Coronary Disease Research Articles

Introduction: Cardiovascular disease (CVD) remains the leading cause of death among women. Premature menopause (onset <40 years) is a recognized risk-enhancing factor for coronary artery disease (CAD). In parallel, CAD polygenic risk scores (PRS) quantify inherited susceptibility to CAD. However, the extent to which genetic risk interacts with reproductive aging in CAD risk among women is underexplored. Aims: The aim of this study is to assess how menopausal timing and CAD genetic risk jointly affect CAD risk among postmenopausal women. Methods: Postmenopausal women in the UK Biobank without prior histories of CAD or surgical premature menopause were included in this analysis. CAD PRS was computed using GPSMult, a previously validated multi-ancestry CAD PRS. Participants were assigned genetic risk levels by PRS quintile into low (Q1), intermediate (Q2–4), or high (Q5) risk. They were then stratified into six groups by menopausal timing (premature or non-premature) and PRS category (low, intermediate, or high). CAD incidence was assessed using age-based cumulative incidence curves with aligned number-at-risk tables. Results: This study included 105,351 postmenopausal women in the UK Biobank, of whom 3216 (3.05%) experienced premature menopause. Over median [interquartile range] follow-up of 6.99 [6.23-7.62] years, 1102 (1.05%) experienced incident CAD. Relative to women without premature menopause, premature menopause was associated with 1.70 (95% CI 1.30-2.23) risk for CAD. Relative to intermediate, high CAD PRS was associated with 2.32 (95% CI 2.05-2.63) risk for CAD. Together, they were associated with additive risk for CAD (p-interaction 0.27). The highest cumulative incidence (2.86%) was observed in women with both premature menopause and high CAD PRS (Fig 1). Those without premature menopause and high CAD PRS had a cumulative incidence (2.09%) exceeding those with premature menopause and intermediate CAD PRS (1.67%). Conclusion: Combining polygenic risk with menopausal timing yields a deeper understanding of CAD susceptibility in women. While premature menopause and elevated genetic risk independently increase CAD incidence, the combination identifies a subgroup of women at particularly elevated risk in both premature and non-premature menopause subgroups. These findings highlight the potential utility of incorporating reproductive history and genetic risk into personalized cardiovascular risk assessment and early prevention strategies.

Background: Coronary artery disease (CAD) polygenic risk score (PRS), low-density lipoprotein cholesterol (LDL-C), lipoprotein(a) [Lp(a)], and high-sensitivity C-reactive protein (hs-CRP) are blood-based biomarkers that predict CAD. We studied their predictive utility for incident CAD across age and sex. Methods: We studied 215,295 UK Biobank participants aged 40-69 years, free from CAD, not on lipid-lowering therapy, and with hs-CRP, Lp(a), LDL-C, and CAD PRS data. Multivariable Cox models were used to estimate age and sex-specific hazard ratios (HR) of individual and additive effects of the biomarkers on incident CAD. We evaluated the risk of CAD by the number of elevated biomarkers. Model performance was evaluated by calculating the Net reclassification index and C-statistics of a four-biomarker-based model compared to Pooled Cohort Equations (PCE). Results: 94,416 males (mean age 55.88±8.19 years, 88.3% white) and 121,279 females (mean age 55.96±7.81 years, 87.8% white) were followed for a median of 12 years. 4,721 (5%) males and 2426 (2%) females developed CAD. Each biomarker was strongly associated with incident CAD, with effect differences by sex and age. Hs-CRP conferred greater HR per SD in female (1.29; 95%CI 1.25-1.34) compared to male (1.25; 95%CI 1.22-1.29) [p-interaction = 0.03] while CAD PRS conferred greater HR per SD in males (1.49; 95% CI 1.45-1.54) than females (1.37; 95% CI 1.31-1.44) [p-interaction=0.0004]. No significant sex differences were observed in the association of LDL-C and Lp(a) with CAD. LDL-C, hs-CRP, and CAD PRS, but not Lp(a), conferred higher HR at a younger age (p<0.0001). The number of elevated biomarkers (none to four) strongly stratified CAD risk – HR of 4.65 (95%CI 3.90-5.54) when all biomarkers are elevated compared to none(Figure). A combined model of all biomarkers with PCE yielded a C-statistic of 0.753, a net reclassification index of 35.4% vs. PCE alone (C-statistic 0.735). Performance was highest among the 40-45 age group and declined with increasing age. Of all biomarkers, CAD PRS exhibited the highest population attributable risk at all ages, which was highest in the 40-49 age group (Male: 27.55%, 95%CI 25.52–29.58; Female: 17.83%, 95%CI 14.27–21.40). Conclusions: CAD PRS, LDL-C, hs-CRP, and Lp(a) show independent and age and sex specific associations with CAD, with higher predictive power in younger ages. A single measurement of all four biomarkers may improve risk prediction in both sexes across middle age.

