Heritability of death from coronary heart disease: a 36-year follow-up of 20 966 Swedish twins

What Causes Premature Coronary Artery Disease?

PURPOSE OF REVIEW

This review provides an overview of genetic and non-genetic causes of premature coronary artery disease (pCAD).

RECENT FINDINGS

pCAD refers to coronary artery disease (CAD) occurring before the age of 65 years in women and 55 years in men. Both genetic and non-genetic risk factors may contribute to the onset of pCAD. Recent advances in the genetic epidemiology of pCAD have revealed the importance of both monogenic and polygenic contributions to pCAD. Familial hypercholesterolemia (FH) is the most common monogenic disorder associated with atherosclerotic pCAD. However, clinical overreliance on monogenic genes can result in overlooked genetic causes of pCAD, especially polygenic contributions. Non-genetic factors, notably smoking and drug use, are also important contributors to pCAD. Cigarette smoking has been observed in 25.5% of pCAD patients relative to 12.2% of non-pCAD patients. Finally, myocardial infarction (MI) associated with spontaneous coronary artery dissection (SCAD) may result in similar clinical presentations as atherosclerotic pCAD. Recognizing the genetic and non-genetic causes underlying pCAD is important for appropriate prevention and treatment. Despite recent progress, pCAD remains incompletely understood, highlighting the need for both awareness and research.

Gender disparities in all-cause mortality among individuals with early-onset cardiovascular diseases

BACKGROUND AND OBJECTIVE

Gender disparities in mortality among individuals with early-onset cardiovascular disease (CVD) remain uncertain. This study aimed to investigate gender differences in all-cause mortality and identify influencing factors.

METHODS

Data extracted from the Kailuan Study, a prospective cohort study initiated in 2006, were analyzed. A total of 2,829 participants with early-onset CVD were included. Cox proportional hazard models were used to assess hazard ratios (HR) and 95% confidence intervals (CI) for gender disparities in all-cause mortality, adjusting for various factors.

RESULTS

Males experienced a median follow-up duration of 7.54 years with 276 recorded deaths, and females had a median follow-up of 6.45 years with 105 recorded deaths. Gender disparities in all-cause mortality were observed, with men experiencing a higher all-cause mortality risk compared to women (HR: 1.42, 95% CI: 1.04, 1.92) in the fully adjusted model. Both in men and women with early-onset CVD, elevated hs-CRP levels and an eGFR < 60 mL/min/1.73m2 notably escalated the risk of all-cause mortality. Furthermore, the utilization of antiplatelet agents and successful blood glucose control might mitigate the risk of all-cause mortality. Smoking and eGFR decline modified the association between gender and all-cause death, women were more vulnerable to tobacco consumption and kidney misfunctioning than men (P-interaction = 0.019).

CONCLUSION

The study highlights gender disparities in all-cause mortality among individuals with early-onset CVD, with men experiencing a higher risk of mortality compared to women. Addressing these disparities is important for improving outcomes in this population. Further research is needed to develop sex-specific interventions and strategies to reduce gender-related mortality disparities in early-onset CVD.

Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis

The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.

Long-term PM2.5 exposure associated with severity of angina pectoris and related health status in patients admitted with acute coronary syndrome: Modification effect of genetic susceptibility and disease history

Long-term particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) exposure has been associated with the occurrence of acute coronary syndrome (ACS). However, the impact of PM2.5 exposure and its components on the severity of angina pectoris and disease-related health status in patients hospitalized for ACS is understudied. To assess the association between long-term exposure to PM2.5 components and the angina pectoris severity in ACS patients, as well as the modification effects of genetic factors and disease history in north China. During 2017-2019, 6729 ACS patients were collected in Shandong Province and Beijing, with their angina pectoris severity evaluated using Seattle Angina Questionnaire (SAQ). The 0-3 years' average concentrations of PM2.5 and its five major components were assigned to each patient's residential address. Linear mixed-effects model, weighted quantile regression, and quantile g-computation were used to estimate the effects of both single and joint associations between PM2.5 components and SAQ scores. The interactive effect was estimated by polygenic risk scores and disease history. For each interquartile range increase in PM2.5, the overall SAQ score changed by -3.71% (95%CI: -4.54% to -2.88%), with score of angina stability more affected than angina frequency and other dimensions of angina pectoris severity. Sulfate and ammonium were major contributors to the effect of PM2.5 exposure. Significant modification effect was only observed for disease history, especially for the dimension of physical limitation. Among a series of pre-existing diseases, patients with a family history of coronary artery disease, previous percutaneous coronary intervention or coronary artery bypass grafting, and stroke were more susceptible to PM2.5 exposure than others. Greater exposure to PM2.5 is associated with more serious angina pectoris and worse disease-related health status in ACS patients. Public health and clinical priority should be given to cutting down key effective components and protecting highly vulnerable individuals.

Genetic testing in cardiovascular disease

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally and is responsible for an estimated one-third of deaths as well as significant morbidity and health care utilisation. Technological and bioinformatic advances have facilitated the discovery of pathogenic germline variants for some specific CVDs, including familial hypercholesterolaemia, cardiomyopathies and arrhythmic syndromes. Use of these genetic tests for earlier disease identification is increasing due, in part, to decreasing costs, Medicare rebates, and consumer comfort with genetic testing. However, CVDs that occur more commonly, including coronary artery disease and atrial fibrillation, do not display monogenic inheritance patterns. Genetically, these diseases have generally been associated with many genetic variants each with a small effect size. This complexity can be expressed mathematically as a polygenic risk score. Genetic testing kits that provide polygenic risk scoring are becoming increasingly available directly to private-paying consumers outside the traditional clinical setting. An improved understanding of the evidence of genetics in CVD will offer clinicians new opportunities for individualised risk prediction and preventive therapy.

Genetic, lifestyle and metabolic factors contributing to cardiovascular disease in the Italian population: a literature review

Cardiovascular diseases (CVD) represent a major health problem worldwide. In Italy, despite the decline in CVD mortality and disability-adjusted life years recently observed, CVD remains the leading cause of death. The development of CVD has a complex and multifactorial etiology that involves environmental, lifestyle/behavioral (e.g., unhealthy diet, physical inactivity, smoking, and alcohol abuse), metabolic, and genetic factors. Although a large number of CVD susceptibility genetic variants have been identified, some seem to confer risk according to the genetic background or ethnicity of the population. Some CVD-associated polymorphisms with appreciable frequency in the Italian population may be important contributors to the development and progression of the most prevalent CVD in the population. This literature review aims to provide an overview of the epidemiology of CVD in Italy, as well as to highlight the main genetic, lifestyle/behavioral, and metabolic factors contributing to CVD risk in this population.

Evaluating cardiovascular disease risk stratification using multiple-polygenic risk scores and pooled cohort equations: insights from a 17-year longitudinal Korean cohort study

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.

Lifestyle factors, genetic susceptibility to obesity and their interactions on coronary artery disease risk: A cohort study in the UK Biobank

OBJECTIVE

We aimed to evaluate potential modifying effects of genetic susceptibility to obesity on the association of lifestyle factors with coronary artery disease (CAD) risk.

