European Journal of Preventive Cardiology

BackgroundSex hormone alterations, such as estrogen deficiency or testosterone excess, substantially increase cardiovascular disease (CVD) risk in females. Dietary fibre and its microbial by-products, short-chain fatty acids (SCFAs), have cardioprotective effects, but it remains unclear whether these benefits extend to females with an altered sex hormone profile. In this study, we aim to investigate whether dietary fibre intake, measured via plasma acetate--the most abundant SCFA--is associated with improved cardiovascular outcomes in females with altered sex hormone profiles. MethodsThis cohort study included 116,235 female participants from the UK Biobank and Biobank Japan with up to 10 years of follow-up. We analysed early menopause (as a surrogate for estrogen insufficiency) and plasma free testosterone (in a subset). The primary outcome was major adverse cardiovascular events (MACE). Secondary outcomes were blood pressure. Proteomics analyses explored potential mechanisms. ResultsAcetate levels were associated with lower 10-year MACE incidence (-0.618/1000 woman-year, HR=0.900, p=0.002) and systolic blood pressure (-0.231 mmHg per 1 SD, p<0.001) in the UK Biobank. High acetate levels attenuated the increased MACE risk associated with early menopause (HR=1.158, p=0.057) compared with low acetate (HR=1.425, p<0.001), with similar patterns replicated in Biobank Japan (high: HR=1.322, p=0.090; low: HR=1.385, p=0.042). Proteomics analyses suggested a mechanism involving pro-inflammatory proteins. Moreover, high acetate levels attenuated the increased MACE associated with elevated free testosterone in the UK Biobank (high: HR=1.238, p=0.024; low: HR=1.056, p=0.666). A significant interaction between acetate and free testosterone on systolic blood pressure indicated that the effect of rising testosterone on blunting acetates effect ({beta}=0.167, 95% CI: [5.212x10-2-2.818x10-1], p=0.004) was partially mediated by central obesity (waist-to-hip ratio). ConclusionsHigher plasma acetate levels were associated with lower cardiovascular risk, particularly in females with early menopause or elevated free testosterone, potentially via inflammatory pathways. These findings underscore the importance of hormonal context in shaping cardiometabolic resilience and support personalised CVD prevention strategies for females with altered sex hormone profiles, including increasing dietary fibre intake.

Background The postmenopausal period is associated with a more adverse cardiometabolic risk factor profile as well as unfavourable cardiac remodelling patterns. However, it remains unclear whether and how the associations between risk factors and cardiac remodelling differ before and after menopause and in the corresponding age groups in men. Methods We used cross-sectional data from the baseline examination of the population-based German National Cohort (NAKO, age range 19-74 years). Cardiovascular resonance imaging (CMR) was performed on 3T MRI, and morphofunctional data of both ventricles were derived from standard short-axis cine balanced steady-state free precession. Associations between cardiometabolic risk factors and cardiac parameters were evaluated using adjusted multivariable linear regression, stratified by menopausal status in women and age group (<50 / [&ge;]50 years) in men. Results The final sample comprised 20,152 participants (40% women; mean age 47{+/-}12 years) from the NAKO MRI subsample. Cardiometabolic risk factor profiles differed across the stratified groups, with higher systolic blood pressure and less favourable lipid profiles in older participants. Ventricular volumes declined and concentric remodelling increased with age in both sexes, with a steeper age-related pattern observed in women than in men. Higher BMI in women was associated with higher left ventricular concentricity index (LVCI) in postmenopausal than in premenopausal women (0.097 vs. 0.047; p for difference = 0.016). Associations between triglycerides and ventricular volumes were strongest in premenopausal women and significantly stronger than in men younger than 50 years (e.g., right ventricular end-diastolic volume (RVEDV): -0.173 vs. -0.064, p for difference < 0.001). Sleep problems were more strongly associated with cardiac parameters in men, with significant sex differences in older men compared with postmenopausal women (e.g. left ventricular end-diastolic volume (LVEDV): -0.105 vs. 0.043, p for difference = 0.023). Conclusions Less favourable cardiac remodelling observed in postmenopausal women appeared to be associated with a higher burden of cardiometabolic risk factors rather than stronger associations between these risk factors and cardiac structure. Several associations showed sex- and age-specific patterns, including Body Mass Index (BMI), triglyceride levels, and sleep problems. These findings highlight the importance of controlling cardiometabolic risk factors across adulthood, and raising awareness for sex-specific differences.

