European Journal of Preventive Cardiology

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.

Background and AimsDespite 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. MethodsPlasma 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. ResultsThe 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. ConclusionsIn 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.

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.

INTRODUCTIONMost randomized controlled trials (RCTs) found that omega-3 fatty acids have little to no effect on cardiovascular disease risk. However, a few suggested that a specific omega-3 fatty acid, eicosapentaenoic acid (EPA), reduces cardiovascular disease risk in patients with high triglycerides (TG). It is unclear whether EPA is beneficial in the general population or how it affects triglyceride-rich lipoproteins (TRL) and related traits. Using two-sample Mendelian randomization (MR), this study aimed to evaluate whether EPA has a protective effect on ischemic heart disease (IHD), TRL, and related traits in a general population. METHODSAssociations of genetic variants with plasma EPA (EPIC-Norfolk, INTERVAL; n=14,267), and the outcomes IHD (Aragam et al., cases/n=181,522/1,165,690; FinnGen, N cases/n=31,640/218792), TRL, and related traits (Karjalainen et al.; n=68,559) were based on summaries from previous genome wide association studies (GWAS) of participants of European descent. Using eight proposed instruments associated with plasma EPA (P<5*10-5), inverse-variance weighted (IVW), MR-Egger, and weighted median (WM) estimators were used to determine the effect of a period shift in the natural log of plasma EPA one standard deviation, or EPA, on these outcomes. RESULTSUsing IVW, EPA was associated with higher odds of IHD (OR=1.05; 95% CI=1.00, 1.10), but the CI included the null value. The WM estimate was similar, and the MR-Egger estimate was closer to the null (OR=1.01; 95% CI: 0.90, 1.11). EPA was associated with lower serum TG and lower large to small very low-density lipoprotein (VLDL) particle concentrations, but with increases in very small VLDL, intermediate density lipoproteins, and low-density lipoproteins. Although the distribution changed from larger to smaller TRL, there was no change in apolipoprotein B. EPA was also associated with increases in very large to medium high-density lipoprotein (HDL) particles and no change in small HDL, consistent with an increase in apolipoprotein A-I. EPA was also associated with increases in both remnant cholesterol and total serum cholesterol. DISCUSSIONThis study suggests that EPA may not have a beneficial effect on IHD in the general population of European ancestry. Rather, EPA appears to remodel TRL, possibly through lipolysis of large particles without full clearance of the resulting smaller particles, and this may have mixed implications for cardiovascular disease risk. A cardiovascular outcome trial of EPA monotherapy in a general population that collects lipid/lipoprotein subfractions would be needed to confirm these findings.

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

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

AimsWhile traditional anthropometric indices are established cardiovascular predictors, their prognostic value for incident infective endocarditis (IE) remains undefined. MethodsWe 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. ResultsOver 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). ConclusionCompared 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. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/26351534v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@a281e7org.highwire.dtl.DTLVardef@fe7fb0org.highwire.dtl.DTLVardef@7108a1org.highwire.dtl.DTLVardef@edb9a5_HPS_FORMAT_FIGEXP M_FIG C_FIG

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 Elevated resting heart rate (RHR) predicts mortality in older adults, primarily through cardiovascular disease (CVD). Prior cohort evidence suggests that RHR also predicts mortality in younger adults, but whether this association operates through cardiovascular or non-cardiovascular pathways has not been directly tested. Methods and Results We analyzed 3291 adults aged 20 to 49 years from NHANES 1999-2004 linked to mortality data through 2019 (median follow-up, 17.8 years; 120 deaths). RHR and heart rate reserve (HRR) were modeled per 10-bpm increment using Cox regression adjusted for demographic, lifestyle, and comorbidity covariates. Each 10-bpm RHR increase was associated with higher all-cause mortality (hazard ratio [HR], 1.26; 95% CI, 1.07-1.50; P=.007), driven by non-CVD mortality (HR, 1.28; 95% CI, 1.07-1.55; P=.009) rather than CVD mortality (HR, 1.15; 95% CI, 0.77-1.71; P=.51). A behavioral/external composite (accidents and NCHS residual causes, including suicide and liver disease) reached significance (HR, 1.35; P=.02), whereas a disease-oriented composite did not (P=.20). The association was absent before age 35 (HR, 0.98; P=.88) but pronounced at ages 35-39 (HR, 2.60; P=.001). HRR was not associated with any outcome. Conclusions In young US adults, elevated RHR predicted mortality through non-cardiovascular rather than cardiovascular pathways, concentrated among behavioral and external causes. The association emerged at age 35, below current screening thresholds. HRR under submaximal conditions carried no prognostic value. RHR in young adults may reflect global health vulnerability rather than cardiovascular risk alone.