Background: Coronary Artery Disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known to overestimate future CAD risk in some populations, resulting in unnecessary preventive treatment and reduced cost-effectiveness and safety. Combining machine learning model with the metaheuristic optimisation approach using the PSO algorithm may outperform QRISK3 in predicting CAD. It improves performance by selecting the best-performing subset of features related to clinical outcomes. Research Question: Does the performance of Machine Learning Models Combined with PSO Algorithm for Feature Selection as a Metaheuristic Optimisation Approach in Predicting Coronary Arterial Disease using the UK Biobank dataset outperform the QRISK3 calculator? Aims: This study is to assess the accuracy of QRISK3 in predicting CAD using the UK Biobank dataset. It aims to evaluate the efficacy of machine learning models on the identical dataset for predicting CAD. The work utilises the PSO algorithm for feature selection to identify the optimal subset of features from the UK Biobank dataset. Methods: This study utilises data from the UK Biobank. The dataset consists of 348,015 participants aged 24-84 with no prior diagnosis of CAD. The performance of both QRISK3 and machine learning models was evaluated separately using ROC analysis. Several machine learning models were employed: Logistic Regression, Decision Tree, Random Forest, Naïve Bayes, and Gradient Boosting. The dataset was split into training and test sets with a ratio of 4:1 for the machine learning models. Each model has been developed by adding a PSO algorithm to enhance the model's classification accuracy. Results: Out of the total 348,015 participants, 23,136 individuals (6.64%) were diagnosed with CAD within 10 years following their first visit, while 324,879 individuals (93.4%) did not develop CAD. The AUC value of the QRISK3 prediction is 0.6113, while the combined machine learning models using the PSO algorithm using the gradient boosting model achieve an AUC of 0.7258, showing better performance. Conclusions: This study shows hybrid machine learning models optimised with the PSO algorithm can better predict CAD than QRISK3. These ML models can effectively identify high-risk CAD patients, allowing for more personalised preventative strategies and supporting policymakers in implementing lifestyle change recommendations.

Background: Patients with ischemic heart disease and hypothyroidism face a higher risk of death compared to euthyroid individuals in the U.S. The relationship between Hypothyroidism and ischemic heart disease is notable, as hypothyroidism can exacerbate cardiovascular conditions and increase the risk of ischemic heart disease. Objective: Aim of our study is to evaluate trends and disparities in hypothyroidism and ischemic heart disease mortality among US adults from 1999 to 2020. Methods: Mortality data from CDC WONDER database were analyzed for the period 1999 to 2020 to examine hypothyroidism and ischemic heart disease mortality among U.S. adults aged more than 25 years with ICD-10 codes E03.9 for hypothyroidism and I20-I25 for Ischemic Heart Diseases. We calculated age-adjusted mortality rates (AAMRs) per 100,000 individuals stratified by year, sex, race/ethnicity, urbanization, states and geographic region. Joinpoint regression analysis was performed to calculate annual percent changes (APCs) with 95% confidence intervals (CIs) and p-value<0.01 Results: Between 1999 and 2020, there were a total of 133,413 deaths related to hypothyroidism and ischemic heart disease. AAMR decreased from 3.56 in 1999 to 2.33 in 2018 and then increased to 2.78 in 2020 (2018-2020 APC 11.69 [95% CI, 2.14 to 22.12]). Females had higher AAMR (3.08) compared to males (2.3), and both sexes experienced an initial decline in AAMRs (1999-2018 APC: -3.20 [F], -1.12 [M]) followed by a rise from 2018 to 2020 (APC: 11.28 [F], 11.69 [M]). Among the races in descending order, AAMR was highest in non-Hispanic white individuals(2.94) followed by Hispanics (1.91), Black individuals(1.56) and lastly Asians (1.09). AAMRs in Non metro areas were higher (3.56) than in the Metro areas (2.61). Among census regions, AAMR was highest in the Midwest (3.27) followed by Northeast (2.89), West (2.55) and lastly South (2.51). West Virginia (5.97) and North Dakota (5.69) shows highest AAMRs while, Utah (1.01) and Nevada (1.13) shows the lowest AAMRs. Conclusion: From 1999 to 2018, the Age-Adjusted Mortality Rates (AAMRs) for hypothyroidism and ischemic heart disease in the U.S. generally decreased. However, after 2018, there was a dramatic increase in AAMRs across nearly all demographic groups including sex, race and geographic regions. This rise calls for further investigation and highlights the need for improved access to care, earlier diagnosis, and protective measures for vulnerable populations.

Introduction: Several studies have shown that alterations of gut microbiome are associated with various diseases, such as atherosclerosis. Published literature often compared the gut microbiome of healthy individuals only and those with atherosclerotic coronary artery disease (CAD). Data on the gut microbiome structure of high-risk individuals, who are neither completely healthy nor diseased, were missed and largely unknown. Objective and Hypothesis: This study aimed to investigate human gut microbiome association and atherosclerotic coronary artery disease risk status. We hypothesize that risk factors drive alterations in the gut microbiome, which are associated with the overall risk of developing CAD. We further propose that these changes in the gut microbiome composition occur before significant disease development. Methods: The study recruited 30 patients from a tertiary hospital: at low risk (LR) (n=10), at high risk (HR) ( n =10), and with CAD (CD) ( n =10). The risk of developing CAD was determined by ASCVD Risk Score. Microbial DNA was isolated from stool samples and sequenced using Illumina MiSeq. The taxonomic and functional profiles of the gut microbiome were determined by MetaPhlAn2 and HUMAnN2. Data were analyzed using the Kruskal-Wallis H test and multiple pairwise comparisons by the Mann-Whitney U test. Results: Taxonomic profiling demonstrated that relative abundance of Proteobacteria , Enterobacteriaceae , Bacteroides , and Collinsella were increased in individuals with high-risk status and CAD while, Bifidobacterium and Lactobacillus were higher in the gut of low-risk individuals. The relative abundance of Streptococcaceae and Akkermansia muciniphila were highest in the gut microbiota of high-risk individuals. Gut microbiome diversity was noted to be richer as the risk of CAD becomes higher. Functionally, this study revealed that microbial genes for nitrogen utilization, DNA repair, and DNA conformation change were associated with healthier gut microbiome while, transport of nutrients, harnessing of energy from dietary sources, cell wall component biosynthesis, phosphorylation, signal transduction, and biosynthesis of certain amino acids and phospholipids appeared to be linked with the risk of atherosclerotic CAD. Conclusion: Metagenomic profiling of the gut microbiome across various risk statuses of atherosclerotic CAD identifies distinct taxonomic and functional signatures. Thus, the altered gut microbiome signatures may serve as early predictor for CAD.

