Coronary Heart Disease Risk Research Articles

Associations of TyG index with coronary heart disease risk and coronary artery sclerosis severity in OSA

BackgroundInsulin resistance (IR) is involved in the pathogenesis and progression of obstructive sleep apnea (OSA) and coronary heart disease (CHD). The triglyceride glucose(TyG) index, an alternative indicator of IR with high reliability, is linked to CHD development and severity. However, the association of TyG index with CHD in OSA cases remains undefined. This study explores the association of TyG index with CHD risk and coronary artery sclerosis severity in the OSA population.MethodsOSA cases with suspected CHD, enrolled at the Department of Hypertension, The First Affiliated Hospital of Xinjiang Medical University between February 2020 and June 2024, were assigned to the OSA and OSA + CHD groups, followed by TyG index assessment. The t-test, Mann-Whitney U-test and one-way analysis of variance were utilized to compare continuous data, while comparisons of categorical data utilized the chi-square test or Fisher’s exact test. Logistic regression analysis was conducted to determine factors independently predicting OSA with CHD and Gensini scores. Restrictive cubic spline (RCS) was used to assess potential non-linear associations of TyG index with CHD risk and Gensini score in OSA patients.ResultsTotally 1059 OSA patients were included, with 514 diagnosed with CHD (48.54%). Multivariable logistic regression analysis upon adjustment for age, gender, hypertension, diabetes, and smoking history revealed TyG index as a risk factor for CHD in OSA cases. CHD risk in the high-TyG index group was 1.977 fold higher versus the low-TyG index group (OR = 1.977, 95% CI 1.424-2.800, P < 0.001). In addition, TyG index had a linear relationship with CHD (P for nonlinearity = 0.0709). In moderate to severe OSA cases, the high-TyG index group had a significantly higher CHD risk (OR = 2.430, 95% CI 1.601–3.690, P < 0.001). Gensini score and TyG index (P for non-linearity = 0.0033) had a non-linear relationship, while high TyG index was a risk factor for high Gensini score.ConclusionTyG index is a risk factor for CHD in OSA cases and reflects the severity of coronary atherosclerosis. TyG, a surrogate indicator for IR evaluation, may help predict CHD in OSA cases, especially in moderate to severe OSA.

Biomarkers of cellular senescence and major health outcomes in older adults.

The geroscience hypothesis proposes that underlying biological processes, such as the accumulation of senescent cells, have deleterious effects on multiple tissues and increase the risk of many chronic conditions with aging. Senescent cells produce heterogenous biomarkers, also called senescence-associated secretory phenotype (SASP). Circulating concentrations of senescence biomarkers may reflect an underlying burden of senescent cells in various tissues. Plasma levels of these proteins have been associated with increased mortality and poorer physical function. The associations of them with the incidence of major age-related conditions including heart failure, cardiovascular disease, stroke, and dementia, have not been studied. We measured 35 senescence biomarkers in baseline plasma samples from 1678 participants aged 70-79years old in the longitudinal Health ABC cohort study. Clinical outcomes were ascertained and validated over an average 11.5year follow-up. In models adjusted for age, sex, and race, higher levels of most of senescence biomarkers were associated with increased risk of all-cause mortality, mobility limitation, and heart failure. Several were also associated with an increased risk of coronary heart disease, stroke, and dementia. Very few were associated with the risk of cancer. Proteins that were selected by Lasso regression for each outcome that commonly included GDF15 and IL6, significantly improved the prediction of mortality, mobility limitation, and heart failure compared with age, sex, and race alone. These results indicate that levels of senescence biomarkers predict an increased risk of several age-related clinical outcomes and may identify individuals most likely to benefit from senotherapeutics.

Urban Built Environment as a Predictor for Coronary Heart Disease—A Cross-Sectional Study Based on Machine Learning