METHODS

A total of 328,606 participants (54% women) were included using data from the UK Biobank. We evaluated the risk of developing CAD associated with obesity-related polygenic scores (PGSs) and healthy lifestyle scores (HLSs). HLSs were constructed using six lifestyle factors. Obesity PGSs were created using genetic variants identified by genome-wide association studies, including 941 variants for body mass index (BMI) and 457 for waist-to-hip ratio (WHR). Both HLSs and PGSs were categorized into three groups.

RESULTS

During a 9-year median follow-up, 14,541 participants developed CAD. An unhealthy lifestyle was significantly associated with an increased CAD risk (hazard ratio [HR] = 2.24, 95% confidence interval [CI] = 2.09-2.40). High BMI and WHR PGSs were each significantly associated with an increased CAD risk (HRBMI = 1.23, 1.17-1.29; HRWHR = 1.15, 1.09-1.21). Lifestyle factors explained 41% (95% CI = 38%-45%) of CAD, while genetic variants for BMI explained only 10% (7%-14%). Risks of CAD were increased with poorer HLS independent of obesity-related PGSs. Individuals with the most unhealthy lifestyle and highest BMI PGS had the highest risk of CAD risk (HR = 2.59, 95% CI = 2.26-2.97), compared with participants with the healthiest lifestyle and lowest BMI PGS.

CONCLUSIONS

While the observational nature of the study precludes the establishment of causality, our study provides supports for a causal association between obesity and CAD risk and the importance of lifestyle modification in the prevention of CAD.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Use of Machine Learning for the Identification and Validation of Immunogenic Cell Death Biomarkers and Immunophenotypes in Coronary Artery Disease

Objective

Immunogenic cell death (ICD) is part of the immune system's response to coronary artery disease (CAD). In this study, we bioinformatically evaluated the diagnostic and therapeutic utility of immunogenic cell death-related genes (IRGs) and their relationship with immune infiltration features in CAD.

Methods

We acquired the CAD-related datasets GSE12288, GSE71226, and GSE120521 from the Gene Expression Omnibus (GEO) database and the IRGs from the GeneCards database. After identifying the immune cell death-related differentially expressed genes (IRDEGs), we developed a risk model and detected immune subtypes in CAD. IRDEGs were identified using least absolute shrinkage and selection operator (LASSO) analysis. Using a nomogram, we confirmed that both the LASSO model and ICD signature genes had good diagnostic performance.

Results

There was a high degree of coincidence and immune representativeness between two CAD groups based on characteristic genes and hub genes. Hub genes were associated with the interaction of neuroactive ligands with receptors and cell adhesion receptors. The two groups differed in terms of adipogenesis, allograft rejection, and apoptosis, as well as the ICD signature and hub gene expression levels. The two CAD-ICD subtypes differed in terms of immune infiltration.

Conclusion

Quantitative real-time PCR (qRT-PCR) correlated CAD with the expression of OAS3, ITGAV, and PIBF1. The ICD signature genes are candidate biomarkers and reference standards for immune grouping in CAD and can be beneficial in precise immune-targeted therapy.

Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance

Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.

Association of air pollution exposure and increased coronary artery disease risk: the modifying effect of genetic susceptibility

BACKGROUND

Both genetic factors and air pollution are risk factors for coronary artery disease (CAD), but their combined effects on CAD are uncertain. The study aimed to comprehensively investigate their separate, combined and interaction effects on the onset of CAD.

METHODS

We utilized data from the UK Biobank with a recruitment of 487,507 participants who were free of CAD at baseline from 2006 to 2010. We explored the separate, combined effect or interaction association among genetic factors, air pollution and CAD with the polygenic risk score (PRS) and Cox proportional hazard models.

RESULTS

The hazard ratios (HRs) [95% confidence interval (CI)] of CAD for 10-µg/m3 increases in PM2.5, NO2 and NOx concentrations were 1.25 (1.09, 1.44), 1.03 (1.01, 1.05) and 1.01 (1.00, 1.02), respectively. Participants with high PRS and air pollution exposure had a higher risk of CAD than those with the low genetic risk and low air pollution exposure, and the HRs (95% CI) of CAD in the PM2.5, PM10, NO2 and NOx high joint exposure groups were 1.56 (1.48, 1.64), 1.55(1.48, 1.63), 1.57 (1.49, 1.65), and 1.57 (1.49, 1.65), respectively. Air pollution and genetic factors exerted significant additive effects on the development of CAD (relative excess risk due to the interaction [RERI]: 0.12 (0.05, 0.19) for PM2.5, 0.17 (0.10, 0.24) for PM10, 0.14 (0.07, 0.21) for NO2, and 0.17 (0.10, 0.24) for NOx; attributable proportion due to the interaction [AP]: 0.09 (0.04, 0.14) for PM2.5, 0.12 (0.07, 0.18) for PM10, 0.11 (0.06, 0.16) for NO2, and 0.13 (0.08, 0.18) for NOx).

CONCLUSION

Exposure to air pollution was significantly related to an increased CAD risk, which could be further strengthened by CAD gene susceptibility. Additionally, there were positive additive interactions between genetic factors and air pollution on the onset of CAD. This can provide a more comprehensive, precise and individualized scientific basis for the risk assessment, prevention and control of CAD.

Clinical applications of polygenic risk score for coronary artery disease through the life course

Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide, highlighting the limitations of current primary and secondary prevention frameworks. In this review, we detail how the polygenic risk score for CAD can improve our current preventive and treatment frameworks across three clinical applications that span the life course: (i) identification and treatment of people at increased risk early in the life course prior to the onset of clinical risk factors, (ii) improving the precision around risk estimation in middle age, and (ii) guiding treatment decisions and enabling more efficient clinical trials even after the onset of CAD. We end by summarizing the efforts needed as we head towards more widespread use of polygenic risk score for CAD in clinical practice.

Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study

Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.

Ancestry-specific polygenic risk scores are risk enhancers for clinical cardiovascular disease assessments

Clinical implementation of new prediction models requires evaluation of their utility in a broad range of intended use populations. Here we develop and validate ancestry-specific Polygenic Risk Scores (PRSs) for Coronary Artery Disease (CAD) using 29,389 individuals from diverse cohorts and genetic ancestry groups. The CAD PRSs outperform published scores with an average Odds Ratio per Standard Deviation of 1.57 (SD = 0.14) and identify between 12% and 24% of individuals with high genetic risk. Using this risk factor to reclassify borderline or intermediate 10 year Atherosclerotic Cardiovascular Disease (ASCVD) risk improves assessments for both CAD (Net Reclassification Improvement (NRI) = 13.14% (95% CI 9.23-17.06%)) and ASCVD (NRI = 10.70 (95% CI 7.35-14.05)) in an independent cohort of 9,691 individuals. Our analyses demonstrate that using PRSs as Risk Enhancers improves ASCVD risk assessments outlining an approach for guiding ASCVD prevention with genetic information.

