Genetic analysis of emerging risk factors in coronary artery disease

The genetic correlation and causal association between key factors that influence vascular calcification and cardiovascular disease incidence

Background

Serum calcium (Ca), vitamin D (VD), and vitamin K (VK) levels are key determinants of vascular calcification, which itself impacts cardiovascular disease (CVD) risk. The specific relationships between the levels of these different compounds and particular forms of CVD, however, remain to be fully defined.

Objective

This study was designed to explore the associations between these serum levels and CVDs with the goal of identifying natural interventions capable of controlling vascular calcification and thereby protecting against CVD pathogenesis, extending the healthy lifespan of at-risk individuals.

Methods

Linkage disequilibrium score (LDSC) regression and a two-sample Mendelian randomization (MR) framework were leveraged to systematically examine the causal interplay between these serum levels and nine forms of CVD, as well as longevity through the use of large publically accessible Genome-Wide Association Studies (GWAS) datasets. The optimal concentrations of serum Ca and VD to lower CVD risk were examined through a restrictive cubic spline (RCS) approach.

Results

After Bonferroni correction, the positive genetic correlations were observed between serum Ca levels and myocardial infarction (MI) (p = 1.356E-04), as well as coronary artery disease (CAD) (p = 3.601E-04). Negative genetic correlations were detected between levels of VD and CAD (p = 0.035), while elevated VK1 concentrations were causally associated with heart failure (HF) [odds ratios (OR) per 1-standard deviation (SD) increase: 1.044], large artery stroke (LAS) (OR per 1-SD increase: 1.172), and all stroke (AS) (OR per 1-SD increase: 1.041). Higher serum Ca concentrations (OR per 1-SD increase: 0.865) and VD levels (OR per 1-SD increase: 0.777) were causally associated with reduced odds of longevity. These findings remained consistent in sensitivity analyses, and serum Ca and VD concentrations of 2.376 mmol/L and 46.8 nmol/L, respectively, were associated with a lower CVD risk (p < 0.001).

Conclusion

Our findings support a genetic correlation between serum Ca and VD and CVD risk, and a causal relationship between VK1 levels and CVD risk. The optimal serum Ca (2.376 mmol/L) and VD levels (46.8 nmol/L) can reduce cardiovascular risk.

Elevated lipoprotein(a) and genetic polymorphisms in the LPA gene may predict cardiovascular events

Elevated lipoprotein(a) [Lp(a)] is a risk factor for coronary heart disease (CHD), but there are few studies on the prediction of future cardiovascular events by Lp(a) and its LPA single nucleotide polymorphisms (SNPs). The aim of this study was to investigate whether elevated Lp(a) and its SNPs can predict cardiovascular events. We evaluated whether Lp(a) and LPA SNPs rs6415084 and rs12194138 were associated with the incidence rate and severity of CHD. All participants were followed up for 5 years. Elevated Lp(a) is an independent risk factor for the risk and severity of CHD (CHD group vs. control group: OR = 1.793, 95% CI: 1.053–2.882, p = 0.043; multiple-vessel disease group vs. single-vessel disease group: OR = 1.941, 95% CI: 1.113–3.242, p = 0.027; high GS group vs. low GS group: OR = 2.641, 95% CI: 1.102–7.436, p = 0.040). Both LPA SNPs were risk factors for CHD, and were positively associated with the severity of CHD (LPA SNPs rs6415084: CHD group vs. control group: OR = 1.577, 95% CI: 1.105–1.989, p = 0.004; multiple-vessel disease group vs. single-vessel disease group: OR = 1.613, 95% CI: 1.076–2.641, p = 0.030; high GS group vs. low GS group: OR = 1.580, 95% CI: 1.088–2.429, p = 0.024; LPA SNPs rs12194138: CHD group vs. control group: OR = 1.475, 95% CI: 1.040–3.002, p = 0.035; multiple-vessel disease group vs. single-vessel disease group: OR = 2.274, 95% CI: 1.060–5.148, p = 0.038; high GS group vs. low GS group: OR = 2.067, 95% CI: 1.101–4.647, p = 0.021). After 5 years of follow-up, elevated Lp(a) and LPA SNPs rs6415084 and rs12194138 can independently predict cardiovascular events. The increase of serum Lp(a) and LPA SNPs rs6415084 and rs12194138 are associated with increased prevalence and severity of CHD, and can independently predict cardiovascular events.