The relationship between coronary heart disease (CHD) and complex urban built environments remains a subject of considerable uncertainty. The development of predictive models via machine learning to explore the underlying mechanisms of this association, as well as the formulation of intervention policies and planning strategies, has emerged as a pivotal area of research. A cross-sectional dataset of hospital admissions for CHD over the course of a year from a hospital in Dalian City, China, was assembled and matched with multi-source built environment data via residential addresses. This study evaluates five machine learning models, including decision tree (DT), random forest (RF), eXtreme gradient boosting (XGBoost), multi-layer perceptron (MLP), and support vector machine (SVM), and compares them with multiple linear regression models. The results show that DT, RF, and XGBoost exhibit superior predictive capabilities, with all R2 values exceeding 0.70. The DT model performed the best, with an R2 value of 0.818, and the best performance was based on metrics such as MAE and MSE. Additionally, using explainable AI techniques, this study reveals the contribution of different built environment factors to CHD and identifies the significant factors influencing CHD in cold regions, ranked as age, Digital Elevation Model (DEM), house price (HP), sky view factor (SVF), and interaction factors. Stratified analyses by age and gender show variations in the influencing factors for different groups: for those under 60 years old, Road Density is the most influential factor; for the 61–70 age group, house price is the top factor; for the 71–80 age group, age is the most significant factor; for those over 81 years old, building height is the leading factor; in males, GDP is the most influential factor; and in females, age is the most influential factor. This study explores the feasibility and performance of machine learning in predicting CHD risk in the built environment of cold regions and provides a comprehensive methodology and workflow for predicting cardiovascular disease risk based on refined neighborhood-level built environment factors, offering scientific support for the construction of sustainable healthy cities.

Cardiorespiratory Fitness as a Risk Factor for Requiring Coronary Artery Bypass Grafting in a Veteran Population

Background: Regular physical activity is widely recommended to reduce the risk of coronary heart disease. Coronary artery bypass grafting is the gold standard treatment for severe multi-vessel coronary artery disease that has failed medical management. However, there is limited information on the relationship between cardiorespiratory fitness (CRF) and the likelihood of undergoing coronary bypass. This study aims to determine the association between CRF and the likelihood of requiring future coronary artery bypass in a US Veteran population. Methods: From a cohort of 740,075 United States Veterans who completed an exercise treadmill test between October 1, 1999, and September 3, 2020, with no evidence of cardiovascular disease, we identified 14,860 individuals who underwent a bypass more than six months after their fitness assessment. To assess the association between CRF and the risk of coronary bypass, we divided participants into CRF quintiles based on peak workload achieved: Least-fit: 4.7 ± 1.5 metabolic equivalents (METs) (n = 141,893); Low-fit: 7.2 ± 0.9 METs (n = 181,550), Moderate-fit: 8.5 ± 1.3 METs (n = 142,895), Fit: 10.5 ± 1.0 METs (n = 192,061) and High-fit: 13.5 ± 1.8 METs (n = 81,676). Cox proportional hazard models were used to calculate the risk of bypass across fitness categories. The models were adjusted for age, body mass index, race, cardiovascular medications, and cardiovascular risk factors. Results: The association between cardiorespiratory fitness and coronary artery bypass was inverse, independent, and graded. For every 1-MET increase in exercise capacity the risk of surgery was 10% lower (HR = 0.90; 95% CI: 0.89–0.91; p &lt; 0.001). Comparisons across CRF quintiles revealed that the risk for surgery was lower by 29% in the Low-fit group (HR = 0.71; 95% CI: 0.68–0.74; p &lt; 0.001), 37% in the Moderate-fit group (HR = 0.63; 95% CI: 0.60–0.66; p &lt; 0.001), 47% in the Fit group (HR = 0.53; 95% CI: 0.54–0.60; p &lt; 0.001), and 53% in the High-fit group (HR = 0.47; 95% CI: 0.43–0.50; p &lt; 0.001). Conclusions: Our findings support a graded, inverse relationship between CRF and the likelihood of undergoing future coronary bypass surgery. A moderate CRF level, achievable by most older individuals engaging in age-appropriate physical activity, was associated with a 40% lower likelihood of undergoing future coronary bypass.

Associations of plasma acylcarnitine and bile acid levels with incidence of coronary heart disease in Chinese adults

