European Heart Journal

Background and Aims: Epicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. Methods: In this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. Results: Percentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA- indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). Conclusion: Age- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.

Background: The INTERHEART-Middle East study identified the Middle East and North Africa (MENA) region as having the youngest age at first acute myocardial infarction (AMI) globally, with a population-attributable risk of 97.5% across nine modifiable risk factors. The population-level trajectories of cardiometabolic risk factors that precede this premature MI signature in young MENA adults remain incompletely characterized. Methods: NCD Risk Factor Collaboration (NCD-RisC) modeled prevalence estimates were analyzed across 16 MENA countries (Bahrain, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, Yemen) in adults aged 20-29 and 30-39 years, stratified by sex: obesity and diabetes prevalence through 2022, hypertension prevalence through 2019 (ages 30-39 only, by data availability), and non-HDL cholesterol through 2018. Five-year age bands were aggregated into 20-29 and 30-39 groups by equal-weighted mean (with UN World Population Prospects 2024 population-weighted aggregation tested as a sensitivity analysis). Each country x sex x age-band x risk-factor series was analyzed using (1) joinpoint regression for the average annual percent change (AAPC); (2) posterior probability of true 1990-to-endpoint change derived from published credible intervals; and (3) a mixed-effects model with a year x region (MENA vs. rest-of-world [ROW]) interaction and country-level random slopes. Sensitivity analyses excluded conflict-affected states and Iran. Results: MENA diverged significantly from ROW in 6 of 14 sex x age-band comparisons, with a sex-asymmetric direction. In men, MENA worsened faster than ROW: obesity, ages 20-29 (AAPC +3.49%/year; p=0.009); obesity, ages 30-39 (AAPC +2.65%/year; p=0.043); and diabetes, ages 30-39 (AAPC +1.90%/year; p=0.014). In women, MENA improved faster than ROW: hypertension, ages 30-39 (AAPC -0.58%/year; p=0.001); non-HDL cholesterol, ages 20-29 (p=0.017); and non-HDL cholesterol, ages 30-39 (p=0.017). Country-level posteriors confirmed near-universal regional patterns: 60 of 64 obesity cells showed a very probable increase since 1990, and 52 of 64 (81%) non-HDL cholesterol cells showed a probable or very probable decrease. Five of the six divergent findings survived correction for multiple testing. Conclusion: Cardiometabolic risk in young MENA adults is diverging from global patterns in a sex-asymmetric way: obesity and diabetes are accelerating in young men, while hypertension and lipid profiles are improving in young women. This pattern maps directly onto the young-male AMI signature reported by INTERHEART-Middle East and identifies obesity and diabetes in young men as the most urgent targets for regional primary prevention.

Background Patients with normal perfusion, normal myocardial flow reserve (MFR) and no coronary artery calcium (CAC) on myocardial perfusion imaging are considered low risk. Yet, adverse events still occur and no routinely reported imaging marker stratifies residual risk. This study aims to determine whether fully automated ascending aortic calcification (AAC) from the attenuation correction CT stratifies risk in these patients. Methods In the multicenter REFINE-PET registry, AAC was quantified from non-contrast CT using deep learning aortic segmentation and Agatston scoring. Triple-normal was defined as stress total perfusion deficit (TPD) <5%, MFR >2 and CAC 0. The primary endpoint was cardiovascular death, myocardial infarction or heart failure admission, with heart failure admission as key secondary endpoint. Cox models were adjusted for clinical confounders. Results Of 21,923 patients, 3,580 (16.3%) were triple-normal, of whom 1,322 (36.9%) had AAC (median Agatston 65, IQR 22-212). Agreement with three blinded readers was good to excellent (Intraclass correlation coefficient 0.87-0.90). Over a median follow-up of 52 months (IQR 26-69), 194 primary events occurred. Per standard deviation, AAC was independently associated with the primary endpoint (adjusted HR 1.24, 95% CI 1.09-1.40; p<0.001), heart failure admission (adjusted HR 1.30, 95% CI 1.10-1.55; p=0.003) and all-cause mortality (adjusted HR 1.17, 95% CI 1.04-1.32; p=0.009). AAC improved model fit beyond clinical factors, MFR and TPD (p< or =0.009), with modest gains in discrimination ({Delta}C 0.007-0.009). Conclusions In patients with normal PET readouts, automated AAC was independently associated with adverse outcomes, most strongly heart failure admission, beyond clinical risk factors, perfusion and flow.

