Coronary Heart Disease Risk Assessment Research Articles

Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol

Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. LDL-C, cumulative past LDL-C, FH variant status. Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Association of metabolic health and obesity with coronary heart disease in adult cancer survivors.

The metabolically healthy obese (MHO) phenotype is associated with an increased risk of coronary heart disease (CHD) in the general population. However, association of metabolic health and obesity phenotypes with CHD risk in adult cancer survivors remains unclear. We aimed to investigate the associations between different metabolic health and obesity phenotypes with incident CHD in adult cancer survivors. We used National Health Insurance Service (NHIS) to identify a cohort of 173,951 adult cancer survivors aged more than 20 years free of cardiovascular complications. Metabolically healthy nonobese (MHN), MHO, metabolically unhealthy nonobese (MUN), metabolically unhealthy obese (MUO) phenotypes were created using as at least three out of five metabolic health criteria along with obesity (body mass index ≥ 25.0 kg/m2). We used Cox proportional hazards model to assess CHD risk in each metabolic health and obesity phenotypes. During 1,376,050 person-years of follow-up, adult cancer survivors with MHO phenotype had a significantly higher risk of CHD (hazard ratio [HR] = 1.52; 95% confidence intervals [CI]: 1.41 to 1.65) as compared to those without obesity and metabolic abnormalities. MUN (HR = 1.81; 95% CI: 1.59 to 2.06) and MUO (HR = 1.92; 95% CI: 1.72 to 2.15) phenotypes were also associated with an increased risk of CHD among adult cancer survivors. Adult cancer survivors with MHO phenotype had a higher risk of CHD than those who are MHN. Metabolic health status and obesity were jointly associated with CHD risk in adult cancer survivors.

Birth Weight, Childhood and Young Adult Overweight, and the Risk of Coronary Heart Disease in Men.

Low birth weight is a known risk factor for adult coronary heart disease (CHD), but the additional effect of weight development during childhood and early adult life has not been studied. We included 35 659 men born 1945 to 1961 from the population-based BMI Epidemiology Study Gothenburg, with data available on birthweight, BMI in childhood (8 years), and BMI in young adulthood (20 years). Information on CHD diagnoses was retrieved from national registers. We used Cox proportional hazards regression to estimate hazard ratios and 95% CIs for the risk of early and late CHD (before and after 58.4 years of age, respectively). During follow-up, a total of 3380 cases of CHD (fatal and nonfatal) were registered. Birth weight was inversely associated with the risk of both early (hazard ratio, 0.88 per SD increase [95% CI, 0.84-0.92]) and late (hazard ratio, 0.94 per SD increase [95% CI, 0.90-0.98]) CHD, independently of BMI at 8 years and BMI change during puberty. In a model including birth weight (below or above the median) together with overweight at 8 and 20 years, only birth weight and young adult overweight, but not overweight in childhood, were significantly associated with the risk of CHD. A birth weight below the median, followed by overweight at 20 years of age was associated with a more than doubled risk of early CHD (hazard ratio, 2.29 [95% CI, 1.86-2.81]), compared with the reference (birth weight above the median and normal weight at 20 years of age). This excess risk was even more pronounced for a birthweight below 2.5 kg. We demonstrate that low birth weight and young adult overweight are important developmental markers of risk for adult CHD. These findings motivate a life course perspective for prevention and risk assessment of adult CHD.

Identification of an association between coronary heart disease and ITGB2 methylation in peripheral blood by a case-control study

BackgroundBlood DNA methylation was associated with coronary heart disease (CHD) risk in Caucasians. We investigated the association between DNA methylation in peripheral blood at the reported loci and CHD in the Chinese population. MethodsThe integrin subunit beta 2 (ITGB2) gene was identified in 196 CHD cases and 184 controls, and its methylation level was determined by mass spectrometry. Logistic regression was used to assess the association. ResultsHypomethylation of ITGB2 was significantly associated with heart failure CHD and NYHA Ⅰ&Ⅱ CHD patients with minor to medium cardiac function impairment (ITGB2_CpG_11/cg08422803, OR per −10 % methylation = 1.15 and 1.16; p = 0.012 and 0.018 by Bonferroni correction, respectively). Hypomethylation of ITGB2_CpG_11/cg08422803 was a risk factor for CHD in people < 65 years and males (p < 0.05 after Bonferroni correction). The combination of ITGB2 methylation and conventional CHD risk factors could efficiently discriminate CHD, heart failure CHD, NYHA I&II CHD, and myocardial infarction CHD patients from controls (AUC = 0.78, 0.81, 0.80, and 0.81, respectively). ConclusionBlood-based ITGB2 methylation has the potential as a biomarker for CHD. The combination of ITGB2 methylation and conventional CHD risk factors may improve the risk assessment and detection of CHD.