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.

IntroductionAccurate 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. MethodsThis 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). ResultsAmong 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. ConclusionsGGT 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.

BackgroundThe Lifes Essential 8 (LE8) metric is a well-validated tool to assess cardiovascular health. The tool relies on self-reported physical activity (PA) and sleep data which may be subject to recall bias when compared with objective device-derived data. We used objectively captured device data from Fitbit devices linked to the electronic health record (EHR) from the All of Us Research Program (AoURP) to examine the association between LE8 and incident cardiovascular disease (CVD). MethodsWe analyzed AoURP participants with [&ge;]6 months of Fitbit-derived PA and sleep data from 2009 to 2023. Remaining LE8 components were obtained via EHR and combined with Fitbit components to calculate LE8 scores. Cox proportional hazards models analyzed the association between LE8 scores and a composite CVD outcome (myocardial infarction, coronary artery disease, heart failure, stroke, and peripheral artery disease). Relative explained variation (REV) assessed the contribution of each LE8 component to model performance. We modeled the impact of plausible changes in weekly activity and sleep on the composite CVD outcome. Results11,542 participants were included (50.1 years [IQR: 35.9, 61.7], 74% female, 81% white) with a median monitoring duration of 4.48 years [2.00, 6.87]. The median LE8 score was 68.1 [60.6, 74.4]. Higher LE8 score was linearly associated with lower CVD risk (HR = 0.74; CI, 0.69-0.80) per 10-point increase. Risk of MI, CAD, HF, PAD, and stroke showed similar independent associations with LE8 scores. Among LE8 components, physical activity had the highest median REV 0.35 [0.21, 0.47], followed by blood pressure (0.23, CI = 0.11-0.36) and blood glucose (0.14, CI = 0.05-0.24). Increasing weekly moderate to vigorous physical activity by 30 minutes (120min to 150min) decreased the risk of incident CVD by 23% (HR=0.77; CI, 0.721-0.81), and increasing sleep duration from 4-5 hours to 7-9 hours decreased the risk of incident CVD by 35% (HR=0.65; CI, 0.50-0.84). ConclusionThese results underscore the potential of calculating the LE8 score using objective PA and sleep data from consumer devices and highlight the disproportionate impact of lifestyle behaviors on CVD risk among patients seeking care. Consumer wearable devices offer valuable information when included in cardiovascular risk assessment.

Background: Regular exercise is a highly effective yet underutilized strategy to reduce cardiometabolic disease burden. Whether brief structured exercise programs confer lasting cardiometabolic benefits remains unclear. The STRRIDE-Prediabetes Reunion study examined legacy effects of exercise training on cardiorespiratory fitness, body composition, and cardiometabolic health. Methods: Seventy-three participants (71.3 {+/-} 7.2 years; 64% women; 77% White) completed Reunion assessments ~11 years after completing one of four 6-month interventions differing in exercise amount, intensity, and inclusion of diet-induced weight loss. Linear mixed effects models evaluated longitudinal trajectories; secondary analyses examined baseline-adjusted associations among short-term intervention response and Reunion outcomes. Results: Abdominal adiposity improved across all groups from baseline to Reunion, with waist circumference decreasing ~3 cm over the follow-up period. In contrast, cardiorespiratory fitness and fat-free mass declined significantly. A significant group by time interaction was observed for total fat mass (p=0.01), with continued fat mass reductions observed in women randomized to high amount exercise. After baseline adjustment, greater short-term intervention response was associated with more favorable Reunion outcomes across fitness, body composition, and cardiometabolic domains; fat-free mass showed the strongest association ({beta}=0.84, p<0.0001). Conclusions: In older adults with prediabetes, the STRRIDE-Prediabetes interventions produced several legacy health effects persisting more than a decade later. Legacy effects differed by sex and exercise dose, and short-term intervention response relative to baseline was associated with long-term outcomes, supporting targeted exercise strategies to preserve cardiometabolic health and functional independence with aging.

