Apolipoprotein E E3/E4 genotype is associated with an increased risk of premature coronary artery disease.

OBJECTIVE: Dyslipidemia is one of the causes of coronary heart disease (CAD), and apolipoprotein E (APOE) gene polymorphism affects lipid levels. However, the relationship between APOE gene polymorphisms and premature CAD (PCAD, male CAD patients with ≤ 55 years old and female with ≤ 65 years old) risk had different results in different studies. The aim of this study was to assess this relationship and to further evaluate the relationship between APOE gene polymorphisms and PCAD risk in the Hakka population. METHODS: This study retrospectively analyzed 301 PCAD patients and 402 age matched controls without CAD. The APOE rs429358 and rs7412 polymorphisms were genotyped by polymerase chain reaction (PCR) -chip technique. The distribution of APOE genotypes and alleles between the case group and the control group was compared. The relationship between APOE genotypes and PCAD risk was obtained by logistic regression analysis. RESULTS: The frequency of the APOE ɛ3/ɛ4 genotype (18.9% vs. 10.2%, p = 0.001) and ε4 allele (11.1% vs. 7.0%, p = 0.007) was higher in the PCAD patients than that in controls, respectively. PCAD patients with ɛ2 allele had higher TG level than those with ɛ3 allele, and controls carried ɛ2 allele had higher HDL-C level and lower LDL-C level than those carried ɛ3 allele. Regression logistic analysis showed that BMI ≥ 24.0 kg/m2 (BMI ≥ 24.0 kg/m2 vs. BMI 18.5-23.9 kg/m2, OR: 1.763, 95% CI: 1.235-2.516, p = 0.002), history of smoking (Yes vs. No, OR: 5.098, 95% CI: 2.910-8.930, p < 0.001), ɛ3/ɛ4 genotype (ɛ3/ɛ4 vs. ɛ3/ɛ3, OR: 2.203, 95% CI: 1.363-3.559, p = 0.001), ε4 allele (ε4 vs. ε3, OR: 2.125, 95% CI: 1.333-3.389, p = 0.002), and TC level (OR: 1.397, 95% CI: 1.023-1.910, p = 0.036) were associated with PCAD. CONCLUSIONS: In summary, BMI ≥ 24.0 kg/m2, history of smoking, APOE ɛ3/ɛ4 genotype, and TC level were independent risk factors for PCAD. It means that young individuals who are overweight, have a history of smoking, and carried APOE ɛ3/ɛ4 genotype had increased risk of PCAD.

The Significance of Genetically Determined Methylation and Folate Metabolism Disorders in the Pathogenesis of Coronary Artery Disease: A Target for New Therapies?

Methylation is a biochemical process involving the addition of a methyl group (-CH3) to various chemical compounds. It plays a crucial role in maintaining the homeostasis of the endothelium, which lines the interior surface of blood vessels, and has been linked, among other conditions, to coronary artery disease (CAD). Despite significant progress in CAD diagnosis and treatment, intensive research continues into genotypic and phenotypic CAD biomarkers. This review explores the significance of the methylation pathway and folate metabolism in CAD pathogenesis, with a focus on endothelial dysfunction resulting from deficiency in the active form of folate (5-MTHF). We discuss emerging areas of research into CAD biomarkers and factors influencing the methylation process. By highlighting genetically determined methylation disorders, particularly the MTHFR polymorphism, we propose the potential use of the active form of folate (5-MTHF) as a novel CAD biomarker and personalized pharmaceutical for selected patient groups. Our aim is to improve the identification of individuals at high risk of CAD and enhance their prognosis.

Distinct genetic liability profiles define clinically relevant patient strata across common diseases.

Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases.

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Modifiable risk factors, oxidative stress markers, and SOD2 rs4880 SNP in coronary artery disease: an association study.