Comparative evaluation of LDL-CT, non-HDL/HDL ratio, and ApoB/ApoA1 in assessing CHD risk among patients with type 2 diabetes mellitus

BackgroundResearch proved the importance of dosing apolipoprotein B (ApoB) over LDL cholesterol as a predictor of cardiovascular events. In this study, we aimed to observe the input apolipoprotein A1 (ApoA1) and ApoB, primarily if its ratio could provide in patients with type 2 diabetes mellitus (T2DM) without known atherosclerotic events regarding the coronary heart disease (CHD) risk. MethodsWe enrolled 83 patients with T2DM who attended the National Institute of Diabetes (Bucharest) between March 2022 and December 2022. A blood sample was taken from all patients to measure the different lipid parameters, including ApoA1 and ApoB. Spearman's correlation test for correlation between variables was used, and a multivariate regression analysis was performed to determine whether there are associations between CHD and the ApoB/ApoA1 and non-HDL-cholesterol/HDL-cholesterol ratios. Values of p < 0.05 were considered significant. ResultsCorrelation analyses revealed that LDL-C was moderately associated with CHD (r = 0.199, p = 0.067). The non-HDL-C/HDL-C ratio exhibited a stronger, significant correlation with CHD (r = 0.366, p = 0.001). Evaluating apolipoproteins, ApoA1 levels negatively correlated with CHD (r = −0.233, p = 0.035), whereas ApoB levels showed a positive association (r = 0.292, p = 0.008). Notably, the severity of CHD risk increased with the ApoB/ApoA1 ratio (r = 0.530, p < 0.001). Similar trends in correlation coefficients were observed for fatal CHD and ASCVD, albeit with varied significance levels. ConclusionsAmong patients with T2DM, the ApoB/ApoA1 ratio exhibited the strongest correlation with CHD risk, surpassing traditional LDL-C and even the non-HDL-C/HDL-C ratio, suggesting its potential utility as a more reliable marker for cardiovascular risk assessment in this population.

Genetic Polymorphism of NQO1 Influences Susceptibility to Coronary Heart Disease in a Chinese Population: A Cross-Sectional Study and Meta-Anaylsis.

The present study is to explore the association between NQO1 gene polymorphism and coronary heart disease (CHD) risk. This research were selected 80 CHD patients as the observation group and 130 healthy people who participated in normal physical examination during the same period as the control group. NQO1 gene polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. In addition, we conducted a meta-analysis to summarize the results of three relevant previously published adult population studies on the association between NQO1 gene polymorphism and coronary heart disease (CHD) risk. There were three genotypes (CC, CT, and TT) for NQO1 C609T polymorphism. The significant associations were found in TT genotype and T allele (all p<0.05). Specifically, People with the TT genotype have 2.06 times CHD risk as those with the CC genotype. And People with the T allele have 1.62 times CHD risk as those with the C allele. No significant association was found by any genetic models in the meta-analysis (all p >0.05). NQO1 gene polymorphism increased the CHD risk in a Chinese population. Combined with individual gene polymorphism, the accuracy of risk assessment for CHD can be improved and individualized health education can be provided for CHD patients by nurses.