BackgroundInflammation plays a key role in atrial fibrillation (AF) pathogenesis. The empirical dietary inflammatory potential (EDIP) score predicts circulating inflammatory biomarkers and adverse cardiac outcomes, but its association with incident AF is unclear. This study aimed to examine the relationship between EDIP score and AF risk. MethodsParticipants from the Atherosclerosis Risk in Communities (ARIC) free of baseline AF who completed a validated food frequency questionnaire were included. Correlation of EDIP with inflammatory biomarkers (factor VIII, fibrinogen, von Willebrand factor, and C-reactive protein) was examined at baseline. Incident AF was ascertained using electrocardiograms, hospital records, and death certificates. Cox proportional hazards models estimated hazard ratios of AF across EDIP quantiles and per SD increase, adjusting for sociodemographic and cardiovascular risk factors. ResultsAmong 8,277 participants (54.1 years old, 51.3% women, 80% white), higher EDIP score correlated with circulating inflammatory biomarkers at baseline. Over a median 24.2 years of follow-up, 1,453 had incident AF (incident rate 8.6 per 1,000 person-years). Compared with the most anti-inflammatory diet (EDIP Q1), the most pro-inflammatory diet (EDIP Q5) was associated with increased AF risk (HR 1.21; 95% CI 1.03-1.43). Sex-stratified analyses showed a stronger association in men (HR 1.43; 95% CI 1.14-1.79), while no significant association was observed in women. ConclusionsPro-inflammatory dietary patterns are independently associated with higher AF risk in a middle-aged cohort. These findings would support incorporating dietary inflammatory load into AF risk stratification. Clinical Perspective What Is New?O_LIHigher Empirical Dietary Inflammatory Potential (EDIP) scores, indicating a more pro inflammatory diet, were associated with an increased long-term risk of atrial fibrillation (AF) in a large, biracial, community-based cohort followed for over two decades. C_LIO_LISex stratified analyses revealed a significant sex difference: higher EDIP scores were consistently associated with increased AF risk in men, whereas no significant association was observed in women, suggesting sex-specific susceptibility to EDIP. C_LIO_LIObesity modified the association between EDIP and AF, with the strongest risk observed among individuals with BMI [&ge;]30, while an inverse or attenuated association was seen among normal weight participants. C_LI What Are the Clinical Implications?O_LIDietary inflammatory load may serve as a meaningful and modifiable upstream AF risk factor, complementing conventional cardiovascular risk assessment, particularly in men and individuals with obesity. C_LIO_LIIncorporating dietary pattern assessment into routine AF risk stratification may help identify individuals who could benefit most from targeted lifestyle interventions. C_LIO_LIPublic health and clinical prevention strategies promoting anti-inflammatory dietary patterns (e.g., increased intake of fruits, vegetables, and whole grains; reduced intake of processed meats and refined carbohydrates) could meaningfully reduce AF incidence. C_LIO_LIRecognition of sex specific differences in AF pathways reinforces the need for personalized preventive strategies, as diet inflammation mechanisms appear to influence AF development more prominently in men. C_LI

Background: Cardiovascular diseases (CVD) are more common in lower occupational classes, but the mediating role of health behaviours remains unclear. This study aimed to quantify the extent to which health behaviours mediate the association between occupational class and CVD, evaluate their relative contributions to CVD risk, and assess occupational class differences in the effects of health behaviours. Methods: Municipal employees from Helsinki, aged 40-60 at baseline, were followed from 2000-2002 (response rate 67%) to 2022. CVD events were identified from national registers, including hospitalizations, long-term sickness absence, disability pensions, and mortality. Counterfactual mediation analysis using additive survival regression was used to assess the contribution of health behaviours - excessive alcohol consumption, smoking, unhealthy diet, and insufficient physical activity - to the association of occupational class and CVD. Occupational class differences in the effects of health behaviours were assessed with Cox regression. Results: During follow-up, 50% of participants in the low occupational class and 46% in the high occupational class had a CVD event. All unhealthy behaviours except heavy alcohol use were more common in the low occupational class. Health behaviours explained approximately 40% of the excess risk of CVD when moving from high occupational class to low occupational class. Insufficient physical activity (HR 1.44, 95% CI 1.35-1.54) was the strongest predictor of CVD. Unhealthy diet was more strongly associated with CVD in the high occupational class. Conclusion: Health behaviours explained a part of occupational class inequalities in CVD, but most of the inequality remained unexplained, highlighting broader social determinants.