Genetic and Nongenetic Components of Stroke Family History: A Population Study of Adopted and Nonadopted Individuals

Background Genetic and nongenetic factors account for the association of family history with disease risk. Comparing adopted and nonadopted individuals provides an opportunity to disentangle those factors. Methods and Results We examined associations between family history of stroke and heart disease with incident stroke and myocardial infarction (MI) in 495 640 UK Biobank participants (mean age, 56.5 years; 55% women) stratified by childhood adoption status (5747 adoptees). We estimated hazard ratios (HRs) per affected family member, and for polygenic risk scores in Cox models adjusted for baseline age and sex. A total of 12 518 strokes and 23 923 MIs occurred over a 13-year follow-up. In nonadoptees, family history of stroke and heart disease was associated with increased stroke and MI risk, with the strongest association of family history of stroke for incident stroke (HR, 1.16 [95% CI, 1.12-1.19]) and family history of heart disease for incident MI (HR, 1.48 [95% CI, 1.45-1.50]). In adoptees, family history of stroke associated with incident stroke (HR, 1.41 [95% CI, 1.06-1.86]), but family history of heart disease was not associated with incident MI (P>0.5). Polygenic risk scores showed strong disease-specific associations in both groups. In nonadoptees, the stroke polygenic risk score mediated 6% risk between family history of stroke and incident stroke, and the MI polygenic risk score mediated 13% risk between family history of heart disease and incident MI. Conclusions Family history of stroke and heart disease increases risk for their respective conditions. Family history of stroke contains substantial potentially modifiable nongenetic risk, indicating a need for novel prevention strategies, whereas family history of heart disease represents predominantly genetic risk.

Clinical utility of polygenic risk scores: a critical 2023 appraisal

Since their first appearance in the context of schizophrenia and bipolar disorder in 2009, polygenic risk scores (PRSs) have been described for a large number of common complex diseases. However, the clinical utility of PRSs in disease risk assessment or therapeutic decision making is likely limited because PRSs usually only account for the heritable component of a trait and ignore the etiological role of environment and lifestyle. We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare. In conclusion, the benefit to individual patients or the health care system in general of PRS-based extensions of existing diagnostic or treatment regimens is still difficult to judge.

The Genetics of Coronary Artery Disease: A Vascular Perspective

Genome-wide association studies (GWAS) have identified a large number of genetic loci for coronary artery disease (CAD), with many located close to genes associated with traditional CAD risk pathways, such as lipid metabolism and inflammation. It is becoming evident with recent CAD GWAS meta-analyses that vascular pathways are also highly enriched and present an opportunity for novel therapeutics. This review examines GWAS-enriched vascular gene loci, the pathways involved and their potential role in CAD pathogenesis. The functionality of variants is explored from expression quantitative trait loci, massively parallel reporter assays and CRISPR-based gene-editing tools. We discuss how this research may lead to novel therapeutic tools to treat cardiovascular disorders.

Evolutionary Action-Machine Learning Model Identifies Candidate Genes Associated With Early-Onset Coronary Artery Disease

Background Coronary artery disease is a primary cause of death around the world, with both genetic and environmental risk factors. Although genome-wide association studies have linked >100 unique loci to its genetic basis, these only explain a fraction of disease heritability. Methods and Results To find additional gene drivers of coronary artery disease, we applied machine learning to quantitative evolutionary information on the impact of coding variants in whole exomes from the Myocardial Infarction Genetics Consortium. Using ensemble-based supervised learning, the Evolutionary Action-Machine Learning framework ranked each gene's ability to classify case and control samples and identified 79 significant associations. These were connected to known risk loci; enriched in cardiovascular processes like lipid metabolism, blood clotting, and inflammation; and enriched for cardiovascular phenotypes in knockout mouse models. Among them, INPP5F and MST1R are examples of potentially novel coronary artery disease risk genes that modulate immune signaling in response to cardiac stress. Conclusions We concluded that machine learning on the functional impact of coding variants, based on a massive amount of evolutionary information, has the power to suggest novel coronary artery disease risk genes for mechanistic and therapeutic discoveries in cardiovascular biology, and should also apply in other complex polygenic diseases.

Improving Genetic Association Studies with a Novel Methodology that Unveils the Hidden Complexity of All-Cause Heart Failure

Motivation

Genome-Wide Association Studies (GWAS) commonly assume phenotypic and genetic homogeneity that is not present in complex conditions. We designed Transformative Regression Analysis of Combined Effects (TRACE), a GWAS methodology that better accounts for clinical phenotype heterogeneity and identifies gene-by-environment (GxE) interactions. We demonstrated with UK Biobank (UKB) data that TRACE increased the variance explained in All-Cause Heart Failure (AHF) via the discovery of novel single nucleotide polymorphism (SNP) and SNP-by-environment (i.e. GxE) interaction associations. First, we transformed 312 AHF-related ICD10 codes (including AHF) into continuous low-dimensional features (i.e., latent phenotypes) for a more nuanced disease representation. Then, we ran a standard GWAS on our latent phenotypes to discover main effects and identified GxE interactions with target encoding. Genes near associated SNPs subsequently underwent enrichment analysis to explore potential functional mechanisms underlying associations. Latent phenotypes were regressed against their SNP hits and the estimated latent phenotype values were used to measure the amount of AHF variance explained.

Results

Our method identified over 100 main GWAS effects that were consistent with prior studies and hundreds of novel gene-by-smoking interactions, which collectively accounted for approximately 10% of AHF variance. This represents an improvement over traditional GWAS whose results account for a negligible proportion of AHF variance. Enrichment analyses suggested that hundreds of miRNAs mediated the SNP effect on various AHF-related biological pathways. The TRACE framework can be applied to decode the genetics of other complex diseases.

Availability

All code is available at https://github.com/EpistasisLab/latent_phenotype_project.

Increasing number of long-lived ancestors marks a decade of healthspan extension and healthier metabolomics profiles

Globally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2143 families containing index persons with 26 follow-up years and two ancestral generations, comprising 17,539 persons. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that both lifespan and healthspan are quantitatively linked to ancestral longevity, making family data invaluable to identify protective mechanisms of multimorbidity.

Chromosome Y Haplogroup R Was Associated with the Risk of Premature Myocardial Infarction with ST-Elevation: Data from the CholeSTEMI Registry

Cardiovascular disease (CVD) is the leading cause of death worldwide, with coronary artery disease (CAD) being one of its main manifestations. Both environmental and genetic factors are widely known to be related to CAD, such as smoking, diabetes mellitus, dyslipidemia, and a family history of CAD. However, there is still a lack of information about other risk factors, especially those related to genetic mutations. Sex represents a classic CAD risk factor, as men are more likely to suffer CAD, but there is lack of evidence with regard to sex-specific genetic factors. We evaluated the Y chromosome haplogroups in a cohort of young Spanish male patients who suffered from STEMI. In this cohort, haplogroup R was significantly more frequent in STEMI patients.