Background: Coronary artery calcium (CAC) scores inform subclinical atherosclerotic cardiovascular disease (ASCVD) burden, helping guide preventative treatments. However, prediction of cardiovascular (CV) events by CAC is largely limited to ASCVD outcomes. This study investigated whether a previously validated proteomic test for predicting a broad composite of four-year CV events could enhance the prognostic utility of CAC. Methods: We used a 27-protein CV risk score (Prot-CVR), derived from ~5,000 SomaScan? Assay plasma protein measurements, to predict four-year risk of a composite CV and mortality outcome (myocardial infarction, stroke/TIA, heart failure hospitalization, death) in 2,122 participants with ?1 CV risk factors from the Multi-Ethnic Study of Atherosclerosis (MESA) observational cohort at exam 5 and compared predictions to CAC Agatston scores. Discriminatory performance was assessed using C-Index and 4-year area under the curve (AUC). Cox Proportional Hazard (CoxPH) ratios were calculated for the composite outcome, ASCVD outcome (myocardial infarction, resuscitated cardiac arrest, stroke, coronary heart disease death), and individual events. Changes in Prot-CVR and CAC scores from baseline to MESA exam 5 (+10-years) in CV event versus event-free participants were assessed using 2-tailed paired t-tests. CoxPH regression models of CV event status distributed by Prot-CVR, CAC, and relevant co-variates were evaluated for performance relative to individual models. Results: Individual Prot-CVR and CAC models predicting the composite outcome had comparable 4-year AUCs, but Prot-CVR had a higher C-index (0.68 (0.65-0.70) versus 0.63 (0.60-0.65), p=0.001) and greater hazard ratios for the composite outcome (p<0.001), death (p<0.001), and heart failure (p=0.015). A combined CoxPH model of Prot-CVR + CAC + Age had a higher 4-year AUC (0.72, p<0.05) and C-Index (0.71, p<0.05) than Prot-CVR or CAC alone. Both Prot-CVR and CAC scores detected an increase in risk prior to an approaching CV event in ~10-year sensitivity-to-change analysis. For 49.6% of MESA population with CAC=0 at baseline, Prot-CVR was greater in composite event versus event free participants at 4 years (0.23 versus 0.15, p=0.006) and full follow-up (0.18 versus 0.13, p<0.001). Conclusion: Protein testing complements CAC for CV risk assessment although the improvement is modest. Prot-CVR may resolve which patients with CAC=0 are at heightened CV risk.