Objective: To explore the associations of plasma acylcarnitine and bile acid levels with the risk of incident coronary heart disease (CHD) in Chinese adults. Methods: The baseline survey of China Kadoorie Biobank (CKB) took place in 10 areas across China during 2004-2008, and the first resurvey took place from July to October 2008, with collection of data via questionnaire, physical examination and blood samples. The current study was based on 2 159 individuals with targeted mass spectrometry metabolomic measurements from the first resurvey of CKB. The associations of acylcarnitines and bile acids with incident CHD were assessed using Cox proportional hazards regression models. Unweighted metabolites scores were constructed to assess the overall effect of acylcarnitines and bile acids on incident CHD. The impact of metabolites on the performance of CHD prediction model was evaluated with the receiver operating characteristic (ROC) area under the curve (AUC). Follow-up for CHD incidence was censored on December 31, 2018. Results: The mean age of the participants was (53.1±9.8) years and 754 were males (34.9%). During (10.5±0.1) years of follow-up, 140 cases of CHD were recorded. Four metabolites including acylcarnitines C3-OH, C5:1, C5:1-DC, and deoxycholic acid (DCA) showed associations with CHD incidence and the HR (95%CI) were 1.474 (1.230-1.767), 0.761 (0.637-0.909), 0.773 (0.650-0.918), and 1.309 (1.113-1.539), respectively [false discovery rate (FDR)0.05]. All metabolite scores, including short-chain, medium-chain, long-chain acylcarnitines, primary and secondary bile acids scores were associated with the risk of CHD (FDR0.05). Compared to the traditional models, the addition of DCA or 4 key metabolites increased the AUC of the predictive model from 0.803 (0.761-0.845) to 0.812 (0.772-0.852) and 0.817 (0.778-0.857), respectively (all P0.05). Conclusions: Acylcarnitine and bile acid levels are associated with the risk of CHD, and DCA or 4 key metabolites can improve the predictive ability for CHD incidence.

The level of thyroid stimulating hormones in different gender and age and the association with the risk of coronary heart disease in cohort population

Objective: To analyze the thyroid stimulating hormone (TSH) levels in different genders and ages, and the association between TSH level and the risk of coronary heart disease. Methods: The baseline survey was conducted using a multi-stage cluster random sampling method from September to December 2015, in Jurong City, Jiangsu Province. A total of 10 703 participants were included in the analysis. The proportion of participants with abnormally elevated TSH defined by three cut-off values (4.5, 7.0, and 10.0 mU/L) were calculated. The cohort was followed up until August 2023 to collect and verify new cases of coronary heart disease. The population was divided into age-and gender-specific quintile subgroups based on TSH. Multivariate Cox regression analysis was used to examine the relationship between TSH and the risk of coronary heart disease. Results: The median age was [M (Q1, Q3)] 61.1(51.8, 67.9) years-old, and there were 4 168 males (38.94%) in the study. The proportions of participants with abnormally increased TSH rose with aging in different genders, and was higher in females than in males (all Ptrend0.05). A total of 206 participants with coronary heart disease at baseline were excluded, and the other 10 497 were followed up for an average of (7.33±1.49) years, during which 350 new cases of coronary heart disease occurred, and the cumulative incidence rate was 3.34%. The cumulative incidence rates among TSH quintile Q1-Q5 groups were 3.62%, 3.32%, 3.56%, 3.28% and 2.57% respectively. Multivariate Cox regression analysis indicated that compared with TSH Q1 group, participants in Q5 group had a lowest risk of coronary heart disease (HR=0.704, 95%CI: 0.498-0.994). The TSH Q5 group was associated with a reduced risk of coronary heart disease in individuals60 years old (HR=0.484, 95%CI: 0.243-0.965), and the risk of coronary heart disease decreased as TSH levels increased (Ptrend=0.008). Conclusions: TSH level increases with aging, and is higher in females than in males. In individuals 60 years old, higher levels of TSH may assaciate with a lower incidence rate of coronary heart disease.

Development and Evaluation of a Comprehensive Prediction Model for Incident Coronary Heart Disease Using Genetic, Social, and Lifestyle-Psychological Factors: A Prospective Analysis of the UK Biobank.

Clinical risk calculators for coronary heart disease (CHD) do not include genetic, social, and lifestyle-psychological risk factors. To improve CHD risk prediction by developing and evaluating a prediction model that incorporated a polygenic risk score (PRS) and a polysocial score (PSS), the latter including social determinants of health and lifestyle-psychological factors. Cohort study. United Kingdom. UK Biobank participants recruited between 2006 and 2010. Incident CHD (myocardial infarction and/or coronary revascularization); 10-year clinical risk based on pooled cohort equations (PCE), Predicting Risk of cardiovascular disease EVENTs (PREVENT), and QRISK3; PRS (Polygenic Score Catalog identification: PGS000018) for CHD (PRSCHD); and PSSCHD from 100 related covariates. Machine-learning and time-to-event analyses and model performance indices. In 388 224 participants (age, 55.5 [SD, 8.1] years; 42.5% men; 94.9% White), the hazard ratio for 1 SD increase in PSSCHD for incident CHD was 1.43 (95% CI, 1.38 to 1.49; P < 0.001) and for 1 SD increase in PRSCHD was 1.59 (CI, 1.53 to 1.66, P < 0.001). Non-White persons had higher PSSCHD than White persons. The effects of PSSCHD and PRSCHD on CHD were independent and additive. At a 10-year CHD risk threshold of 7.5%, adding PSSCHD and PRSCHD to PCE reclassified 12% of participants, with 1.86 times higher CHD risk in the up- versus down-reclassified persons and showed superior performance compared with PCE as reflected by improved net benefit while maintaining good calibration relative to the clinical risk calculators. Similar results were seen when incorporating PSSCHD and PRSCHD into PREVENT and QRISK3. A predominantly White cohort; possible healthy participant effect and ecological fallacy. A PSSCHD was associated with incident CHD and its joint modeling with PRSCHD improved the performance of clinical risk calculators. National Human Genome Research Institute.