Genetic Risk Factors Related to Coronary Artery Disease and Role of Transforming Growth Factor Beta 1 Polymorphisms

Coronary artery disease (CAD) is one of the leading causes of mortality globally and has long been known to be heritable; however, the specific genetic factors involved have yet to be identified. Recent advances have started to unravel the genetic architecture of this disease and set high expectations about the future use of novel susceptibility variants for its prevention, diagnosis, and treatment. In the past decade, there has been major progress in this area. New tools, like common variant association studies, genome-wide association studies, meta-analyses, and genetic risk scores, allow a better understanding of the genetic risk factors driving CAD. In recent years, researchers have conducted further studies that confirmed the role of numerous genetic factors in the development of CAD. These include genes that affect lipid and carbohydrate metabolism, regulate the function of the endothelium and vascular smooth muscles, influence the coagulation system, or affect the immune system. Many CAD-associated single-nucleotide polymorphisms have been identified, although many of their functions are largely unknown. The inflammatory process that occurs in the coronary vessels is very important in the development of CAD. One important mediator of inflammation is TGFβ1. TGFβ1 plays an important role in the processes leading to CAD, such as by stimulating macrophage and fibroblast chemotaxis, as well as increasing extracellular matrix synthesis. This review discusses the genetic risk factors related to the development of CAD, with a particular focus on polymorphisms of the transforming growth factor β (TGFβ) gene and its receptor.

Polymorphisms of TRIB1 Genes for Coronary Artery Disease and Stroke Risk: A Systematic Review and Meta-analysis

BACKGROUND AND AIMS

In recent years, the results of the association between Tribbles Pseudokinase 1 (TRIB1) gene polymorphism and the risk of coronary artery disease (CAD) and stroke are inconsistent. This study aimed to systematically review the literature on TRIB1 gene polymorphisms and susceptibility to coronary atherosclerotic heart disease (CAD) and stroke.

METHODS

This study collected studies published until May 2022 through a systematic search of PubMed, Web of Science, and Google Scholar databases. After a systematic literature search, pooled odds ratio (OR) and their corresponding 95% confidence interval (CI) were used to assess the strength of the association.

RESULTS

We identified 6 studies on rs17321515, including 12892 controls and 4583 patients, and 3 on rs2954029, including 1732 controls and 1305 patients. In different genetic models, the rs2954029 genetic polymorphism significantly increased the risk of CAD and stroke. In the codominant model, the AA genotype increased the risk of CAD and stroke (OR=1.74, 95% CI=1.39-2.17, P<0.001); the TA genotype also increased the prevalence of CAD and stroke risk (OR=1.39, 95% CI=1.18-1.64, P<0.001). Compared with the control group, the TT+TA genotype increased the risk of CAD and stroke in the dominant genetic model (OR=1.46, 95%CI=1.25-1.71, P<0.001), and in the recessive model, the TA+AA genotype increased the risk of CAD and stroke (OR=1.41, 95% CI=1.15-1.72, P<0.001). In addition, the TRIB1 rs17321515 polymorphism was not found to be associated with the risk of CAD and stroke, which may be related to other factors such as race.

CONCLUSIONS

The rs2954029 A allele was significantly associated with an increased risk of CAD and stroke, according to the present meta-analysis. However, the association of rs17321515 polymorphism with susceptibility to CAD and stroke has not been found in this study.

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Alcohol consumption and lower risk of cardiovascular and all-cause mortality: the impact of accounting for familial factors in twins

BACKGROUND

A moderate to high alcohol consumption is associated with a lower risk of cardiovascular disease (CVD) mortality in comparison with low consumption. The mechanisms underlying this association are not clear and have been suggested to be caused by residual confounding. The main objective of this study was to separate the familial and individual risk for CVD mortality and all-cause mortality related to alcohol consumption. This will be done by estimating the risk for CVD mortality and all-cause mortality in twin pairs discordant for alcohol consumption.

METHODS

Alcohol consumption was assessed at two time points using self-report questionnaires in the Norwegian Twin Registry. Data on CVD mortality was obtained from the Norwegian Cause of Death Registry. Exposure-outcome associations for all-cause mortality and mortality due to other causes than CVD were estimated for comparison.

RESULTS

Coming from a family with moderate to high alcohol consumption was protective against cardiovascular death (HR = 0.54, 95% CI 0.65-0.83). Moderate and high alcohol consumption levels were associated with a slightly increased risk of CVD mortality at the individual level (HR = 1.33, 95% CI 1.02-1.73). There was no association between alcohol consumption and all-cause mortality both at the familial nor at the individual level.

CONCLUSIONS

The protective association of moderate to high alcohol consumption with a lower risk of CVD mortality was accounted for by familial factors in this study of twins. Early life genetic and environmental familial factors may mask an absence of health effect of moderate to high alcohol consumption on cardiovascular mortality.

Transcriptome-wide association study reveals novel susceptibility genes for coronary atherosclerosis

Background

Genetic risk factors substantially contributed to the development of coronary atherosclerosis. Genome-wide association study (GWAS) has identified many risk loci for coronary atherosclerosis, but the translation of these loci into therapeutic targets is limited for their location in non-coding regions. Here, we aimed to screen the potential coronary atherosclerosis pathogenic genes expressed though TWAS (transcriptome wide association study) and explore the underlying mechanism association.

Methods

Four TWAS approaches (PrediXcan, JTI, UTMOST, and FUSION) were used to screen genes associated with coronary atherosclerosis. Enrichment analysis of TWAS-identified genes was applied through the Metascape website. The summary-data-based Mendelian randomization (SMR) analysis was conducted to provide the evidence of causal relationship between the candidate genes and coronary atherosclerosis. At last, the cell type-specific expression of the intersection genes was examined by using human coronary artery single-cell RNA-seq, interrogating the immune microenvironment of human coronary atherosclerotic plaque at different stages of maturity.

Results

We identified 19 genes by at least three approaches and 1 gene (NBEAL1) by four approaches. Enrichment analysis enriching the genes identified at least by two TWAS approaches, suggesting that these genes were markedly enriched in asthma and leukocyte mediated immunity reaction. Further, the summary-data-based Mendelian randomization (SMR) analysis provided the evidence of causal relationship between NBEAL1 gene and coronary atherosclerosis, confirming the protecting effects of NBEAL1 gene and coronary atherosclerosis. At last, the single cell cluster analysis demonstrated that NBEAL1 gene has differential expressions in macrophages, plasma cells and endothelial cells.

Conclusion

Our study identified the novel genes associated with coronary atherosclerosis and suggested the potential biological function for these genes, providing insightful guidance for further biological investigation and therapeutic approaches development in atherosclerosis-related diseases.

Genetic and non-genetic components of family history of stroke and heart disease: a population-based study among adopted and non-adopted individuals

Background

It is increasingly clear that genetic and non-genetic factors account for the association of family history with disease risk in offspring. We sought to distinguish the genetic and non-genetic contributions of family history of stroke and heart disease on incident events by examining adopted and non-adopted individuals.