BACKGROUND: Coronary artery disease (CAD) has been linked to single nucleotide polymorphism (SNP) in superoxide dismutase 2 (SOD 2) gene. Additionally, several modifiable risk factors are also known to influence the CAD risk. AIM: To investigate the association between selected modifiable risk factors and oxidative stress markers with the SOD2 rs4880 SNP in CAD patients. METHODS: A cohort of 150 angiographically confirmed CAD patients, and 100 control subjects in the same geographic area were enrolled. SOD levels and lipid peroxidation were assessed in the blood samples using standard protocols. The genotyping of the SOD2 gene was conducted through the PCR-sequencing method. RESULTS: This study indicated that CAD patients with the rs4880 SNP having heterozygous AG and mutated homozygous GG genotypes have increased oxidative stress, decreased SOD activity, and a positive association with CAD risk (OR 2.85) in comparison with control individuals. The investigation among CAD patients was then carried out based on modifiable risk factors. The risk factors selected were clinical characteristics, physical habits, nutritional status, and body mass index. In all the cases, MDA levels showed a positive association, and SOD activity showed a negative association with the selected polymorphism. CONCLUSIONS: The study suggests that the selected modifiable risk factors have an important role in the higher oxidative stress found in patients, which may lead to SOD2 polymorphism. It also suggests that the SOD2 locus can be identified as a marker gene for CAD susceptibility.

Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation.

Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.

A robust cis-Mendelian randomization method with application to drug target discovery.

Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on a single genomic region using only cis-SNPs. For example, using cis-pQTLs for a protein as exposure for a disease opens a cost-effective path for drug target discovery. However, few methods effectively handle pleiotropy and linkage disequilibrium (LD) of cis-SNPs. Here, we propose cisMR-cML, a method based on constrained maximum likelihood, robust to IV assumption violations with strong theoretical support. We further clarify the severe but largely neglected consequences of the current practice of modeling marginal, instead of conditional genetic effects, and only using exposure-associated SNPs in cis-MR analysis. Numerical studies demonstrated our method's superiority over other existing methods. In a drug-target analysis for coronary artery disease (CAD), including a proteome-wide application, we identified three potential drug targets, PCSK9, COLEC11 and FGFR1 for CAD.

B-cell hub genes play a cardiovascular pathogenic role of in childhood obesity and Kawasaki disease as revealed by transcriptomics-based analyses.

The study aims to explore the central genes that Kawasaki disease (KD) and Obesity (OB) may jointly contribute to coronary artery disease. Investigating single-cell datasets (GSE168732 and GSE163830) from a comprehensive gene expression database, we identified characteristic immune cell subpopulations in KD and OB. B cells emerged as the common immune cell characteristic subgroup in both conditions. Subsequently, we analyzed RNA sequencing datasets (GSE18606 and GSE87493) to identify genes associated with B-cell subpopulations in KD and OB. Lastly, a genome-wide association study and Mendelian randomization were conducted to substantiate the causal impact of these core genes on myocardial infarction. Quantitative real-time PCR (qRT-PCR) to validate the expression levels of hub genes in KD and OB. The overlapping characteristic genes of B cell clusters in both KD and OB yielded 70 shared characteristic genes. PPI analysis led to the discovery of eleven key genes that significantly contribute to the crosstalk. Employing receiver operating characteristic analysis, we evaluated the specificity and sensitivity of these core genes and scored them using Cytoscape software. The inverse variance weighting analysis suggested an association between TNFRSF17 and myocardial infarction risk, with an odds ratio of 0.9995 (95% CI = 0.9990-1.0000, p = 0.049). By employing a single-cell combined transcriptome data analysis, we successfully pinpointed central genes associated with both KD and OB. The implications of these findings extend to shedding light on the increased risk of coronary artery disease resulting from the co-occurrence of OB and KD.

Identifying risk factors and mortality rate of premature coronary artery disease in young Saudi population.

Coronary artery disease is a leading cause of morbidity and mortality worldwide. It occurs due to a combination of genetics, lifestyle, and environmental factors. Premature coronary artery disease (PCAD) is a neglected clinical entity despite the rising number of cases worldwide. This study aimed to investigate the risk factors of premature coronary artery disease. In this study, we searched articles that had studied the risk factors of premature coronary artery diseases from January 2000 to July 2022 in Saudi Arabia in Web of Science, Pub Med, Scopus, Springer, and Wiley databases. The final analysis is based on seven articles. The smoking prevalence was 39%, diabetes mellitus 41%, hypertension 33%, overweight and obesity 18%, family history of coronary artery disease (CAD) 19%, dyslipidemia 37%, and the prevalence range of low-density lipoprotein cholesterol was 33.8-55.0%. The results revealed a mortality prevalence of 4% ranging from 2 to 8% which is similar to the prevalence in older patients which was 2-10%. Smoking, diabetes mellitus, hypertension, family history of CAD, dyslipidemia, and overweight/obesity are significantly and positively associated with premature coronary artery diseases. The health authorities should design and implement an intensive and effective prophylactic plan to minimize the subsequent impact of PCAD on the young population. In addition, early diagnosis of PCAD has great value in providing timely treatment, managing the patients, and minimizing the burden of the disease.

