk factor for multiple cardiovascular diseases including atrial fibrillation (AF). The causal relationship between type 1 diabetes mellitus (T1D) and AF is poorly defined. T1D and AF share many underlying risk factors, but how T1D may promote AF independently of obesity and other features typical of T2D is not known. Here, we critically review the quality of the available clinical evidence specifically linking AF with the distinct characteristics of T1D and evaluate the mechanistic insights from preclinical models. We provide a conceptual overview of candidate contributing players and highlight important gaps in knowledge, unmet clinical needs, and potential therapeutic perspectives.

It is unclear whether the increase in protein expression of PP2A regulatory subunit PR72 seen in human heart failure represents a primary compensatory mechanism or the final reaction to contractile decompensation. To address this question, we have explored the effects of chronic catecholaminergic stress in a transgenic (TG) mouse model with heart-specific overexpression of PR72 that exhibits hypercontractility at basal conditions.

Na1.5 channels, encoded by , are essential for the genesis and shaping of the cardiac action potential (AP). (GoF) variants in are associated with long QT syndrome (LQTS), whereas loss-of-function (LoF) mutations are linked with Brugada syndrome. MOG1 is an integral part of the Na1.5 channelosome, increasing both current and membrane expression of Na1.5. Two LoF variants in MOG1 (E61X and E83D) cause Brugada Syndrome in patients, but no association with LQTS has been reported.

Heart failure (HF) affects over 60 million individuals globally. Contemporary guideline-directed medical therapies (GDMT) reduce cardiovascular mortality and HF hospitalizations. However, medication non-adherence represents a critical barrier limiting real-world efficacy of GDMT. This scientific statement aims to provide a comprehensive framework for understanding, measuring, and addressing medication non-adherence in HF management across diverse healthcare settings. Addressing medication non-adherence requires systematic, multifaceted approaches targeting individual patient barriers while implementing system-level interventions. Polypills, digital monitoring platforms, enhanced patient education and empowerment, and multidisciplinary care models represent promising strategies to optimize therapeutic adherence and improve clinical outcomes in HF management.

Inflammation is a central driver of atherothrombosis, yet the temporal behavior of key inflammasome mediators following acute coronary syndrome (ACS) is not well characterized. The NLRP3 inflammasome, a major regulator of interleukin (IL)-1β activation, has been implicated in plaque destabilization and recurrent cardiovascular risk. This study aims to investigate the temporal expression of NLRP3 inflammasome components in peripheral blood mononuclear cells (PBMCs) of patients with ACS. In this prospective observational study, PBMCs were collected from 73 patients with ACS during the early in-hospital phase and at 8-12 weeks follow-up. Gene expression of NLRP3, caspase-1, and IL-1β was quantified by qRT-PCR, and fold-change was calculated using the 2 method. Associations with clinical and biochemical variables were evaluated using multivariable linear regression. Expression of all measured inflammasome-related genes increased significantly at follow-up compared with baseline: caspase-1 (≈2-fold, = 0.003), NLRP3 (>10-fold, < 0.001), and IL-1β (≈4-fold, < 0.001). Subgroup analyses showed that the post-ACS upregulation of NLRP3, caspase-1, and IL-1β was consistent across STEMI and NSTEMI presentations and was not significantly modified by diabetes status. Caspase-1 fold-change correlated positively with IL-1β, LDL-cholesterol, peak troponin I, and high sensitivity C reactive protein, whereas NLRP3 showed minimal correlations with clinical variables. In multivariable analysis, caspase-1 upregulation was independently associated with STEMI presentation and low-density lipoprotein-cholesterol, and IL-1β with type 2 diabetes. Patients with ACS exhibit significant and persistent upregulation of NLRP3 inflammasome components weeks after the acute event, indicating sustained immune cell priming during recovery. These findings highlight a potential molecular substrate for residual inflammatory risk and support further exploration of inflammasome-targeted therapies in the post-ACS period.

Type 2 diabetes mellitus typically has the lipid features of elevated trigycerides, reduced HDL-cholesterol (both parts of the metabolic syndrome) and average or slightly elevated LDL-cholesterol. In consequence of hypertriglyceridemia, LDL particles are small and dense and therefore highly atherogenic. Outcome studies reveal that LDL-C lowering drugs have an above-average efficacy in type 2 diabetes as compared with non-diabetic patients. A minor increase of glycaemia in statin trials does not impair the beneficial cardiovascular results. Non-statin lipid lowering drugs do not impair glycaemia. Type 2 diabetes mellitus is now considered a major indication for lipid lowering drugs, thus there is a high value of and no major limitation for those compounds.

