Atherosclerotic Cardiovascular Disease Risk Research Articles

Background/Introduction: Atherosclerotic cardiovascular disease (ASCVD) risk calculators perform poorly among people with HIV (PWH). Non-calcified coronary plaque (NCP) volume measured using coronary computed tomographic angiography (CCTA) predicts future ASCVD events in the general population, and NCP is increased among PWH. However, the ability of ASCVD risk calculators to predict NCP among PWH is unknown. Methods: We included individuals ages 40-79 with treated and suppressed HIV and ≥ 1 additional cardiovascular risk factor besides HIV. We measured blood pressure and fasting lipid panels. CCTA was performed according to standard research protocol and interpreted by a blinded core lab. The primary outcome was non-calcified plaque volume (excluding calcified plaque). We calculated predicted 10-year atherosclerotic ASCVD risk using four equations: Predicting Risk of cardiovascular disease EVENTs (PREVENT), Pooled Cohort Equation (PCE), Data Collection on Adverse Events of Antiretroviral Drugs (DAD-reduced)-an HIV specific calculator, and Framingham. We used linear regression to assess the amount of variation in log-transformed NCP volume explained by each risk prediction equation. Results: We included 81 individuals with mean age of 60 years, 4% female (Table) . The mean total cholesterol, calculated LDL-C, HDL-C, and triglycerides were 190 mg/dl, 113 mg/dl, 49 mg/dl, and 143 mg/dl, respectively. The mean predicted 10-year ASCVD risk was 5.4% using PREVENT, 12.3% using PCE, 11.5% using DAD, and 17.0% using Framingham. Predicted risk with each of the four equations correlated with NCP volume (p<0.01 for each), and predicted risk was higher among those with more plaque with all four ( Table ). However, the proportion of variance in NCP volume explained by each model was low with R 2 values of 16.4%, 11.1%, 11.7%, and 11.1% for PREVENT, PCE, DAD, and Framingham, respectively ( Figure , p<0.01 for each). Among those with <5% calculated 10-year risk (“low risk”), median plaque volume was 69 mm 3 for PREVENT (45 people), 23 mm 3 for PCE (15 people), 14 mm 3 for DAD (11 people), and 8 mm 3 for Framingham (2 people). Conclusions: Both traditional and HIV specific ASCVD risk prediction equations only explain a small amount of the variation in NCP volume among PWH at elevated cardiovascular risk; this finding may underlie the poor performance of these risk calculators to predict cardiovascular events among this high-risk population.

Background: Behavioral factors such as physical activity, sleep, and heart rate are associated with cardiovascular (CV) health but are not used in current CV risk prediction tools. Consumer wearable devices offer continuous behavioral data that may enhance atherosclerotic cardiovascular disease (ASCVD) risk prediction. Hypothesis: Incorporation of wearable-derived metrics into CV risk prediction algorithms may improve accuracy. Development of demographic and wearable-only CV risk prediction algorithms may enable continuous and more scalable monitoring compared to existing models that require in-person assessments. Methods: We conducted a retrospective cohort study using electronic health record (EHR) data from the All of Us Research Program linked to participants’ Fitbit data. Adults (≥18 years) with EHR and Fitbit data (up to 180 days prior to ASCVD event) were included; those with pre-existing CV disease were excluded. Incident ASCVD was defined using ICD-10 codes (myocardial infarction, ischemic stroke) and CPT codes (percutaneous coronary intervention and coronary artery bypass grafting). ASCVD risk was assessed using PREVENT equations. Multiple imputation was used for missing data (up to 2 missing variables per participant). Logistic regression was used to estimate ASCVD risk. Model performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC) and Youden's J statistic. Results: Among 4,193 participants (median age 52, 74% female) with a calculable PREVENT score, 162 had incident ASCVD during a median follow-up of 4.1 years. Those with incident ASCVD were older (59.4 vs. 51.2 years, P<0.001), more often male (47% vs. 25%), and had higher rates of hypertension (47% vs. 37%, P=0.01) and smoking (48% vs. 33%, P<0.001). A wearable-based model supplemented with basic, patient-known demographic information achieved an AUC of 0.741 (Table 1) vs. AUC of 0.728 for PREVENT alone. Adding wearable data to PREVENT yielded modest improvement (AUC 0.738 vs 0.728), but with low specificity. A wearable-based model with demographics predicted the ASCVD risk category (≥7.5% vs. <7.5% risk per PREVENT) with an AUC 0.95, 77% sensitivity, and 95% specificity (Table 2). Conclusions: Wearable-based models using behavioral metrics and basic demographics perform similarly to PREVENT, and offer remote, personalized, dynamic ASCVD risk assessment. Model adjustments to improve specificity and validation in other cohorts are warranted.