BACKGROUND Contemporary cardiovascular risk equations guide prevention, yet cardiovascular risk remains distributed beyond the highest-risk groups. Whether broader baseline phenotyping can improve risk stratification and whether this information can be reduced to clinically accessible measures is uncertain. OBJECTIVES To assess whether baseline phenotyping improves cardiovascular risk stratification beyond PREVENT and CHARGE-AF and whether this information can be compressed into clinically accessible measures. METHODS We studied 266,410 UK Biobank participants without prevalent CHD, HF, AF, or stroke, divided into training, validation, and held-out test samples. PREVENT equations were used to estimate 10-year risk for CHD, HF, and stroke, and CHARGE-AF to estimate 5-year AF risk. Models considered 3,838 baseline phenotypes. Geographic replication was assessed in Scotland and Wales. RESULTS The highest-risk 20% identified by the clinical equations accounted for 44.8% to 55.2% of subsequent events across the 4 outcomes. Broad phenotyping refined risk stratification beyond these equations. After compression from 3,838 baseline phenotypes, disease-specific sets of 13 to 19 clinically accessible measures retained part of the incremental discrimination provided by broader phenotyping, yielding held-out IPCW AUC improvements of 0.013 to 0.030 relative to the corresponding clinical equations, with the largest gain for HF. At the same 20% prioritization level, the clinically accessible measures increased the proportion of subsequent events captured by 2.7 to 4.9 percentage points. Findings were directionally consistent in geographic replication. CONCLUSIONS Disease-specific sets of clinically accessible measures retained part of the information identified from broad phenotyping and refined cardiovascular risk stratification beyond contemporary clinical equations. Independent external validation is required before clinical use.

Observational studies suggest an association between COVID-19 and acute myocardial infarction (AMI), however, whether this relationship is causal remains unclear. We conducted a multi-ancestry Mendelian randomization (MR) study across European, East Asian, South Asian, and African populations, evaluating three COVID-19 phenotypes: very severe COVID-19, hospitalized COVID-19, and general infection association with AMI. GWAS summary statistics were obtained from the COVID-19 Host Genetics Initiative Round 7 and UK Biobank/Biobank Japan for AMI. Inverse-variance weighted (IVW) MR was the primary method, with fixed- or random-effects models selected according to heterogeneity test. MR-Egger, weighted median and weighted mode were conducted as sensitivity analyses. In European ancestry, genetic liability to very severe COVID-19 and hospitalized COVID-19 was slightly inversely associated with AMI risk, but without statistical significances across sensitivity analyses. Hospitalized COVID-19 showed a suggestive but non-significant inverse association in South Asian ancestry. No significant associations were identified in East Asian or African ancestries. Our findings did not support a robust causal association between COVID-19 susceptibility or severity and AMI risk across ancestries, suggesting that the observed cardiovascular burden may be driven more by acute pathophysiological mechanisms than shared genetic architecture.

Background: DNA methylation (DNAm) signatures capture cumulative lifestyle exposures and biological aging. This prospective study evaluated whether DNAm-based scores and epigenetic aging clocks are associated with clinical outcomes and mortality in a multinational cohort of patients with heart failure (HF). Methods: We studied 2,594 patients with HF from 40 countries in the Global Congestive Heart Failure (G-CHF) registry with whole-blood DNAm data. Fifteen published DNAm-based scores and epigenetic aging clocks reflecting lifestyle, environmental and physiological exposures, inflammation, frailty, mortality risk, and biological aging were derived. Associations with HF hospitalization, cardiovascular death, and all-cause death were assessed using multivariable Cox regression adjusted for age, sex, ancestry, the MAGGIC risk score, and NT-proBNP. Incremental prognostic value was compared to MAGGIC score and NT-proBNP. Extreme DNAm profiles were defined as scores or clocks exceeding {+/-}1.5 standard deviations (s.d.) from the population mean. Results: Mean age was 62.7{+/-}14.0 years, 66.2% were male, and mean left ventricular ejection fraction was 40.1{+/-}14.1%. During a median follow-up of 3.0 years, 338 patients were hospitalized for HF, 349 died from cardiovascular causes, and 565 died from any cause. Higher epigenetic age and DNAm scores for CRP, frailty, and mortality were associated with increased risk, whereas higher diet-related DNAm scores were inversely associated. For all-cause death, adjusted hazard ratios per 1-s.d. were 1.36 (95% CI, 1.24-1.50) for GrimAge, 1.27 (95% CI, 1.17-1.38) for the DNAm score for CRP, 1.44 (95% CI, 1.28-1.63) for the DNAm score for frailty, and 1.48 (95% CI, 1.32-1.65) for the DNAm score for mortality, compared with 0.81 (95% CI, 0.75-0.88) and 0.86 (95% CI, 0.79-0.94) for the DNAm scores for Alternative Healthy Eating Index and Mediterranean Diet Score. These patterns were directionally consistent for cardiovascular death and weaker for HF hospitalization and were more pronounced among patients with lower clinical risk (MAGGIC<17, Pinteraction<0.05), particularly for all-cause death. Patients with 4-5 extreme-high DNAm scores or clocks had more than twice the risk of death (HR, 2.27; 95% CI, 1.65-3.13). Conclusions: DNAm-based scores and epigenetic aging clocks reflect multiple dimensions of biological vulnerability in HF and are associated with clinical outcomes and mortality beyond clinical risk factors.