Atrial fibrillation and other cardiac arrhythmias pose a major public health burden, but prevention remains difficult. We investigated a genetic variant that we found to act like a natural lifelong cardiac sodium channel blockade.

Catheter ablation (CA) in patients with atrial fibrillation (AF) can be performed under procedural sedation and analgesia (PSA). Risk factors for respiratory complications during PSA are unclear. We aimed to determine the incidence and severity of respiratory complications during PSA and identify predictive factors for development of per-procedural respiratory complications.

Systemic lupus erythematosus (SLE) is an autoimmune disease associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). However, risk stratification remains an unmet need. In 2025, the European Atherosclerosis Society (EAS) introduced a novel metabolic disorder staging system. This study aimed at assessing the prevalence and prognostic value of metabolic disorders as defined by the EAS 2025 consensus statement in a cohort of SLE patients.

To understand the genetic basis of heart failure (HF) in the Japanese population, we performed genome-wide association studies (GWASs) comprising 16,251 all-cause HF cases, 4254 HF with reduced ejection fraction (HFrEF) cases, 7154 HF with preserved ejection fraction cases, and 11,122 non-ischemic HF cases among 213,828 individuals and identified five novel loci. A subsequent cross-ancestry meta-analysis and multi-trait analysis of the GWAS data identified 19 novel loci in total, with 31 out of the 76 genome-wide significant loci associated with HFrEF despite its smaller sample size. Among these susceptibility loci, a common non-coding variant in TTN (rs1484116) was associated with reduced cardiac function and worse long-term mortality. We leveraged the HF meta-GWASs along with cardiac function-related GWASs to develop a polygenic risk score (PRS) for HF. The PRS successfully identified early-onset HF and those with an increased risk of long-term HF mortality. Our results shed light on the shared and distinct genetic basis of HF between Japanese and European populations and improve the clinical value of HF genetics.

In nonischemic cardiomyopathy, mitochondrial Ca handling is involved in arrhythmogenesis by modulating diastolic sarcoplasmic reticulum (SR) Ca release. Recently, it has been reported that lysosomal Ca release can trigger an SR Ca release. We investigated whether lysosomal Ca flux through the TRPML1 (transient receptor potential mucolipin 1) channel could contribute to ischemic cardiomyopathy-related arrhythmia by causing diastolic SR Ca release.

Large-scale genome-wide association studies have identified common genetic variants that predict the risk of peripheral artery disease (PAD). This study assessed whether a polygenic risk score (PRS) is associated with PAD and the incidence of major adverse limb events (MALE) independent of clinical risk factors in patients with established cardiometabolic disease.

Whether artificial intelligence (AI) analysis of single-lead ECG (1 L ECG) can predict incident AF is unknown. In the VITAL-AF trial (ClinicalTrials.gov NCT03515057, registered 2/24/2021) of primary care patients aged ≥65 years undergoing handheld 1 L ECG screening, we tested three AI approaches to incident AF prediction, and compared the best model to the CHARGE-AF risk score. In a test set of 4,221 individuals, a published AI model trained using single standard ECG leads ("1 L ECG-AI") provided similar 2-year AF discrimination to models trained with VITAL-AF data. In the full VITAL-AF sample of 15,694 individuals without prevalent AF (2-year incident AF 3.1%), 1 L ECG-AI with age/sex (1 L ECG-AI AS) had comparable discrimination (area under the receiver operating characteristic curve [AUROC] 0.695[0.637-0.742]; average precision [AP] 0.060[0.050-0.078]) to CHARGE-AF (AUROC 0.679[0.623-0.730]; AP 0.062[0.052-0.080], AUROC p = 0.46, AP p = 0.92). Net reclassification improvement was favorable versus age ≥65 years (0.27[0.22-0.32]). 1 L ECG-AI may increase efficiency and reach of AF screening.