Background: Elevated low-density lipoprotein cholesterol (LDL-C) and lipoprotein(a) [Lp(a)] are each independent drivers of atherosclerotic cardiovascular disease (ASCVD). Although PCSK9 inhibitors effectively lower LDL-C and Lp(a)-lowering therapies are currently being developed, their combined effect on long-term ASCVD risk remains unclear. Research Question: In this study, we investigate the effects of genetically proxied inhibition of LPA and PCSK9, both individually and in combination, on ASCVD risk. Methods: We analyzed ~450,000 unrelated European ancestry participants from the UK Biobank. Two sets of complementary genetic instruments for LPA and PCSK9 were derived: (1) rare (minor allele frequency < 0.001) predicted loss-of-function (pLoF) variants from whole-exome sequencing and (2) common cis-pQTLs (cis-acting protein quantitative trait loci) from imputed genotype arrays and the proteomics data. We used logistic regression models (separately for rare variants and common cis-pQTLs), adjusted for age, sex, and the first five genetic principal components, to estimate associations between these genetic instruments and ASCVD (a composite of coronary artery disease, myocardial infarction, and ischemic stroke) and all-cause mortality. Odds ratios (ORs) were reported per allele (for cis-pQTLs) or per carrier status (for rare variants). Mendelian randomization (MR) and other cardiovascular endpoints served as a sensitivity analysis. Results: Rare pLoF variants in PCSK9 (OR 0.74, p=0.0034) - as well as having a rare variant in either LPA or PCSK9 (OR 0.88, p=0.033) - were associated with lower ASCVD odds. In contrast, rare LPA variants alone showed no significant association with ASCVD (OR, 0.97; p = 0.67). For the common cis-pQTL instruments, lower genetically proxied LPA, PCSK9, or both were associated with significantly reduced ASCVD odds. Dual inhibition showed the greatest effect on reducing ASCVD risk (OR 0.82, p = 5.9 × 10^-34) and was also associated with reduced all-cause mortality (OR 0.95, p = 0.003). MR analyses supported these findings. Notable risk reduction was also found for endpoints including aortic stenosis, abdominal aortic aneurysm, and peripheral artery disease. Conclusion: In this large genetic analysis, combined inhibition of Lp(a) and PCSK9 was associated with the most pronounced reduction in ASCVD and mortality risk. These findings support the use of dual inhibition strategies in patients with elevated Lp(a) and LDL-C levels.

Introduction: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death in male service members and veterans. This study assessed the 10-year ASCVD risk in male military service members and veterans using the model construct of the VA women CVD risk score and the 2013 ACC/AHA ASCVD risk calculator using direct military health system and Veterans Affairs (VA) Electronic Health Records (EHR) data extracted from national VA corporate data warehouse (CDW) database. Research hypothesis: Military exposure at earlier life may lead to poorer health and ultimately decreased longevity. We hypothesize that military services in earlier life may alter aging trajectory and ASCVD risk—elevated risk of ASCVD events at a younger age than 40. Methods: We retrospectively followed 3.6 million Non-Hispanic (N-H) White (n=2,823,446) and Black (n=734,940) male military service members aged 20-79 from 2012 to 2024 (development cohort). Risk factors and ASCVD events (non-fatal myocardial infarction, non-fatal stroke, cardiac arrests, and cardiac deaths) were identified using diagnostic and procedural codes from Electronic Health Records (EHR) data. Following the same constructs of the VA women CVD risk score and the 2013 ACC/AHA ASCVD risk calculators, coefficients for risk factors were estimated for men by applying time-varying Cox models to the study male development cohort data. Results: N-H Black male service members, on average 3 years younger than their white counterparts, had significantly higher systolic blood pressure, total cholesterol, HDL-C, and were more likely to be treated with anti-hypertensive medications (Tables 1 and 2). We found a log-linear association of aging with increased risk of 10-year ASCVD event in military service male members starting at ages as young as 20 years old (Figure 1.A.) across both N-H White and Black groups in contrast with the ACC/AHA ASCVD risk score (Figure 1.B.). The VA CVD risk model performed well in predicting ASCVD events at 10 years for men (C statistics N-H White 0.72 and N-H Black 0.71), while the ACC/AHA ASCVD risk calculator showed a moderate performance (C statistics N-H White 0.69; N-H Black 0.69). Conclusions: Our results point to a log-linear association of aging with increased ASCVD risk in military males starting at age 20. We call to action the need to create a better cardiovascular risk calculator that adequately assesses young male (<40 years old) military service members’ ASCVD risk.

Background: Despite increased atherosclerotic cardiovascular disease (ASCVD) risk, Black and Hispanic individuals are underrepresented in ASCVD clinical trials. Black individuals have the highest prevalence and median levels of elevated lipoprotein(a) [Lp(a)] among U.S. populations, contributing to a significantly higher ASCVD risk. Aim: Address and mitigate systemic barriers to clinical trial participation for historically underrepresented populations to enhance diversity and inclusion in cardiovascular research. Methods: The Lp(a)FRONTIERS EXPANSION trial is a randomized, double-blind, phase 3b multicenter study evaluating the efficacy of pelacarsen, an Lp(a)-targeted therapy, vs placebo in lowering Lp(a) levels in U.S. Black and Hispanic patients with elevated Lp(a) (≥125 nmol/L) and established ASCVD. To increase trial participation in minority populations, the study used a 2:1 randomization ratio, increasing the chance of receiving the investigational treatment. Considering disparities in healthcare access and quality, the trial included a post-screening standard-of-care (SoC) visit, if needed, to optimize participants’ modifiable ASCVD risk factors. To reduce patient burden, required on-site visits were minimized. The trial aimed to enroll 400 participants across 150 strategically selected sites, including those in underserved areas, to improve accessibility and reduce travel time. Additional patient support included transportation assistance, childcare reimbursement and flexible scheduling. Sites were compensated for additional screening time, particularly to accommodate family involvement in decision-making, which is culturally significant in Hispanic communities. Results: A total of 423 participants were enrolled over 11 months at 103 sites, a full year ahead of schedule. Of these, 65% identified as Black non-Hispanic, 30% as Hispanic and 5% as Black Hispanic. Women comprised 49% of the cohort; mean age was 63.2 years. Sixty participants received the optional SoC visit, with 37 initiating or adjusting treatment for ASCVD risk factors. Conclusion: The Lp(a)FRONTIERS EXPANSION trial successfully demonstrated that deliberate, culturally tailored strategies can improve participation of minority populations, underrepresented in cardiovascular clinical trials. These results highlight the importance of inclusive trial design and operational efforts to achieve equitable representation in clinical research, ensuring generalizability of trial results.