Background: Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of the more than 64 million heart failure cases globally, yet its pathophysiology is incompletely understood, its molecular determinants are poorly defined, and disease-specific therapies remain limited. Comprehensive characterization of the cardiac motion abnormalities central to HFpEF has not been feasible at the population level. Methods: We developed a deep learning framework integrating image segmentation with optical flow motion analysis and applied it to standard cine cardiac magnetic resonance images from 83,569 UK Biobank participants, deriving 32 myocardial and inner cavity velocity phenotypes spanning the cardiac cycle, including mid-diastolic velocities not previously quantified at population scale. We examined the prognostic relevance, genetic architecture, and candidate causal mediators of the optical flow velocity phenotypes. Results: In a pragmatically defined HFpEF subcohort, mid-diastolic and late-diastolic optical flow velocities were reduced relative to healthy reference participants, while higher systolic left ventricular myocardial velocity was associated with lower all-cause mortality (HR 0.61 per SD; 95% CI 0.45-0.82). Genome-wide association analyses identified 12 risk loci associated with optical flow velocity phenotypes. Phospholamban (PLN), the canonical regulator of sarcoplasmic reticulum calcium reuptake, demonstrated the broadest pleiotropy across all cardiac phases. SOX5, a transcription factor involved in extracellular matrix development, showed significant genome-wide association exclusively with mid-diastolic velocities. Mendelian randomization implicated RABGAP1L as a candidate causal mediator of early diastolic velocity (IVW {beta} = -0.255 per NPX for early diastolic right ventricular inner circumferential velocity; p = 5.49 x 10^-22), nominating a calcium-handling pathway in diastolic dysfunction. Conclusion: Genetic and causal-inference evidence implicates intracellular calcium handling and extracellular matrix remodeling as candidate mechanisms underlying diastolic dysfunction. Together, this work establishes deep-learning-enabled cardiac motion phenotyping as a scalable approach to interrogate the molecular basis of HFpEF and nominates candidate targets for therapeutic development.

Background: Comprehensive guideline-directed medical therapy (GDMT) remains underused in older patients with HFrEF, but whether the potential for treatment-associated myocardial recovery is preserved with advancing age remains uncertain. Objectives: To characterize age-related GDMT gaps and determine whether GDMT intensity is associated with left ventricular (LV) reverse remodeling across age and subsequent outcomes. Methods: We studied 1,795 patients with HFrEF receiving angiotensin receptor-neprilysin inhibitor (ARNI)-based therapy in the multicenter STRATS-HF-ARNI registry. GDMT intensity was defined by the number of foundational therapies used during the first year after ARNI initiation. Serial LV remodeling and subsequent death or HF hospitalization were evaluated using multivariable models and a 1-year landmark analysis. Results: Triple/quadruple GDMT was achieved in 59.1%, 50.8%, 53.4%, and 43.0% of patients aged <60, 60-69, 70-79, and [&ge;]80 years, respectively (P<0.001). Older age and renal dysfunction independently predicted less comprehensive GDMT. Each additional GDMT pillar was associated with greater improvements in LVEF (+1.23 percentage points; P=0.012) and LV global longitudinal strain (+0.32 percentage points; P=0.049) and greater reductions in LV volumes. Substantial remodeling remained evident at advanced age. Greater LV reverse remodeling predicted lower subsequent risk, and exploratory bootstrap analyses supported significant indirect associations between greater GDMT intensity and lower risk through all four LV remodeling measures. Conclusions: Older patients received less comprehensive GDMT despite preserved potential for LV reverse remodeling. Greater GDMT intensity was associated with greater myocardial recovery, which may represent a pathway to better prognosis. These findings support intensive GDMT implementation in older patients when clinically tolerated.

Background Targeted pharmacologic therapies for transthyretin amyloid cardiomyopathy (ATTR-CM) improve survival; however, their effects on cardiac structural parameters remain incompletely defined. Objectives To evaluate the pooled effects of disease-modifying therapies for ATTR-CM on echocardiographic structural parameters. Methods In accordance with PRISMA guidelines, we performed a systematic review and meta-analysis of randomized controlled trials and observational studies published through March 2025 assessing transthyretin stabilizers and RNA-silencing therapies in adults with cardiac amyloidosis. Outcomes included changes in global longitudinal strain (GLS), left ventricular ejection fraction (LVEF), interventricular septal (IVS) thickness, left ventricular mass, stroke volume, E/e? ratio, and LV end-diastolic volume. Pooled between-group mean differences were calculated using random-effects models. Sensitivity analyses were performed. Results Eighteen studies (11 randomized, 7 observational) encompassing 3,646 patients were included. Compared with control, drug therapy was associated with attenuation of GLS decline (mean difference [MD] -0.69%; 95% CI -1.10 to -0.29; P<0.001) and preservation of LVEF (MD 1.62%; 95% CI 0.73 to 2.51; P<0.001). Treatment was also associated with reduced worsening of E/e? ratio, and preservation of stroke volume. No significant between-group differences were observed for IVS thickness, LV mass and LV end-diastolic volume. Within-group analyses showed no change in echocardiographic parameters between baseline and follow-up in treated patients, in contrast to significant worsening in the control cohort. Conclusions Disease-modifying therapies for ATTR-CM are associated with stabilization and attenuated progression of cardiac remodeling rather than reversal of structural abnormalities.