Methods

We examined associations between family history of stroke and heart disease with incident stroke and myocardial infarction (MI) in 495,640 participants of the UK Biobank (mean age 56.5 years, 55% female) stratified by early childhood adoption status into adoptees (n=5,747) and non-adoptees (n=489,893). We estimated hazard ratios (HRs) per affected nuclear family member, and for polygenic risk scores (PRS) for stroke and MI in Cox models adjusted for baseline age and sex.

Results

12,518 strokes and 23,923 MIs occurred over a 13-year follow-up. In non-adoptees, family history of stroke and heart disease were associated with increased stroke and MI risk, with the strongest association of family history of stroke for incident stroke (HR 1.16 [1.12, 1.19]) and family history of heart disease for incident MI (HR 1.48 [1.45, 1.50]). In adoptees, family history of stroke associated with incident stroke (HR 1.41 [1.06, 1.86]), but family history of heart disease did not associate with incident MI (p>0.5). PRS showed strong disease-specific associations in adoptees and non-adoptees. In non-adoptees, the stroke PRS mediated 6% risk between family history of stroke and incident stroke, and the MI PRS mediated 13% risk between family history of heart disease and MI.

Conclusions

Family history of stroke and heart disease increase risk for their respective conditions. Family history of stroke contains a substantial proportion of potentially modifiable non-genetic risk, indicating a need for further research to elucidate these elements for novel prevention strategies, whereas family history of heart disease represents predominantly genetic risk.

Differences in genetic risk score profiles for drug use disorder, major depression, and ADHD as a function of sex, age at onset, recurrence, mode of ascertainment, and treatment

BACKGROUND

Do genetic risk profiles for drug use disorder (DUD), major depression (MD), and attention-deficit hyperactivity disorder (ADHD) differ substantially as a function of sex, age at onset (AAO), recurrence, mode of ascertainment, and treatment?

METHODS

Family genetic risk scores (FGRS) for MD, anxiety disorders, bipolar disorder, schizophrenia, alcohol use disorder, DUD, ADHD, and autism-spectrum disorder were calculated from 1st-5th degree relatives in the Swedish population born 1932-1995 (n = 5 829 952). Profiles of these FGRS were obtained and compared across various subgroups of DUD, MD, and ADHD cases.

RESULTS

Differences in FGRS profiles for DUD, MD, and ADHD by sex were modest, but they varied substantially by AAO, recurrence, ascertainment, and treatment with scores typically higher in cases with greater severity (e.g. early AAO, high recurrence, ascertainment in high intensity clinical settings, and treatment). However, severity was not always related to purer genetic profiles, as genetic risk for many disorders often increased together. However, some results, such as by mode of ascertainment from different Swedish registries, produced qualitative differences in FGRS profiles.

CONCLUSIONS

Differences in FGRS profiles for DUD, MD, and ADHD varied substantially by AAO, recurrence, ascertainment, and treatment. Replication of psychiatric studies, particularly those examining genetic factors, may be difficult unless cases are matched not only by diagnosis but by important clinical characteristics. Genetic correlations between psychiatric disorders could arise through one disorder impacting on the patterns of ascertainment for the other, rather than from the direct effects of shared genetic liabilities.

The Acute and Chronic Effects of Resistance and Aerobic Exercise in Hemostatic Balance: A Brief Review

Hemostatic balance refers to the dynamic balance between blood clot formation (coagulation), blood clot dissolution (fibrinolysis), anticoagulation, and innate immunity. Although regular habitual exercise may lower the incidence of cardiovascular diseases (CVD) by improving an individual’s hemostatic profile at rest and during exertion, vigorous exercise may increase the risk of sudden cardiac death and venous thromboembolism (VTE). This literature review aims to investigate the hemostatic system’s acute and chronic adaptive responses to different types of exercise in healthy and patient populations. Compared to athletes, sedentary healthy individuals demonstrate similar post-exercise responses in platelet function and coagulatory and fibrinolytic potential. However, hemostatic adaptations of patients with chronic diseases in regular training is a promising field. Despite the increased risk of thrombotic events during an acute bout of vigorous exercise, regular exposure to high-intensity exercise might desensitize exercise-induced platelet aggregation, moderate coagulatory parameters, and up-regulate fibrinolytic potential via increasing tissue plasminogen activator (tPA) and decreasing plasminogen activator inhibitor (PAI-1) response. Future research might focus on combining different types of exercise, manipulating each training characteristic (frequency, intensity, time, and volume), or investigating the minimal exercise dosage required to maintain hemostatic balance, especially in patients with various health conditions.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Lifestyle Factors, Genetic Risk, and Cardiovascular Disease Risk among Breast Cancer Survivors: A Prospective Cohort Study in UK Biobank

BACKGROUND

Evidence is limited regarding the association between lifestyles and cardiovascular disease (CVD), and the extent to which healthy lifestyles could offset the genetic risk of CVD in females with breast cancer (BC).

METHODS

Females diagnosed as BC, who were free of CVD at baseline, from UK Biobank were included. Five modifiable lifestyle factors were considered to calculate the healthy lifestyle score, namely body mass index (BMI), smoking, alcohol drinking, dietary habits, and physical activity. The polygenetic risk score (PRS) was derived for coronary heart disease (CHD), ischemic stroke (IS), and heart failure (HF).

RESULTS

In 13,348 female BC survivors, there were 986 CVD events (736 CHD, 165 IS, and 353 HF) over a median of 8.01 years of follow-up. Participants with 4-5 healthy lifestyle components were associated with a decreased risk of incident CVD (HR: 0.50; 95%CI: 0.37, 0.66), CHD (HR: 0.49; 95%CI: 0.35, 0.69), IS (HR: 0.35; 95%CI: 0.19, 0.65), and HF (HR: 0.59; 95%CI: 0.36, 0.97), compared with those with 0-1 lifestyle components. Evidence for the genetic-lifestyle interaction was observed for CHD (p = 0.034) and HF (p = 0.044). Among participants at high genetic risk, a healthy lifestyle was associated with a lower risk of CHD (HR: 0.37; 95%CI: 0.24, 0.56), IS (HR: 0.37; 95%CI: 0.15, 0.93) and HF (HR: 0.39; 95%CI: 0.21, 0.73).

CONCLUSIONS

Our findings suggest that BC survivors with a high genetic risk could benefit more from adherence to a healthy lifestyle in reducing CVD risk.

Various Expressions of PIK3C2A and TXNIP Genes and Their Potential Role as Independent Risk Factors for Chronic Stable Angina and Acute Coronary Syndrome

BACKGROUND AND AIM

Genetic factors play a significant role in the onset and progression of coronary artery disease (CAD). PIK3C2A may contribute to the development of acute coronary syndrome (ACS) by affecting blood glucose levels and oxidative stress. The expression levels of TXNIP were significantly higher in patients with unstable angina pectoris. However, the situation is different in ACS. In the current study, we aim to investigate the role of PIK3C2A and TXNIP as independent risk factors for chronic stable angina (CSA) and ACS.