Background: Artificial Intelligence (AI) applied to high-resolution imagery offers a novel, scalable approach to comprehensively characterize nuanced environmental exposures. A growing body of evidence implicates the built and natural environment in atherosclerotic cardiovascular disease (ASCVD) risk. Hypothesis: We hypothesized that a proportion of observed ASCVD events attributable to AI-derived geospatial features from the natural and built environment is mediated by traditional risk factors and moderated by underlying genetic susceptibility. Methods: Individual-level data from the UK ( n > 502,000, UKB) and the US Mass General Brigham ( n > 144,000, MGB) biobanks served as training/test and validation cohorts, respectively. Using convolutional neural networks (CNNs), > 8,000 natural and built environment features extracted from Google Satellite Images (GSI) and Street Views (GSV) were used to derive cross-validated sparse partial least squares personalized geospatial GSI/GSV scores. Associations between these scores with MACE and key risk factors (LDL-C, BMI, SBP, T2DM) were modeled by multivariate Cox PH models, adjusted for demographics, clinical, and area-level socioeconomic status covariates. Polygenic Risk Score (PRS) moderation and causal mediation analyses were performed along with geospatial mapping. Results: Out of 7 GSI and 4 GSV derived scores, 10 were significantly associated with MACE (all p < 0.001), with hazard ratios ranging from 0.961 to 1.048, comparable in magnitude to social deprivation and air pollution measures in UKB. Adding GSI/GSV scores to traditional risk models combining demographics, socio-determinants of health, and risk factors significantly improved model fit (GSI: likelihood ratio test (LRT) = 279.3, p < 0.001; GSV: LRT = 99.3, p < 0.001). Findings were validated in the MGB cohort for 4 of 7 GSI and 2 of 4 GSV features. Significant interaction effects were observed between GSI/GSV and PRS for LDL-C (p = 0.007), BMI (p = 0.05), and T2DM (p = 0.013). Causal mediation analysis revealed significant indirect effects and mediated proportions of GSI/GSV on SBP (p < 0.0001; 0.7%), T2DM (p < 0.0001; 0.5%), and BMI (p < 0.0001; 9.7%). Conclusion: AI-derived environmental geospatial features are associated with ASCVD risk, partially mediated by traditional risk factors, while moderated by genetic susceptibility. These findings highlight the potential for scalable environmental risk modeling to advance precision cardiovascular prevention.

Introduction: Social determinants of atherosclerotic cardiovascular disease (ASCVD) risk factors in second generation, young adult South Asians have not been investigated. Individual-level educational attainment is a strong upstream social determinant of health; however, parental education may also influence health outcomes. Research Question: Is higher parental education associated with better ASCVD risk factor levels among second generation, young adult South Asians in the United States (US)? Methods: Among US South Asian adults age ≥18 years who participated in the MASALA-2G Second Generation Study as children of participants in the MASALA (Mediators of Atherosclerosis in South Asians Living in America) Study, we evaluated the association of paternal and maternal educational attainment (higher: college graduate and higher; lower: some college or less) with ASCVD risk factors using multivariable linear regression adjusted for age, sex, participant’s own educational attainment, and place of birth (in versus outside the US). Results: Among 116 second generation South Asian Americans (mean age 34.3 [SD 9.3] years; 49% female, 51% male), of whom 88% had a college degree or higher, 85% had a father with a college degree or higher, and 72% had a mother with a college degree or higher. Mean (SD) values of ASCVD risk factors in the overall sample were: fasting glucose 91 (7) mg/dL, hemoglobin A1c 5.3% (0.3), total cholesterol 180 (32) mg/dL, non-high density lipoprotein cholesterol 127 (31) mg/dL, triglycerides 103 (53) mg/dL, body mass index 23.5 (4.3) kg/m 2 , waist circumference 89 (13) cm, systolic blood pressure (BP) 115 (12) mmHg, diastolic BP 73 (9) mmHg, and sleep duration 7.1 (1.1) hours. In unadjusted analysis, higher paternal education was associated with lower diastolic BP, higher sleep duration, smaller waist circumference, and smaller waist-hip ratio in the adult child. After adjustment (Table), higher paternal education remained significantly associated with lower diastolic BP (ß -7 mmHg, 95% CI -12, -2), compared with lower paternal education. There was no association between maternal educational attainment and young adult child’s ASCVD risk factors. Conclusions: Among South Asian young adults in the MASALA-2G Study, higher paternal educational attainment may be associated with better ASCVD risk factors, independent of one’s own educational attainment. Future research should investigate how parental education may influence ASCVD risk in this group.