ImportanceCardiovascular disease remains the leading cause of mortality worldwide. Although machine learning models have demonstrated strong predictive performance, limited attention has been given to uncertainty quantification and gender-specific risk factor identification, which are essential for clinically trustworthy artificial intelligence. ObjectiveTo develop and evaluate an interpretable and uncertainty-aware machine learning framework for cardiovascular disease prediction that integrates an association study on biomarkers, explainable artificial intelligence, and gender-stratified risk assessment. Design, Setting, and ParticipantsThis retrospective observational study utilized the UCI Heart Disease dataset comprising 918 participants, including 725 males and 193 females. Demographic, clinical, laboratory, and exercise-related variables were analyzed. Missing values were addressed using a hybrid imputation strategy combining MICE and supervised Random Forest imputation. MethodsAn ensemble machine learning imputation strategy was developed to address missingness. Then advanced machine learning models were developed and evaluated using stratified training/testing partitions and 5-fold cross-validation. Predictive performance was assessed using several evaluation metrics. Uncertainty was quantified through bootstrap resampling, predictive entropy, and mutual information. Linear Double machine learning and Causal Forest double machine learning were applied to estimate gender-specific averages and association studies for risk factors. ResultsRandom Forest achieved the strongest and most stable predictive performance across male and female cohorts, with ROC-AUC values exceeding 0.90 and robust cross-validation performance. Hybrid imputation improved classification performance, increasing the F1-score from 0.87 to 0.89 and ROC-AUC from 0.90 to 0.92. The causal association study analyzes identified the number of major vessels, ST-segment slope, thalassemia, and exercise-induced angina as the strongest determinants of heart disease, with notable differences observed between male and female subgroups. Conclusions and RelevanceIntegrating predictive modeling, uncertainty quantification, and association study machine learning provides a robust and clinically interpretable framework for cardiovascular disease risk assessment. The proposed approach improves prediction reliability while identifying gender-specific causally important risk factors, supporting precision cardiovascular medicine and trustworthy clinical artificial intelligence.

Background and Aims: Cardiovascular disease (CVD) remains the leading cause of global mortality. We evaluated 24 year global trends in age-standardized CVD mortality across 204 countries and territories (2000-2023) and decomposed the independent longitudinal associations of major cardiometabolic risk factor pathways. Methods: The study analyzed a balanced panel of 4,896 country-year observations using Global Burden of Disease 2023 and World Bank data. Two-way fixed-effects panel regression models adjusting for country fixed effects, year fixed effects, GDP per capita, and urbanization were specified using Driscoll-Kraay robust standard errors. Hierarchical path mediation and extended 1- to 10-year lag models evaluated risk pathways and disease latency. Results: Global age-standardized CVD mortality declined from 340.2 -+ 156.4 to 258.4 -+ 132.1 deaths per 100,000 population (2000-2023), but annual declines stagnated post-2019 (-1.31% to -0.03% per year). High SBP (adjusted beta = 1.129), high LDL cholesterol (beta = 0.622), smoking (beta = 0.452), and high fasting glucose (beta = 0.410) were independently associated with CVD mortality (P < 0.001 for all). High SBP reduction accounted for 70.91% of the global mortality decline. High BMI was not directly associated with mortality (beta = 0.049, P = 0.421); mediation analysis proved that 99.20% of its population impact is mediated through downstream metabolic intermediaries. Conclusions: Elevated SBP and cumulative LDL cholesterol are the primary drivers of global cardiovascular mortality. Obesity acts as an upstream driver operating almost entirely through downstream metabolic intermediaries. Sustained progress requires prioritizing universal blood pressure control, lipid lowering, and multi-sectoral obesity prevention.