The high burden of dilated cardiomyopathy (DCM) in individuals of African descent remains incompletely explained. Here, to explore a genetic basis, we conducted a genome-wide association study in 1,802 DCM cases and 93,804 controls of African genetic ancestry (AFR). A nonsense variant ( rs3211938 :G) in CD36 was associated with increased risk of DCM. This variant, believed to be under positive selection due to a protective role in malaria resistance, is present in 17% of AFR individuals but <0.1% of European genetic ancestry (EUR) individuals. Homozygotes for the risk allele, who comprise ~1% of the AFR population, had approximately threefold higher odds of DCM. Among those without clinical cardiomyopathy, homozygotes exhibited an 8% absolute reduction in left ventricular ejection fraction. In AFR, the DCM population attributable fraction for the CD36 variant was 8.1%. This single variant accounted for approximately 20% of the excess DCM risk in individuals of AFR compared to those of EUR. Experiments in human induced pluripotent stem cell-derived cardiomyocytes demonstrated that CD36 loss of function impairs fatty acid uptake and disrupts cardiac metabolism and contractility. These findings implicate CD36 loss of function and suboptimal myocardial energetics as a prevalent cause of DCM in individuals of African descent.

Elevated lipoprotein(a) [Lp(a)] is an independent risk factor for coronary artery disease (CAD). Data on long-term outcomes following invasive coronary angiography (ICA) in those with elevated Lp(a) are limited. This study examined the association of Lp(a) levels with clinical outcomes after index ICA, accounting for baseline atherosclerotic plaque burden.

Mass General Brigham, an integrated healthcare system based in the Greater Boston area of Massachusetts, annually serves 1.5 million patients. We established the Mass General Brigham Biobank (MGBB), currently encompassing 142,238 participants, to unravel the intricate relationships among genomic profiles, environmental context, and disease manifestations within clinical practice. In this manuscript, we described genetic and phenotypic diversity and their interaction in the MGBB by employing population genetics, geospatial assessment, and association analyses of rare and common genetic variants. The population genetic variation captured the demographic histories in the Greater Boston area throughout American history, highlighting communities tied to shared genetic and environmental factors. Furthermore, our phenome-wide association analysis with socioeconomic factors, as well as common and rare genetic variants, prioritized disease causes across a tertiary academic medical center and community-based health system. Our investigation underscores the potency of unbiased, large-scale analyses in a healthcare-affiliated biobank, elucidating the dynamic interplay across genetics, immigration, structural geospatial factors, and health outcomes in one of the earliest American sites of European colonization.

Bone morphogenetic protein-10 (BMP10), a protein predominantly secreted by atrial cardiomyocytes, has emerged as a promising biomarker in patients with atrial fibrillation (AF) and as a marker of atrial stress in patients with heart failure. Its clinical correlates in community-dwelling adults and its association with incident AF remain unexplored. BMP10 was measured in 5,883 participants from the Prevention of Renal and Vascular End-stage Disease (PREVEND) community-based cohort (mean age 53.6 yr; 51.5% females). The mean BMP10 concentration was 2.20 ± 0.43 ng/mL. In multivariable linear regression analyses, the strongest positive correlates of BMP10 were female sex [standardized beta-(Sβ): 0.34], high-density lipoprotein cholesterol (HDL-C; Sβ: 0.16), total cholesterol (Sβ: 0.13), and -terminal pro-B-type natriuretic peptide (NT-proBNP; Sβ: 0.13). The strongest negative correlates were relative fat mass (Sβ: -0.21), C-reactive protein (CRP; Sβ: -0.16), and estimated glomerular filtration rate (eGFR; Sβ: -0.13); for all < 0.001. BMP10 was not significantly associated with prevalent hypertension, myocardial infarction, stroke, or heart failure. Over a median follow-up of 6.4 years, 154 participants (2.6%) developed incident AF, corresponding to 4.2 cases per 1,000 person years. In a multivariable Cox-regression model, higher BMP10 levels were significantly associated with incident AF (Hazard ratio per 1SD increase: 1.58; 95%CI: 1.23-2.04). In summary, among community-dwelling adults, BMP10 levels are higher in women, positively associated with HDL-C and NT-proBNP, and inversely associated with fat mass, inflammation, and kidney function. Although not linked to prevalent cardiovascular disease, higher BMP10 levels are independently associated with incident AF. This is the first population-based study of circulating bone morphogenetic protein 10 (BMP10), a heart-specific protein mainly secreted by atrial cardiomyocytes. In over 5,800 community-dwelling adults, BMP10 showed distinct physiological and pathophysiological correlates, including higher levels in women, an inverse association with fat mass and inflammation (CRP), and a positive association with incident atrial fibrillation. These findings represent an important first step toward understanding the role of BMP10 in atrial biology and disease.