Background: It is well known that Autoimmune disorders such as rheumatoid arthritis and systemic lupus erythematosus confer atherosclerotic cardiovascular disease (ASCVD) risk comparable to diabetes mellitus (DM). However, prescribing patterns of lipid-lowering therapy in this population remain underexplored. Hypothesis: Patients with autoimmune disease are less likely to receive statins and non-statin lipid-lowering therapy than those with DM across low-density-lipoprotein-cholesterol (LDL-C) strata. Methods: We conducted a nationwide retrospective cohort study using the TriNetX platform, which provides real-time, deidentified clinical data from electronic health records. Adults (≥18 years) with either rheumatoid arthritis or systemic lupus erythematosus or DM type 1 or 2 and at least one low-density lipoprotein cholesterol value were included. Patients were stratified into six LDL-C categories: <70, 70–99, 100–129, 130–159, 160–189, and ≥190 mg/dL. Initiation of lipid-lowering therapy within six months of cholesterol measurement was assessed. Statins included atorvastatin, rosuvastatin, simvastatin, pravastatin, lovastatin, fluvastatin, pitavastatin. Non-statin therapies included icosapent ethyl, colesevelam, alirocumab, evolocumab, Bempedoic acid, cholestyramine, Inclisiran, colestipol, ezetimibe, gemfibrozil, omega-3 acid, fenofibrate. Individuals with major ASCVD risk factors, prior major adverse cardiovascular events, known statin intolerance, or liver disease were excluded. Comparisons were made using chi-square tests with significance defined as p<0.05. Results: Among 41,805 patients with autoimmune disease and 427,909 with DM, statin use was significantly lower in the autoimmune group across all LDL-C categories: 23.65% vs 33.44% (<70 mg/dL), 17.65% vs 27.86% (70–99), 14.21% vs 25.41% (100–129), 17.20% vs 28.50% (130–159), 26.00% vs 35.59% (160–189), and 39.15% vs 44.91% (≥190) (all p<0.0001). Non-statin lipid-lowering therapy use was significantly lower in autoimmune patients compared to those with diabetes across all LDL-C tertiles, with the largest differences observed at LDL <70 mg/dL (6.19% vs 10.24%, p<0.0001) and 70–99 mg/dL (4.05% vs 7.06%, p<0.0001). Conclusion: Despite comparable ASCVD risk, patients with autoimmune disease are significantly less likely to receive statins or non-statin lipid-lowering therapy than those with DM across LDL-C levels. These findings show a need for improved cardiovascular prevention in this high-risk population.

Background: Immune-mediated inflammatory diseases (IMID) such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and psoriasis increase atherosclerotic cardiovascular disease (ASCVD) risk. Epicardial adipose tissue (EAT) is biologically active fat depot that may provide prognostic information and can be opportunistically quantified on CT calcium score (CTCS) scans. Hypothesis: Spatial- and attenuation-based EAT radiomic features differ and differentially predict ASCVD events in IMID patients versus matched controls. Methods: Patients without known ASCVD who underwent CTCS between 2014 and 2020 in the CLARIFY Registry (NCT0407516224) were included in this analysis. A validated AI tool was used to segment EAT. Next, 215 “fat-omics” features were extracted, including spatial positioning of EAT from inferior-to-superior cardiac spanning slab quartiles (PQ), and Hounsfield unit (HU) histogram bins (20-HU increments). IMID patients were matched 2:1 on age, sex, race, hypertension, diabetes, and smoking. Incident myocardial infarction (MI)/revascularization was analyzed over a median 4-year follow-up. Results: IMID patients (N=1095, SLE: 162, RA: 557, Psoriasis: 430) had significantly higher EAT volume (p<0.005) and a greater incidence of MI/revascularization (12.9 vs. 8.6 per 1000 person-years) than matched controls (n = 2190). After false-discovery-rate correction, 70 features differed, driven by high-density EAT (HEAT), with HU between -90 and -30. Consistent with prior work, controls demonstrated that high-attenuation EAT (Hi-HEAT) in the superior cardiac spanning slab (PQ4, HU [-50, –30]) was associated with ASCVD events (HR 1.16 [1.05–1.28]; p=0.005). Hi-HEAT was absent in IMID patients. Instead, Lo-HEAT (HU [-90, -70], [-70, -50], [-50, -30]) in the inferior slab (PQ1) predicted events with significant HRs of 1.20 [1.04, 1.37], 1.30 [1.09–1.55], and 1.15 [1.00, 1.31] respectively after adjusting for EAT volume. Conclusion: Spatial- and attenuation-based EAT radiomics reveal a distinct inferio-superior spatially segregate phenotype (Lo-HEAT) that drives ASCVD risk in IMID patients, suggesting differential EAT relationships. Lo-HEAT might reflect more systemic EAT inflammation as opposed to focal coronary inflammation (Hi-HEAT). Future studies should prospectively validate the Lo-HEAT phenotype and test whether targeted anti-inflammatory therapies can mitigate ASCVD risk in IMID patients.

Background: Abdominal aortic calcification (AAC) is a marker of subclinical atherosclerotic cardiovascular disease (ASCVD). Cardiovascular-kidney-metabolic (CKM) syndrome reflects dysfunction across cardiovascular, renal, and metabolic systems. The relationship between AAC and CKM is poorly understood. This study examined associations of CKM stages and predicted 10-year ASCVD risk with AAC in US adults aged ≥40 years. Methods: This cross-sectional study used National Health and Nutrition Examination Survey (NHANES) 2013–2014 data. AAC was measured by dual-energy X-ray absorptiometry and scored via the Kauppila method (range: 0–24). AAC was categorized as absent (score = 0), present (score > 0 to ≤ 6), and severe (score > 6). CKM stages (0–3+) were characterized as follows: Stage 0 included healthy individuals with normal BMI and waist circumference without other risk factors; Stage 1 included elevated BMI/waist circumference or prediabetes; Stage 2 included hypertension, diabetes, hypertriglyceridemia, metabolic syndrome, or moderate-to-high-risk CKD; Stage 3+ included very-high-risk CKD or ASCVD risk ≥20%. Multivariable linear and multinomial logistic regression were used to examine associations of ASCVD risk and CKM stage with AAC. Results: A total of 3140 participants (mean age 57.4 years, 48.1% male, 71% Non-Hispanic White) were included. Mean AAC scores progressively increased across CKM stages: 0.42 (stage 0), 0.81 (stage 1), 1.96 (stage 2), and 4.61 (stage 3+) (p<0.001). Each 10% ASCVD risk increase correlated with a 1.46-point higher AAC score (95% CI: 1.19–1.74). CKM stage 3+ was linked to a 1.16-point higher AAC score vs. stage 0 (95% CI: 0.43–1.89). Odds of any AAC increased 80% per 10% ASCVD increase (OR=1.80; 95% CI: 1.47–2.20), and odds of severe vs. absent AAC were over threefold higher (OR=3.45; 95% CI: 2.78–4.28). CKM stage 3+ had 3.38-fold greater odds of severe vs. absent AAC (95% CI: 1.29–8.86). Race/ethnicity modified AAC–ASCVD (p<0.01) and AAC–CKM (p<0.01) associations. Compared to stage 0, CKM stage 3+ was linked to AAC score increases of 3.37 (95% CI: 2.61–4.12) in Non-Hispanic White, 3.66 (95% CI: 1.75–5.57) in Asian, 2.01 (95% CI: 0.974-3.060) in Non-Hispanic Black, and 1.76 (95% CI: 0.40–3.13) in Hispanic populations. Conclusions: CKM stage and ASCVD risk are associated with AAC, with the magnitude of associations varying by race/ethnicity. AAC may serve as a useful imaging marker for early cardiometabolic risk detection.