Higher remnant cholesterol increases the risk of coronary heart disease and diabetes in postmenopausal women

BackgroundPostmenopausal women represent the demographic increasingly susceptible to cardiovascular and metabolic diseases. Elevated levels of remnant cholesterol (RC) have been implicated in atherosclerosis and insulin resistance.MethodsThis study aimed to investigate the relationship between RC and the prevalence of coronary heart disease (CHD), diabetes, and CHD combined with diabetes in a nationally representative sample of US postmenopausal women using data from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. Multivariate logistic regression models were employed to evaluate the association between RC and the outcomes of interest. Nonlinear associations were assessed using restricted cubic splines (RCS), and subgroup analyses, along with interaction tests, were performed.ResultsA total of 1611 participants were included in the final analysis. Higher RC levels were significantly associated with increased risks of CHD [OR=1.67, 95%CI (1.02, 2.74)], diabetes [OR=1.77, 95%CI (1.22, 2.58)], and CHD combined with diabetes [OR=2.28, 95%CI (1.17, 4.42)] (all P&amp;lt;0.05). Compared to the lowest RC quartile (Q1), the highest quartile (Q4) demonstrated elevated incidences of CHD [OR=1.76, 95%CI (1.04, 2.98)], diabetes [OR=1.81, 95%CI (1.30, 2.53)], and CHD combined with diabetes [OR=3.08, 95%CI (1.29, 7.37)] (all P&amp;lt;0.05). RCS curves indicated a nearly linear relationship between RC and the risks of CHD, diabetes, and CHD combined with diabetes.ConclusionOur study reveals a significant positive correlation between RC levels and the prevalence of CHD, diabetes, and CHD combined with diabetes among postmenopausal women. Understanding these associations could potentially inform targeted prevention and management strategies tailored to this vulnerable population.

Per- and polyfluoroalkyl substances, apolipoproteins and the risk of coronary heart disease in US men and women

BackgroundExisting evidence for associations of per- and polyfluoroalkyl substances (PFASs) with blood lipids, lipoproteins and apolipoproteins (apo), and coronary heart disease (CHD) risk is limited and inconsistent. This study aims to explore associations between plasma PFASs, blood lipoprotein subspecies defined by apolipoproteins, and CHD risk.MethodsA case–control study of CHD was conducted in the Health Professionals Follow-Up Study (HPFS) and Nurses' Health Study (NHS). Among participants initially free of cardiovascular disease at blood collection in 1994 (HPFS) or 1990 (NHS), 101 participants who developed non-fatal myocardial infarction or fatal CHD were identified and confirmed. A healthy control was matched to each case for age, smoking status, and date of blood draw. Plasma levels of perfluorohexane sulfonic acid (PFHxS), perfluorooctanoic acid (PFOA), total perfluorooctane sulfonic acid (PFOS), branched PFOS (brPFOS), linear PFOS (nPFOS), perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) were measured. Conditional logistic regression and cubic spline regression models were used to examine associations between baseline PFASs and CHD risk. Linear regression models were applied to study PFAS associations with lipids and their subfractions.ResultsAfter multivariate adjustments, total PFOS, brPFOS and nPFOS were significantly associated with increased risk of developing CHD, and HRs (95% CIs) per log(ng/mL) increment of PFASs were 3.66 (1.36–9.89), 3.68 (1.55–8.76), and 3.01 (1.16–7.86), respectively. Significant positive dose–response relationships were identified for these PFASs (Plinearity = 0.01, 0.002, 0.02, respectively). Other PFASs were not associated with CHD risk. PFNA and PFDA were positively associated with total apoE levels among HDL particles with or without apoC-III. No associations were observed for other PFASs with blood lipid subspecies. Blood lipid subfractions did not explain the association between PFOS and CHD risk.ConclusionsPlasma PFOS and its isomers were positively associated with CHD risk. These findings suggest that PFOS exposure causes public health risks that are greater than hitherto believed.