SUBJECTS AND METHODS

This study involved 215 subjects (60 patients with CSA, 55 patients with ACS, and 100 controls). All subjects were exposed for assaying gene expressions of PIK3C2A and TXNIP by quantitative real-time polymerase chain reaction.

RESULTS

It was found that TXNIP was upregulated, whereas PIK3C2A was downregulated in patients with CAD compared to the control group. PIK3C2A was significantly downregulated in patients with ACS compared to that in patients with CSA (p < 0.001), but TXNIP was not (p = 0.7). TXNIP was significantly upregulated in STEMI-ACS patients compared to CSA (p = 0.045) and NSTEMI ACS (p = 0.046), among non-diabetic (p = 0.023) smokers (p = 0.036) with hypertension (p = 0.005) and hypercholesterolemia (p = 0.001). ROC (receiver operating characteristic) curve analysis revealed that PIK3C2A (0.981; p < 0.001; 98.18) was the most sensitive mRNA for discriminating ACS from control, followed by TXNIP (0.775; p < 0.001; 70.91). However, for discriminating ACS from CSA combined mRNAs, (PIK3C2A + TXNIP) (0.893; p < 0.001; 98.18) and PIK3C2A (0.892; p < 0.001; 81.82) are promising biomarkers. On the other hand, the most sensitive mRNA for differentiating CSA from control is mRNAs (PIK3C2A + TXNIP) (0.963; p < 0.001; 95), then TXINP (81.3; p < 0.001; 93.33), and finally, PIK3C2A (0.782; p < 0.001; 81.67). In the multivariate regression model, PIK3C2A ((p = 0.002), 0.118 (0.031-0.445)) and smoking status ((p = 0.034); 0.151 (0.026-0.866)) were independent variables for ACS. Moreover, PIK3C2A ((p < 0.013); 0.706 (0.614-0.812)), Hb ((p = 0.013); 0.525 (0.317-0.871)), and total cholesterol ((p = 0.04); 0.865 (0.784-0.955)) were significantly (p < 0.05) and independently related to the prognosis of CSA. Furthermore, PIK3C2A ((p = 0.002), 0.923 (0.877-0.971)), TXNIP ((p = 0.001); 2.809 (1.558-5.064)) the body weight ((p = 0.033); 1.254 (1.018-1.544)) were independently associated with CSA.

CONCLUSIONS

Our study concluded that the dysregulated mRNA PIK3C2A and TXNIP gene expressions may be useful in diagnosis of CAD and prediction of ACS development.

Advances and Applications of Polygenic Scores for Coronary Artery Disease

Polygenic scores quantify inherited risk by integrating information from many common sites of DNA variation into a single number. Rapid increases in the scale of genetic association studies and new statistical algorithms have enabled development of polygenic scores that meaningfully measure-as early as birth-risk of coronary artery disease. These newer-generation polygenic scores identify up to 8% of the population with triple the normal risk based on genetic variation alone, and these individuals cannot be identified on the basis of family history or clinical risk factors alone. For those identified with increased genetic risk, evidence supports risk reduction with at least two interventions, adherence to a healthy lifestyle and cholesterol-lowering therapies, that can substantially reduce risk. Alongside considerable enthusiasm for the potential of polygenic risk estimation to enable a new era of preventive clinical medicine is recognition of a need for ongoing research into how best to ensure equitable performance across diverse ancestries, how and in whom to assess the scores in clinical practice, as well as randomized trials to confirm clinical utility.

Polygenic risk scores in coronary artery disease

PURPOSE OF REVIEW

Recent advances in genetics have facilitated the calculation of polygenic risk scores (PRSs) based on common genetic risk variants of coronary artery disease (CAD). Here, we provide an explanation of the genetic basis for PRSs and review recent literature investigating PRSs and the clinical utility for different aspects of CAD.

RECENT FINDINGS

CAD-based PRSs are strongly associated with atherosclerosis burden in the coronary arteries and other vascular beds. In multiple studies, PRSs have proven to be a measure of CAD risk, more powerful than most established risk factors alone, that can be used from early life to stratify individuals into varying trajectories of lifetime risk. When implemented in risk stratification models for primary prevention of cardiovascular disease, PRSs provide modest improvements in discrimination (C-index generally increasing 0-4% points) and reclassification, but yield significant clinical benefit as a risk enhancer. Additionally, data suggest possible value of PRSs for aiding decisions in other aspects of diagnostics and treatment in CAD.

SUMMARY

Once genotyped, the genetic information may be used to calculate an infinite number of PRSs and contribute to personalize medicine providing clinical value for risk stratification, diagnostics and treatment in CAD as well as in other diseases.

Microvascular and macrovascular complications of type 2 diabetes mellitus: Exome wide association analyses

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic, metabolic disorder in which concomitant insulin resistance and β-cell impairment lead to hyperglycemia, influenced by genetic and environmental factors. T2DM is associated with long-term complications that have contributed to the burden of morbidity and mortality worldwide. The objective of this manuscript is to conduct an Exome-Wide Association Study (EWAS) on T2DM Emirati individuals to improve our understanding on diabetes-related complications to improve early diagnostic methods and treatment strategies.

METHODS

This cross-sectional study recruited 310 Emirati participants that were stratified according to their medically diagnosed diabetes-related complications: diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and cardiovascular complications. The Illumina's Infinium Exome-24 array was used and 39,840 SNPs remained for analysis after quality control.

FINDINGS

The analysis revealed the associations of various genes with each complication category: 1) diabetic retinopathy was associated to SHANK3 gene in locus 22q13.33 (SNP rs9616915; p=5.18 x10^-4), ZSCAN5A gene in locus 19q13.43 (SNP rs7252603; p=7.55 x10^-4), and DCP1B gene in locus 12p13.33 (SNPs rs715146, rs1044950, rs113147414, rs34730825; p=7.62 x10^-4); 2) diabetic neuropathy was associated to ADH4 gene in locus 4q23 (SNP rs4148883; p=1.23 x10^-4), SLC11A1 gene in locus 2q35 (SNP rs17235409; p=1.85 x10^-4), and MATN4 gene in locus 20q13.12 (SNP rs2072788; p=2.68 x10^-4); 3) diabetic nephropathy was associated to PPP1R3A gene in locus 7q31.1 (SNP rs1799999; p=1.91 x10^-4), ZNF136 gene in locus 19p13.2 (SNP rs140861589; p=2.80 x10^-4), and HSPA12B gene in locus 20p13 (SNP rs6076550; p=2.86 x10^-4); and 4) cardiovascular complications was associated to PCNT gene in locus 21q22.3 (SNPs rs7279204, rs6518289, rs2839227, rs2839223; p=2.18 x10^-4,3.04 x10^-4,4.51 x10^-4,5.22 x10^-4 respectively), SEPT14 gene in locus 7p11.2 (SNP rs146350220; p=2.77 x10^-4), and WDR73 gene in locus 15q25.2 (SNP rs72750868; p=4.47 x10^-4).