Background: Cardiovascular disease is a leading cause of morbidity and mortality worldwide, and coronary artery disease is its most common subtype. While common variants have been extensively studied, much of the genetic architecture of coronary artery disease remains unexplained. Rare coding variants offer an opportunity to discover novel disease-associated genes with direct biological relevance. Research question: Can we identify genes carrying rare loss of function variants associated with coronary artery disease, and what are their broader cardiometabolic effects? Methods: We analyzed sequencing data from three large biobanks including UK Biobank with 59,236 cases and 422,329 controls, All of Us with 48,395 cases and 267,650 controls, and Mass General Brigham Biobank with 10,400 cases and 39,888 controls, totaling over 847,000 individuals. We performed gene-based burden testing aggregating rare loss of function variants to identify genes associated with coronary artery disease. Our mixed effects models were adjusted for age, sex, population structure, and relatedness. Genes reaching statistical significance (P<3.20x10 -6 ) were further evaluated using phenome-wide association of 1587 PheCodes and 7 cardiometabolic traits. Results: Six genes were significantly associated with coronary artery disease: LDLR (OR 4.74 P=1.06 ×10 -19 ), TTN (OR 1.49, P=8.59x10 -22 ), PKD1 (OR 1.67, P=1.25×10 -6 ), ADGRL1 (OR 4.2, P=7.24x10 -7 ), RMC1 (OR 2.84, P=1.58×10 -6 ), and RBM12 (OR 3.46, P=2.63×10 -6 ). ADGRL1, RMC1, and RBM12 showed significant associations despite no prior implication in coronary or cardiometabolic traits, in contrast to LDLR , TTN and PKD1 , which have established roles. Phenome wide analysis revealed links between the novel genes and conditions such as hypertension, obesity, diabetes, and arrhythmias. Risk factor analyses showed that ADGRL1 and RMC1 were associated with higher body mass index and triglycerides and lower high density lipoprotein cholesterol. RBM12 was additionally associated with elevated low density lipoprotein cholesterol. Conclusions and Relevance: We identified five novel genes associated with coronary artery disease through exome wide rare variant analysis. Follow up phenome wide and risk factor analyses suggest functional relevance, particularly for ADGRL1 , RMC1 , and RBM12 , offering new biological insights into coronary artery disease.

Introduction: Oxidized low density lipoproteins (OxLDL) present in atherosclerotic plaques. Epidemiological studies demonstrate that IgM antibody against malondialdehyde LDL (MDA-LDL), the major subtype of OxLDL, is inversely associated with severity of coronary artery disease (CAD), heart attack and death. In human, circulating marginal zone B cells (MZB) were recently identified as producers of these atheroprotective IgM to MDA-LDL. The frequency of circulating MZB cells correlates with CAD severity. We further discover that MZB cells from subjects with high CAD burden produce less atheroprotective IgM to MDA-LDL. This study explores phenotypic changes in MZB cells in relation to CAD severity and investigates underlying mechanisms Hypothesis: The chemokine receptor CCR6 regulates the production of atheroprotective IgM against MDA-LDL by MZB cells and is downregulated in subjects with severe CAD. Methods: Humanized mice were adoptively transferred with sort-purified human MZB cells from low and high CAD severity subjects. Single cell multi-omics (CITE-Seq) was performed on B cells from both low and high CAD groups. In-vitro migration study, imaging-flow cytometry, as well as CRISPR-mediated gene knock down were utilized to further investigate mechanisms. Results: Humanized mice receiving MZB cells from low-CAD subjects (n = 7) produced higher levels of atheroprotective IgM than those receiving cells from high-CAD subjects (n = 6). Single-cell analysis of B cells from low (n = 30) and high (n = 30) CAD subjects revealed higher CCR6 expression in MZB cells from the low-CAD group. In vitro activation of MZB cells with MDA antigen led to downregulation of both CD24 and CCR6. Imaging flow cytometry and proximity ligation assays suggested co-localization of CD24 and CCR6. Blocking CD24 with a monoclonal antibody reduced surface CCR6 expression and impaired CCL20-induced migration. Finally, CCR6-knockdown MZB cells (n = 4) exhibited reduced splenic migration and IgM production in humanized mice compared to wild-type controls (n = 6). Conclusion: MZB cells from individuals with severe CAD exhibit reduced CCR6 expression and impaired atheroprotective IgM production. CCR6 is critical for splenic migration of human MZB cells and subsequent IgM production.