Background: Established heart-failure (HF) risk scores were developed largely in Western cohorts, assume linear predictor effects, and stop at prognosis without indicating action. We developed and externally validated machine-learning (ML) models for 30-day and 1-year mortality in a multi-ethnic Asian HF population, benchmarked against three established scores, and tested whether they localised correctable guideline-directed medical therapy (GDMT) gaps. Methods: We analysed 9,050 adults hospitalised with HF across eight Singapore hospitals (November 2016?March 2023). Gradient-boosted trees (XGBoost, primary) and elastic-net logistic regression were developed on three hospitals (n=4,034) and validated on five independent hospitals (n=5,016), without patient or site overlap. Comparators (MAGGIC, Singapore HF Score, OPTIMIZE-HF-Asia) were logistically recalibrated on development data. Results: On external validation XGBoost achieved AUROCs of 0.862 (95% CI 0.833?0.890) for 30-day and 0.749 (0.734?0.764) for 1-year mortality, versus 0.711?0.754 and 0.682?0.699 for the three recalibrated scores; logistic regression performed near-identically (0.864, 0.757) and was better calibrated at 1 year. Superiority held under temporal validation, multiple imputation and optimism correction, although the 30-day advantage was no longer distinguishable from MAGGIC once medications were removed. Among predicted-high-risk patients with reduced ejection fraction, mean GDMT exposure was 0.92 of four pillars versus 1.87 across all HFrEF patients, and 36.3% received none of the four versus 2.0% of low-risk patients. Ten variables reproduced full-model 30-day discrimination (AUROC 0.865). Conclusions: In external validation, interpretable models substantially outperformed established HF risk scores for short- and long-term mortality and simultaneously localised correctable therapeutic gaps, supporting a prediction-to-action tool deployable with ten bedside variables.

Background: Atrial fibrillation detected after stroke (AFDAS) is frequently diagnosed after embolic stroke of undetermined source (ESUS) and has important implications for secondary stroke prevention. Although prediction scores have been proposed to identify patients at increased risk of AFDAS, prospective evidence supporting their implementation to guide rhythm monitoring in routine clinical practice is limited. Methods: In this prospective, population-based implementation cohort study, adults with ESUS were enrolled between January 2022 and December 2024 across all stroke centers in Styria, Austria. The Graz AF Risk Score was prospectively implemented as part of a risk-adapted diagnostic pathway for cardiac rhythm monitoring. Patients with a score [&ge;]4 were recommended for implantable loop recorder monitoring, whereas monitoring in those with scores <4 remained at the treating physician's discretion. The primary outcome was AFDAS detection; recurrent ischemic stroke and recurrent stroke etiology were secondary outcomes. Results: Among 784 patients (median age 73 years [IQR 64-80], 45.7% women), AFDAS was detected in 166 patients (21.2%) during a median follow-up of 26.3 months (IQR 20-34). AFDAS detection was substantially higher in patients with a Graz AF Risk Score [&ge;]4 than <4 (38.1% vs. 3.9%; p<0.001). After adjustment for age, sex and ILR monitoring, a score [&ge;]4 independently predicted AFDAS (HR 6.3, 95% CI 3.5-11.2; p<0.001) and recurrent ischemic stroke (HR 2.2, 95% CI 1.1-4.1; p=0.023). Only one recurrent stroke in patients with a score <4 was attributable to atrial fibrillation (AF) (1/18, 5.6%). Conclusions: Prospective implementation of the Graz AF Risk Score identified patients with ESUS at markedly different risks of AFDAS. A Graz AF Risk Score [&ge;]4 was also independently associated with recurrent ischemic stroke. These findings support a risk-adapted approach to cardiac rhythm monitoring after ESUS.

Background: Tirzepatide and semaglutide improve functional status and heart failure (HF) events in patients with obesity and HF with preserved ejection fraction. Tirzepatide has been associated with greater control of cardiometabolic risk factors in patients with obesity compared to semaglutide. Whether tirzepatide is associated with lower risk of new-onset HF than semaglutide in patients with obesity is underexplored. Methods: A retrospective cohort study was conducted using data pooled from the TriNetX platform. Patients with obesity who initiated therapy with tirzepatide or semaglutide during the period Jun 4, 2021 to Aug 13, 2026 were identified and 1:1 propensity-score matched to produce two study cohorts. The one-year incidence of new-onset HF was calculated and compared between the two cohorts. Secondary outcomes included new-onset systolic HF, new-onset diastolic heart failure, new-onset atrial fibrillation or flutter, all-cause mortality, and hospital encounters. Cox proportional hazards models were fitted to calculate hazard ratios (HR) along with 95% confidence intervals (CI). Results: Two well-matched cohorts (N=424,269 in each) were formed. The incidence of new-onset HF was lower in the tirzepatide group (1.0% vs. 1.3%; absolute risk difference -0.3%, 95% CI -0.35 to -0.26; HR 0.9, 95% CI 0.86[boxh]0.93). The tirzepatide group were also at lower risk of all-cause mortality (HR, 95% CI: 0.8, 0.77[boxh]0.91) and new-onset systolic HF (0.8, 0.79[boxh]0.92). All other secondary outcomes occurred at similar rates in both study groups. Conclusion: Among patients with obesity, tirzepatide therapy was associated with lower risk of new-onset HF compared to semaglutide although the effect sizes were modest.