INTERPRETATION

We have identified susceptibility loci associated with each category of T2DM-related complications in the Emirati population. Given that only 16% of the markers from the Illumina's Infinium Exome chip passed quality control assessment, this demonstrates that multiple variants were, either, monomorphic in the Arab population or were not genotyped due to the use of a Euro-centric EWAS array that limits the possibility of including targeted ethnic-specific SNPs. Our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci associated to T2DM complications. Further effort must be conducted to improve the representation of diverse populations in genotyping and sequencing studies.

Trans-interaction of risk loci 6p24.1 and 10q11.21 is associated with endothelial damage in coronary artery disease

BACKGROUND AND AIMS

Single nucleotide polymorphism rs6903956 has been identified as one of the genetic risk factors for coronary artery disease (CAD). However, rs6903956 lies in a non-coding locus on chromosome 6p24.1. We aim to interrogate the molecular basis of 6p24.1 containing rs6903956 risk alleles in endothelial disease biology.

METHODS AND RESULTS

We generated induced pluripotent stem cells (iPSCs) from CAD patients (AA risk genotype at rs6903956) and non-CAD subjects (GG non-risk genotype at rs6903956). CRISPR-Cas9-based deletions (Δ63-89bp) on 6p24.1, including both rs6903956 and a short tandem repeat variant rs140361069 in linkage disequilibrium, were performed to generate isogenic iPSC-derived endothelial cells. Edited CAD endothelial cells, with removal of 'A' risk alleles, exhibited a global transcriptional downregulation of pathways relating to abnormal vascular physiology and activated endothelial processes. A CXC chemokine ligand on chromosome 10q11.21, CXCL12, was uncovered as a potential effector gene in CAD endothelial cells. Underlying this effect was the preferential inter-chromosomal interaction of 6p24.1 risk locus to a weak promoter of CXCL12, confirmed by chromatin conformation capture assays on our iPSC-derived endothelial cells. Functionally, risk genotypes AA/AG at rs6903956 were associated significantly with elevated levels of circulating damaged endothelial cells in CAD patients. Circulating endothelial cells isolated from patients with risk genotypes AA/AG were also found to have 10 folds higher CXCL12 transcript copies/cell than those with non-risk genotype GG.

CONCLUSIONS

Our study reveals the trans-acting impact of 6p24.1 with another CAD locus on 10q11.21 and is associated with intensified endothelial injury.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Etiologic Puzzle of Coronary Artery Disease: How Important Is Genetic Component?

In the modern era, coronary artery disease (CAD) has become the most common form of heart disease and, due to the severity of its clinical manifestations and its acute complications, is a major cause of morbidity and mortality worldwide. The phenotypic variability of CAD is correlated with the complex etiology, multifactorial (caused by the interaction of genetic and environmental factors) but also monogenic. The purpose of this review is to present the genetic factors involved in the etiology of CAD and their relationship to the pathogenic mechanisms of the disease. Method: we analyzed data from the literature, starting with candidate gene-based association studies, then continuing with extensive association studies such as Genome-Wide Association Studies (GWAS) and Whole Exome Sequencing (WES). The results of these studies revealed that the number of genetic factors involved in CAD etiology is impressive. The identification of new genetic factors through GWASs offers new perspectives on understanding the complex pathophysiological mechanisms that determine CAD. In conclusion, deciphering the genetic architecture of CAD by extended genomic analysis (GWAS/WES) will establish new therapeutic targets and lead to the development of new treatments. The identification of individuals at high risk for CAD using polygenic risk scores (PRS) will allow early prophylactic measures and personalized therapy to improve their prognosis.

NPAS4 Polymorphisms Contribute to Coronary Heart Disease (CHD) Risk

As genetic inheritance is an inevitable risk factor in the development of coronary heart disease (CHD), it is critical to identify the polymorphisms of CHD risk. This study explored whether the NPAS4 polymorphisms are related to the CHD risk in the Chinese Han population. Five SNPs in NPAS4 were genotyped using Agena Mass ARRAY from 499 CHD and 500 controls. RT-PCR detected the NPAS4 expression levels in peripheral blood mononuclear cells from 50 CHD and 50 controls. χ² test compared the distributions of gender, allele and genotypes frequencies between cases and controls. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). MDR analyzed the SNP-SNP interactions on risk of CHD. U test compared the differences in gene expression between different groups. The results showed that rs4466842 was correlated with an increased CHD risk in overall, males and age ≤ 60; rs117186164 and rs12785321 were significantly related to an increased CHD risk in male and age ≤ 60, respectively; haplotype A_rs117186164C_rs4466842 was significantly correlated with an increased CHD risk. SNP-SNP interactions results showed that the best model was the four-locus model was the combination of rs117770654, rs117957381, rs12785321, and rs4466842 (CVC = 10/10, Testing Sensitivity = 0.647). The expression levels of NPAS4 in the case group (0.365 ± 0.139) were significantly lower than that in the control group (0.782 ± 0.224) (P < 0.001). The results revealed that SNPs in NPAS4 may play an important role in the occurrence and development of CHD.

Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies

Diabetes-related complications reflect longstanding damage to small and large vessels throughout the body. In addition to the duration of diabetes and poor glycemic control, genetic factors are important contributors to the variability in the development of vascular complications. Early heritability studies found strong familial clustering of both macrovascular and microvascular complications. However, they were limited by small sample sizes and large phenotypic heterogeneity, leading to less accurate estimates. We take advantage of two independent studies-UK Biobank and the Action to Control Cardiovascular Risk in Diabetes trial-to survey the single nucleotide polymorphism heritability for diabetes microvascular (diabetic kidney disease and diabetic retinopathy) and macrovascular (cardiovascular events) complications. Heritability for diabetic kidney disease was estimated at 29%. The heritability estimate for microalbuminuria ranged from 24 to 60% and was 41% for macroalbuminuria. Heritability estimates of diabetic retinopathy ranged from 6 to 33%, depending on the phenotype definition. More severe diabetes retinopathy possessed higher genetic contributions. We show, for the first time, that rare variants account for much of the heritability of diabetic retinopathy. This study suggests that a large portion of the genetic risk of diabetes complications is yet to be discovered and emphasizes the need for additional genetic studies of diabetes complications.

Associations of carotid intima media thickness with gene expression in whole blood and genetically predicted gene expression across 48 tissues

Carotid intima media thickness (cIMT) is a biomarker of subclinical atherosclerosis and a predictor of future cardiovascular events. Identifying associations between gene expression levels and cIMT may provide insight to atherosclerosis etiology. Here, we use two approaches to identify associations between mRNA levels and cIMT: differential gene expression analysis in whole blood and S-PrediXcan. We used microarrays to measure genome-wide whole blood mRNA levels of 5647 European individuals from four studies. We examined the association of mRNA levels with cIMT adjusted for various potential confounders. Significant associations were tested for replication in three studies totaling 3943 participants. Next, we applied S-PrediXcan to summary statistics from a cIMT genome-wide association study (GWAS) of 71 128 individuals to estimate the association between genetically determined mRNA levels and cIMT and replicated these analyses using S-PrediXcan on an independent GWAS on cIMT that included 22 179 individuals from the UK Biobank. mRNA levels of TNFAIP3, CEBPD and METRNL were inversely associated with cIMT, but these associations were not significant in the replication analysis. S-PrediXcan identified associations between cIMT and genetically determined mRNA levels for 36 genes, of which six were significant in the replication analysis, including TLN2, which had not been previously reported for cIMT. There was weak correlation between our results using differential gene expression analysis and S-PrediXcan. Differential expression analysis and S-PrediXcan represent complementary approaches for the discovery of associations between phenotypes and gene expression. Using these approaches, we prioritize TNFAIP3, CEBPD, METRNL and TLN2 as new candidate genes whose differential expression might modulate cIMT.