BACKGROUND: Coronary artery disease (CAD) and Impaired Cognitive (IC) disease share sociodemographic, genetic, and clinical factors, but the association of IC with statin use in CAD remains unclear. OBJECTIVES: To determine the association between IC and statin use in CAD based on APO (e) genotype, sex, and lipid levels. DESIGN, SETTING, AND PARTICIPANTS: We performed a retrospective study of AllofUS (AoU) participants with CAD (Age [&ge;]60 yrs) enrolled from 2017 to 2023. We defined CAD as having a history of angina/myocardial infarction/chronic ischemic heart disease or having percutaneous coronary intervention/CABG, and IC defined as mild cognitive impairment or all cause dementia, using ICD/SNOMED codes. MEASURES: We assessed the association between IC and statin use using logistic regression analysis, while adjusting for clinical factors, sociodemographics, and APO (e) genotypes before and after propensity score matching. We further performed stratified analysis by sex, and APO (e) genotypes. We finally assessed the association between IC and statin users, based magnitude on the change in lipid levels before CAD and after IC (TC: Total cholesterol, LDL: low density lipoprotein, HDL: High Density Lipoprotein). Significance was defined at p < 0.05. RESULTS: The cohort included 22,089 participants with CAD and 1343 with IC. Thirty-nine percent of participants were females, 77% were European, 13% were African American, and 9% were of Admixed American ancestry. The proportion of IC was higher (6.8% vs 3.5%, p<0.001) in statin users (n=17,191) vs non-statin users (n=4,898). IC was significantly associated with statin use (OR:1.70;1.40-2.10, p = 4.9e-7) after adjustment for clinical factors, sociodemographics, and APO (e) genotypes. After propensity-score matching between IC and CAD, we observed an association between IC and statin use (OR:1.55;1.24-1.94, p =1e-4). In stratified analysis, the association between IC and statin use was strongest in the APO e3/e3 group (OR:2.04;1.53-2.75, p = 1e-6), and in females (OR:2.20;1.60-3.06, p = 2.e-6) compared to males (OR:1.43;1.10-1.90, p = 0.01). We finally observed an increased magnitude of association between IC and statin users having higher HDL increase (> 10 mg/dl: OR:1.95;1.44-2.66, p=1e-5) as compared to statin users with lesser HDL increase (<=; 10mg/dl: OR:1.61;1.22-2.15, p=8e-4). CONCLUSION: In the AllofUS cohort, IC was significantly associated with statin use in CAD participants. We observed the strongest association in the APO e3/e3 group, among females, and with a greater increase in HDL levels in statin users.

Background: Resting electrocardiogram (ECG) is not currently recommended as part of cardiovascular disease (CVD) risk assessment, although accumulating evidence suggests a potential role. Objective: To examine the association between ECG abnormalities and incident CVD events as assessed by the 2023 Predicting Risk of Cardiovascular Disease Events (PREVENT) equations. Design: Secondary data analysis from the REasons for Geographic And Racial Differences in Stroke (REGARDS) prospective cohort, including study participants without a baseline CVD. Exposure: ECG abnormalities were classified by Minnesota Code (MC) as normal, any minor, or major abnormality at baseline (2003-2007). Outcome: Participants were followed for expert adjudicated incident CVD events through December 31, 2021. Results: Among 19,173 participants (mean age at baseline of 63.7 years; 57.8% were female). According to the PREVENT risk equations, 39.4% were classified as <7.5% 10-year risk CVD risk, 44.6% as 7.5-20% risk, and 16.0% as >20% risk. Overall, 47.0% had normal ECG, 44.0% had any minor abnormality, and 9.0% had any major abnormality. During follow-up, CVD events occurred in 12.4% of participants with normal ECG, 17.0% of those with any minor abnormality, and 25.4% of those with any major abnormality. Compared to those without ECG abnormality, the adjusted HR for incident CVD were 1.19 (95% CI 1.10-1.29) for any minor abnormality, and 1.53 (1.36-1.72) for any major ECG abnormality. In the <7.5% risk group, 43.6% had at least one ECG abnormality; in this risk group compared to those without ECG abnormality, the HR for incident CVD associated with any major ECG abnormality, present in 5.0% of the <7.5% risk group, was 1.87 (95% CI 1.34-2.62), The HR for any minor ECG abnormalities, present in 38.6% was 1.13 ( 95% CI 0.93 - 1.37). Conclusion: ECG abnormalities were associated with risk of CVD events across PREVENT risk groups. A substantial proportion of low-risk participants (according to the PREVENT equation) had ECG abnormalities and associated elevated risk. This supports the potential for using ECG to identify a subgroup of low-risk patients who may benefit from more aggressive primary prevention especially with major ECG abnormalities. Addition of electrocardiographic evaluation to the PREVENT risk equations may improves cardiovascular risk discrimination.