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with metabolic stress, hypertension, systemic inflammation, and microvascular dysfunction. Early cell-type-specific events and intercellular communication programs that accompany disease onset and progression remain poorly defined. MethodsWe performed a longitudinal study of HFpEF progression in high-fat diet (HFD)+L-NAME mice at control/baseline (0 weeks, 0w/Ctrl), early (1w), intermediate (4w), and established (8w) stages. Metabolic, hemodynamic, exercise, echocardiographic, and single-cardiomyocyte function were assessed. Cardiac non-cardiomyocytes (non-CMs) were profiled by single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq for tissue-level comparison. Endothelial remodeling was assessed in an L-NAME-independent HFD plus mild transverse aortic constriction model (HFD+mTAC) and a published human HFpEF single-nucleus RNA-seq cohort. An endothelial-macrophage adhesion assay tested whether HFpEF-mimic stress promotes endothelial activation and macrophage adhesion. ResultsIn the HFD+L-NAME model, metabolic dysfunction, hypertension, reduced exercise tolerance, abnormal diastolic filling with preserved ejection fraction, and altered cardiomyocyte calcium handling were detected by 1w and persisted through 8w. Bulk RNA-seq showed progressive remodeling, with limited change between 8w and 12w, guiding scRNA-seq timepoint selection. scRNA-seq of 94,848 cardiac non-CMs identified nine major populations with stage-dependent remodeling. Endothelial cells (ECs) were recovered in high proportion and showed an early, pronounced transcriptional response, with inflammatory, adhesion, interferon-response, migratory, and vascular-remodeling programs emerging by 1w. Related EC activation signatures were observed in HFD+mTAC and human HFpEF data. Functionally, HFpEF-mimic stress increased adhesion and chemokine expression in human ECs and enhanced macrophage adhesion. Fibroblast matrix remodeling occurred at later stages, while macrophages progressively shifted toward inflammatory states. CellChat suggested stage-dependent communication remodeling from early endothelial-immune interactions toward later macrophage-fibroblast crosstalk. ConclusionTime-resolved scRNA-seq reveals coordinated, stage-dependent remodeling of the cardiac microvascular and interstitial microenvironment during HFpEF progression. Early endothelial activation emerges before later fibroblast matrix remodeling and inflammatory macrophage remodeling, identifying candidate cell states and signaling pathways for future mechanistic investigation. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study provides a time-resolved single-cell atlas of the cardiac non-cardiomyocyte compartment across baseline, early, intermediate, and established stages of HFpEF progression, rather than a single late-stage snapshot. C_LIO_LIEndothelial cells exhibit early inflammatory, adhesion, interferon-response, and vascular-remodeling programs within the first week of disease, preceding the later predominance of fibroblast matrix remodeling and inflammatory macrophage remodeling. C_LIO_LIThis endothelial activation signature is supported across two mechanistically distinct HFpEF mouse models and aligns with endothelial inflammatory and vascular-remodeling programs in human HFpEF myocardium, supporting its translational relevance. C_LI What Are the Clinical Implications?O_LIEarly endothelial activation may represent a targetable stage of HFpEF pathogenesis that arises before more established structural and fibrotic remodeling. C_LIO_LITherapeutic strategies aimed at limiting endothelial inflammatory activation or endothelial-immune interactions may help attenuate downstream vascular, immune, and stromal remodeling in HFpEF. C_LIO_LIThese findings provide a preclinical foundation for future longitudinal human studies testing whether early endothelial activation can serve as a biomarker, therapeutic target, or disease-staging feature in HFpEF. C_LI

Background Several disease-modifying agents for transthyretin amyloid cardiomyopathy (ATTR-CM) have been investigated, but differences in trial design and background stabilizer use complicate interpretation of their efficacy. This meta-analysis assessed their efficacy overall and by background stabilizer use. Methods PubMed, Embase, and the Cochrane Library were searched through September 2026 for phase III randomized, placebo-controlled trials of disease-modifying therapy in ATTR-CM. Primary endpoints were all-cause mortality, 6-minute walk distance (6MWD), Kansas City Cardiomyopathy Questionnaire-Overall Summary (KCCQ-OS) score, and N-terminal pro-B-type natriuretic peptide (NT-proBNP), pooled with a random-effects model. Treatment effects were compared between the monotherapy and baseline stabilizer strata using a mixed-effects model. Results Five trials (ATTR-ACT, APOLLO-B, ATTRibute-CM, HELIOS-B, CARDIO-TTRansform; N=3497) were included. Disease-modifying therapy reduced all-cause mortality (risk ratio, 0.76; 95% confidence interval [CI], 0.66-0.87; I2=0%) and improved 6MWD (pooled standardized mean difference [SMD], 0.43; 95% CI, 0.20-0.67), KCCQ-OS score (SMD, 0.37; 95% CI, 0.19-0.55), and NT-proBNP (SMD, -0.53; 95% CI, -0.89 to -0.18). The mortality benefit was similar whether therapy was given alone or added to a background stabilizer (pooled risk ratio, 0.77 vs. 0.71; P for interaction = 0.59), but treatment effects on 6MWD (pooled SMD, 0.49 vs. 0.14), KCCQ-OS score (0.44 vs. 0.07), and NT-proBNP (-0.65 vs. -0.13) were smaller among patients receiving a background stabilizer (P for interaction = 0.012, <0.001, and 0.029, respectively). Conclusion Disease-modifying treatments reduced all-cause mortality and favored functional capacity, health status, and NT-proBNP outcomes in patients with ATTR-CM. Exploratory subgroup analyses showed smaller treatment effects on 6MWD, KCCQ-OS score, and NT-proBNP among patients receiving a background stabilizer, with no statistically significant difference in the mortality effect according to baseline stabilizer use.