A gender specific risk assessment of coronary heart disease based on physical examination data

Large-scale screening for the risk of coronary heart disease (CHD) is crucial for its prevention and management. Physical examination data has the advantages of wide coverage, large capacity, and easy collection. Therefore, here we report a gender-specific cascading system for risk assessment of CHD based on physical examination data. The dataset consists of 39,538 CHD patients and 640,465 healthy individuals from the Luzhou Health Commission in Sichuan, China. Fifty physical examination characteristics were considered, and after feature screening, ten risk factors were identified. To facilitate large-scale CHD risk screening, a CHD risk model was developed using a fully connected network (FCN). For males, the model achieves AUCs of 0.8671 and 0.8659, respectively on the independent test set and the external validation set. For females, the AUCs of the model are 0.8991 and 0.9006, respectively on the independent test set and the external validation set. Furthermore, to enhance the convenience and flexibility of the model in clinical and real-life scenarios, we established a CHD risk scorecard base on logistic regression (LR). The results show that, for both males and females, the AUCs of the scorecard on the independent test set and the external verification set are only slightly lower (<0.05) than those of the corresponding prediction model, indicating that the scorecard construction does not result in a significant loss of information. To promote CHD personal lifestyle management, an online CHD risk assessment system has been established, which can be freely accessed at http://lin-group.cn/server/CHD/index.html.

LOW-DENSITY LIPOPROTEIN CHOLESTEROL ESTIMATION BY FRIEDEWALDS FORMULA AND BY DIRECT MEASUREMENT - A COMPARISON

Introduction: Low-density lipoprotein cholesterol (LDL-C) levels in serum is the basis of diagnosis, classification and management of hypercholesterolemia as per the current recommendations of the Adult Treatment Panel III of National Cholesterol Education Program. Friedewalds formula is used in most laboratories to measure LDL-C levels indirectly. But, Friedewalds formula is not reliable always. Now-a-days, various homogenous assay kits for direct estimation of LDL-C based on precipitation and solubilisation using specific detergents have been evolved. This makes estimation of LDL-C levels easier but costlier. So we conducted a study to compare the results obtained by estimating LDL-C level by direct assay kit and also indirectly by using Friedewalds formula in order to assess the cost effectiveness of both the methods. Aim: To compare LDL-C levels obtained by direct homogenous assay (D-LDL-C) to that obtained by Friedewalds formula (F-LDL-C) in fasting serum samples. Materials And Methods: Serum separated from 404 blood samples was analysed for Total cholesterol (TC), Triglycerides (TG), High- density lipoprotein (HDL) and LDL using specific assay kits. Simultaneously, LDL-C was also estimated in the same samples indirectly by using Friedewalds formula. Results: Statistical analysis by Pearson correlation showed high correlation between D-LDL-C and indirect F-LDL-C. But in all ranges of TG, F-LDL-C showed underestimation of LDL-C when compared to D-LDL-C. Conclusion:Use of Friedewald formula for estimation of LDL-C is not suitable in all cases. In samples showing hypertriglyceridemia, direct homogenous assay was found to be better for CHD risk assessment and management.

PPBP gene as a biomarker for coronary heart disease risk in postmenopausal Thai women.

BackgroundEstrogen is an important ovarian hormone with anti-atherogenic and cardioprotective effects. Postmenopausal women have lower estrogen levels, associated with significantly higher risks of coronary heart disease (CHD) and CHD-related death. Effective biomarkers for the diagnosis, prediction, and treatment of CHD are needed to address this problem and thus reduce the mortality due to CHD in postmenopausal women. We recently reported that the PPBP and DEFA1/DEFA3 genes may be feasible synergistic biomarkers for CHD risk in Thai men with hyperlipidemia. The PPBP gene encodes pro-platelet basic protein (PPBP) from activated platelets, and DEFA1/DEFA3 encodes human neutrophil peptides (HNP) 1–3, mainly produced by activated neutrophils. Both platelets and neutrophils are involved in chronic inflammation during the development of atherogenesis and CHD. This study investigated the potential roles of PPBP and DEFA1/DEFA3 and their proteins as biomarkers for CHD risk in postmenopausal Thai women.MethodsThis cross-sectional study enrolled 90 postmenopausal Thai women, including 12 healthy controls (N), 18 patients with hyperlipidemia (H), and 21 patients diagnosed with CHD. The remaining 39 women were receiving cholesterol-lowering drugs for hyperlipidemia (HD) were excluded from the study. All CHD patients underwent coronary bypass grafting or coronary angioplasty. PPBP and DEFA1/DEFA3 mRNA expression levels in peripheral blood mononuclear cells isolated from heparinized blood were determined by quantitative reverse-transcription polymerase chain reaction. Levels of PPBP and HNP-1–3 proteins in corresponding plasma samples were assessed by enzyme-linked immunosorbent assay. Differences in parameters were compared among groups and correlations between parameters and clinical manifestations were analyzed.ResultsPPBP mRNA and protein levels were significantly increased in the CHD group compared with the N and H groups. In contrast, DEFA1/DEFA3 mRNA and HNP-1–3 protein levels did not differ significantly among the groups. None of the levels were associated with any of the clinical parameters analyzed in this study.ConclusionThe results indicate that gene and protein expression levels of PPBP, but not DEFA1/DEFA3, and HNP-1–3, may be feasible biomarkers for assessing CHD risk in postmenopausal Thai women with hyperlipidemia.