Apolipoprotein B Modifies the Association between Lipoprotein(a) and ASCVD Risk

Background: Elevated lipoprotein(a) (Lp[a]) and apolipoprotein B (apoB) are individually associated with the risk of atherosclerotic cardiovascular disease (ASCVD). Moreover, previous basic research has implicated the potential interaction between apoB and Lp(a) in the atherogenic process. We aimed to determine whether apoB levels significantly modulate ASCVD risk associated with Lp(a) in a large community-based population without baseline cardiovascular disease. Methods: Plasma Lp(a) and apoB were measured in the Atherosclerosis Risk In Communities (ARIC) study. Elevated Lp(a) was defined as the highest race-specific quintile, and elevated apoB was defined as ≥89 mg/dl (median value). The modifying effect of apoB on the Lp(a)-related risk of ASCVD and coronary heart disease (CHD) was determined using Cox regression models adjusted for cardiovascular risk factors. Results: Among 12,988 ARIC participants, 3,888 ASCVD events and 1754 CHD events were observed. Elevated apoB (≥89 mg/dl) and elevated Lp(a) (race-specific quintile 5) were independently associated with ASCVD (hazard ratio [HR]: 1.19; 95% CI: 1.08-1.30; P <0.001; HR: 1.27; 95% CI: 1.16-1.40; P <0.001, respectively). Lp(a)-by-apoB interaction was noted [Lp(a) (quintile 1-4 or quintile 5) * apoB (<89 or ≥89 mg/dl) = 0.002]. Compared to the concordantly low Lp(a) group, the individuals with high Lp(a) had a greater ASCVD risk only when apoB was elevated (HR: 1.48; 95% CI: 1.34-1.63; P <0.001). Conclusions: In the context of primary prevention, ASCVD risk associated with Lp(a) was observed only when apoB was elevated. The measurement of apoB can further refine and contextualize the ASCVD risk associated with Lp(a).

Unique cardiometabolic factors in women that contribute to modified cardiovascular disease risk.

Major risk factors of cardiovascular disease (CVD) include hypertension, obesity, diabetes mellitus and metabolic syndrome; all of which are considered inflammatory conditions. Women are disproportionately affected by inflammatory conditions, with sex differences emerging as early as adolescence. Hormonal fluctuations associated with reproductive events such as menarche, pregnancy and menopause, are hypothesized to promote a pro-inflammatory state in women. Moreover, women who have experienced inflammatory-type conditions such as polycystic ovarian syndrome (PCOS), gestational diabetes or pre-eclampsia, have a cardiometabolic phenotype that pre-disposes to increased risk of myocardial infarction, stroke and coronary heart disease. Women with no notable CVD risk factors are often relatively protected from CVD pre-menopause; but overtake men in risk of major cardiovascular events when the cardiovascular protective effects of oestrogen begin to wane. Sex differences and female-specific factors have long been considered challenging to study and this has led to an underrepresentation of females in clinical trials and lack of female-specific data from pre-clinical studies. However, there is now a clear prerogative to include females at all stages of research, despite inherent complexities and potential variability in data. This review explores recent advancements in our understanding of CVD in women. We summarise the underlying factors unique to women that can promote CVD risk factors, ultimately contributing to CVD burden and the emerging therapies aimed to combat this.

Misalignment Between Circadian Preference and Accelerometer-Derived Sleep-Wake Cycle With Increased Risk of Cardiometabolic Diseases

BackgroundThe relationship of circadian misalignment, sleep-wake cycle, and cardiometabolic diseases (CMDs) remains unclear. ObjectivesThis prospective study investigated the associations between circadian misalignment and CMDs, including type 2 diabetes (T2D), coronary heart disease (CHD), and stroke, and explored potential mechanisms. MethodsData from 60,965 participants without pre-existing CMDs from the UK Biobank study and followed for an average of 7.9 years were analyzed. Circadian misalignment was determined by comparing self-reported chronotype and accelerometer-derived sleep timing. Incident CMDs were documented via multiple medical registries and self-reported information. Cox proportional hazards models were applied to estimate HRs and 95% CIs for these associations. ResultsA U-shaped relationship between circadian misalignment and both T2D and CHD was observed. Compared to individuals with aligned midsleep and circadian preferences (the third quintile, Q3), those with advanced and delayed circadian misalignment had higher risks of T2D (HR: 1.22 [95% CI: 1.03-1.45] for Q1 and 1.39 [95% CI: 1.18-1.62] for Q5). Delayed circadian misalignment also associated with higher CHD risk (HR: 1.15 [95% CI: 1.01-1.31] for Q4 and 1.16 [95% CI: 1.02-1.33] for Q5). The association between delayed circadian misalignment and CMDs was greater in women (T2D, Pinteraction = 0.03) and younger adults (CHD, Pinteraction = 0.02). Early (HR: 1.19 [95% CI: 1.06-1.34]), rather than late, chronotype was associated with an increased T2D risk. ConclusionsBoth advanced and delayed circadian misalignment were associated with an increased CMD risk, highlighting the potential health benefits of aligning sleep-wake cycles with individual circadian preferences.