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.

Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes.

Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.

Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances.

BACKGROUND: Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort. METHODS: Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data. RESULTS: Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia. CONCLUSIONS: Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Impacts of ACE insertion/deletion variant on cardiometabolic risk factors, premature coronary artery disease, and severity of coronary lesions.

Angiotensin-converting enzyme (ACE) is closely related to cardiometabolic risk factors and atherosclerosis. This study aims to investigate whether the insertion/deletion (I/D) variant of ACE gene impacts cardiometabolic risk factors, premature coronary artery disease (PCAD), and severity of coronary lesions. PubMed, Cochrane Library, Central, CINAHL, and ClinicalTrials.gov were searched until December 22, 2023. 94,270 individuals were included for the analysis. Carriers of DD genotype had higher levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), and waist circumference (WC) than carriers of II or ID genotypes. In addition, carriers of DD genotype were at high risk of PCAD and multiple vessel lesions. The impacts of ACE I/D variant on lipid levels were significant in American individuals but stronger in male individuals. In contrast, the impacts of ACE I/D variant on PCAD and severity of coronary lesions were primarily significant in Caucasian individuals. This study indicates that the ACE I/D variant has a slight but significant impact on cardiometabolic risk factors, PCAD, and severity of coronary lesions. Angiotensin-converting enzyme inhibitors (ACEI) may benefit high-risk populations with ACE DD genotype to prevent PCAD and multiple vessel lesions.PROSPERO registration number: CRD42023426732.

Disparity of gene expression in coronary artery disease: insights from MEIS1, HIRA, and Myocardin.

INTRODUCTION: Coronary artery disease (CAD) in young adults can have devastating consequences. The cardiac developmental gene MEIS1 plays important roles in vascular networks and heart development. This gene effects on the regeneration capacity of the heart. Considering role of MEIS1 in cardiac tissue development and the progression of myocardial infarction this study investigated the expression levels of the MEIS1, HIRA, and Myocardin genes in premature CAD patients compared to healthy subjects and evaluated the relationships between these genes and possible inflammatory factors. METHODS AND RESULTS: The study conducted a case-control design involving 35 CAD patients and 35 healthy individuals. Peripheral blood mononuclear cells (PBMCs) were collected, and gene expression analysis was performed using real-time PCR. Compared with control group, the number of PBMCs in the CAD group exhibited greater MEIS1 and HIRA gene expression, with fold changes of 2.45 and 3.6. The expression of MEIS1 exhibited a negative correlation with IL-10 (r= -0.312) expression and positive correlation with Interleukin (IL)-6 (r = 0.415) and tumor necrosis factor (TNF)-α (r = 0.534) gene expression. Moreover, there was an inverse correlation between the gene expression of HIRA and that of IL-10 (r= -0.326), and a positive correlation was revealed between the expression of this gene and that of the IL-6 (r = 0.453) and TNF-α (r = 0.572) genes. CONCLUSION: This research demonstrated a disparity in expression levels of MEIS1, HIRA, and Myocardin, between CAD and healthy subjects. The results showed that, MEIS1 and HIRA play significant roles in regulating the synthesis of proinflammatory cytokines, namely, TNF-α and IL-6.

Homocysteine concentration in coronary artery disease and severity of coronary lesions.

Our previous study reckons that the impact of the rs1801133 variant of 5,10-methylenetetrahydrofolate reductase (MTHFR) on coronary artery disease (CAD) is possibly mediated by cardiometabolic disorder. This study is performed to verify this hypothesis. Four hundred and thirty CAD patients and 216 CAD-free individuals were enrolled in this case-control study. The rs1801133 variant was genotyped by PCR-RFLP. Severity of coronary lesions was evaluated by number of stenotic coronary vessels and extent of coronary stenosis. The rs1801133 T allele significantly increased homocysteine levels in patients with CAD and CAD-free individuals. Individuals with the T allele of rs1801133 had an increased risk of developing CAD. In contrast, individuals with the TT genotype of rs1801133 were at high risk of multiple vessel lesions. The carriers of CT genotype had higher levels of systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and high-sensitivity C-reactive protein (hs-CRP), and lower levels of apolipoprotein A1 (APOA1) than those with CC genotype in male patients with CAD. The receiver operating characteristic (ROC) curve and precision-recall (PR) curve indicated that hyperhomocysteinemia was sensitive to predict the severity of CAD. Multivariate logistic regression revealed that homocysteine, rs1801133, age, smoking, weight, body mass index (BMI), lipoprotein(a) [Lp(a)], and hs-CRP were independent risk factors for CAD. The increased risk of CAD and severity of coronary lesions associated with rs1801133 in the Chinese Han population were attributed, at least partly, to high homocysteine levels. Hyperhomocysteinemia had a high predictive value for severe CAD or multiple vessel lesions.