Heterogeneity in coronary heart disease risk

There is large inter-individual heterogeneity in risk of coronary heart disease (CHD). Risk factors traditionally used in primary risk assessment only partially explain this heterogeneity. Residual, unobserved heterogeneity leads to age-related attenuation of hazard rates and underestimation of hazard ratios. Its magnitude is unknown. Therefore, we aimed to estimate a lower and an approximate upper bound. Heterogeneity was parametrized by a log-normal distribution with shape parameter σ. Analysis was based on published data. From concordance indices of studies including traditional risk factors and additional diagnostic imaging data, we calculated the part of heterogeneity explained by imaging data. For traditional risk assessment, this part typically remains unexplained, thus constituting a lower bound on unobserved heterogeneity. Next, the potential impact of heterogeneity on CHD hazard rates in several large countries was investigated. CHD rates increase with age but the increase attenuates with age. Presuming this attenuation to be largely caused by heterogeneity, an approximate upper bound on σ was derived. Taking together both bounds, unobserved heterogeneity in studies without imaging information can be described by a shape parameter in the range σ = 1–2. It substantially contributes to observed age-dependences of hazard ratios and may lead to underestimation of hazard ratios by a factor of about two. Therefore, analysis of studies for primary CHD risk assessment should account for unobserved heterogeneity.

Assessment of Remnant Lipoprotein Cholesterol and Oxidized Low density Lipoprotein Associated with Low-grade Inflammation in Coronary Heart Disease Subjects of Young South Indian Population.

Coronary heart disease (CHD) is a major disease entity responsible for significant mortality and morbidity in the Indian population. The prevalence of CHD is increasing day by day in India. The hardening of arteries is linked to oxidative variations in low-density lipoproteins (LDLs). Modification of LDL to oxidized LDL (ox-LDL) is a crucial step in the oxidation hypothesis of atherogenesis. Oxidized LDL and remnant lipoprotein cholesterol (RLP-C) stimulate the immune and inflammatory reactions and promote atherosclerosis. Because of its lesser size along with high cholesterol content, and increased residence period in blood the remnant lipoproteins are highly atherogenic. Remnant lipoproteins transport more cholesterol to macrophages compared to LDL particles. Remnant lipoproteins enter into the arterial wall easily and are taken up directly by macrophages. This leads to the formation of foam cells, thus initiating the lipid-laden plaque. High sensitive C-reactive protein acts as a nonspecific inflammatory marker. Oxidized LDL along with RLP-C and high-sensitivity C-reactive protein (hs-CRP) play crucial role in progression of CHD. The aim of the study is to assess ox-LDL and RLP-C associated with hs-CRP as potential biomarkers in the development of CHD. This cross-sectional study was conducted in Sri Ramaswamy Memorial Medical College Hospital and Research Centre on subjects appearing for master health check-up and medicine. This cross-sectional study was conducted on 273 subjects who were age and sex match in the age group of ≤45 years. 91 Non-Diabetic subjects with CHD, 91 Diabetic subjects with CHD, and 91 normal healthy subjects were selected as control. After overnight fasting, body fluid samples were collected for analysis for lipid profile, ox-LDL, and hs-CRP. Oxidized LDL and hs-CRP were measured by enzyme-linked immunosorbent assay (ELISA) method and lipid profile was measured using Auto Analyser AU480. Statistical analysis was done using Student's t-test and Pearson's correlation analysis for the comparison between two groups. The mean level of ox-LDL, RLP-C, and hs-CRP was significantly elevated in CHD group. A significantly positive correlation was observed between plasma ox-LDL, RLP-C, and hs-CRP. These results suggest that the link between high ox-LDL, RLP-C, and hs-CRP levels might be interrelated to atherogenesis in subjects with CHD. In addition to conventional parameters, ox-LDL, RLP-C, and hs-CRP can prove to be a valuable tool in risk assessment of CHD. Journal of the Association of Physicians of India (2022): 10.5005/japi-11001-0009.