A Survey on Hybrid Deep Learning and Neural Fuzzy Inference Systems for Early Coronary Heart Disease Detection

coronary heart disease (CHD) continues to be a primary cause of global mortality, highlighting the critical necessity for precise and early detection techniques to enable prompt management and prevention. Recent breakthroughs in ML and DL have demonstrated potential in improving diagnosis accuracy; yet, challenges remain regarding interpretability, computational complexity, and the management of ambiguous or unclear medical data. This survey examines advanced methodologies and investigates the possibility of hybrid frameworks that combine deep learning models with neural fuzzy inference systems (NFIS) for the identification and prevention of CHD. Hybrid techniques, which integrate the feature extraction and learning capabilities of deep learning with the interpretability and uncertainty management of neuro-fuzzy inference systems, provide a robust framework for enhancing early coronary heart disease diagnosis and risk evaluation. We offer an extensive comparison of modern machine learning, deep learning, and hybrid models, evaluating their performance across multiple measures, including accuracy, sensitivity, and computing demands. This paper examines upcoming topics such as transfer learning, multi-modal data integration, and explainable AI, emphasising the prospective applications of these systems in clinical environments. Our research indicates that hybrid DL-NFIS models possess considerable potential for improving CHD identification and, thus, augmenting patient outcomes in preventive healthcare.

Effects of α-Mangostin-Loaded Self-Nanoemulsion (MG-SNE) and Physical Exercise on The Reduction of Waist Circumference in Wistar Rats

BACKGROUND : Waist circumference (WC) is a marker of intra-abdominal adipose tissue and a risk factor for cardiometabolic disease. A higher risk of coronary heart disease was associated with an increased WC. Garcinia mangostana Linn's anti-inflammatory activity would reduce abdominal fat deposition and WC. Additionally, Garcinia mangostana Linn's potential would increase in nanotechnology. AIMS : To demonstrate that WC in Wistar rats induced by an atherogenic diet can be decreased by α-Mangostin-loaded self-nanoemulsion (MG-SNE) treatment combined with physical activity. METHOD : Experimental research with Randomized Control Trial design using a total sample of 15 male white rats (Rattus novergicus strain Wistar) weighing 300 grams and aged between 6 and 8 weeks, split into 3 groups given physical exercise for 8 weeks along with 3 different doses of medication (group K received Atorvastatin 1.44 mg once; group P1 received Garcinia mangostana Linn pericarp extract, at a dose of 800 mg/kg, divided into 3 administrations; and group P2 received MG-SNE 50 mg/kg once). Waist circumference was measured using a metline, before and after treatment. RESULT : WC decreased in Groups K, P1, and P2, with deltas of -5.00±21.21 mm, -12.50±24.75 mm, and -17.50±12.58 mm. The greatest decrease in WC was P2. There was no significant difference, according to the paired test between the pre-test and posttest in all groups. The p value &gt;0.05 was determined to indicate that there were no significant differences between the groups. CONCLUSION : WC in Wistar rats induced by an atherogenic diet can be decreased by MG-SNE treatment combined with physical exercise.

Examining the potential causal relationships among smoking behaviors, blood DNA methylation profiles, and the development of coronary heart disease and myocardial infarction