BackgroundLipoprotein(a) [Lp(a)] can be reported as mass concentration (mg/dL) or particle concentration (nmol/L). Because Lp(a) biology is likely mediated at the particle level, molar concentration may better reflect biologically relevant exposure. We compared molar- and mass-based Lp(a) measurements in relation to cardiovascular outcomes, LPA genetic variation, and apo(a) isoform phenotype in a population-based cohort. MethodsLp(a) was measured in 6,182 participants in the Young Finns Study. Among participants aged [&ge;]40 years, associations with prevalent coronary artery disease (CAD) and composite cardiovascular disease (CVD) were assessed using logistic regression models. Lp(a) was modeled as quintiles, inverse-normal transformed continuous variables, and clinically relevant cut-points. Discrimination and model fit were evaluated using c-statistics and Akaikes Information Criterion. Associations with an LPA genetic risk score (GRS) and apo(a) isoform phenotype were examined using Spearmans correlation analyses. ResultsThe relation between molar and mass Lp(a) was not constant across the concentration range. The molar-to-mass ratio increased across higher clinically relevant Lp(a) categories, indicating concentration-dependent correspondence between nmol/L and mg/dL. The molar-to-mass ratio was directly associated with the LPA GRS and inversely associated with apo(a) isoform size, and these associations were more strongly attenuated after adjustment for molar than for mass Lp(a). Across CAD and composite CVD, molar- and mass-based Lp(a) showed broadly similar associations. In fully adjusted CAD models, the odds ratio for the highest versus lowest quintile was 1.55 for molar Lp(a) and 1.67 for mass Lp(a); corresponding continuous-model ORs were 1.20 and 1.22 per 1-unit increase in inverse-normal transformed Lp(a). Discrimination and global model fit were essentially identical between the two measurement scales. ConclusionsMolar- and mass-based Lp(a) measurements showed comparable epidemiologic associations with prevalent cardiovascular outcomes. However, molar reporting aligned somewhat more closely with the genetic and structural determinants of Lp(a), supporting continued standardization toward particle-based reporting. Clinical PerspectivesO_ST_ABSWhat Is New?C_ST_ABSO_LIIn the Young Finns Study, Lp(a) reported in molar and mass units showed highly similar associations with prevalent coronary artery disease and composite cardiovascular disease. C_LIO_LIThe relation between molar and mass Lp(a) was not fixed: the molar-to-mass ratio varied across clinically relevant Lp(a) concentration ranges and according to apo(a) isoform size. C_LIO_LIMolar Lp(a) showed slightly stronger alignment with the LPA genetic risk score, and ratio-based analyses suggested that genetically and structurally determined assay discordance was more closely captured by molar than by mass measurement. C_LI What Are the Clinical Implications?O_LIMass- and molar-based Lp(a) remain broadly comparable for cardiovascular risk association analyses, but they should not be treated as directly interchangeable using a single universal conversion factor. C_LIO_LIParticle-based reporting in nmol/L may better reflect the biologic dimension of Lp(a), even when disease discrimination is similar to that of mass-based reporting. C_LI