BMP10 (bone morphogenetic protein 10) is a ligand of the TGF (transforming growth factor) β superfamily secreted mainly by atrial cardiomyocytes. Elevated BMP10 blood concentrations predict atrial fibrillation (AF), AF recurrence after ablation, and AF-related cardiovascular complications like stroke. The conditions increasing BMP10 secretion and the downstream effects of BMP10 in cardiomyocytes are poorly understood. We assessed BMP10 secretion dynamics and BMP10 effects in a human 3-dimensional model of atrial and ventricular engineered heart tissue (EHT).

Cardiovascular disease remains the leading cause of global mortality. Understanding its complexity requires dissecting the heart's cellular landscape. We present HeartMap, a comprehensive single-nucleus RNA sequencing atlas of the adult human heart. This resource integrates data from nine studies, encompassing over 2.4 million nuclei, 209 individuals, eight anatomical regions, and seven disease and healthy states. After rigorous data harmonization and benchmarking of batch-correction methods, we characterized transcriptional diversity across 14 cell types. To demonstrate the utility of HeartMap, we identified robust disease-associated gene signatures in dilated cardiomyopathy by comparing across multiple studies. Notably, we identified distinct activated fibroblast populations, with COL22A1 or TNC enrichment, revealing potential differences between inherited and ischemic cardiomyopathies. HeartMap provides a valuable tool for exploring cardiac disease at the single-cell level, facilitating both fundamental research and potential therapeutic development.

Guidelines recommend considering coronary calcium score (CCS) in asymptomatic patients to aid risk stratification. However, calcification occurs late in atherosclerosis. Coronary CT angiography (CCTA) can detect non-calcific plaque and inflammation before calcification develops, but impact on clinical management is not well documented. We compare coronary artery disease (CAD) detection and grading between CCS and CCTA, impact on management, and explore CCTA-derived inflammation biomarker (pericoronary fat attenuation index [FAI]) in the lipid clinic. Exploratory analysis of a prospectively maintained database of lipid clinic patients with CCS and CCTA (2018-2020). CCS grade was compared with CCTA stenosis, presence of high-risk plaque (HRP) and FAI-score analysis. UK Consultant Lipidologists completed an anonymised survey, documenting lipid target and management after sequential unblinding of CCS and CCTA data. In 45 asymptomatic patients (49% female, mean age 55 ± 9), CCTA re-classified CAD presence in 22% (p = 0.002) and severity in 62% (p = 0.005) vs. CCS. HRP was observed in 20% (9/45), including 56% with CCS ≤ 100. Median LDL target with clinical vignette was 101 mg/dL (IQR 77-120), reducing to 89 mg/dL (77-120) after CCS, and 77 mg/dL (70-116) after CCTA unblinding. CCS altered LDL target in 12%, and CCTA a further 19% (χ2 57.0, p < 0.005). High FAI-score was demonstrated in 20%, including 22% of those with CCS ≤ 100 and 75% of those with ≤ mild CAD on CCTA. CCTA increased CAD prevalence and re-classified severity versus CCS, altering hypothetical management. High FAI-scores were observed across CCS and CCTA severity grades, including patients with no overt CAD.

Cardiovascular diseases became the first cause of maternal death in France, but only scarce epidemiological data have been published about heart failure (HF) in pregnancy/postpartum.

Heart failure (HF) and atrial fibrillation (AF) are major global health challenges with rising prevalence and significant morbidity, mortality, and healthcare burden. Despite advances in HF management, AF remains a critical comorbidity that worsens outcomes and requires ad hoc treatment strategies, increasing the risk of non-adherence and side effects. While rhythm control strategies in AF have gained attention for their prognostic benefits in HF, the pharmacological treatment of HF in patients with AF, including the benefit of rhythm versus rate control, remains underexplored. The relationship between HF and AF lacks sufficient evidence and targeted research to assess the optimal treatment strategies. This narrative review critically examines current HF pharmacotherapy in the context of AF, focusing on the four cornerstone treatments and modifiers of prognosis for HF with reduced ejection fraction: beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/sacubitril-valsartan, aldosterone antagonists, and sodium-glucose co-transporter 2 inhibitors. Although these therapies are well-established in HF patients, their efficacy in patients with concomitant AF requires further prospective investigation. The unique challenges posed by AF, including arrhythmia-induced remodelling and cardiomyopathy, necessitate a more individually tailored treatment. We also highlight critical knowledge gaps and the need for dedicated clinical trials specifically assessing HF therapies in AF subgroups, such as paroxysmal, long-standing persistent and permanent AF, and the benefit of heart rate and rhythm control strategies. The future of precision medicine in HF-AF management lies in bridging these evidence gaps through targeted research and interdisciplinary collaboration.

The locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF--driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at modulates CAD risk via -a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype.

The Global Registry of Acute Coronary Events (GRACE) scoring system guides the management of patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) according to current guidelines. However, broad validation of the sex-specific GRACE 3.0 in-hospital mortality model, and corresponding models for predicting long-term mortality and the personalised effect of early invasive management, are still needed.

Direct current cardioversion (DCCV) is commonly performed for atrial fibrillation and flutter (AF/AFL). However, temporal trends and contemporary practices surrounding DCCV are poorly characterized.

Polygenic scores (PGSs) can improve atrial fibrillation (AF) risk prediction, both alone and alongside clinical scores, offering potential for guiding targeted screening. However, their limited accuracy and cross-ancestry transferability remain major barriers to clinical translation. Here, we explored several multi-PGS approaches to generate ancestry-optimized PGSs for AF, and tested these in independent samples from the All of Us Research Program. Our ancestry-specific multi-trait approach, which leverages correlated traits, in particular outperformed the current gold-standard PGS among Asian (OR/SD = 1.76 [1.56-1.99]; AUROC = 0.637; AUPRC = 0.055), Admixed American (1.45 [1.38-1.53]; 0.595; 0.054) and African ancestry groups (1.39 [1.32-1.45]; 0.573; 0.064). Although predictive accuracy remained highest among Europeans (1.89 [1.85-1.93]; 0.646; 0.157) - in whom our PGS explained ~ 50% of SNP-heritability - our multi-trait approach yielded relatively larger gains in non-European populations. Improved risk stratification was also observed at PGS extremes, identifying a substantial proportion of European individuals with risk comparable to rare variants (e.g., 5.8% with > 4-fold odds). Overall, our ancestry-tailored multi-trait PGSs advance equitable AF risk prediction and provide a foundation for implementation.

Mechanical complications following acute myocardial infarction (MI) represent some of the most challenging conditions in contemporary cardiology, often leading to rapid clinical deterioration and high mortality despite advances in reperfusion therapy. These complications span a spectrum of presentations, from early-phase structural disruptions such as ventricular septal rupture, papillary muscle rupture with acute mitral regurgitation (MR), and left ventricular free wall rupture (LVFWR), to later-stage manifestations, including true ventricular aneurysms and pseudoaneurysms. While surgical intervention has traditionally been considered the standard of care, surgical intervention is often associated with prohibitive risk in hemodynamically unstable or frail patients. In this context, transcatheter approaches have gained traction as viable, less invasive alternatives, offering the potential for hemodynamic stabilization, symptom relief, and improved short-term outcomes in selected patients. Nonetheless, data from observational studies and registry-based analyses remain limited, underscoring the need for further research. This review synthesizes the current evidence base and clinical experience related to transcatheter management of mechanical complications after MI, emphasizing patient selection, procedural strategies, device selection, and reported outcomes.

Atrial fibrillation (AF) is currently diagnosed by ECG, creating a binary, lifelong diagnosis. AF burden, estimated as the proportion of time spent in AF, quantifies AF severity dynamically. AF burden can modulate the risk of AF-related outcomes. Whether AF burden modulates cardiovascular outcomes with rhythm-control therapy is unknown.

Coronary artery disease (CAD) polygenic risk scores (PRS) enhance risk stratification, but it is unknown whether the degree varies across the spectrum of atherosclerotic cardiovascular disease (ASCVD). We compared the association of a CAD PRS and coronary events in patients with ASCVD and a prior ischemic event, ASCVD without event, and without overt ASCVD.