Subclinical cardiovascular disease and utility of coronary artery calcium score

ASCVD are the leading causes of mortality and morbidity among Globe. Evaluation of patients' comprehensive and personalized risk provides risk management strategies and preventive interventions to achieve gain for patients. Framingham Risk Score (FRS) and Systemic Coronary Risk Evaluation Score (SCORE) are two well studied risk scoring models, however, can miss some (20-35%) of future cardiovascular events. To obtain more accurate risk assessment recalibrating risk models through utilizing novel risk markers have been studied in last 3 decades and both ESC and AHA recommends assessing Family History, hs-CRP, CACS, ABI, and CIMT. Subclinical Cardiovascular Disease (SCVD) has been conceptually developed for investigating gradually progressing asymptomatic development of atherosclerosis and among these novel risk markers it has been well established by literature that CACS having highest improvement in risk assessment. This review study mainly selectively discussing studies with CACS measurement. A CACS = 0 can down-stratify risk of patients otherwise treated or treatment eligible before test and can reduce unnecessary interventions and cost, whereas CACS ≥ 100 is equivalent to statin treatment threshold of ≥ 7.5% risk level otherwise statin ineligible before test. Since inflammation, insulin resistance, oxidative stress, dyslipidemia and ongoing endothelial damage due to hypertension could lead to CAC, ASCVD linked with comorbidities. Recent cohort studies have shown a CACS 100-300 as a sign of increased cancer risk. Physical activity, dietary factors, cigarette use, alcohol consumption, metabolic health, family history of CHD, aging, exposures of neighborhood environment and non-cardiovascular comorbidities can determine CACs changes.

Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review

Childhood cancer survivors (CCS) are at increased risk to develop metabolic syndrome (MetS), diabetes, and cardiovascular disease. Common criteria underestimate adiposity and possibly underdiagnose MetS, particularly after abdominal radiotherapy. A systematic literature review and meta-analysis on the diagnostic and predictive value of nine newer MetS related biomarkers (adiponectin, leptin, uric acid, hsCRP, TNF-alpha, IL-1, IL-6, apolipoprotein B (apoB), and lipoprotein(a) [lp(a)]) in survivors and adult non-cancer survivors was performed by searching PubMed and Embase. Evidence was summarized with GRADE after risk of bias evaluation (QUADAS-2/QUIPS). Eligible studies on promising biomarkers were pooled. We identified 175 general population and five CCS studies. In the general population, valuable predictive biomarkers are uric acid, adiponectin, hsCRP and apoB (high level of evidence), and leptin (moderate level of evidence). Valuable diagnostic biomarkers are hsCRP, adiponectin, uric acid, and leptin (low, low, moderate, and high level of evidence, respectively). Meta-analysis showed OR for hyperuricemia of 2.94 (age-/sex-adjusted), OR per unit uric acid increase of 1.086 (unadjusted), and AUC for hsCRP of 0.71 (unadjusted). Uric acid, adiponectin, hsCRP, leptin, and apoB can be alternative biomarkers in the screening setting for MetS in survivors, to enhance early identification of those at high risk of subsequent complications.

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease-rationale and design of the GESS study

Background

Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score—GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies.

Methods

GESS (ClinicalTrials.gov Identifier: NCT03150680) is a prospective, non-interventional clinical study designed to enroll 1080 consecutive patients with no prior history of coronary revascularization procedure, who undergo scheduled or emergency coronary angiography in AHEPA, University General Hospital of Thessaloniki. Next generation sequencing (NGS) technology will be used to genotype specific single-nucleotide polymorphisms (SNPs) across the genome of study participants, which were identified as clinically relevant to CAD after extensive bioinformatic analysis of literature-based SNPs. Enrichment analyses of Gene Ontology-Molecular Function, Reactome Pathways and Disease Ontology terms were also performed to identify the top 15 statistically significant terms and pathways. Furthermore, the SYNTAX score will be calculated for the assessment of CAD severity of all patients based on their angiographic findings. All patients will be followed-up for one-year, in order to record any major adverse cardiovascular events.

Discussion

A group of 228 SNPs was identified through bioinformatic and pharmacogenomic analysis to be involved in CAD through a wide range of pathways and was correlated with various laboratory and clinical parameters, along with the patients' response to clopidogrel and statin therapy. The annotation of these SNPs revealed 127 genes being affected by the presence of one or more SNPs. The first patient was enrolled in the study in February 2019 and enrollment is expected to be completed until June 2021. Hence, GESS is the first trial to date aspiring to develop a novel risk prediction algorithm, the GEnetic Syntax Score, able to identify patients at high risk for complex CAD based on their molecular signature profile and ultimately promote pharmacogenomics and precision medicine in routine clinical settings.

Trial registration GESS trial registration: ClinicalTrials.gov Number: NCT03150680. Registered 12 May 2017- Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03150680.

Genetic risk scores in lipid disorders

PURPOSE OF REVIEW

Extensive work has gone into understanding the genetics of cardiovascular disease (CVD) and implicating genes involved in hyperlipidaemia. Translation into routine practise involves using genetic risk scores (GRS) to identify high-risk individuals in the general population. Some of these risk scores are beginning to disentangle the complex nature of CVD and inherited dyslipidaemias.

RECENT FINDINGS

GRS of varying complexity have been used to identify high-risk groups of patients with polygenic CVD including some individuals with risk equivalent to monogenic disease. In phenotypic familial hypercholesterolaemia a six or 12 gene lipid GRS may identify polygenic cases that comprise up to 50% of cases. In high triglyceride syndromes including even cases of familial chylomicronaemia syndrome more than 80% of cases are polygenic and not even associated with rare variants. In both familial hypercholesterolaemia and familial chylomicronaemia syndrome individuals with polygenic disease have a lower risk than those with monogenic disease.