Epigenetics of hypertension as a risk factor for the development of coronary artery disease in type 2 diabetes mellitus.

Hypertension, a multifaceted cardiovascular disorder influenced by genetic, epigenetic, and environmental factors, poses a significant risk for the development of coronary artery disease (CAD) in individuals with type 2 diabetes mellitus (T2DM). Epigenetic alterations, particularly in histone modifications, DNA methylation, and microRNAs, play a pivotal role in unraveling the complex molecular underpinnings of blood pressure regulation. This review emphasizes the crucial interplay between epigenetic attributes and hypertension, shedding light on the prominence of DNA methylation, both globally and at the gene-specific level, in essential hypertension. Additionally, histone modifications, including acetylation and methylation, emerge as essential epigenetic markers linked to hypertension. Furthermore, microRNAs exert regulatory influence on blood pressure homeostasis, targeting key genes within the aldosterone and renin-angiotensin pathways. Understanding the intricate crosstalk between genetics and epigenetics in hypertension is particularly pertinent in the context of its interaction with T2DM, where hypertension serves as a notable risk factor for the development of CAD. These findings not only contribute to the comprehensive elucidation of essential hypertension but also offer promising avenues for innovative strategies in the prevention and treatment of cardiovascular complications, especially in the context of T2DM.

Joint association of genetic risk and accelerometer-measured physical activity with incident coronary artery disease in the UK biobank cohort.

Previous research demonstrates the joint association of self-reported physical activity and genotype with coronary artery disease. However, an existing research gap is whether accelerometer-measured overall physical activity or physical activity intensity can offset genetic predisposition to coronary artery disease. This study explores the independent and joint associations of accelerometer-measured physical activity and genetic predisposition with incident coronary artery disease. Incident coronary artery disease based on hospital inpatient records and death register data serves as the outcome of this study. Polygenic risk score and overall physical activity, measured as Euclidean Norm Minus One, and intensity, measured as minutes per day of moderate-to-vigorous intensity physical activity (MVPA), are examined both linearly and by decile. The UK Biobank population-based cohort recruited over 500,000 individuals aged 40 to 69 between 2006 and 2010, with 103,712 volunteers participating in a weeklong wrist-worn accelerometer study from 2013 to 2015. Individuals of White British ancestry (n = 65,079) meeting the genotyping and accelerometer-based inclusion criteria and with no missing covariates were included in the analytic sample. In the sample of 65,079 individuals, the mean (SD) age was 62.51 (7.76) and 61% were female. During a median follow-up of 6.8 years, 1,382 cases of coronary artery disease developed. At the same genetic risk, physical activity intensity had a hazard ratio (HR) of 0.41 (95% CI: 0.29-0.60) at the 90th compared to 10th percentile, equivalent to 31.68 and 120.96 minutes of moderate-to-vigorous physical activity per day, respectively, versus an HR of 0.61 (95% CI: 0.52-0.72) for overall physical activity. The combination of high genetic risk and low physical activity intensity showed the greatest risk, with an individual at the 10th percentile of genetic risk and 90th percentile of intensity facing an HR of 0.14 (95% CI: 0.09-0.21) compared to an individual at the 90th percentile of genetic risk and 10th percentile of intensity. Physical activity, especially physical activity intensity, is associated with an attenuation of some of the risk of coronary artery disease but this pattern does not vary by genetic risk. This accelerometer-based study provides the clearest evidence to date regarding the joint influence of genetics, overall physical activity, and physical activity intensity on coronary artery disease.

MSGene: a multistate model using genetic risk and the electronic health record applied to lifetime risk of coronary artery disease.

Coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods lack the ability to incorporate new information throughout the life course or to combine innate genetic risk factors with acquired lifetime risk. We designed a general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. This model is designed to handle longitudinal data over the lifetime to address this unmet need and support clinical decision-making. We analyze longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improves discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), in held-out data. We also use MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore our multistate model's potential public health value for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics toward earlier more effective prevention.

Identification and verification of circRNA biomarkers for coronary artery disease based on WGCNA and the LASSO algorithm.

BACKGROUND: The role of circular RNAs (circRNAs) as biomarkers of coronary artery disease (CAD) remains poorly explored. This study aimed to identify and validate potential circulating circRNAs as biomarkers for the diagnosis of CAD. METHODS: The expression profile of circRNAs associated with CAD was obtained from Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operation (LASSO) were employed to identify CAD-related hub circRNAs. The expression levels of these hub circRNAs were validated using qRT-PCR in blood samples from 100 CAD patients and 100 controls. The diagnostic performance of these circRNAs was evaluated through logistic regression analysis, receiver operator characteristic (ROC) analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Functional enrichment analyses were performed to predict the possible mechanisms of circRNAs in CAD. RESULTS: A total of ten CAD-related hub circRNAs were identified through WGCNA and LASSO analysis. Among them, hsa_circ_0069972 and hsa_circ_0021509 were highly expressed in blood samples of CAD patients, and they were identified as independent predictors after adjustment for relevant confounders. The area under the ROC curve for hsa_circ_0069972 and hsa_circ_0021509 was 0.760 and 0.717, respectively. The classification of patients was improved with the incorporation of circRNAs into the clinical model composed of conventional cardiovascular risk factors, showing an IDI of 0.131 and NRI of 0.170 for hsa_circ_0069972, and an IDI of 0.111 and NRI of 0.150 for hsa_circ_0021509. Functional enrichment analyses revealed that the hsa_circ_0069972-miRNA-mRNA network was enriched in TGF-ß、FoxO and Hippo signaling pathways, while the hsa_circ_0021509-miRNA-mRNA network was enriched in PI3K/Akt and MAPK signaling pathways. CONCLUSION: Hsa_circ_0069972 and hsa_circ_0021509 were identified by integrated analysis, and they are highly expressed in CAD patients. They may serve as novel biomarkers for CAD.

A systematic review and bioinformatic study on clinical, paraclinical, and genetic factors predisposing to stent restenosis following percutaneous coronary intervention.

BACKGROUND: Stent restenosis is a relatively common phenomenon among patients with coronary heart disease undergoing percutaneous coronary intervention (PCI). It seems that a set of clinical, laboratory, and even genetic factors make people susceptible to such a phenomenon and in fact, this is multi-factorial. We aimed to first determine the underlying clinical and laboratory risk factors for the occurrence of stent re-stenosis after PCI based on a systematic review study, and after that, through a bioinformatics study, to evaluate the related genes and microRNAs with the occurrence of stent re-stenosis. MAIN TEXT: In the first step, the manuscript databases including Medline, Web of Knowledge, Google Scholar, Scopus, and Cochrane were deeply searched by the two blinded investigators for all eligible studies based on the considered keywords to introduce clinical and laboratory determinants of stent re-stenosis. In the bioinformatic phase, and following a review of the literature to identify genes and microRNAs involved in restenosis, the interaction of each gene with other genes associated with stent re-stenosis was determined by GeneMANIA network analysis and Cytoscape software. Overall, 67 articles (including 40,789 patients) on clinical and biochemical predictors for stent restenosis and 25 articles on genetic determinants of this event were eligible for the final analysis. The predictors for this event were categorized into four subgroups patient-based parameters including traditional cardiovascular risk profiles, stent-based parameters including type and diametric characteristics of the stents used, coronary lesion-based parameters including several two target lesions and coronary involvement severity and laboratory-based parameters particularly related to activation of inflammatory processes. In the bioinformatic phase, we uncovered 42 genes that have been described to be involved in such a phenomenon considering a special position for genes encoding inflammatory cytokines. Also, 12 microRNAs have been pointed to be involved in targeting genes involved in stent re-stenosis. CONCLUSIONS: The incidence of stent re-stenosis will be the result of a complex interaction of clinical risk factors, laboratory factors mostly related to the activation of inflammatory processes, and a complex network of gene-to-gene interactions.