Background Galectins regulate inflammation, fibrosis, immunity, and vascular remodeling. Although galectin-3 has been widely studied in cardiovascular disease, the relative contributions of other galectins to blood pressure regulation remain unclear. We systematically evaluated associations between galectin gene expression and systolic blood pressure (SBP) in African Americans. Methods Whole-blood mRNA sequencing data were analyzed from 419 African American participants in the GENE-FORECAST cohort who were free of type 2 diabetes and not receiving antihypertensive medications. LGALS1, LGALS3, LGALS8, and LGALS9 were evaluated using generalized linear models adjusted for age, sex, and body mass index. Associations with cardiac magnetic resonance imaging traits and circulating inflammatory cytokines were also examined. Results LGALS1 showed the strongest association with SBP ({beta}=13.25 mm Hg per standard deviation increase; P=7.57e-15). LGALS9 was positively associated with SBP ({beta}=9.73; P=7.59e-9), whereas LGALS3 showed a weaker positive association ({beta}=4.06; P=0.019). LGALS8 was inversely associated with SBP ({beta}=-6.45; P=1.66e-4), as was the LGALS3/LGALS1 ratio ({beta}=-10.2; P=2.34e-9). Galectin genes also showed distinct associations with cardiac imaging traits. Cytokine associations were modest and inconsistent, although LGALS1 was positively associated with interleukin-1{beta}. Conclusions Whole-blood transcriptomics identified LGALS1 as the strongest galectin correlate of SBP in African Americans. Divergent associations across galectin genes suggest heterogeneous, potentially nonredundant cardiovascular roles. These findings broaden the focus beyond LGALS3 and support further investigation of LGALS1 as a biomarker and possible mediator of hypertension-related vascular stress.

Background: Coronary perivascular fat attenuation index score (FAI-Score) on coronary computed tomography angiography (CCTA) quantifies vascular inflammation and predicts cardiac mortality in symptomatic cohorts. However, its prevalence, anatomical distribution, and clinical correlates in asymptomatic primary prevention populations remain uncharacterized. Methods: In an IRB-approved prospective study across two clinical sites, 84 consecutive asymptomatic adults (mean age 53.7 {+/-} 8.6 years; 63.1% men) with no prior coronary artery disease underwent screening CCTA and comprehensive clinical, metabolic, and biomarker profiling. AI-standardized FAI-Score was quantified across three epicardial vessels (LAD, LCx, RCA). High and very high perivascular inflammation were pre-specified as any vessel [&ge;]75th and [&ge;]90th percentiles, respectively. Luminal stenosis and plaque were graded using CAD-RADS 2.0. Results: Elevated FAI-Score ([&ge;]75th percentile) was present in 42.9% of participants (36/84; 95% CI 32.8% - 53.5%), with 17.9% (15/84; 95% CI 11.1% - 27.4%) exhibiting very high inflammation ([&ge;]90th percentile). Multi-vessel inflammation was identified in 17.9% (15/84), with the RCA most frequently involved ([&ge;]90th percentile in 13.1%). Standard circulating biomarkers, including ApoB, non-HDL-C, HbA1c, and PREVENT-ASCVD 10-year risk showed no association with binary inflammation. Systemic hs-CRP (median 0.8 mg/L) exhibited an inverse correlation with maximum vessel FAI-Score (Spearman {rho}=-0.27, p=0.014). Men demonstrated higher rates of elevated FAI-Score than women (52.8% vs. 25.8%, p=0.016; [&ge;]90th percentile: 26.4% vs. 3.2%, p=0.007). Strikingly, 46.2% (30/65) of participants with normal luminal anatomy (CAD-RADS 0) and 47.2% (25/53) with zero plaque burden harbored elevated FAI-Score; all 15 individuals with very high FAI-Score had CAD-RADS 0 (Fisher's exact p=0.018). Body mass index was the sole secondary correlate surviving false discovery rate correction (AUC = 0.71, p=0.001, all-test FDR q=0.028). Regularized multivariable models showed modest out-of-sample discrimination for FAI-Score elevation (cross-validated AUC = 0.71). Conclusions: Coronary perivascular inflammation is common among asymptomatic adults and frequently uncouples from structural plaque and luminal stenosis. Routine circulating biomarkers and clinical risk calculators fail to identify inflamed vessels, highlighting FAI-Score as an independent dimension of primary cardiovascular risk assessment.