Background: Elevated lipoprotein(a) [Lp(a)] is associated with atherosclerotic cardiovascular disease (ASCVD) risk, and vascular inflammation is one mechanism through which Lp(a) causes ASCVD. Biomarkers associated with inflammation and cardiovascular disease, such as interleukin-6 (IL-6), may help risk stratify individuals with elevated Lp(a). Research Questions: We aimed to evaluate whether the association between Lp(a) and ASCVD risk is modified by IL-6. Methods: Data from participants in the Multi-Ethnic Study of Atherosclerosis (MESA, n=6,514) and the UK Biobank (UKB, n=26,574) was used for this analysis. The associations between Lp(a) and IL-6 with coronary heart disease (CHD, defined as myocardial infarction or resuscitated cardiac arrest), ASCVD (CHD and ischemic stroke) and peripheral vascular disease (PVD) were evaluated separately and with mutual adjustment in Cox proportional hazards models adjusted for traditional cardiovascular risk factors and high-sensitivity c-reactive protein (hsCRP). Hazard ratios (HR) were presented per SD. Participants were also grouped by Lp(a) level (≤ or >50 mg/dL or 125 nmol/L) and IL-6 level (≤ or >median) in similar models. Results: Participants with higher IL-6 levels were more likely to have higher body mass index, systolic blood pressure, triglycerides and hsCRP with lower high-density lipoprotein-cholesterol. Lp(a) (HR 1.13, 95% CI 1.04-1.23 in MESA; HR 1.11, 95% CI 1.09-1.13 in UKB) and IL-6 (HR 1.22, 95% CI 1.10-1.35 in MESA; HR 1.19, 95% CI 1.15-1.24 in UKB) were both independently associated with CHD events when evaluated separately. When evaluated together, no significant change was noted, and interaction testing was not significant. Similar results were seen for ASCVD and PVD. When participants were categorized by both Lp(a) and IL-6 levels, the strongest association for each outcome was noted when both levels were high (for CHD: HR 1.72, 95% CI 1.25-2.36 in MESA; HR 1.39, 95% CI 1.12-1.72 in UKB, Figure ). Conclusions: In two independent primary prevention cohorts, Lp(a) and IL-6 are independent predictors of ASCVD risk, and their combination identifies individuals at highest risk

Background: Lipoprotein(a) [Lp(a)] is a known risk factor for atherosclerotic cardiovascular disease (ASCVD). However, it is unclear whether the ASCVD risk associated with elevated Lp(a) is uniform or differs according to baseline risk profiles. Aims: To compare the association of elevated Lp(a) with incident ASCVD across levels of risk factor burden and 10-year predicted ASCVD risk. Methods: We performed a prospective analysis among participants at Visit 4 (1996-98) of the ARIC study without baseline ASCVD and with Visit 4 Lp(a) measurements (Denka Seiken assay). ASCVD risk factors were smoking, hypercholesterolemia, diabetes, hypertension, and chronic kidney disease (CKD), and ASCVD risk was estimated using the PREVENT-ASCVD calculator. Elevated Lp(a) was defined as ≥30 mg/dL. We assessed the association of elevated Lp(a) with incident ASCVD events (nonfatal myocardial infarction, fatal coronary heart disease, or ischemic stroke) after Visit 4 through 12/31/22 with multivariable adjusted Cox proportional hazards models. Lp(a) associations were assessed for those with and without individual risk factors, by number of risk factors and at different levels of predicted ASCVD risk. Results: Among 9,483 participants (mean age 63, 58% female, and 21% Black adults), there were 2,311 ASCVD events over a median 19.8 years of follow-up. Individuals with smoking, diabetes, hypertension, and CKD had nominally higher risk (HRs 1.3-1.4) associated with elevated Lp(a) than those without those conditions (HRs 1.1-1.2), with a significant interaction for diabetes (p=0.02) ( Table 1 ). Higher risk in association with elevated Lp(a) was seen for those with a greater number of risk factors and with higher predicted ASCVD risk ( Table 2 ). Elevated Lp(a) was associated with higher risk in those with 3-5 risk factors (HR 1.44 [95% 1.20-1.73]) than in those with 0-2 risk factors (HR 1.11 [95% CI: 1.00-1.23] p-interaction = 0.015). Similarly, elevated Lp(a) was associated with higher risk in those with ≥10% predicted risk (HR 1.42 [95% CI: 1.20-1.68]) than in those with <10% predicted risk (HR 1.11 [95% CI 1.00-1.24] p-interaction = 0.017). Conclusions: Elevated Lp(a) has stronger ASCVD risk associations in those with a higher burden of clinical risk factors, especially diabetes. These finding suggest the importance of risk factor prevention and control for reducing Lp(a)-related risk and may help to inform the optimal targeting of emerging Lp(a) lowering therapies.