BackgroundSmoking has been identified as a standalone risk factor for coronary heart disease (CHD) and myocardial infarction (MI), but the precise underlying mechanisms remain incompletely elucidated.ResultsIn this study, we conducted a two-sample Mendelian randomization analysis to examine the impact of smoking behaviors (including smoking initiation, age of smoking initiation, cigarettes per day, and smoking cessation) and smoking-related DNA methylation at CpG sites on CHD and MI based on the UK Biobank dataset. Additionally, we included the FinnGen and Biobank Japan datasets as replications and performed a meta-analysis to combine the results from different data sources. We further validated our results using genetic colocalization analysis. In genomic analysis, we provided compelling evidence on the association between genetically predicted smoking initiation and increased susceptibility to CHD and MI. In epigenetic analysis, we identified 11 smoking-related CpG sites linked to CHD risk and 10 smoking-related CpG sites associated with the risk of MI based on the UK Biobank dataset. Subsequently, some of these CpG sites were further replicated using the FinnGen or BBJ datasets. Ultimately, a meta-analysis was conducted to integrate findings from various data sources (3 for CHD, and 2 for MI), revealing that 7 of 11 CpG sites were linked to CHD risk; whereas, 7 of 10 CpG sites were associated with MI risk. Furthermore, we performed genetic colocalization analysis and found that cg19744173 (FBLN7), cg00395063 (ARHGEF12), and cg16822035 (MCF2L) exhibited robust evidence of colocalization with coronary heart disease; whereas, cg19529732 (DIABLO), cg26405020 (FES), and cg08940075 (CNN3) demonstrated strong colocalization evidence with the risk of myocardial infarction.ConclusionsOur research offers a novel insight into the impact of smoking on the susceptibility to CHD and MI through the lens of epigenetic DNA methylation.

Food consumption patterns and Framingham cardiovascular risk score among shift workers: A NOVA-based approach

ObjectiveTo evaluate the association between dietary quantity and variety, by extent and purpose of processing, and Framingham cardiovascular disease (CVD) risk score among rotating shift workers. MethodsThe cross-sectional study included male shift workers. Dietary intake was assessed using a 24-hour recall method conducted by trained interviewers. Food items were classified using two approaches: the first was based on the amount of food consumed in each food group. Fruits, vegetables, and legumes (FVL) intake, is classified as recommended at 400g per day by WHO guidelines. Ultraprocessed foods (UPFs) were analyzed based on tertiles of daily caloric contribution. The second approach, the NOVA dietary diversity score (DDS-NOVA) assessed the variety of consumed items within each food group, assigning points for each unique item consumed, irrespective of quantity or frequency. The CVD-risk score was evaluated using the Framingham coronary heart disease risk score, categorizing participants as low risk (<5%) or intermediate to high risk (>5%). Descriptive, univariate, and multivariate logistic regression were used, with adjustments made for age, skin color, schooling, duration of shift work, physical activity, BMI and total caloric intake. ResultsThe study involved 213 participants, with an average age of 38.67 years (±6.96), a minimum of 26 and a maximum of 60. The majority (62.4%) were between 30 and 40 years old; 49.3% identified themselves as brown; 56.8% had completed high school; and 79.3% were married. The Framingham CVD-risk score indicated that 56.2% were at low risk (<5%) and 43.7% at intermediate to high risk (≥5%). The average consumption of FVL was 272.32g (±350.43), with 70.4% meeting the recommendation of ≥400g/day. Participants consumed an average of 3.46 fresh food items, 3.74 minimally processed food items, 2.54 processed food items and 3.39 ultra-processed food items. In the multivariate model, consuming ≥400g/day of FVL reduced the likelihood of cardiovascular risk ≥5% by 2.12 times (OR: 0.47; 95%CI: 0.23-0.98). Each additional item of fresh food reduced the risk by 49% (OR: 0.67; 95%CI: 1.01-1.66), while each additional item of ultra-processed food increased the risk by 30% (OR: 1.30; 95%CI: 0.52-0.87). There was no significant association between the calorie intake of ultra-processed foods and cardiovascular risk. ConclusionBoth adequate consumption of FVL quantity and a greater variety of fresh-foods were associated with a lower chance of CVD-risk, while a higher variety of consumption of UPF items increased this chance.

A Mendelian randomization study of alcohol use and cardiometabolic disease risk in a multi-ancestry population from the Million Veteran Program.