Myocarditis is an inflammatory disease of the heart characterized by a complex interplay between innate and adaptive immune responses. The innate immune system provides first-line defense and includes soluble molecules, including macrophages, neutrophils, dendritic cells, and molecular mediators, but lacks immunological memory. In contrast, the adaptive immune system, via T and B lymphocytes, offers high specificity and long-term memory, which can sometimes target myocardial tissue, causing autoimmune injury. Particularly, acute myocarditis is characterized by dysregulated immune signaling, with cytokines (IL-2, IFN-γ, IL-12, IL-4, IL-10) and chemokines (MCP-1, CXCL4, CXCL10) driving disease progression, while adhesion molecules (ICAM-1, VCAM-1, VAP-1) promote leukocyte trafficking and cardiac inflammation. The balance between pro-inflammatory and regulatory responses determines disease outcomes, ranging from resolution with recovery to fulminant myocarditis or progression to dilated cardiomyopathy. Emerging therapeutic approaches targeting cytokines, chemokines, and adhesion molecules, along with established immunosuppressive treatments, underline the potential for modulating immune responses in myocarditis and, thereby, improving patient outcomes.

: Ischemic cardiomyopathy is a major cause of morbidity and mortality. Obesity is paradoxically associated with better outcomes, while clustering of cardiometabolic risk factors (CMRFs)-diabetes mellitus, arterial hypertension, and hyperlipidemia-is associated with worse prognosis in heart failure (HF) patients. The interplay between vascular function, obesity and clustering of CMRFs in ischemic HF is not thoroughly investigated. : In a prospective, single-center cohort study, 560 patients with ischemic cardiomyopathy were followed for a median of 43 months. Baseline BMI, CMRFs and markers of vascular function including flow-mediated dilation (FMD), and carotid-femoral pulse wave velocity (cf-PWV) were assessed. Major adverse cardiovascular events (MACE), including death, myocardial infarction, coronary revascularization, stroke, and hospitalization for heart failure or other cardiovascular causes, were recorded. Cox proportional hazards models and cubic spline analyses evaluated associations and nonlinear relationships. : Obesity was independently associated with a 50% lower risk of MACE (HR 0.50; 95% CI 0.32-0.981; = 0.01) and improvement of FMD by 1% corresponded to a 7% reduction in MACE risk (HR 0.93; 95% CI 0.87-0.99; = 0.03) after adjusting for multiple confounders. Clustering of all three CMRFs predicted greater MACE risk (HR 1.42; 95% CI 1.03-1.95; = 0.03). No significant differences in FMD or cf-PWV were observed across BMI groups. cf-PWV values were impaired among patients with all 3 CMRFs but cf-PWV did not predict MACE. : Higher BMI and FMD each independently predict improved outcomes in ischemic cardiomyopathy. The clustering of cardiometabolic risk factors is a strong predictor of adverse events.

Incomplete penetrance, or absence of disease phenotype in an individual with a disease-associated variant, is a major challenge in variant interpretation. Studying individuals with apparent incomplete penetrance can shed light on underlying drivers of altered phenotype penetrance. Here, we investigate clinically relevant variants from ClinVar in 807,162 individuals from the Genome Aggregation Database (gnomAD), demonstrating improved representation in gnomAD version 4. We then conduct a comprehensive case-by-case assessment of 734 predicted loss of function variants in 77 genes associated with severe, early-onset, highly penetrant haploinsufficient disease. Here, we identify explanations for the presumed lack of disease manifestation in 701 of 734 variants (95%). Individuals with unexplained lack of disease manifestation in this set of disorders are rare, underscoring the need and power of deep case-by-case assessment presented here to minimize false assignments of disease risk, particularly in unaffected individuals with higher rates of secondary properties that result in rescue.

Atrial fibrillation, the most frequent cardiac arrhythmia, causes heart failure and stroke. Here we describe that combining the typical risk factors of atrial fibrillation (hypertension, obesity and mitral valve regurgitation (HOMER)) activates adaptive immunity in wild-type mice, ultimately causing electrical remodeling of cardiomyocytes. In HOMER mice, dendritic cells expanded in the left atria and heart-draining lymph nodes, where we detected cardiomyocyte-derived proteins. Systemically expanding B cells, while exposed to interferon-α, produced autoantibodies that disrupted calcium handling in cardiomyocytes. Depleting B cells by using μMT HOMER mice or plasma cells by using Mb1 Prdm1 HOMER mice reduced atrial fibrillation while mitigating the prolonged action potential duration we observed in the left atria of HOMER mice. CD20 antibody B cell depletion, a clinical tool in treating lymphoma and autoimmune disease, reduced atrial fibrillation fivefold in HOMER mice. Targeting humoral immunity may provide therapeutic avenues for patients with autoantibody-induced atrial fibrillation.