Abstract Background: Poor sleep quality is associated with increased cardiovascular risk, although its relationship with left ventricle (LV) structure is poorly understood and ethnic differences in the relationship between sleep and LV structure have not been studied. We investigated the association between poor sleep quality and LV structure in a tri-ethnic cohort. Methods: A total of 1284 participants were analysed from the Southall and Brent Revisited (SABRE) study (age=49.9{+/-} 6.2y; male 75.9%, Europeans (EU)=615, South Asians (SA)=457, African/African-Caribbean (AC)=212). A composite sleep quality score was calculated, and LV structure was measured using echocardiography. Associations between sleep quality and LV mass indexed to height1.7 (LVMi), relative wall thickness (RWT) and LV end-diastolic volume indexed to height1.7 (LVEDVi) were estimated using multivariable linear regression with adjustment for demographic and lifestyle factors across three models. Analyses were performed in the whole cohort and stratified by ethnicity. Results: Compared with those who reported very good sleep quality, participants with poorer sleep quality had higher LVMi (4.8 (95% CI 1.4; 8.2)g/(m1.7*unit sleep score); p=0.006). When stratifying by ethnicity, the association between sleep quality and LVMi was unconvincing in EU (1.9(-3.5, 7.3)g/(m1.7*unit sleep score); p=0.493), whereas poor sleep was associated with higher LVMi in AC and SA participants (9.1(1.3;16.8)g/(m1.7*unit sleep score); p=0.023 and 5.8(0.5;11.0)g/(m1.7*unit sleep score); p=0.031 respectively). Conclusions: Poor sleep quality is associated with higher LVMi in older African/African-Caribbeans and South Asians, but not in Europeans. This may contribute to cardiovascular risk. Keywords: sleep, left ventricle, hypertrophy, remodelling

ObjectiveObesity is a major risk factor for coronary heart disease (CHD). This study aims to develop a metabolite signature of body mass index (BMI-MetSig) then assess its association with incident CHD and responsiveness to metabolic and bariatric surgery (MBS). Research Design and MethodsIn a case-control study of incident CHD nested within the Southern Community Cohort Study (SCCS) including 600 case-control pairs, we used elastic net regression with 10-fold cross-validation to derive the BMI-MetSig. Associations of BMI-MetSig with incident CHD was examined using conditional logistic regression in the nested case-control study. Further, in a cohort of 95 patients who received MBS, we evaluated this BMI-MetSig in association with estimated 30-year cardiovascular disease (CVD) risks, which was estimated by the American Heart Associations PREVENT equations, and examined changes of its constituent metabolites after surgery using linear mixed-effects models. ResultsIn the SCCS, the BMI-MetSig, comprising 94 metabolites, was significantly associated with incident CHD risk among all participants (OR per standard deviation [SD] increase: 1.48; 95% CI, 1.28-1.71) and across subgroups. Among MBS patients, the BMI-MetSig was significantly associated with increased estimated 30-year risks of CHD ({beta} per SD increase: 1.29; p<0.001) and other CVDs. Levels of 17 (20.0%) and 19 (22.4%) metabolites in the BMI-MetSig significantly changed 3- and 12-month post-surgery (FDR<0.10 and log2FC > 0.15), including choline and acetyl-2-aminoadipate. ConclusionsThe BMI-MetSig is associated with higher CHD incidence and estimated 30-year CVD risks and responds to MBS. BMI-MetSig may serve as a blood-based biomarker for cardiometabolic risk stratification and monitoring.

Background and AimSedentary lifestyle and obesity are considered to be significant risk factors that create a pathway for the appearance of the sedentary cardiac phenotype consisting of cardiac atrophy, myocardial stiffening, and altered haemodynamics. Although exercise training has the potential to reverse this detrimental process, the literature data on the magnitude of improvements and the certainty of evidence are inconsistent. This systematic review and meta-analysis aimed to evaluate the effects of exercise interventions on cardiac morphology, systolic/diastolic function, and haemodynamics in sedentary and obesity-prone individuals. MethodIn accordance with the PRISMA guidelines, the study was conducted by searching the PubMed, Web of Science, and Scopus databases from 1990 to 2025 without applying any filters, using Covidence software. As a result of this comprehensive search, 15 randomised controlled trials (RCTs; N=559) comparing exercise training with a control group in sedentary individuals were included in the analysis. Data were pooled using the Standardised Mean Difference (SMD) and a random-effects model. Publication bias and methodological robustness of the results were tested using the Egger regression test, the Trim-and-Fill method, and Leave-One-Out sensitivity analysis. The certainty of the evidence was graded using the GRADE system. ResultsExercise training was associated with a significant reduction in resting HRs and SBPs, which was a strong improvement in the haemodynamic profile. The improvements in SV and LVEF, although on the statistical threshold in the primary analysis, were statistically significant and methodologically stable in the Leave-One-Out sensitivity analysis, which excluded confounding studies. The exercise training was associated with a marked improvement in the E/A ratio and S wave, and the triggering of a physiological athletes heart-like eccentric hypertrophy, defined by improvements in LVMass and LVEDV. The exercise training was associated with diastolic adaptation and mass increase, with HIIT being the most superior method for diastolic adaptation and mass increase, and aerobic exercise being the most effective method for blood pressure reduction. Importantly, the meta-regression analyses revealed two important findings: first, the improvement in blood pressure and diastolic function was independent of weight loss; second, the improvement in structure and function was linearly related to improvements in body composition. ConclusionExercise acts as a cardiac polypill reversing the sedentary phenotype by improving hemodynamics and diastolic function independently of weight loss, while linking structural remodeling to BMI optimization; our data prioritize HIIT for structural/diastolic gains and Aerobic training for blood pressure control.