Background: Adults aged [&ge;]75 years represent a rapidly growing population at risk of acute myocardial infarction (AMI), yet they remain markedly underrepresented in statin trials for primary prevention. The limited evidence base, together with multimorbidity, functional heterogeneity, and competing mortality risks, has contributed to uncertainty regarding the potential role of statins in very old adults. This study evaluated the association between baseline statin exposure and incident AMI among community-dwelling adults aged [&ge;]75 years without prior cardiovascular disease. Methods: We conducted a retrospective population-based cohort study using linked primary-care, hospital, laboratory, and pharmacy dispensing data from the Community of Madrid. Statin exposure was ascertained during a 24-month exposure-assessment period from 1 January 2018 to 31 December 2019 and classified at a landmark date of 1 January 2020, when outcome follow-up began. Participants were classified as exposed if they had received at least two statin dispensations during the exposure-assessment period and had no record of prior lipid-lowering therapy before 2018. Individuals with prior cardiovascular disease, type 1 diabetes, cancer, dementia, or advanced chronic kidney disease were excluded. Missing data were addressed using multiple imputation. The association between baseline statin exposure and incident AMI was estimated using multivariable Cox proportional hazards regression. Propensity-score matching and Fine-Gray competing-risk regression, with all-cause mortality as the competing event, were performed as sensitivity analyses. Results: Among 174,014 individuals included in the final cohort, 32,698 (18.8%) met the criteria for baseline statin exposure. The mean age was 82.5 years. During a median follow-up of 5 years, AMI occurred in 533 (1.63%) statin-exposed individuals and 2722 (1.93%) non-exposed individuals (p=0.0003). The observed absolute risk difference was 0.30 percentage points (95% CI, 0.14-0.45), corresponding to an estimated observational number needed to treat of 338 over 5 years (95% CI, 222-708). In the fully adjusted Cox model, baseline statin exposure was associated with a lower risk of incident AMI (HR, 0.805; 95% CI, 0.731-0.887). In the full-cohort Fine-Gray model accounting for competing mortality, baseline statin exposure remained associated with a lower cumulative incidence of AMI (sHR, 0.823; 95% CI, 0.748-0.905). After propensity-score matching, the association remained in the competing-risk analysis (subdistribution HR, 0.852; 95% CI, 0.738-0.983). Conclusions: In this large population-based cohort of adults aged [&ge;]75 years without prior cardiovascular disease, baseline statin exposure was associated with a lower incidence of AMI across several analytical approaches. The observed absolute risk difference was modest, and the findings should be interpreted in light of the observational design, residual confounding, and the potential for selection related to survival to the landmark date. Further randomized evidence is needed to determine whether this association reflects a causal effect of statin therapy in very old adults. Keywords: Statins; primary prevention; acute myocardial infarction; aged [&ge;]75 years; landmark analysis; competing risks; propensity-score matching; real-world data.

Background: Glucagon-like peptide-1 receptor agonists (GLP1-RA) improve cardiovascular outcomes in patients with type 2 diabetes (T2D) and obesity, and more recently they have been shown to be beneficial in patients with obesity and heart failure with preserved ejection fraction. Their role in patients with heart failure and reduced ejection fraction (HFrEF) and T2D remains underexplored. Methods: A retrospective cohort study was conducted using data pooled from the TriNetX platform. Patients with T2D and HFrEF who were initiated on GLP1-RA therapy during the period May-13-2026 to Jun-6-2026 were identified. One:one propensity-score matching with controls was performed. Time-to-event analysis was conducted to compare the one-year incidences of all-cause mortality and a primary composite outcome of acute myocardial infarction, ischemic stroke and acute heart failure, between the two matched-cohorts. Secondary outcomes included individual components of the primary composite outcome and any inhospital encounter. Results: Two well-matched cohorts with 38,879 patients in each were formed. Patients treated with GLP1-RAs had a lower incidence of all-cause mortality (4.2% vs. 12%; absolute risk difference [ARD] -7.8, 95% CI -8.17 to -7.41; HR 0.4, 95% CI 0.34[boxh]0.38) and the primary composite outcome (32.5% vs. 48.3%; ARD -15.8, 95% CI -16.47 to -15.11; HR 0.6, 95% CI 0.57[boxh]0.60) compared to the control group. The GLP1-RA group were also at lower risk of all secondary outcomes compared to the control group. Conclusion: In a real-world study, GLP1-RA therapy was associated with lower risk of all-cause mortality and cardiovascular outcomes in patients with T2D and HFrEF.