STRUCTERED ABSTRACTO_ST_ABSBACKGROUNDC_ST_ABSCoronary artery bypass graft (CABG) is a widely performed procedure for coronary artery disease (CAD), yet its association with Impaired Cognition (IC), i.e., mild-cognitive impairment or all-cause dementia, while accounting for APO ({varepsilon}) genotype, remains unclear. METHODSWe analyzed AllofUS participants with CAD (Age[&ge;]60 yrs) from 2017-2023. We defined CAD as a history of angina/myocardial infarction/chronic ischemic heart disease or having percutaneous coronary intervention/CABG, and IC as mild cognitive impairment or all-cause dementia using ICD/SNOMED codes. We performed logistic regression analyses to assess the association between CABG and IC, adjusting for clinical factors (age, sex, hypertension, diabetes, hyperlipidemia, depression, stroke, smoking, alcohol use, statin/antihypertensive/antidiabetic use), social determinants (self-reported race/ethnicity, income, employment), and APO ({varepsilon}) genotypes. We further performed stratified analyses across APO ({varepsilon}) genotypes ({varepsilon}2/{varepsilon}2, {varepsilon}2/{varepsilon}3 {varepsilon}3/{varepsilon}3, {varepsilon}2/{varepsilon}4, {varepsilon}3/{varepsilon}4, {varepsilon}4/{varepsilon}4). We defined significance at p [&le;] 0.05. RESULTSWe included 22,349 with CAD and identified 908 with IC after CAD till 2023. 40% were females, 70% were White, 12% were Black, and 9% were Hispanic. The proportion of IC was higher (5.1% vs 3.5%, p=1e-08) in CABG (n=8,135) vs non-CABG (n=14,214). After adjusting for clinical factors, social determinants, and APO ({varepsilon}) genotypes, CABG (1.23;1.06-1.41, p = 0.005) was associated with IC. In APO ({varepsilon}) stratified analysis, the association of CABG with IC was strongest in the APO {varepsilon}2/{varepsilon}3 group (1.91;1.21-3.02, p = 0.005). CONCLUSIONIn the AllofUS cohort, we observed an association between CABG and IC in CAD participants, with the strongest association in the APO {varepsilon}2/{varepsilon}3 group. Key MessageO_ST_ABSWhat is already known on this topicC_ST_ABSCoronary artery disease (CAD) and Impaired Cognitive (IC) disease, i.e., mild cognitive impairment and all-cause dementia, share genetic, sociodemographic, and clinical factors, including cardiovascular conditions like coronary artery bypass grafting (CABG) procedure. What this study addsWe observed an association between CABG and IC in CAD participants after adjusting for sociodemographic, clinical factors, and APO ({varepsilon}) effects. Further, when CAD participants were stratified across APO ({varepsilon}) groups, CABG was significantly associated with IC in the APO {varepsilon}2/{varepsilon}3 group. How this study might affect research, practice or policyOur observations highlight the role of APO ({varepsilon}) genotype evaluation in CAD patients for IC risk assessment.

Background: People with ischemic heart disease (IHD) remain at high risk of recurrent major cardiovascular events despite contemporary therapy. Over two decades, a translational research program has evaluated pressure pain sensitivity (PPS) as a non-invasive marker of central autonomic dysfunction and a mutual risk phenotype in IHD and type 2 diabetes. A PPS-guided non-pharmacological intervention has been shown to substantially reduce five-year all-cause mortality in IHD. Methods: In a randomized controlled trial, 213 adults with stable IHD and elevated PPS, suggesting ANSD, were allocated to PPS-guided intervention (n=106) or control (n=107). The active group received three months of structured education (daily PPS self-measurement, cutaneous sensory nerve stimulation, supportive mental and physical exercises, telemedical feedback) followed by self-directed continuation. Controls received a booklet on general stress-management. The primary endpoint for this prespecified secondary analysis was a composite of eight major cardiovascular events. Results: Over 5 years, at least one major adverse cardiovascular event occurred in 19.8% of the PPS-guided group versus 43.8% of controls (odds ratio 0.32, 95% CI 0.17-0.62, P=0.0003). Incidence rates were directionally in favor of active intervention across all event categories (P=0.004). Conclusions: A brief PPS-guided non-pharmacological intervention, followed by self-directed continuation, was associated with a marked long-term reduction in major adverse cardiovascular events, complementing previously reported large reductions in all-cause mortality in the same cohort. Within the context of a multi-decade PPS research program, these findings support PPS-guided care as a low-resource autonomic intervention ready for pragmatic scale-up testing as an adjunct to cardiometabolic care.

Lipoprotein(a) (Lp(a)) is associated with atherothrombosis through several mechanisms, including putative antifibrinolytic properties. In the ASPREE randomized trial of daily low-dose aspirin for primary prevention in older adults, 72% of trial participants in Australia provided baseline blood samples from which Lp(a) and related oxidized phospholipids and plasminogen have been measured in a specialized laboratory at University of California San Diego. Recent findings from our group suggest that aspirin may benefit older individuals with genotypes associated with elevated lipoprotein(a). We present an analysis plan to address key hypotheses relating to whether the effects of aspirin on cardiovascular disease might vary based on a person's measured levels of lipoprotein(a), oxidized phospholipid levels present on protein carriers apoB-100 (OxPL-apoB), Lp(a) (OxPL-apo(a)) and plasminogen (OxPL-PLG), and plasminogen. The analysis plan also articulates safety analyses involving major hemorrhage.