Background and Aims Despite treatment, patients with established atherosclerotic cardiovascular disease (ASCVD) are at high risk of recurrent events. Existing clinical risk scores for recurrence provide only moderate predictive performance and rely largely on the same conventional risk factors used to predict disease onset. Proteomics is a promising source of new biomarkers but the technologies need focused use cases in order to achieve utility and implementation. We aimed to determine whether plasma proteomics improves prediction of recurrent cardiovascular events beyond established clinical risk models in secondary prevention in a population-scale cohort. Methods Plasma proteomic profiles from ~9,300 participants in the UK Biobank with established ASCVD at baseline were analysed using machine learning methods to derive and evaluate proteomic predictors of recurrent cardiovascular events. The top performing model comprised proteins with non-zero weights (full protein score). Predictive performance of the proteomic predictors, an established clinical risk score (SMART2), and their combination was evaluated across six pre-defined testing datasets representing multiple ethnic and geographic groups. A parsimonious set of proteins with existing clinical-grade enzyme-linked immunosorbent assays (ELISAs) available was then derived. Results The full protein score achieved higher performance for recurrent ASCVD than the SMART2 risk score across all ethnic and geographic subgroups (mean C-index 0.743 vs 0.653). Adding the full protein score to SMART2 improved discrimination, with the largest increase in White Irish participants ({Delta}C-index, 0.140; 95% CI, 0.074-0.205; P<0.001). However, adding SMART2 to the protein score provided minimal additional value. The parsimonious score preserved most of the discrimination of the full protein model with C-indices of the recurrent ASCVD risk model comprising age, sex and the parsimonious protein score being nearly identical to the full protein model in the largest testing set (0.723 vs 0.728 for White British in England and Wales). The parsimonious protein score showed a marked gradient of risk with the top, middle and bottom quintiles showing 10-year recurrent ASCVD rates of ~27.4%, ~9.6% and ~2.4%, respectively. Conclusions In patients with established ASCVD, plasma protein measurements substantially improved prediction of recurrent events beyond conventional clinical risk factors, supporting their potential as a complementary tool to guide secondary prevention of cardiovascular disease.

ObjectiveDiabetes mellitus (DM) approximately doubles the risk of atherosclerotic cardiovascular disease (ASCVD) events, but the molecular basis is poorly understood. We aimed to define arterial differentially expressed genes (DEGs) associated with DM, validate hits as plasma proteins, and ascertain whether these complement ASCVD risk prediction tools. Research design and methodsRNA-sequencing data from the Genotype-Tissue Expression (GTEx) cohort was used to define DEGs associated with DM in two arterial sites in >90 people with DM and >330 controls. UK Biobank (UKB) was used to corroborate that DEGs in their plasma protein form were differentially abundant in people with DM and associated with ASCVD events. Finally, we assessed if including these plasma proteins improved performance of the SCORE2 and SCORE2-Diabetes ASCVD risk models. Results619 and 356 DEGs were associated with DM in the thoracic aorta and tibial artery, respectively. Of these, 22 were common to both arteries, all of which were directionally concordant. Of these, 5 were included in the UKB plasma proteomics dataset and we corroborated 4 (ACP5, LEFTY2, LILRA5 and PSME2) as showing concordant differential abundance in people with DM; all demonstrated associations with a range of incident ASCVD events. Addition of the 4 proteins to SCORE2 and SCORE2-Diabetes (for people without and with DM, respectively) improved the population-level discrimination, classification and calibration of these models. ConclusionsDM is associated with a distinct arterial gene expression profile, hits from which are associated with ASCVD events and add value to risk prediction. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/26345847v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@19e0228org.highwire.dtl.DTLVardef@9fd086org.highwire.dtl.DTLVardef@3315f0org.highwire.dtl.DTLVardef@1e5770f_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundWhile multi-omics approaches, incorporating polygenic risk scores (PRS), metabolomics, and proteomics have shown promise in predicting major adverse cardiovascular events (MACE), their added value beyond cardiovascular disease (CVD) risk factors remains underexplored. We aimed to assess whether integrating multi-omics biomarkers into the SCORE2 model improves the prediction of MACE in apparently healthy individuals. MethodsThis study included 24,042 UK Biobank participants without CVD or diabetes mellitus, aged 40-69 years. Multi-omics biomarkers were fitted in sex-specific models including the variables of SCORE2 and 9 metabolites, 12 proteins, and a PRS for CVD in males, as well as 7 metabolites, 11 proteins, and a PRS for CVD in females. The performance of the SCORE2 model and its multi-omics extensions was compared using Harrells C-index and the net reclassification index (NRI) in a training and test set (70% and 30% of study population). ResultsIn 10-year follow-up, 1,204 MACE events occurred. Integrating multi-omics biomarkers into SCORE2 significantly improved the predictive performance (C-index: 0.708 to 0.769, P<0.001; NRI=26.2%). In males, the C-index improved from 0.682 to 0.752 ({Delta}C-index=+0.070, P<0.001; NRI=12.4%), while in females, it increased from 0.724 to 0.782 ({Delta}C-index=+0.058, P<0.001; NRI=30.4%). However, full multi-omics measurements may not be needed because the combination of proteomics and PRS yielded comparable performance in males (C-index=0.749) and females (C-index=0.782). ConclusionsIntegrating a protein panel and a PRS significantly improves MACE risk prediction by the SCORE2 model, which includes HDL and total cholesterol. Adding further metabolites has limited additional predictive value.