Background: While polygenic risk scores (PRS) and social determinants of health (SDOH) are established predictors of coronary artery disease (CAD), interactions between PRS and individual SDOH remain largely underexplored. Research Question: Do income, education, material deprivation, and social isolation modify the effect of PRS on incident CAD? Methods: We studied 409,877 participants aged 40-69 years from the UK Biobank free from CAD at baseline and with available genotyping and SDOH data. A CAD PRS consisting of 1,296,172 variants (GPSmult, PGS PGP000466) was calculated. Four SDOH were examined: income (defined as self-reported household income before tax), education (highest educational qualification), area-level material deprivation (quantified through the Townsend Deprivation Index), and social isolation (defined as living alone). Cox proportional hazards models were used to examine the associations between each SDOH and incident CAD. Interactions between PRS and each SDOH were assessed to understand whether social factors modify the effect of PRS on CAD risk. Results: Among 409,877 participants (mean age 56.0 ± 8.1 years, 53.5% female), 12,244 incident CAD events occurred over a median follow-up time of 13.7 years. Each standard deviation (SD) increase in PRS was associated with a 1.88-fold increase in incident CAD risk (95% CI: 1.84, 1.91). Lower income (Hazard Ratio (HR) 1.48, 95% CI: 1.33, 1.64), lower educational attainment (HR 1.34, 95% CI: 1.27, 1.41), and higher TDI (HR 1.18, 95% CI: 1.11, 1.25) were all independently associated with greater incident CAD risk. Living alone was not significantly associated with CAD risk (HR 1.04, 95% CI: 0.99, 1.09). The absolute CAD risk difference between the high and low income groups was 2.62% in the highest PRS decile, compared to only 0.77% in the lowest decile. Similarly, the absolute risk difference between college graduates and those without a high school diploma decreased from 1.40% in the highest PRS decile to 0.68% in the lowest. ( Figure ). Multiplicative interactions between PRS and both income ( P interaction = 4.9×10 -5 ) and education ( P interaction = 6.1×10 -6 ) were statistically significant. Conclusion: These findings suggest a complex interaction between genetic risk and SDOH in relation to CAD risk, particularly for income and education. Integrating these insights into predictive models could enable more accurate risk stratification and inform targeted interventions for those at greatest risk.

Introduction: Accurate assessment of coronary artery disease (CAD) before Transcatheter Aortic Valve Replacement (TAVR) is crucial for optimal outcomes. Al- enhanced coronary a andiocraphy (CCA shows promise for CAD detection, but its vertormance in TAVR patients lacks systemaic eva uation. his reviev analyzes Al-based CCTA models for pre-TAVR CAD detection focusing on both anatomic and physiologic criteria. Methods: We searched Pubiied and Embase tor studies on Al-based CAD detection via CCIA in pre-TAVR patients. Five studies met inclusion criteria, each using different Al models. Key metrics analyzed included sensitivity, specificity, accuracy, negative predictive value (NPV), positive predictive value (PPV), and Net reclassification index (NRI) for CAD+ve and CAD-ve populations. Results: The studies showed significant variability in Al model performance for CAD detection. Sensitivity ranged from 94.9% to 100%, specificity from 40.0% to 100%, and accuracy from 60.0% to 91.9%. CAD+ve NRI: -0.28 to 0.66 (e.g., Brandt et al. 2022 showed strong positive reclassification). CAD-Ve NAl: 005 to 0.13 (most models showed postive reclassication) Models integrating anatomic and physiological criteria (e.g., Brendel et al. 2024 with Al-based CAD-RADS + Al-derived FFR) achieved superior accuracy (96.8% sensitivity, 100% specificity, 91.9% accuracy, CAD+ve NRI 0.11, CAD-ve NRI 0.07). In contrast, purely anatomic models (e.g., Gohman et al. 2022) had lower performance (52.0% specificity, 67.3% accuracy, CAD +ve NRI -0.05, CAD-ve NRI 0.13). Conclusions: Al-based CCTA models show high sensitivity for CAD detection in pre-TAVR assessment, with varying specificity and accuracy. Combining anatomic and physiological parameters improves diagnostic accuracy and NRI. This review underscores the potential of integrated Al models for more precise pre-TAVR CAD screening, with further research needed for clinical validation.

Background: The lean body mass index (LBMI) is determined by dividing an individual’s lean body mass by the square of their height. It is closely linked to skeletal muscle mass and serves as a key indicator of frailty and sarcopenia. Although abdominal fat distribution (AFD) typically assessed using the ratio of the visceral fat area (VFA) to the subcutaneous fat area (SFA), i.e., the V/S ratio, has been associated with an increased coronary artery disease (CAD) risk, limited studies have explored the combined impact of AFD and overall physique on CAD. A computed tomography (CT)-derived SYNTAX score (CT-SX score) has been proposed as a feasible method for assessing CAD severity based on coronary CT angiography (CCTA). Using the CT-SX score, we aimed to evaluate the impact of AFD based on the V/S ratio and physique classified by LBMI on CAD complexity. Methods: CCTA was performed on 931 consecutive patients with suspected CAD. Additionally, to quantify VFA and SFA, a plain abdomen CT scan was conducted. To assess the AFD, the V/S ratios were also calculated. CAD severity was ascertained using CCTA. A stenosis of ≥50% diameter was considered significant. The CT-SX score was calculated for patients with ≥1 significant stenosis. Finally, the patients were divided into low and high LBMI groups based on their median value (males: 18.8 kg/m 2 , females: 16.0 kg/m 2 ). Results: Of the 931 patients enrolled, 308 (33.1%) exhibited ≥1 significant stenosis. A positive correlation was noted between the V/S ratio and the CT-SX score irrespective of the LBMI. Although VFA was positively correlated with the CT-SX score in the low LBMI group, SFA was negatively correlated with the CT-SX score in the high LBMI group. Multivariate analysis adjusted for traditional coronary risks yielded comparable results (Figure). Conclusions: Although AFD, as indicated by the V/S ratio, appears to be an effective indicator of CAD severity irrespective of the physique and frailty of patients based on LBMI, the factors contributing to an elevated V/S ratio may vary depending on the physique. Given that body composition varies individually with factors such as aging, lifestyle, sex, racial background, and physical constitution, physique-based personalized interventions—rather than standardized protocols—may more effectively mitigate CAD progression.