Background: Elevated lipoprotein(a) [Lp(a)] is recognized as a causal risk factor for atherosclerotic cardiovascular disease (ASCVD). However, the precise magnitude of this association at different Lp(a) concentrations and potential differences between sexes warrant further elucidation. Objective: This meta-analysis evaluated the association between various Lp(a) thresholds and ASCVD risk, stratified by sex. Methods: We systematically searched PubMed and Google Scholar databases from inception until May 2025. Studies reporting on Lp(a) levels predicting ASCVD risk were included for analysis. Pooled adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for ASCVD were calculated using a DerSimonian–Laird random-effects models for predefined Lp(a) thresholds (>20, >30, >50, and >100 mg/dL) compared to lower levels, separately for men and women. Results: Out of 1,135 studies screened, 5 studies comprising participants were 111,246 included. The mean age was 58.7 ± 12.04 years. Elevated Lp(a) was significantly associated with increased ASCVD risk in men (AOR 1.47 [1.24-1.74], I2:97.98%) and women (AOR 1.39 [1.21-1.59], I2:94.03%), both p<0.001. A dose-response relationship was evident in both sexes. In men, significant risk emerged at Lp(a) >30 mg/dL (AOR 1.18 [1.13-1.22], p<0.001), increasing to an AOR of 2.04 [1.22-3.40] (p=0.01) for levels >100 mg/dL. In women, significant risk was apparent at Lp(a) >50 mg/dL (AOR 1.48 [1.26-1.72], p<0.001), reaching an AOR of 1.74 [1.22-2.48] (p<0.001) for levels >100 mg/dL. A leave-one-out sensitivity analysis demonstrated that the direction and significance of these pooled estimates were not dependent on any single study. Conclusion: This meta-analysis confirms a significant and dose-dependent association between elevated Lp(a) concentrations and increased ASCVD risk in both men and women. While overall risk estimates at high Lp(a) concentrations showed considerable overlap, significant ASCVD risk appeared at Lp(a) concentrations >30 mg/dL in men, whereas in women, this was evident at concentrations >50 mg/dL. These findings underscore the importance of Lp(a) as a key cardiovascular risk factor in both sexes and may inform sex-specific considerations in risk stratification and future guideline development for ASCVD prevention.

Background: Guideline-directed lipid-lowering still leaves up to one-third of high-risk patients above LDL-C targets, sustaining residual cardiovascular risk. Obicetrapib—an oral cholesteryl-ester transfer-protein inhibitor has produced promising results in LDL-C reductions in recent phase 2/3 trials. We aim to quantify the efficacy and safety of Obicetrapib versus placebo in statin-treated adults. Methods: We searched PubMed, Embase, Cochrane, Scopus, and Web of Science (inception to 15 May 2025) for randomised controlled trials (RCTs) that enrolled adults with dyslipidemia (with or without atherosclerotic cardiovascular disease risk (ASCVD) receiving statins and compared Obicetrapib (1, 2.5, 5, or 10 mg) against placebo. Dichotomous outcomes were pooled as risk ratios (RRs), and continuous outcomes as mean differences (MDs), each with 95 % confidence intervals (CIs). Results: A total of 3,386 patients were included across six RCTs. Obicetrapib, compared to placebo, was associated with a significantly greater reduction in LDL-C (MD: -27.29 mg/dL; 95% CI: -33.65 to -20.93; P < 0.0001) and a significantly greater increase in HDL-C (MD: 70.96 mg/dL; 95% CI: 64.71 to 77.20; P < 0.0001). Obicetrapib also significantly increased the likelihood of achieving LDL-C targets of <55 mg/dL (RR: 6.42; 95% CI: 5.15 to 8.01; P < 0.0001), <70 mg/dL (RR: 2.56; P < 0.0001), and <100 mg/dL (RR: 1.34; P < 0.0001). Additionally, apolipoprotein B levels were significantly reduced with Obicetrapib (MD: -14.34 mg/dL; 95% CI: -19.28 to -9.41; P < 0.0001). Additionally, there was no significant difference in total adverse events (AEs) (P= 0.4124), serious AEs (P= 0.3712), and AEs leading to discontinuation of medication (P=0.4035). Conclusion: Our analysis shows that Obicetrapib, a selective CETP inhibitor, significantly improves lipid profiles in statin-treated patients with dyslipidemia, with or without ASCVD. It led to marked reductions in LDL-C, non-HDL-C, and apoB, and substantial increases in HDL-C. These effects significantly increased the achievement of LDL-C targets. Obicetrapib’s safety profile was similar to that of the placebo. Further RCTs are needed to confirm these findings.