Abstract Aims: While traditional anthropometric indices are established cardiovascular predictors, their prognostic value for incident infective endocarditis (IE) remains undefined. Methods: We included 386,859 participants (mean age 57.0 years; 52.9% female) from the UK Biobank between 2006 and 2010 with standardized baseline data on BMI, waist circumference (WC), waist-to-height ratio (WhtR), and the triglyceride-glucose (TyG) index.Multivariable Cox proportional hazard models with restricted cubic splines were used to estimate the hazard ratio (HR) of these indices, adjusting for demographic and clinical risk factors. Results: Over 16.87 median years (25th, 16.02; 75th, 17.60 percentile) of follow-up, there were a total of 1,124 incident IE events. During the follow-up period, 38,342 total deaths were recorded, of which 8,524 were cardiovascular disease (CVD)-related.Overall, compared to individuals with normal weight and baseline metabolic indices, those in the fourth quartile of WC, WHtR, and TyG index exhibited the highest risk of incident IE. Compared to other metabolic indices, WC (HR = 1.53, 95% CI 1.23?1.90,P < 0.001) and WHtR (HR = 1.46, 95% CI 1.20?1.78,P < 0.001) demonstrated higher relative increases in risk associated with IE. Furthermore, the risk of IE was significantly elevated among the younger population with abdominal obesity and concomitant diabetes. However, no significant increase in IE risk was observed among participants with pre-existing valvular heart disease (P = 0.796). Conclusion: Compared with BMI, higher WC and WHtR were robustly associated with increased risk of IE, even after adjusting for traditional risk factors. Furthermore, the risk of IE was markedly elevated among younger individuals with abdominal obesity and diabetes.

Objective: To investigate the association of the modified cardiometabolic index (MCMI) with cardiovascular-kidney-metabolic (CKM) syndrome staging, all-cause and cardiovascular mortality, and compare its predictive performance with traditional indices. Methods: This prospective cohort study included 5,189 adults with CKM syndrome (stages 0-4) from NHANES 1999-2018 (median follow-up 10.4 years). Associations were assessed using polynomial/ordinal logistic regression, Cox models, and restricted cubic splines. Mediation analysis explored diabetes' role. Competing risks (Fine-Gray), E-values, and sensitivity analyses ensured robustness. Predictive performance was compared using C-index and AUC. Results: MCMI showed a "decelerating increase" nonlinear association with CKM staging (adjusted OR=3.90, 95%CI: 3.38-4.50). For all-cause mortality, MCMI>3.5 exhibited a threshold effect (Q4 vs Q1: HR=1.412, 1.046-1.907); RCS curves identified MCMI<3.5 as a safety interval. For cardiovascular mortality, MCMI showed a fluctuating nonlinear pattern with low-risk (3.0-3.5) and high-risk (<2.5 or >4.0) intervals. Diabetes mediated 45.5% of MCMI-cardiovascular mortality risk (total HR=1.374, indirect HR=1.141). Competing risks revealed substantial underestimation of true effects (Q4 vs Q1 sHR=3.25, trend P<0.001). MCMI remained independently associated with all-cause mortality after extensive adjustments (HR=1.22, 1.05-1.40); E-values (1.73/1.29) indicated robustness. MCMI demonstrated superior predictive performance over CMI and TyG (mean AUC difference 0.0243). Conclusions: MCMI is an independent predictor of CKM progression and mortality. Its cardiovascular mortality risk is predominantly mediated by diabetes. MCMI>3.5 may serve as a clinical cut-off, outperforming traditional metabolic indices for CKM risk stratification. Keywords: modified cardiometabolic index, cardiovascular-kidney-metabolic syndrome, all-cause mortality, cardiovascular mortality, diabetes mellitus, competing risks model, cohort study, risk prediction