Risk Assessment of CHD Using Retinal Images with Machine Learning Approaches for People with Cardiometabolic Disorders.

Background: Coronary heart disease (CHD) is the leading cause of death worldwide, constituting a growing health and social burden. People with cardiometabolic disorders are more likely to develop CHD. Retinal image analysis is a novel and noninvasive method to assess microvascular function. We aim to investigate whether retinal images can be used for CHD risk estimation for people with cardiometabolic disorders. Methods: We have conducted a case–control study at Shenzhen Traditional Chinese Medicine Hospital, where 188 CHD patients and 128 controls with cardiometabolic disorders were recruited. Retinal images were captured within two weeks of admission. The retinal characteristics were estimated by the automatic retinal imaging analysis (ARIA) algorithm. Risk estimation models were established for CHD patients using machine learning approaches. We divided CHD patients into a diabetes group and a non-diabetes group for sensitivity analysis. A ten-fold cross-validation method was used to validate the results. Results: The sensitivity and specificity were 81.3% and 88.3%, respectively, with an accuracy of 85.4% for CHD risk estimation. The risk estimation model for CHD with diabetes performed better than the model for CHD without diabetes. Conclusions: The ARIA algorithm can be used as a risk assessment tool for CHD for people with cardiometabolic disorders.

Genetic and observational evidence: No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment.

BackgroundObservational findings for high‐density lipoprotein (HDL)‐mediated cholesterol efflux capacity (HDL‐CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL‐CEC is limited.ObjectivesA large‐scale observational study on the associations of HDL‐CEC and other HDL‐related measures with CHD and the largest genome‐wide association study (GWAS) of HDL‐CEC.Participants/methodsSix independent cohorts were included with follow‐up data for 14,438 participants to investigate the associations of HDL‐related measures with incident CHD (1,570 events). The GWAS of HDL‐CEC was carried out in 20,372 participants.ResultsHDL‐CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL‐C). In contradiction, almost all HDL‐related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL‐CEC independent of HDL‐C and triglycerides.ConclusionHDL‐CEC is not unequivocally associated with CHD in contrast to HDL‐C, apolipoprotein A‐I, and most of the HDL subclass particle concentrations.

Abstract 13530: Epi+Gen CHD: A More Sensitive and Cost-Effective Tool to Assess Risk and Monitor Treatment Response for Coronary Heart Disease

Coronary heart disease (CHD) is preventable, but current lipid-based risk assessment tools such as The Framingham Risk Score (FRS) and ASCVD Pooled Cohort Equation (PCE) have limitations. Using DNA-based genetic and epigenetic biomarkers, we have developed a more sensitive and cost-effective incident CHD risk assessment tool, Epi+Gen CHD, that can provide actionable insights and monitor treatment response. This test can be administered remotely via telemedicine using at-home sampling, or in a clinical setting. Epi+Gen CHD was developed and validated using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM). It incorporates five SNPs and three methylation markers for predicting 3-year incident CHD. It was more sensitive than FRS and PCE and had high generalizability across cohorts with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. In contrast, the sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for the PCE. To assess cost effectiveness, we conducted cost-utility analyses of Epi+Gen CHD. As compared to the PCE, we found that the use of Epi+Gen CHD was associated with both better survival and highly competitive negative incremental cost-effective ratios (cost savings) ranging from -$42,000 to -$-8,000 per quality-adjusted life year with and without accounting for a secondary test. Finally, to understand if the epigenetic biomarkers in Epi+Gen CHD could be leveraged to monitor treatment response, we performed a proof-of-concept study that assessed the three Epi+Gen CHD methylation sites in 39 subjects before and after 3 months of biochemically verified smoking cessation, then analyzed the relationship between change in methylation at each of the sites to the change in smoking intensity (cg05575921 methylation). We showed that in those who quit smoking, methylation change at one Epi+Gen CHD site (cg00300879) was significantly associated with change in smoking intensity (p &lt; 0.04). We conclude that Epi+Gen CHD can identify patients at risk for CHD, save more lives, reduce more healthcare spending and guide prevention interventions better than current methods.