Introduction: The hypertensive disorders of pregnancy (HDPs), i.e., preeclampsia and gestational hypertension, are characterized by endothelial dysfunction in pregnancy and are epidemiologically and genetically associated with risk for coronary artery disease (CAD). A recent study suggested that endothelial cell (EC)-acting CAD risk variants may identify individuals who benefit from more intensive lipid-lowering treatment. This study evaluated whether the same EC CAD genetic risk score is also associated with HDPs using comprehensive statistical genetic approaches. Hypothesis: EC-acting risk variants are more strongly associated with HDPs than non-EC-acting risk variants. Methods: We examined 35 previously identified EC-acting and 205 non-EC-acting risk variants associated with CAD. First, using the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b), a prospective, multicenter U.S. pregnancy cohort, we calculated polygenic scores (PRS) comprised of either EC-acting or non-EC-acting CAD risk variants. Scores were adjusted for population structure with ten principal components, then associated with HDPs using logistic regression models adjusted for age. Second, we tested the genetic association of EC-acting and non-EC-acting CAD variants with preeclampsia and gestational hypertension using two-sample Mendelian randomization (MR). Results: Among 5,638 unrelated nuMoM2b participants of European ancestry, we observed higher incidence of HDPs in participants with higher EC-acting PRS ( Figure 1 ). Each standard deviation of higher EC-acting PRS was associated with 1.10-fold increased odds of HDP (95% CI: 1.02–1.19; P=0.01). In contrast, the non-EC-acting PRS was not significantly associated with HDP risk (OR: 1.04, 95% CI: 0.97–1.12; P=0.25). In two-sample MR, EC-acting variants were strongly associated with both preeclampsia (P <0.001) and gestational hypertension (P = 0.009); genetic associations were stronger for EC-acting vs. non-EC-acting CAD risk variants for both outcomes (P heterogeneity <0.05, Figure 2 ). Conclusion: Using PRS and two-sample MR approaches, we observed enrichment for EC-acting genetic risk variants in women with HDPs. These findings support a shared genetic architecture between HDPs and CAD through endothelial dysfunction and suggest that women with a history of HDPs may benefit from more intensive lipid control for cardiovascular disease prevention.

Background: Ambient air pollution is associated with ischemic heart disease (IHD), but the metabolic mechanisms mediating this relationship remain unclear. Methods: In 218,047 UK Biobank participants without baseline IHD, we identified plasma metabolic signatures associated with air pollution (PM 2.5 , PM 10 , NO 2 , NO x ) using elastic net regression. Cox proportional hazards models assessed relationships between air pollution, metabolic signatures, and incident IHD. Mediation analyses quantified the contribution of metabolic signatures to pollution-IHD associations. Results: We identified 41 metabolites significantly associated with air pollution, primarily comprising lipoprotein lipid concentrations, fatty acids, and amino acids. During follow-up, 18,911 participants developed IHD. High metabolic signature scores were associated with 26% increased IHD risk compared to low scores (HR=1.26, 95% CI: 1.20-1.32). The metabolic signature mediated 19.49% of the total effect of air pollution on IHD risk, with stronger mediation for PM 2.5 (21.24%). Associations were more pronounced in older individuals (≥65 years) and those with lower genetic susceptibility to IHD. Conclusions: Air pollution exposure induces specific plasma metabolic alterations that independently predict IHD risk and substantially mediate pollution-IHD associations. These findings provide novel insights into biological pathways linking environmental exposures to cardiovascular pathology and identify vulnerable subpopulations.