Observational studies link moderate alcohol consumption to reduced risk of cardiometabolic diseases, including coronary heart disease (CHD) and type 2 diabetes mellitus (T2D). Mendelian randomization (MR) studies suggest that these associations are due to confounding. We present observed and genetically proxied associations between alcohol consumption and the incidence of CHD and T2D among African Americans (AA), European Americans (EA), and Hispanic Americans (HA) from the Million Veteran Program. We conducted two retrospective, nested case-control studies of 33,053 CHD and 28,278 T2D cases matched to five controls each at the time of the event (index date). We used the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) score closest in time prior to the index date to estimate alcohol exposure. Models were adjusted for smoking, body mass index (BMI), chronic kidney disease, rheumatoid arthritis, and the use of statins or antihypertensive medications. MR analyses used either a single variant in ADH1B or a genetic score (GS) as instrumental variables. Observational analysis showed a U-shaped association of alcohol consumption with CHD and T2D risk. However, in MR analyses, neither ADH1B genotype-predicted (in 36,465 AAs, 146,464 EAs, and 11,342 HAs) nor GS-predicted (in EAs) alcohol consumption was associated with CHD risk. Similarly, T2D was not associated with alcohol consumption predicted either by ADH1B genotype (in 42,008 AAs, 109,351 EAs, and 13,538 HAs) or GS (in EAs). Multivariable MR analyses that adjusted for the effects of blood pressure and smoking also showed no association between alcohol consumption and cardiometabolic diseases. We replicate prior observational studies that show a U-shaped association between alcohol consumption and cardiometabolic diseases, but MR findings show no causal association between these traits. This is largely consistent with previous MR analyses in EAs and expands the literature by providing similar findings in AA and HA populations.

Formulation and Evaluation of Anti-Hyperlipidemic Tablet

Hyperlipidemia is one of the leading causes of mortality in developed as well as in developing countries like India. It attributes to the high risk of coronary heart disease and atherosclerosis which is referred as a silent killer. Herbal treatment for hyperlipidemia is inexpensive, readily available locally, and has no negative side effects. Medicinal plants are the "backbone" of traditional medicine so considered as good source of life for all people due to its wealthy therapeutic properties and being 100% natural. Several drugs in Siddha have been found to be beneficial in lowering lipid levels without any major adverse effects. Numerous plants like arjuna, ashwagandha, garlic, guggul, etc. have been reported to have lipid-lowering effects. The goal of the review paper is to examine the potential anti-hyperlipidemic effects of herbal plants using a variety of models. The anti-hyperlipidemic activity of the most well-known medicinal herbs is the focus of this review.

Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores

Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized. To characterize the individual-level agreement of CHD PRSs that perform similarly at the population level. Cross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data. Polygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples. PRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ. A total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement. CHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians.

Ethnic disparities and lifestyle determinants in the prevalence of cardiovascular disease among Han majority and Ha Ni ethnic minority older adults in rural Southwest China

ObjectivesCardiovascular disease (CVD) is the leading cause of death in China. This study compared ethnic disparities and lifestyle determinants in the prevalence of CVD (hypertension, coronary heart disease [CHD], and stroke) among older adults of the Han majority and Ha Ni ethnic minority in rural southwest China, to provide evidence for preventing and controlling CVD among older-adult minority communities.MethodsA multi-stage stratified random sampling method was used to select 1,413 Han majority participants and 1,402 Ha Ni ethnic minority participants aged ≥ 60 years in rural Southwest China. Data on general demographic characteristics, behavioral lifestyle, and self-reported diagnostic information for patients with CHD and stroke were collected using a standardized questionnaire. The height, weight, waist circumference, and blood pressure of each participant were recorded. The relationship between lifestyle factors and CVD was analyzed using multivariate logistic regression.ResultsHan majority older adults had a higher prevalence of CHD (6.4% vs. 3.6%) and stroke (7.9% vs. 2.9%) than their Ha Ni minority counterparts (P < 0.01). Han majority participants had a markedly higher prevalence of obesity, central obesity, and physical inactivity than their Ha Ni ethnic minority counterparts (9.2%, 48.3%, and 55.1% vs. 3.4%, 19.1%, and 49.2%, respectively, P < 0.01). By contrast, Ha Ni ethnic minority participants had a higher prevalence of current drinking than Han majority participants (31.2% vs. 14.4%, P < 0.01). Among Han majority and Ha Ni ethnic minority older adults, participants with central obesity (OR = 2.09, 95% CI: 1.62–2.69 vs. OR = 2.66, 95% CI: 1.88–3.76) had a higher risk of hypertension, participants with obesity (OR = 1.99, 95% CI: 1.02–3.67 vs. OR = 3.66, 95% CI: 1.39–9.66) were more likely to suffer from CHD, and participants with physical inactivity (OR = 1.88, 95% CI: 1.18–2.98 vs. OR = 2.29, 95% CI: 1.13–4.64) had a higher probability of suffering from stroke. Furthermore, Current drinking status increased the risk of CHD (OR = 2.31, 95% CI: 1.05–5.08), but decreased the risk of stroke (OR = 0.33, 95% CI: 0.13–0.83) in Ha Ni ethnic minority participants.ConclusionCHD and stroke are more prevalent among the Han majority older adults in rural Southwest China, and lifestyle factors significantly influence CVD.