Introduction: Lifestyle modification with weight loss is recommended in type 2 diabetes (T2D) with metabolic dysfunction-associated steatotic liver disease (MASLD). However, the effects of an intensive lifestyle intervention (ILI) targeting weight loss on MASLD in T2D has not been fully characterized. Furthermore, the associations of baseline and longitudinal changes in MASLD with risk of atherosclerotic cardiovascular disease (ASCVD) in T2D is not well-established. Methods: Look AHEAD (Action for Health in Diabetes) trial participants with T2D and overweight or obesity were included. AST, ALT, and GGT were measured at baseline and 1-year follow-up. The probability of MASLD was calculated using the Dallas Steatosis Index (DSI) and the Framingham Steatosis Index (FSI) which were compared with proton magnetic resonance spectroscopy ( 1 H MRS) in a subset of participants with 244 studies. MASLD was defined as hepatic steatosis ≥5.5%. The effect of the ILI versus diabetes support and education (DSE) on measures of MASLD were assessed using least-square means. Adjusted Cox models were created to evaluate the associations of baseline and 1-year longitudinal changes in probability of MASLD with risk of ASCVD (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina). Results: The present study included 3,938 participants with AST, ALT, and GGT data. Among 244 1 H MRS studies, DSI demonstrated fair performance for predicting MASLD (C-statistic: 0.693) and was similar for the FSI at 0.688. The probability of MASLD was estimated in all study participants using the DSI. At 1-year of follow-up, the ILI (versus DSE) reduced the probability of MASLD by 10.3% ( Figure 1A ), decreased the proportion of participants with high probability of MASLD (≥70%) ( Figure 1B ), and reduced AST, ALT, and GGT ( Figure 1C ). In adjusted analyses, higher baseline probability of MASLD was significantly associated with higher risk of ASCVD ( Figure 1D ). Increase in probability of MASLD over 1-year follow-up was significantly associated with higher risk of ASCVD. Conclusions: Among adults with T2D and overweight or obesity, an ILI targeting weight loss reduced the probability of MASLD as well as AST, ALT, and GGT. Higher baseline and longitudinal increases in the probability of MASLD were associated with ASCVD.

Background: Prediabetes is a precursor to type 2 diabetes and a significant risk factor for atherosclerotic cardiovascular disease (ASCVD). There is concern for increasing the impact of prediabetes on risk of ASCVD, whereas large-scale contemporary data is lacking. Methods: We conducted a retrospective cohort study of adults (ages 18-90) between 2015-2018 without type 1 or 2 diabetes and without established ASCVD. All individuals were members of Kaiser Permanente Northern California, a large integrated health care delivery system. Using electronic health records, we identified individuals with prediabetes and identified a similarly sized comparison cohort of adults without prediabetes. Multivariable Cox proportional hazards models were specified to estimate the hazards of 5-year ASCVD risk by prediabetes and obesity (BMI ≥30 mg/dL) status, adjusted for baseline characteristics for the entire cohort and stratified by obesity. Incident ASCVD events were defined as a composite of nonfatal myocardial infarction, ischemic stroke, or coronary heart disease death through December 31, 2023. Results: A total 1,358,882 individuals met the selection criteria. Of these, 688,575 (50.7 %) had prediabetes and of those with prediabetes, 260,795 had obesity. The comparison group was those without prediabetes at baseline. The mean age was 52.5 years, 55.8% were women, and the mean follow up time was 4.1 years. Both prediabetes with obesity (HR 1.29, 95% CI 1.25-1.34) and prediabetes without obesity (HR 1.19, 95% CI 1.16,1.23) were significantly associated with 5-year ASCVD risk compared to those without prediabetes (Table). ASCVD free Kaplan-Meier curve showed similar significant higher risk (p < 0.001) (Figure). Conclusion: Prediabetes and prediabetes plus obesity had worse outcomes overtime. Early lifestyle and pharmacologic interventions to address both obesity and prediabetes are warranted.

Background: African Americans (AAs) face higher mortality from atherosclerotic cardiovascular disease (ASCVD) than Whites. Inflammation plays a central role in atherosclerosis, yet the association between high-sensitivity C-reactive protein (hs-CRP) and ASCVD in AAs remains unclear. This study examined serial hs-CRP measurements and incident ASCVD in the Jackson Heart Study (JHS), a community-based AA cohort. Methods: JHS Participants without prior ASCVD were analyzed using hs-CRP measurements at Visit 1 (baseline; 2000–2004, "single-visit cohort"), Visits 1 and 2 (2005–2008, "two-visit cohort"), and Visit 1–3 (2009–2013) for joint modeling. hs-CRP was evaluated as both continuous and categorized (≥3 mg/L defined as elevated) variables. In the two-visit cohort, participants were divided by hs-CRP status as: normal at both visits, elevated at Visit 1 or 2 or both. ASCVD was defined as coronary heart disease (CHD; myocardial infarction and fatal CHD) and stroke. Cox proportional hazards models were used to assess the association between hs-CRP and incident ASCVD, adjusted for cardiovascular risk factors. Joint modeling was utilized to examine the time-dependent relationship of hs-CRP with incident ASCVD. Results: In the single-visit cohort (n = 3,948, mean age (standard deviation) 53.6 (12.8), female 64.3%), 340 participants developed ASCVD (6.9 cases per 1,000 person-years) during median 13.7 years follow-up. Each unit increase in hs-CRP was associated with greater ASCVD risk (adjusted hazard ratio (HR) 1.02, 95% confidence interval (CI) 1.01–1.02, P < 0.001). Elevated hs-CRP showed a trend toward increased risk. In the two-visit cohort (n = 2,324), 110 participants developed ASCVD (5.3 cases per 1,000 person-years) during median 8.9 years follow-up. Those with elevated hs-CRP were found to have a higher risk of ASCVD, with those with elevated hs-CRP at both visits the highest risk (HR 2.31, 95% CI 1.41–3.80, P < 0.001, Table). Joint modeling revealed a significant time-dependent association of hs-CRP trajectory with incident ASCVD (HR 1.03 per 1.0 mg/L increase, 95% CI 1.02–1.05, P < 0.001). Conclusion: In the AA general cohort, temporal hs-CRP changes were associated with the risk of ASCVD.