Introduction: Coronary artery disease (CAD) is the leading cause of death worldwide. Medication management is the priority for its secondary prevention. However, medication adherence was sub-optimal among older adults with CAD, who had greater challenges than younger adults, due to more concerns about the side-effects, forgetfulness and polypharmacy. Comprehensive and rigorously designed educational programmes are needed to improve their medication adherence. Aim: To evaluate the effects of a Health Belief Model based educational programme in improving medication adherence and other related outcomes among older adults with CAD. Methods: This is a two-arm, single-blind, pilot randomised controlled trial, conducted from March to May 2025 in the cardiology department of a tertiary hospital, adopting convenience sampling. The intervention group received a Health Belief Model based educational programme and usual care, and the control group received usual care only. Feasibility (recruitment, completion, attrition rate) and acceptability (semi-structured interviews and satisfaction scales) were assessed. Preliminary effects were measured at immediate post-intervention in terms of the level of medication adherence, perceived benefits and concerns about medications, medication self-management capacity, self-efficacy of medication taking, and health-related quality of life. Between group comparisons were analysed by Mann-Whitney U test, with Hedges’ g effect size calculated by changing scores. Qualitative data were analysed via content analysis. Results: A total of 40 older adults with CAD were recruited, with a 44.9% recruitment and 2.5% attrition rate. In the intervention group, 85% participants attended all sessions. Three categories emerged in the interviews, including perceived benefits and advantages of the intervention, and suggestions for improvement. Significant improvements in the intervention group were observed in medication adherence and perceptions about the benefits of medications (Hedge’s g=0.79 and 1.19), comparing with the control group. The intervention group demonstrated greater improvement in medication self-management capacity and self-efficacy (Hedge’s g=0.62 and 0.46), and greater reduction in the concerns about medications (Hedge’s g=-0.56). Conclusion: The educational programme was feasible and acceptable for older adults with CAD. A large scale randomised controlled trial will be conducted to examine the longer-term effect of the programme.

Background: Despite optimization of coronary artery disease (CAD) related factors with lifestyle modifications and medications, complications of CAD are the leading cause of death worldwide among adults. The objective of this study was to characterize the proteomic profile and enriched pathways associated with recurrent CAD events to better understand drivers and mechanisms underlying residual CAD risk. Methods: This retrospective analysis included 1,256 participants from the prospective UK Biobank (UKB) with baseline Olink plasma proteomic measures and CAD at enrollment. Cox proportional hazards regression modeled the association between proteins measured and recurrent CAD events in follow-up. Results: Participants had a mean age of 62.46 years (SD 5.86) at enrollment; 236 (18.79%) were female, and 817 (65.05%) had recurrent CAD over 11.40 [interquartile range 8.00-14.69] years of follow-up. Among the 1,463 proteins tested, 102 proteins at experiment-wide significance (Bonferroni p-value < 3.42×10 -5 ) were independently associated with recurrent CAD events. Molecular functions were significantly enriched for tumor necrosis factor receptor (TNFR) activity by 100-fold (p-value = 6.37×10 -10 ) (Figure 1). Of the 8 proteins related to TNF annotated by the Gene Ontology database, TNF-alpha had a risk estimate of 1.36 (95% CI 1.17-1.57, p-value = 6.38×10 -5 ), a superfamily of TNFR1 (TNFRSF1A) had a risk estimate of 1.73 (95% CI 1.43-2.09, p-value = 1.23×10 -8 ), and a superfamily of TNFR2 (TNFRSF1B) had a risk estimate of 1.27 (95% CI 1.13-1.44, p-value = 9.15×10 -5 ) for recurrent CAD (Figure 2). When stratified by clinical subgroups, there was a significant attenuation of the risk estimate for recurrent CAD in older compared to younger patients for TNF-alpha (1.25 vs 1.74, p-interaction = 0.027) and TNFR2 (1.19 vs 1.64, p-interaction = 0.030). There was also a higher risk of recurrent CAD in males compared to females for TNF-alpha (1.78 vs 1.17, p-interaction = 0.010) and TNFR2 (1.71 vs 1.07, p-interaction = 0.002). Conclusion: Recurrent CAD event rates are high and associated with several plasma proteins. Pathway enrichment analyses prioritized TNFR-related proteins. Further research should explore their role in reducing CAD risk.

Background: Clonal hematopoiesis of indeterminate potential (CHIP) is the aging-related clonal expansion of hematopoietic cells with preleukemic mutations. CHIP is an independent predictor of coronary artery disease (CAD), chronic kidney disease (CKD), arrhythmias such as atrial fibrillation, and heart failure (HF). However, previous HF-focused analyses have lacked sufficient power to examine less common CHIP driver mutations and have not investigated mediators of the association between CHIP and HF. Hypotheses: Key gene-specific CHIP subtypes independently associate with incident HF. Coincident CAD, atrial fibrillation, and CKD collectively mediate only a minority of this association. Methods: UK Biobank participants without prevalent HF or hematologic malignancy and with whole exome sequencing of blood DNA were included. The primary outcome was incident HF ascertained by linkage to inpatient records, with follow-up censored in March 2020. Cox models tested the association of composite CHIP and of key specific variant CHIP subtypes with HF, adjusted for age, sex, race, education, income, BMI, systolic blood pressure, total cholesterol, HDL cholesterol, use of anti-hypertensive and lipid-lowering therapies, smoking, prevalent diabetes, CAD, stroke, and cancer. Mediation analyses examined CAD, atrial fibrillation, and CKD as mediators. Results: Among 362,058 participants, the mean (SD) age was 56.5 (8.1) years, 12,273 (3.4%) had CHIP at baseline, and 8548 (2.4%) developed incident HF over median 11.0 (IQR 10.3-11.7) years of follow-up. Participants with CHIP were older (60.7 [6.7] vs. 56.3 [8.1] years) and more likely to have prevalent CAD (5.3 vs. 3.8%), CKD (0.4 vs. 0.3%), and atrial fibrillation (1.9 vs. 1.5%). Incidence of HF was higher in those with CHIP, irrespective of prevalent CAD ( Figure 1 ). After multivariable adjustment, CHIP was independently associated with higher risk of HF, driven by associations with non- DNMT3A CHIP subtypes (aHR 1.44 [95% CI 1.27-1.63]; P <0.0001). By contrast, there was no association with DNMT3A CHIP ( Table 1 ). In mediation analyses, CAD, atrial fibrillation, CKD, individually or combined, modestly but significantly mediated the association between non- DNMT3A CHIP and HF, accounting for 10.2%, 15.7%, 4.9%, and 27.8% of the effect, respectively ( Figure 2 ). Conclusion: Non- DNMT3A CHIP is independently associated with incident HF. CHIP-associated comorbidities likely explain only a minority of this relationship.