Introduction: Menopause may coincide with rising Lp(a) levels, a causal risk factor for atherosclerotic cardiovascular disease (ASCVD). Characterizing changes in Lp(a) across menopause may inform risk stratification and testing recommendations. Methods: We examined changes in serum Lp(a) levels by menopausal status among women with Lp(a) measured at visits 1 and 2 in the UK Biobank. Lp(a) analyses were examined by menopausal status: those who underwent menopause (N=415), those who remained premenopausal (N=532), and those who remained postmenopausal (N=3,615) between visits. We examined the change in Lp(a) between visits stratified by visit 1 Lp(a) levels. The primary outcome was incident Lp(a) 125 nmol/L at visit 2, estimated using Poisson regression with adjustment for baseline age. Results: Data were available for 4,562 women (mean age at visit 1 = 57{+/-}7 years; median Lp(a) at visit 1 = 22 (IQR: 47) nmol/L; median time between visits = 4 (IQR: 1) years). At visit 1, median Lp(a) was slightly higher in postmenopausal women (23 nmol/L) than premenopausal women (19 nmol/L). Overall, median changes in Lp(a) between visits 1 and 2 were modest. Among women with intermediate visit 1 Lp(a) levels (75-125 nmol/L), those who transitioned through menopause experienced a median increase of 34.9 (-6.7, 53.0) nmol/L between visits, an approximately fourfold greater increase than for women who remained pre- (7.9 nmol/L) or postmenopausal (8.0 nmol/L). Further, 56% of women with intermediate visit 1 Lp(a) levels who transitioned through menopause between visits had incident Lp(a) 125 nmol/L at visit 2, compared with 29% and 28% of women who remained pre- or postmenopausal, representing an age-adjusted risk ratio of 2.26 (95% CI: 1.31, 3.90). Conclusion: Relying on a single lifetime Lp(a) measurement may miss clinically relevant increases during menopause. Repeat testing in women as they age may improve identification of those at high risk for ASCVD.

BACKGROUND: Observational studies have suggested an association between obstructive sleep apnea (OSA) and myocardial infarction (MI), but whether this relationship is causal or largely reflects shared risk factors remains unclear. METHODS AND RESULTS: We performed a 2-sample Mendelian randomization (MR) analysis to evaluate the causal effect of OSA on MI. Summary statistics for OSA were obtained from FinnGen, and MI data were obtained from the UK Biobank, with external validation using CARDIoGRAMplusC4D. Mediation MR was used to assess 13 potential mediators, and a 6-step multivariable MR framework was applied to estimate the direct effect of OSA after sequential adjustment for potential confounders. Reverse MR was conducted to test possible reverse causality. Genetically predicted OSA liability was associated with increased MI risk (odds ratio [OR] per log-OR increase, 1.0024 [95% CI, 1.0010-1.0039]; P=0.001). Body mass index (BMI) was the strongest mediator, explaining 35.94% of the association (P=0.030), whereas systolic blood pressure (SBP) showed minimal mediation (0.28%; P=0.678). In stepwise multivariable MR, the OSA-MI association was attenuated after adjustment for BMI and SBP (P=0.156), suggesting partial confounding by shared cardiometabolic risk. In a model including SBP and atrial fibrillation (AF), AF remained independently associated with MI (P=0.004), whereas OSA showed only a marginal direct effect (P=0.050). Reverse MR found no evidence that MI influenced OSA risk. CONCLUSIONS: These findings support a causal association between OSA and MI and suggest that this relationship may be mediated in part through obesity-related and arrhythmia-related pathways. AF may represent an important intermediate component of OSA-related cardiovascular risk beyond traditional hemodynamic factors. Keywords: obstructive sleep apnea; myocardial infarction; Mendelian randomization; mediation analysis; obesity.

Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. Liver function biomarkers (LFBs), particularly gamma - glutamyl transferase (GGT), have been linked to cardiovascular outcomes, yet their contribution to hard ASCVD risk prediction is not well defined. Methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES, 2005 - 2018) to assess cross - sectional associations between LFBs and 10 - year hard ASCVD risk estimated by the ACC/AHA Pooled Cohort Equations. Multivariable regression, restricted cubic splines, and mediation analyses were applied to examine independent and dose - response relationships. External validation was performed in the China Health and Retirement Longitudinal Study (CHARLS) and NHANES using machine learning models (CoxBoost, Naive Bayes and Random Forest). Results: Among 5,731 NHANES participants, GGT showed an independent linear association with hard ASCVD risk (P - trend = 0.003), partly mediated by systolic blood pressure (44.8%), HbA1c (19.0%), and high density lipoprotein cholesterol (13.4%). Machine learning (ML) models incorporating GGT, alkaline phosphatase (ALP), and globulin alongside traditional risk factors improved predictive accuracy, with Naive Bayes achieving an AUC of 0.751 in NHANES validation. Conclusions: GGT is an independent and biologically plausible biomarker of hard ASCVD risk, acting through cardiometabolic pathways. Incorporating LFBs into risk prediction models, particularly with machine learning, enhances risk stratification and may facilitate early identification of high - risk individuals.