Cryoballoon ablation of atrial fibrillation alters a significant amount of vital myocardium contributing to its electrical activity. However, the effect of pulmonary vein isolation (PVI) on the P-wave is unclear. The study aimed to quantify P-wave changes following individual PVI using signal-averaged ECG analysis.

Shift work is known to be a risk factor for metabolic diseases. Although not established within literature, socioeconomic disadvantage may be associated with increased risk of being engaged in these shift work patterns.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, linked to greater risk of heart failure, stroke and death. Inflammation has been connected to AF emergence, however mechanisms of inflammation-caused AF remain thus far elusive, leading to a lack of mechanism-based treatments. An isogenic, 3D tissue model containing hiPSC-derived atrial-like cardiomyocytes (aCM), cardiac fibroblasts (cfb), and cardiac macrophages was engineered using custom injection-molded pillar devices. Electrophysiological changes were examined via sharp electrode recordings, calcium imaging, and multi-electrode assays. Gene function was interrogated using siRNA knock-down, lentiviral overexpression, and pharmacological modulation. In silico tissue and whole-heart models validated findings under simulated stress and heterogeneous conditions. Activation of M1 macrophages led to a 50% reduction in contraction amplitude, action potential spike amplitude (aCM+cfb+M1: 61.3 mV ±13.9 control: 71.6 mV ±14.5, p < 0.01) and increased beat irregularity (M1: 150.7% ± 388.9 control, p < 0.001). Calcium transient amplitude was reduced (12.3 a.u. ± 14.7, p < 0.05) and upstroke velocity slowed. SCN5A knock-down reduced contraction amplitude (-51.9% ± 37.2, p < 0.01) without inducing arrhythmias, whereas combined GJA5 and ATP1A1 knock-down induced significant irregularity (403% ± 371.3, p < 0.001), increased conduction heterogeneity (+18%), and reduced velocity (-52.4%). In silico modeling confirmed that paired 50% downregulation of sodium-potassium pump and tissue conductivity induced AF under tachycardia even without ectopic activity. This work reveals a novel, inflammation-driven mechanism for AF initiation. Combined downregulation of GJA5 (connexin 40) and ATP1A1 (NaK ATPase) disrupted intercellular connectivity and ion flux, establishing a substrate for arrhythmogenesis. These results were robust across , genetic/pharmacological, and in silico models, defining new avenues for translational intervention.

Some nuclei of the hypothalamus are known for their important roles in maintaining energy homeostasis and regulating food intake. Moreover, obesity has been associated with hypothalamic inflammation and morphological alterations, as indicated by increased volume. However, the reversibility of these changes after bariatric surgery-induced weight loss remains underexplored. The aim of this study was to characterize volume changes in hypothalamic subunits up to 2 years following bariatric surgery. A secondary objective was to explore whether changes in hypothalamic subunit volumes were associated with changes in metabolic parameters and levels of gastrointestinal appetite-regulating hormones. Participants with severe obesity undergoing bariatric surgery were recruited. They completed high-resolution T1-weighted brain magnetic resonance imaging (MRI) before bariatric surgery and at 4, 12, and 24 months post-surgery. Blood samples collected during the fasting and postprandial states were analyzed for concentrations of glucagon-like peptide 1 (GLP-1), peptide YY (PYY), and ghrelin. The hypothalamus was segmented into five subunits per hemisphere using a publicly available automated tool. Linear mixed-effects models were employed to examine volume changes between visits and their associations with variables of interest. A total of 73 participants (mean age 44.5 ± 9.1 years; mean body mass index (BMI) 43.5 ± 4.1 kg/m) were included at baseline, with 22 participants completing 24-month follow-up. Significant volume reductions were observed in the whole left hypothalamus 24 months post-surgery. More specifically, decreases were noted in both the left anterior-superior and left posterior subunits at 12 and 24 months post-surgery (all p < 0.05, after false discovery rate (FDR) correction). Smaller volumes in these subunits were significantly associated with a greater percentage of total weight loss (both subunits p < 0.001), as well as with higher postprandial PYY levels (both subunits p < 0.05). These findings suggest that some hypothalamic morphological alterations observed in the context of obesity could potentially be reversed following bariatric surgery-induced weight loss.