Introduction: Peripheral artery disease (PAD) is associated with high morbidity and mortality, yet palliative care (PC), a supportive, team-based approach integrated remains underutilized. This review contrasted PC components, patient-level and program outcomes, and patient-reported outcomes across heart failure (HF), coronary artery disease (CAD), and peripheral artery disease (PAD). Methods: We searched PubMed and Cochrane databases for English-language studies published from January 1, 2014, to December 19, 2024. Studies included systematic reviews and original investigations of PC interventions in HF, CAD, and PAD. The ROBIS tool was used for quality appraisal. Data were synthesized across seven domains: (1) symptom management, (2) advance care planning (ACP), (3) psychosocial/spiritual support, (4) quality-of-life measurement (QoL), (5) interdisciplinary team integration, (6) referral timing and triggers, and (7) sustainability of care. Results: Fifty-six studies were included (HF: n=48; PAD: n=5; CAD: n=2; HF+CAD: n=1), including randomized trials, meta-analyses, and observational studies. HF studies focused on patients with New York Heart Association (NYHA) Class II–IV and high comorbidity burden, across in- and outpatient settings. PAD studies included patients with chronic limb-threatening ischemia; CAD populations were post-MI or post-revascularization. HF programs used validated QoL tools (e.g., ESAS, KCCQ, EQ-5D) to guide symptom management and referrals. ACP was a central feature of HF interventions, contributing to improved documentation, reduced hospital utilization, and care alignment. In contrast, PAD studies mostly lacked standardized assessment tools and relied on clinical outcomes (e.g., readmissions, complications, mortality). ACP was limited to end-of-life contexts without continuity. Psychosocial and spiritual support services were rarely addressed. CAD studies utilized general and disease-specific QoL instruments (SF-36, Seattle Angina Questionnaire), and focused on education and rehabilitation with minimal PC integration. ACP was rarely emphasized, psychosocial/spiritual support was excluded, and PC referrals for CAD patients were late and lacked continuity. Conclusion: HF programs provide a transferable template for PAD, based on an early, structured and multidisciplinary PC. This could lead to a PAD-specific care model that integrates best practices from HF and that helps address underuse in a vulnerable and overlooked population.

Introduction: Advances in coronary computed tomography angiography (CCTA) have enhanced the possibilities for assessment and quantification of coronary artery disease (CAD). Using data from the CCTA arm of the PRECISE randomized trial (non-acute chest pain needing testing), we examined the extent and diffuseness of coronary plaque burden using novel CCTA-derived metrics. Methods: All stable, symptomatic patients from the PRECISE randomized trial who underwent CCTA for evaluation of suspected CAD and had ≥50% diameter stenosis in at least one vessel were included, N=196. 3-vessel CAD patterns were assessed using FFR CT and AI-enabled quantitative plaque analysis (Heartflow). Nadir FFR CT was defined as total drop in FFR CT across the entire vessel. The FFR CT drop over a stenosis was termed stenosis FFR CT (sFFR CT ). The decrement in FFR CT due to diffuse disease was termed diffuse FFR CT (dFFR CT ) and defined as 1 – nadir FFR CT – sFFR CT . Patients were stratified into four groups (NoHEM, FOC, DIF and FOC+DIF) using cohort medians of 0.10 (sFFR CT ) and 0.13 (dFFR CT ) (Table). The Seattle Angina Questionnaire (SAQ) was used to assess symptoms. Results: No hemodynamic disease (NoHEM), FOC, DIF and FOC+DIF were present in 21.5%, 28.6%, 29.6% and 20.4% of patients respectively. Clinical characteristics were similar between groups (Table). FOC and DIF+FOC had the lowest FFR CT nadir values as well as the highest stenosis FFR CT (both p<0.001). Per-patient total plaque volume (TPV, mm 3 ) was higher in FOC and DIF+FOC compared to NoHEM and DIF (p=0.008; Figure). Per-patient noncalcified plaque volume (NCPV, mm 3 ) followed a similar pattern (p=0.004), although % NCPV did not differ (0.86). Per-patient calcified plaque volume (CPV, mm 3 ) and %CPV did not differ between groups (p=0.12 and 0.86). Conclusion: CCTA allows for a more refined CAD plaque burden categorization by separating the FFR CT losses due to focal stenoses and diffuse CAD. Patients with focal or mixed (focal and diffuse) CAD phenotypes were not distinguishable by clinical characteristics, risk burden or angina severity. However, they exhibited higher plaque volumes, particularly noncalcified plaque, than those with no NoHEM or only diffuse disease. Further studies are necessary to examine the prognostic and therapeutic implications of these findings.