BackgroundVitamin D supplementation has been investigated for potential associations with cardiometabolic risk factors related to cardiovascular disease (CVD); however, findings from randomized controlled trials (RCTs) remain inconsistent. This meta-analysis aimed to assess the effects of vitamin D supplementation on cardiometabolic risk factors--including lipid profile, blood pressure, and glycaemic parameters--and to explore whether age and baseline serum vitamin D concentrations modify these associations. Research Design and MethodsWe conducted a systematic review and meta-analysis of RCTs comparing oral vitamin D supplementation with placebo in adults. PubMed, the Cochrane Library, and ClinicalTrials.gov. Risk of bias was evaluated using the Cochrane tool, and pooled effect sizes with 95% confidence intervals (CIs) were calculated using random-effects models. Results14,051 abstracts were retrieved, of which 45 were used for data analysis. Vitamin D supplementation reduced low-density lipoprotein cholesterol (LDL-C) by 0.136 mmol/L (95%CI: -0.215, -0.56), systolic blood pressure by 2.79 mm Hg (95% CI: -4.648, -0.938), fasting blood glucose by -0.11 (95%CI:-0.185, -0.036), and hemoglobin A1c by 0.164% (95%CI: -0.322, -0.006) compared with placebo. Subgroup analyses revealed reductions in SBP and LDL cholesterol among participants aged [&ge;]55 years and reductions in fasting blood glucose in participants with age < 55 years. While favourable effects on fasting blood glucose and hemoglobin A1c were observed with a baseline blood level of vitamin D of concentrations (<50 nmol/L). ConclusionsVitamin D supplementation may be associated with modest modifications in selected cardiometabolic risk factors; including systolic blood pressure, LDL-cholesterol, fasting blood glucose, and hemoglobin A1c. Age and baseline vitamin D status appear to modulate these effects. The clinical relevance of these modest effects remains uncertain. Well-designed RCTs with standardized protocols are required to clarify potential effect modification by age and baseline vitamin D status. Trial RegistrationPROSPERO (CRD42020165293) FundingThis research received funding from the Hashemite University, P.O. Box 330127, Zarqa 13133, Jordan

ObjectiveThe objective of this study was to explore the predictors of statin intolerance in the primary and secondary prevention of CVD among patients in the first two years after the date of first prescription using real-world data. MethodsThis study used the Electronic Practice Based Research Network Linked Dataset. An algorithm, which considered the muscle symptoms and creatinine kinase of patients, was used to identify statin intolerant patients. The R software was used for all analyses. Descriptive and multivariate logistic regression analyses were performed along with sensitivity analysis which was done using the Akaike Information Criterion model selection method. ResultsOverall, 4,016 patients accounting for 60,873 visits met the selection criteria. About 3.5% of the patients were statin intolerant. After adjusting for all other variables, statin intolerance was positively associated with gender (AOR 1.5, 95% CI 1.0 - 2.2), SEIFA index (AOR 3.8, 95% CI 2.3 - 6.7), employment status (AOR 2.4, 95% CI 1.1 - 5.7), and comorbidities (AOR 7.0, 95% CI 2.2 - 19.0). A similar direction of associations was seen for the exposures of the model from the sensitivity analysis and the regression model. However, since the unrecorded employment status showed a positive association, the sensitivity analysis suggests that the relationship may be influenced by residual confounding or information bias, indicating that this finding should be interpreted with caution. ConclusionStatin intolerance within the diverse community represented in the dataset is driven by gender, employment status, area-based social advantage and disadvantage index, and comorbidities.

BackgroundMetabolic vulnerability index (MVX), a novel biomarker of systemic inflammation and metabolic malnutrition, is associated with mortality in patients with cardiovascular diseases. Nevertheless, little is known about its association with cardiometabolic diseases (CMDs) and multimorbidity (CMM). We aimed to examine the associations of MVX with the risk of individual CMDs, their progression to CMM, and all-cause mortality in the general population. MethodsIn a prospective cohort of 218,635 UK Biobank participants free of CMDs, MVX was calculated based on plasma metabolomics data. CMM was defined as coexistence of two or more CMDs, including coronary heart disease (CHD), stroke, and type 2 diabetes mellitus (T2DM). Cox proportional hazard and multi-state models were employed to evaluate the associations of MVX with the risks of individual CMDs, CMM, and all-cause mortality. ResultsDuring a median follow-up of 14.4 years, 27,805 (12.7%) participants developed at least one CMD, 3,006 (1.4%) progressed to CMM, and 14,211 (6.5%) died. Each standard deviation increase of MVX score was associated with 9% (95% confidence interval: 8%-10%), 11% (7%-15%), and 12% (10%-14%) higher risks of developing CMDs, CMM, and mortality, respectively. The MVX-CMM associations were more prominent in females and in the sequential onset pattern of T2DM followed by CHD or stroke. Multi-state model analysis further uncovered consistent associations between higher scores of MVX and higher risks of transitions from CMDs free to CMD, subsequently to CMM, and to death. ConclusionsHigher MVX scores were significantly associated with higher risks of incident CMDs, their progressions to CMM, and all-cause mortality. These results underscored the potential of MVX in the primary prevention and management of CMDs and CMM.