Background: It is well known that patients with autoimmune conditions such as rheumatoid arthritis and systemic lupus erythematosus are at increased risk for atherosclerotic cardiovascular disease. However, contemporary patterns of lipid-lowering therapy in autoimmune disease, especially among those with low LDL-C, remain inadequately defined. Hypothesis: We hypothesized that statin therapy is underutilized in autoimmune patients with lower LDL-C levels despite similar or elevated risk of major adverse cardiovascular events (MACE). Methods: Using the TriNetX platform, which provides real-time, deidentified clinical data from the electronic medical records, we conducted a nationwide retrospective cohort analysis of adult patients (≥18 years) with rheumatoid arthritis or systemic lupus erythematosus, stratified by LDL-C into seven groups: <60, 60–79, 80–99, 100–119, 120–139, 140–159, and ≥160 mg/dL. The MACE outcomes defined as myocardial infarction, stroke, coronary revascularization, or cardiovascular death and the respective statin usage were compared between each group and the ≥160 mg/dL reference group using odds ratios (ORs) with 95% confidence intervals. Results: A total of 50,436 autoimmune patients were included. Among patients with autoimmune disease, statin use was consistently lower across all lower LDL-C strata when compared to those with LDL-C >160 mg/dL. The odds ratios (OR) for statin use ranged from 0.435 (95% CI: 0.405–0.468) in the 100–119 mg/dL group to 0.647 (95% CI: 0.597–0.701) in the 140–159 mg/dL group, indicating a substantial treatment gap. In contrast, the risk of major adverse cardiovascular events (MACE) was significantly higher among autoimmune patients with lower LDL-C levels relative to those with LDL-C >160 mg/dL. The highest odds were observed in the <60 mg/dL group (OR 1.980, 95% CI: 1.669–2.347), followed by the 60–79 mg/dL (OR 1.431, 95% CI: 1.222–1.675) and 80–99 mg/dL (OR 1.198, 95% CI: 1.029–1.393) groups. No statistically significant differences in MACE risk were observed in the higher LDL-C strata. Conclusion: Among autoimmune patients, statin therapy is markedly underprescribed in those with lower LDL-C levels, despite persistent or elevated cardiovascular risk. These findings suggest that current LDL-C–based thresholds may inadequately capture cardiovascular risk in autoimmune populations and support the need for broader risk-based treatment strategies.

Background: Familial hypercholesterolemia (FH) is an autosomal dominant disorder characterized by elevated low density lipoprotein cholesterol (LDL-C) and increased lifetime risk of atherosclerotic cardiovascular disease (ASCVD). While clinical criteria have been established to diagnose FH, genetic testing is now widely available providing an additional avenue for diagnosis. We aimed to describe the yield of genetic testing for FH in children evaluated in a dedicated pediatric cardiology clinic. Methods: We conducted a retrospective cohort study based on the initial evaluation of children in a dyslipidemia clinic between 2017 and 2024. Genetic testing for FH was performed based on assessment of clinical criteria by the attending preventive cardiologist. The cohort was divided into three categories based on genetic testing: genotype positive, genotype negative and phenotype negative (genetic testing not ordered). Patient characteristics and lab parameters (fasting LDL-C and triglycerides, and lipoprotein(a) in mg/dL) were compared between the three groups using descriptive statistics, chi-squared, or Kruskal-Wallis tests. Results: Of 863 pediatric patients evaluated (47% female, mean age 12.6 ± 3.3 years) genetic testing was performed in 176 probands. A pathogenic or likely pathogenic variant was identified in 72 (41%) including 58 LDLR (81%), 12 APOB (17%), 2 PCSK9 (2%) variants. Data are summarized in Table 1. The genotype positive cohort had higher LDL-C compared to the phenotype negative and genotype negative cohorts. Genotype negative patients had higher lipoprotein (a). The phenotype negative group had higher triglyceride levels and BMI. An additional 304 patients (164 adult patients) underwent cascade family screening that yielded 169 patients (87 adult patients) with pathogenic or likely pathogenic variants (137 LDLR [81.5%], 31 APOB [18%], 1 PCSK9 [0.5%]). Conclusion: The diagnostic yield of genetic testing to confirm FH in clinically suspected pediatric patients is high and enables effective cascade screening. Lipoprotein (a) should be considered in all patients, especially those with negative FH genetic testing. Systematic implementation of pediatric lipid screening and targeted genetic testing may enhance early diagnosis of FH in children and family members, enabling timely interventions in this high-risk cohort.

Introduction: Adults with type 2 diabetes (T2D) and overweight or obesity have a high prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD is associated with risk of atherosclerotic cardiovascular disease (ASCVD). However, the relationship between MASLD and risk of heart failure (HF), including HF subtypes, in T2D is less well-established. Methods: We included participants with T2D and overweight/obesity from the Look AHEAD (Action for Health in Diabetes) trial who had available AST, ALT, and GGT data. The probability of MASLD was estimated using the Dallas Steatosis Index and classified as low, intermediate, or high based on probabilities <40%, ≥40 to <70%, and ≥70%, respectively. Adjusted Cox models were created to evaluate the associations of baseline and 1-year longitudinal changes in probability of MASLD with risk of overall HF, HF with preserved and reduced ejection fraction (HFpEF and HFrEF, respectively). Results: The present study included 3,938 participants (mean age 59 years, 59% female, 67% White race). During follow-up, 211 HF events occurred (107 HFpEF, 84 HFrEF). Compared with a low probability of MASLD at baseline, high probability of MASLD at baseline was associated with overall HF risk ( Table ). In HF subtype analyses, higher probability of MASLD was significantly associated with higher risk of HFpEF but not HFrEF. In longitudinal analysis, 1-year increase in the probability of MASLD was significantly associated with higher risk of overall HF with a similar, non-significant pattern of association observed for both HF subtypes. Conclusions: Among adults with T2D and overweight or obesity in the Look AHEAD trial, higher probability of MASLD at baseline and increase in MASLD probability over 1-year follow-up were associated with higher risk of overall HF. Baseline MASLD probability was significantly associated with risk of HFpEF but not HFrEF. These findings underscore the prognostic implications of MASLD and its importance in HF risk assessment in T2D.