High triglyceride to HDL cholesterol ratio is associated with increased coronary heart disease among White but not Black adults

ObjectiveBlack adults are less likely than White adults to present with adverse lipid profiles and more likely to present with low-grade inflammation. The impact of race on the association between atherogenic lipid profiles, inflammation, and coronary heart disease (CHD) is unknown. MethodsWe evaluated the association between high levels (>50th percentile) of high-sensitivity C-reactive protein (hsCRP) and of triglycerides to high density lipoprotein ratio (TG/HDL-C) and CHD events by race in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort with 30,239 Black and White participants aged 45 and older. ResultsParticipants with both high hsCRP and high TG/HDL-C had highest rates of CHD (HR 1.84; 95% CI: 1.48, 2.29 vs HR 1.52; 95% CI: 1.19, 1.94 in White vs Black participants respectively). Whereas isolated high hsCRP was associated with increased CHD risk in both races (HR 1.68; 95% CI: 1.31, 2.15 and HR 1.43; 95% CI: 1.13, 1.81 for White and Black participants respectively), isolated high TG/HDL was associated with increased CHD risk only in White participants (HR 1.44; 95% CI: 1.15, 1.79 vs HR 1.01; 95% CI: 0.74, 1.38). Further, the effects of high hsCRP and high TG/HDL-C were additive, with inflammation being the driving variable for the association in both races. ConclusionIn both races, higher inflammation combined with adverse lipid profile is associated with greater CHD risk. Therefore, inflammation increases CHD risk in both races whereas dyslipidemia alone is associated with a greater risk in White but not in Black adults. hsCRP testing should be a standard feature of CHD risk assessment, particularly in Black patients.

Estimation of low-density lipoprotein cholesterol by machine learning methods

BackgroundAccurate determination of low-density lipoprotein cholesterol (LDL) is important for coronary heart disease risk assessment and atherosclerosis. Apart from direct determination of LDL values, models (or equations) are used. A more recent approach is the use of machine learning (ML) algorithms. MethodsML algorithms were used for LDL determination (regression) from cholesterol, HDL and triglycerides. The methods used were multivariate Linear Regression (LR), Support Vector Machines (SVM), Extreme Gradient Boosting (XGB) and Deep Neural Networks (DNN), in both larger and smaller data sets. Also, LDL values were classified according to both NCEP III and European Society of Cardiology guidelines. ResultsThe performance of regression was assessed by the Standard Error of the Estimate. ML methods performed better than established equations (Friedewald and Martin). The performance all ML methods was comparable for large data sets and was affected by the divergence of the train and test data sets, as measured by the Jensen-Shannon divergence. Classification accuracy was not satisfactory for any model. ConclusionsDirect determination of LDL is the most preferred route. When not available, ML methods can be a good substitute. Not only deep neural networks but other, less computationally expensive methods can work as well as deep learning.

Predictive Value of Small Dense Low-Density Lipoprotein in Coronary Heart Disease in the Chinese Population.

Coronary heart disease (CHD) is a global public health concern, and CHD risk assessment remains a major challenge. Therefore, in this study, the ability of small dense low-density lipoprotein (sdLDL) alone to sufficiently predict CHD risk in the Chinese population was evaluated. Patients with CHD (139) and healthy controls (58) were included in this study. Serum sdLDL was measured using the peroxidase method. Other lipid parameters were also determined. The sdLDL level in the CHD group was significantly higher than that in the control group (p < 0.001). Logistic regression analysis revealed that sdLDL was an independent risk factor for CHD. Based on the receiver operating characteristic curves, the area under the curve (AUC) of sdLDL alone for CHD was 0.722. The AUC of triglycerides (TG), high-density lipoprotein (HDL), and sdLDL combined was 0.763, which was larger than that of the independent ones or combinations of any two; however, the value was not significant. sdLDL alone can predict CHD risk efficiently similar to the combination of TG, HDL, and sdLDL. This finding suggests that sdLDL can be considered as an ideal parameter for the preliminary diagnosis of CHD in Chinese people.