Heritability of Coronary Artery Disease: Insights From a Classical Twin Study

BACKGROUND

Genetics have a strong influence on calcified atherosclerotic plaques; however, data regarding the heritability of noncalcified plaque volume are scarce. We aimed to evaluate genetic versus environmental influences on calcium (coronary artery calcification) score, noncalcified and calcified plaque volumes by coronary computed tomography angiography in adult twin pairs without known coronary artery disease.

METHODS

In the prospective BUDAPEST-GLOBAL (Burden of Atherosclerotic Plaques Study in Twins-Genetic Loci and the Burden of Atherosclerotic Lesions) classical twin study, we analyzed twin pairs without known coronary artery disease. All twins underwent coronary computed tomography angiography to assess coronary atherosclerotic plaque volumes. Structural equation models were used to quantify the contribution of additive genetic, common environmental, and unique environmental components to plaque volumes adjusted for age, gender, or atherosclerotic cardiovascular disease risk estimate and statin use.

RESULTS

We included 196 twins (mean age±SD, 56±9 years, 63.3% females), 120 monozygotic and 76 same-gender dizygotic pairs. Using structural equation models, noncalcified plaque volume was predominantly determined by environmental factors (common environment, 63% [95% CI, 56%-67%], unique environment, 37% [95% CI, 33%-44%]), while coronary artery calcification score and calcified plaque volumes had a relatively strong genetic heritability (additive genetic, 58% [95% CI, 50%-66%]; unique environmental, 42% [95% CI, 34%-50%] and additive genetic, 78% [95% CI, 73%-80%]; unique environmental, 22% [95% CI, 20%-27%]), respectively.

CONCLUSIONS

Noncalcified plaque volume is mainly influenced by shared environmental factors, whereas coronary artery calcification score and calcified plaque volume are more determined by genetics. These findings emphasize the importance of early lifestyle interventions in preventing coronary plaque formation.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT01738828.

Human genetics and its impact on cardiovascular disease

Cardiovascular disease (CVD) is a major cause of death worldwide. Given that CVD is a highly heritable trait, researchers have attempted to fully understand the genetic basis of CVD for a long time. The human genome comprises 3,100 Mbp per haploid genome and 6,200 Mbp in total (diploid genome). However, there is a tendency for rare genetic variations to exhibit a large effect size, whereas common genetic variations have a small effect on diseases, because of natural selection. In this sense, dividing genetic variations into two groups based on allele frequency (and effect sizes on diseases) is a good idea. We know there are several important genes (especially lipid-related genes) in which rare genetic variations are apparently associated with CVD risk, while a polygenic risk score comprising common genetic variations appears to work quite well among general populations. That information can be used not only for risk stratification but also for discoveries for novel pharmacologic targets. In this review article, we provide the important and simple idea that human genetics is important for CVD because it is a highly heritable trait, and we believe that it will lead to precision medicine in this field.

Smoking Status and Type 2 Diabetes, and Cardiovascular Disease: A Comprehensive Analysis of Shared Genetic Etiology and Causal Relationship

OBJECTIVE

This study aimed to explore shared genetic etiology and the causality between smoking status and type 2 diabetes (T2D), cardiovascular diseases (CVDs), and related metabolic traits.

METHODS

Using summary statistics from publicly available genome-wide association studies (GWASs), we estimated genetic correlations between smoking status and T2D, 6 major CVDs, and 8 related metabolic traits with linkage disequilibrium score regression (LDSC) analysis; identified shared genetic loci with large-scale genome-wide cross-trait meta-analysis; explored potential shared biological mechanisms with a series of post-GWAS analyses; and determined causality with Mendelian randomization (MR).

RESULTS

We found significant positive genetic associations with smoking status for T2D (Rg = 0.170, p = 9.39 × 10^-22), coronary artery disease (CAD) (Rg = 0.234, p = 1.96 × 10^-27), myocardial infarction (MI) (Rg = 0.226, p = 1.08 × 10^-17), and heart failure (HF) (Rg = 0.276, p = 8.43 × 10^-20). Cross-trait meta-analysis and transcriptome-wide association analysis of smoking status identified 210 loci (32 novel loci) and 354 gene-tissue pairs jointly associated with T2D, 63 loci (12 novel loci) and 37 gene-tissue pairs with CAD, 38 loci (6 novel loci) and 17 gene-tissue pairs with MI, and 28 loci (3 novel loci) and one gene-tissue pair with HF. The shared loci were enriched in the exo-/endocrine, cardiovascular, nervous, digestive, and genital systems. Furthermore, we observed that smoking status was causally related to a higher risk of T2D (β = 0.385, p = 3.31 × 10^-3), CAD (β = 0.670, p = 7.86 × 10^-11), MI (β = 0.725, p = 2.32 × 10^-9), and HF (β = 0.520, p = 1.53 × 10^-6).

CONCLUSIONS

Our findings provide strong evidence on shared genetic etiology and causal associations between smoking status and T2D, CAD, MI, and HF, underscoring the potential shared biological mechanisms underlying the link between smoking and T2D and CVDs. This work opens up a new way of more effective and timely prevention of smoking-related T2D and CVDs.

Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease in the Asia-Pacific Region

Approximately one-half of the phenotypic susceptibility to atherosclerotic cardiovascular disease (ASCVD) has a genetic basis. Although individual allelic variants generally impart a small effect on risk for ASCVD, an emerging body of data has shown that the aggregation and weighting of many of these genetic variations into “scores” can further discriminate an individual’s risk beyond traditional risk factors alone. Consistent with the theory of population genetics, such polygenic risk scores (PRS) appear to be ethnicity specific because their elements comprise single-nucleotide variants that are always ethnicity specific. The currently available PRS are derived predominantly from European ancestry and thus predictably perform less well among non-European participants, a fact that has implications for their use in the Asia-Pacific region. This paper describes the current state of knowledge of PRS, the available data that support their use in this region, and highlights the needs moving forward to safely and effectively implement them in clinical care in the Asia-Pacific region.

•

Genetic factors should be fully accounted for in the clinical care of atherosclerotic cardiovascular disease.

•

A health inequity exists regarding polygenic risk score for atherosclerotic cardiovascular disease in the world.

•

We propose a call to action to address this issue in the Asia-Pacific region.