Background: Epicardial fat thickness (EFT) has emerged as a potential marker for coronary artery disease (CAD) due to its proximity to coronary vessels and its pro-inflammatory properties. However, its role as a predictor of CAD severity in diabetic patients remains underexplored. This study aimed to evaluate the association between EFT and CAD in a large cohort of type 2 diabetic patients. Methods: This retrospective study was conducted at the Abbas Institute of Medical Sciences (AIMS) between January 2020 and March 2025. A total of 2,340 diabetic patients (mean age: 58.3 ± 9.6 years) were included. Clinical data were collected, and EFT was measured using echocardiography. The presence and severity of CAD were determined through coronary angiography. Data were analyzed using logistic regression, and associations were assessed with 95% confidence intervals (CI) and p-values. Results: Elevated EFT (≥5 mm) was present in 1,281 participants (54.7%). CAD was observed in 1,121 patients (47.9%), with those having elevated EFT showing significantly higher rates of CAD (65.7% vs. 26.3%, p < 0.001). Logistic regression revealed that EFT ≥5 mm was associated with 5.38-fold increased odds of CAD (95% CI: 4.59–6.30, p < 0.001). Additionally, EFT correlated with CAD severity, with a higher prevalence of multi-vessel disease observed in patients with elevated EFT. Conclusions: Elevated EFT is strongly associated with the presence and severity of CAD in diabetic patients, suggesting that EFT may serve as an effective non-invasive marker for CAD risk stratification. Incorporating EFT into routine clinical practice may enhance early detection and management of cardiovascular risk in this high-risk population.

Cardiovascular disease (CVD) is highly prevalent and remains a cause of great morbi-mortality worldwide. Growing evidence suggests clonal hematopoiesis of indeterminate potential (CHIP) as an independent cardiovascular risk factor worsening overall survival (OS). However, actual data either comes from large population databases with heterogenous and/or poorly defined CVD or from smaller better-defined populations but with limited follow-up. We aimed to thoroughly characterize the extent and severity of coronary artery disease (CAD) and OS in CHIP-positive patients using the COROL (COROonary disease cLinico-biological determinants study) cohort which included patients undergoing coronarography and for which we now have up to 24 years of follow-up. We also evaluated if OS in CHIP-positive patients was similar depending on CAD treatment. We retrospectively analyzed data from the 2050 COROL patients included between 2000-2001 at CHU de Lille in France (mean age (standard deviation): 61 (12) years, men: 76.2%). Our primary focus was CAD lesions (% of stenosis) by coronarography, treatment (medical, angioplasty or surgery), CHIP (variant allele frequency (VAF) ≥2%, determined using a 70-gene NGS panel) and OS. Patients with no significant coronary lesion (<50%) served as controls. Statistical analysis for preliminary results included log-rank and Student analysis. Of the 1976/2050 patients that met inclusion criteria, CHIP was found in 28.5%. DNMT3a , TET2 and ASXL1 accounted for two-third of the mutated genes. Preliminary results in 1466/1976 patients showed reduced median OS in CHIP-negative patients with ≥50% lesions compared to those with <50% lesions (p=0.0007). Median OS was worse in both CHIP-positive groups with no difference according to CAD status (table 1). Moreover, no CAD treatment could reverse CHIP effect (figure 1). Our study is the first to provide detailed information on CAD extent and treatment in CHIP-positive patients while offering 20+ years of follow-up. It shows an independent negative effect of CHIP on OS, which raises concerns about CHIP identification and CAD patients management.

Background: Atherosclerotic cardiovascular disease is a leading cause of death globally, accounting for approximately a third of all deaths. Atherosclerosis is a systemic and progressive condition and contributes to ischemic heart disease, stroke, and peripheral artery disease. REACT (Early Cure for Atherosclerosis) is a large international initiative designed to improve the understanding, detection, and early treatment of subclinical atherosclerosis. Here, we aim to estimate the burden of clinical atherosclerotic disease in individuals aged 18–70 years. Research Questions: What is the frequency of clinical atherosclerosis throughout all vascular territories. Methods: A representative sample of Danish individuals aged 18-70 years was selected in December 2024 based on socioeconomic data through national registries. We defined clinical atherosclerosis using diagnosis ICD10 diagnostic codes and procedure codes for ischemic heart disease, stroke, and peripheral artery disease. We stratified the prevalence of atherosclerosis by age and sex and vascular territories. Risks were compared using risk ratios (RR) with 95% confidence intervals (95% CI). Results: We included data from 160,000 individuals with an equal sex distribution. The median age was 46 years (IQR 33-58 years). There were 9,825 individuals (6.1%) with a history of atherosclerotic disease. Figure 1 shows the prevalence of any clinical atherosclerosis and ischemic heart disease stratified by age and sex. The prevalence of any atherosclerotic disease increased from 0.3% in the youngest age-strata (18–29 years) to 17.3% in the oldest age-strata (60–70 years) and was significantly higher in all age strata in males, RR 1.6 (95% CI 1.5-1.6, p<0.001). Ischemic heart disease was the most frequent atherosclerotic disease (n=5,665, 3.5% of the entire sample), followed by stroke (n=3,567, 2.2%), and peripheral artery disease (n=1,581, 1.0%). The mean age was similar for individuals with a history of ischemic heart disease and peripheral artery disease (60.7 years vs 60.8, p=0.75) but was lower for stroke (59.1 years, p<0.001 for both comparisons). Conclusion: Among adults aged 18–70 years, clinical atherosclerotic disease was present in 6% of the population, with parallel increases in the three major vascular territories with increasing age, quantitatively dominated by coronary artery disease, and with male preponderance.