Risk prediction for coronary heart disease by a genetic risk score - results from the Heinz Nixdorf Recall study

BackgroundA Genetic risk score for coronary artery disease (CAD) improves the ability of predicting coronary heart disease (CHD). It is unclear whether i) the use of a CAD genetic risk score is superior to the measurement of coronary artery calcification (CAC) for CHD risk assessment and ii) the CHD risk assessment using a CAD genetic risk score differs between men and women.MethodsWe included 4041 participants (age-range: 45–76 years, 1919 men) of the Heinz Nixdorf Recall study without CHD or stroke at baseline. A standardized weighted CAD genetic risk score was constructed using 70 known genetic variants. The risk score was divided into quintiles (Q1-Q5). We specified low (Q1), intermediate (Q2-Q4) and high (Q5) genetic risk groups. Incident CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. The association between the genetic risk score and genetic risk groups with incident CHD was assessed using Cox models to estimate hazard ratios (HR) and 95%-confidence intervals (CI). The models were adjusted by age and sex (Model1), as well as by established CHD risk factors (RF) and CAC (Model2). The analyses were further stratified by sex and controlled for multiple testing.ResultsDuring a median follow-up time of 11.6 ± 3.7 years, 343 participants experienced CHD events (219 men). Per-standard deviation (SD) increase in the genetic risk score was associated with 18% increased risk for incident CHD (Model1: p = 0.002) which did not change after full adjustment (Model2: HR = 1.18 per-SD (p = 0.003)). In Model2 we observed a 60% increased CHD risk in the high (p = 0.009) compared to the low genetic risk group. Stratifying by sex, only men showed statistically significantly higher risk for CHD (Model2: HR = 1.23 per-SD (p = 0.004); intermediate: HR = 1.52 (p = 0.04) and high: HR = 1.88 (p = 0.008)) with no statistically significant risk observed in women.ConclusionOur results suggest that the CAD genetic risk score could be useful for CHD risk prediction, at least in men belonging to the higher genetic risk group, but it does not outbalance the value of CT-based quantification of CAC which works independently on both men and women and allows better risk stratification in both the genders.

Mercury concentration and fatty acid composition in muscle tissue of marine fish species harvested from Liaodong Gulf: An intelligence quotient and coronary heart disease risk assessment

Marine fish species are an important source of biologically valuable proteins, fats, fat-soluble vitamins, and n-3 polyunsaturated fatty acids, but they are also susceptible to pollutants. Mercury is liable to bioamplify in the aquatic food chain, and the health risks posed by methylmercury (MeHg) could undermine the benefits of eating fish, so risk-benefit assessments are needed for those fish species regularly consumed. The purpose of this study was to analyze the concentrations of mercury and characteristics of fatty acids in marine fish harvested from Liaodong Gulf, China, so as to better understand the risk-benefit effects of marine fish consumption. We found that the ratio of MeHg to total Hg (THg) was normally distributed. The concentrations of THg and MeHg in marine fish muscles (14 species, a total of 239) ranged from 0.920 to 0.288 μg/g and 0.050 to 0.192 μg/g, respectively. There were no significant interannual differences in the muscles' concentrations of MeHg and THg, or of their fatty acids (p > 0.05). The proportion of total saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) varied significantly among different marine fish-feeding habits (predacious, omnivorous, benthivorous and planktivorous), but the differences between polyunsaturated fatty acids (PUFAs) were not significant, which may be due to the undistinguished fatty acids (p < 0.05). The risk-benefit assessment using the intelligence quotient (IQ) scoring model revealed that all the studied marine fish had positive effects on child IQ under different consumption scenarios. Additionally, the integrated risk-benefit analysis for adult cardiovascular health showed that all the studied marine fish, but especially Ditrema temmincki Bleeker, are capable of reducing the relative cardiovascular risk posed by the MeHg in the fish. We conclude the positive effects of eating common marine fish from the Liaodong Gulf far outweigh their negative ones.

Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease

Background and aimsPopulation subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts. MethodsWe applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles. ResultsThe SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour. ConclusionsThese results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.