BackgroundHDL particles can carry microRNAs (miRNAs), capable of regulating gene expression connected to HDL functions. Despite links to some cardiovascular risk factors, miRNA association with incident acute myocardial infarction (AMI) remains unclear. ObjectivesOur aim was to elucidate the association between HDL-bound miRNAs (HDL-miRNAs) and incident AMI using a non-targeted approach in a population-based study. MethodsWe conducted a case-cohort study including 247 participants from the REGICOR cohort in northeastern Spain (51 AMI cases and a random sample of 196 participants, including seven overlapping AMI cases). HDL-miRNAs were isolated from apolipoprotein B-depleted serum and quantified by whole-genome miRNA sequencing. Associations between HDL-miRNAs and incident AMI were assessed using multivariable Cox proportional hazards model. For AMI-associated HDL-miRNAs (p-value <0.10), we retrieved their experimentally validated targets and assessed pathway enrichment of these targets via over-representation analysis. ResultsTwo HDL-miRNAs were associated with incident AMI after FDR correction: miR-628-3p (HR 1.69, 95% CI 1.30 to 2.19) and miR-28-3p (HR 1.58, 95% CI 1.21 to 2.06). Nine additional HDL-miRNAs were nominally associated with AMI incidence (p-value <0.05), eight with a direct association (miR-93-5p, miR-26b-5p, miR-106a-5p, miR-126-3p, miR-15b-5p, let-7a-5p, let-7e-5p, and let-7f-5p) and one with an inverse association (miR-361-5p). These miRNAs regulate the expression of genes in pathways involved in cholesterol regulation, particularly cholesterol efflux and homeostasis. The AMI group exhibited higher variance and a greater number of significant and strong correlations. ConclusionsTwo HDL-miRNAs (miR-628-3p and miR-28-3p) were significantly associated with AMI incidence. A tighter coregulatory network in cases was observed, underscoring their potential clinical utility in risk prediction and cardiovascular prevention. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIIn a population-based case-cohort study we profiled the HDL-bound miRNome and found two miRNAs (miR-628-3p and miR-28-3p) associated with incident AMI. C_LIO_LIThe use of HDL-enriched serum fractions provided a focused analysis on HDL functionality. These miRNAs regulate the expression of genes in pathways involved in cholesterol efflux and homeostasis (ABCA1, ARL4C, SIRT1, NFKBIA, ANXA2, LRP6) and show a tighter coregulatory network among significant miRNAs among cases, supporting biological coherence. C_LI What Are the Clinical Implications?O_LIHDL-miRNA signatures may complement traditional risk factors to refine AMI risk stratification and provide a rationale for HDL-guided, miRNA-targeted preventive interventions using HDL-like delivery platforms. C_LI

BackgroundPrevious studies established handgrip strength (HGS) as a potential risk factor for cardiovascular diseases (CVD). However, existing studies focused exclusively on baseline HGS and neglected longitudinal changes in HGS during follow-up. Thus, our aim was to investigate the associations of transitions and dynamic burdens of HGS with incident CVD risk. MethodsWe analyzed data from the UK Biobank (UKB), the China Health and Retirement Longitudinal Study (CHARLS), the Survey of Health, Ageing and Retirement in Europe (SHARE), and the Korean Longitudinal Study of Ageing (KLOSA). We defined HGS transitions based on HGS at baseline and the first follow-up, and created three indicators to reflect HGS burdens. Cox models were applied to examine the association of HGS transitions and burdens with incident CVD risk. The predictive value of HGS indices was also evaluated. ResultsA total of 73,555 participants were retained, and 4,722 (6.4%) incident CVD cases were identified during follow-up. Transition analyses revealed that increased HGS during follow-up was associated with reduced CVD risk, whereas decreased HGS was associated with an elevated risk. Per standard deviation decrement in HGS slope, cumulative HGS and relative cumulative HGS led to a 19.8% (95%CI 1.5~41.5%), 44.0% (95%CI 10.8~87.2%) or 26.7% (95%CI 9.4~46.8%) elevated risk of CVD, respectively. These associations were independent of and more pronounced than HGS, with stronger effects observed in East Asian cohorts (CHARLS and KLOSA) compared to European cohorts (UKB and SHARE). Incorporating dynamic HGS metrics enhanced the predictive accuracy, with HGS burdens providing greater gains than HGS. For the optimal models, all HGS indices resulted in an increase of AUC up to 7.6% in Europeans and 5.9% in East Asians. ConclusionsHGS burdens outperformed in predicting cardiovascular health compared to single cross-sectional HGS itself, suggesting the clinical utility of longitudinal HGS monitoring in clinical and public health strategies for CVD prevention.