SUMMARY

GRS show promise in identifying individuals with high risks of CVD. They have a close relationship with imaging markers. It is unclear whether GRS, imaging or both will be used to identify individuals at high risk of future events.

Improved detection of common variants in coronary artery disease and blood pressure using a pleiotropy cFDR method

Plenty of genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and blood pressure (BP). However, these SNPs only explain a small proportion of the heritability of two traits/diseases. Although high BP is a major risk factor for CAD, the genetic intercommunity between them remain largely unknown. To recognize novel loci associated with CAD and BP, a genetic-pleiotropy-informed conditional false discovery rate (cFDR) method was applied on two summary statistics of CAD and BP from existing GWASs. Stratified Q-Q and fold enrichment plots showed a high pleiotropic enrichment of SNPs associated with two traits. Adopting a cFDR of 0.05 as a threshold, 55 CAD-associated loci (25 variants being novel) and 47 BP loci (18 variants being novel) were identified, 25 of which were pleiotropic loci (13 variants being novel) for both traits. Among the 32 genes these 25 SNPs were annotated to, 20 genes were newly detected compared to previous GWASs. This study showed the cFDR approach could improve gene discovery by incorporating GWAS datasets of two related traits. These findings may provide novel understanding of etiology relationships between CAD and BP.

Shared Genetic Contribution of Type 2 Diabetes and Cardiovascular Disease: Implications for Prognosis and Treatment

PURPOSE OF REVIEW

The increased cardiovascular disease (CVD) risk in subjects with type 2 diabetes (T2D) is well established. This review collates the available evidence and assesses the shared genetic background between T2D and CVD: the causal contribution of common risk factors to T2D and CVD and how genetics can be used to improve drug development and clinical outcomes.

RECENT FINDINGS

Large-scale genome-wide association studies (GWAS) of T2D and CVD support a shared genetic background but minimal individual locus overlap. Mendelian randomisation (MR) analyses show that T2D is causal for CVD, but GWAS of CVD, T2D and their common risk factors provided limited evidence for individual locus overlap. Distinct but functionally related pathways were enriched for CVD and T2D genetic associations reflecting the lack of locus overlap and providing some explanation for the variable associations of common risk factors with CVD and T2D from MR analyses.

Association of Genetic Variants Related to Serum Calcium Levels With Coronary Artery Disease and Myocardial Infarction

IMPORTANCE

Serum calcium has been associated with cardiovascular disease in observational studies and evidence from randomized clinical trials indicates that calcium supplementation, which raises serum calcium levels, may increase the risk of cardiovascular events, particularly myocardial infarction.

OBJECTIVE

To evaluate the potential causal association between genetic variants related to elevated serum calcium levels and risk of coronary artery disease (CAD) and myocardial infarction using mendelian randomization.

DESIGN, SETTING, AND PARTICIPANTS

The analyses were performed using summary statistics obtained for single-nucleotide polymorphisms (SNPs) identified from a genome-wide association meta-analysis of serum calcium levels (N = up to 61 079 individuals) and from the Coronary Artery Disease Genome-wide Replication and Meta-analysis Plus the Coronary Artery Disease Genetics (CardiogramplusC4D) consortium's 1000 genomes-based genome-wide association meta-analysis (N = up to 184 305 individuals) that included cases (individuals with CAD and myocardial infarction) and noncases, with baseline data collected from 1948 and populations derived from across the globe. The association of each SNP with CAD and myocardial infarction was weighted by its association with serum calcium, and estimates were combined using an inverse-variance weighted meta-analysis.

EXPOSURES

Genetic risk score based on genetic variants related to elevated serum calcium levels.

MAIN OUTCOMES AND MEASURES

Co-primary outcomes were the odds of CAD and myocardial infarction.

RESULTS

Among the mendelian randomized analytic sample of 184 305 individuals (60 801 CAD cases [approximately 70% with myocardial infarction] and 123 504 noncases), the 6 SNPs related to serum calcium levels and without pleiotropic associations with potential confounders were estimated to explain about 0.8% of the variation in serum calcium levels. In the inverse-variance weighted meta-analysis (combining the estimates of the 6 SNPs), the odds ratios per 0.5-mg/dL increase (about 1 SD) in genetically predicted serum calcium levels were 1.25 (95% CI, 1.08-1.45; P = .003) for CAD and 1.24 (95% CI, 1.05-1.46; P = .009) for myocardial infarction.

CONCLUSIONS AND RELEVANCE

A genetic predisposition to higher serum calcium levels was associated with increased risk of CAD and myocardial infarction. Whether the risk of CAD associated with lifelong genetic exposure to increased serum calcium levels can be translated to a risk associated with short-term to medium-term calcium supplementation is unknown.