The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities

Bioinformatics and machine learning approaches reveal key genes and underlying molecular mechanisms of atherosclerosis: A review

Atherosclerosis (AS) causes thickening and hardening of the arterial wall due to accumulation of extracellular matrix, cholesterol, and cells. In this study, we used comprehensive bioinformatics tools and machine learning approaches to explore key genes and molecular network mechanisms underlying AS in multiple data sets. Next, we analyzed the correlation between AS and immune fine cell infiltration, and finally performed drug prediction for the disease. We downloaded GSE20129 and GSE90074 datasets from the Gene expression Omnibus database, then employed the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts algorithm to analyze 22 immune cells. To enrich for functional characteristics, the black module correlated most strongly with T cells was screened with weighted gene co-expression networks analysis. Functional enrichment analysis revealed that the genes were mainly enriched in cell adhesion and T-cell-related pathways, as well as NF-κ B signaling. We employed the Lasso regression and random forest algorithms to screen out 5 intersection genes (CCDC106, RASL11A, RIC3, SPON1, and TMEM144). Pathway analysis in gene set variation analysis and gene set enrichment analysis revealed that the key genes were mainly enriched in inflammation, and immunity, among others. The selected key genes were analyzed by single-cell RNA sequencing technology. We also analyzed differential expression between these 5 key genes and those involved in iron death. We found that ferroptosis genes ACSL4, CBS, FTH1 and TFRC were differentially expressed between AS and the control groups, RIC3 and FTH1 were significantly negatively correlated, whereas SPON1 and VDAC3 were significantly positively correlated. Finally, we used the Connectivity Map database for drug prediction. These results provide new insights into AS genetic regulation.

Mass-spectrometric analysis of APOB polymorphism rs1042031 (G/T) and its influence on serum proteome of coronary artery disease patients: genetic-derived proteomics consequences

Genetic polymorphisms of apolipoprotein B gene (APOB) may result into serum proteomic perturbance in Coronary Artery Disease (CAD). The current case-control cohort of Pakistani subjects was designed to analyze the genetic influence of APOB rs1042031, (G/T) genotype on serum proteome. Subjects were categorized into two groups: CAD patients (n = 480) and healthy individuals (n = 220). For genotyping, tetra ARMS-PCR was carried out and validated through sequencing, whereas LC/MS-based proteomic analysis of serum samples was performed through label-free quantification. In initial step of genotyping, the frequencies of each genotype GG, GT, and TT were 70%, 27%, and 30% in CAD patients, while in control group, the subjects were 52%, 43%, and 5%, respectively, in CAD patients. The genotypic frequencies in patients vs. control groups found significantly different (p = 0.004), and a strong association of dominant alleles GG with the CAD was observed in both dominant (OR: 2.4 (1.71-3.34), p = 0.001) and allelic genetic models (OR: 2.0 (1.45-2.86), p = 0.001). In second step of label-free quantitation, a total of 40 significant proteins were found with altered expression in CAD patients. The enriched Gene Ontology (GO) terms of molecular functions and pathways of these protein showed upregulated pathways as follows: chylomicron remodeling and assembly, complement cascade activation, plasma lipoprotein assembly, apolipoprotein-A receptor binding, and metabolism of fat-soluble vitamins in G allele carrier of rs1042031 (G > T) vs. mutant T-allele carriers. This study provides better understanding of CAD pathobiology by proteogenomics of APOB. It evidences the influence of APOB rs1042031-dominant (GG) genotype with CAD patients.

Contribution of genetic variants in the development of familial premature coronary artery disease in a cohort of cardiac patients

Coronary artery disease (CAD), the most prevalent cardiovascular disease, is the leading cause of death worldwide. Heritable factors play a significant role in the pathogenesis of CAD. It has been proposed that approximately one-third of patients with CAD have a positive family history, and individuals with such history are at ~1.5-fold increased risk of CAD in their lifespans. Accordingly, the long-recognized familial clustering of CAD is a strong risk factor for this disease. Our study aimed to identify candidate genetic variants contributing to CAD by studying a cohort of 60 large Iranian families with at least two members in different generations afflicted with premature CAD (PCAD), defined as established disease at ≤45 years in men and ≤55 years in women. Exome sequencing was performed for a subset of the affected individuals, followed by prioritization and Sanger sequencing of candidate variants in all available family members. Subsequently, apparently healthy carriers of potential risk variants underwent coronary computed tomography angiography (CCTA), followed by co-segregation analysis of the combined data. Putative causal variants were identified in seven genes, ABCG8, CD36, CYP27A1, PIK3C2G, RASSF9, RYR2, and ZFYVE21, co-segregating with familial PCAD in seven unrelated families. Among these, PIK3C2G, RASSF9, and ZFYVE21 are novel candidate CAD susceptibility genes. Our findings indicate that rare variants in genes identified in this study are involved in CAD development.

Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice

Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.

Genetic risk modifies the effect of long-term fine particulate matter exposure on coronary artery disease

BACKGROUND

Although both environmental and genetic factors were linked to coronary artery disease (CAD), the extent to which the association of air pollution exposure with CAD can be influenced by genetic risk was not well understood.

METHODS

A total of 41,149 participants recruited from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) were included. Genetic risk scores of CAD were constructed based on 540 genetic variants. Long-term PM_2.5 exposures were assessed by adopting satellite-based PM_2.5 estimations at 1-km resolution. We used stratified Cox proportional hazards regression model to examine the impact of PM_2.5 exposure and genetic risk on CAD risk, and further analyzed modification effect of genetic predisposition on association between PM_2.5 exposure and CAD risk.

RESULTS

During a median of 13.01 years of follow-up, 1,373 incident CAD events were observed. Long-term PM_2.5 exposure significantly increased CAD risk, and the hazard ratios (HRs) [95% confidence intervals (CIs)] were 1.27 (1.05-1.54) and 1.95 (1.57-2.42) among intermediate and high PM_2.5 exposure groups compared to low PM_2.5 exposure group. The relative risks of CAD were 40% (HR: 1.40, 95%CI: 1.18-1.66) and 133% (HR: 2.33, 95%CI: 1.94-2.79) higher among individuals at intermediate and high genetic risk than those at low genetic risk. Compared with individuals with both low genetic risk and low PM_2.5 exposure, those with high genetic risk and high PM_2.5 exposure had highest CAD risk, with HR of 4.37 (95%CI: 3.13-6.11). We observed significant multiplicative (P < 0.001) and additive interaction [relative excess risk due to interaction (95%CI): 2.75 (1.32-4.20); attributable proportion due to interaction (95%CI): 0.56 (0.42-0.70)] between genetic risk and PM_2.5 exposure on CAD.

CONCLUSION

This study provided evidence that long-term PM_2.5 exposure might increase CAD risk, especially among people at high genetic risk. Our findings highlighted the importance of taking strategies on air quality improvement to cardiovascular disease prevention.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Proprotein Convertase Subtilisin Kexin 9 (PCSK9) and nonHDL Particles Rise During Normal Pregnancy and Differ by BMI

BACKGROUND

Serum lipids, including total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-c), increase during pregnancy. Serum Proprotein Convertase Subtilisin Kexin 9 (PCSK9) is a vital regulator in lipoprotein metabolism. Circulating PCSK9 downregulates the LDL receptor on the surface of liver cells inhibiting clearance of LDL-c.

OBJECTIVE

To determine the influence of weeks of pregnancy and obesity on circulating levels of essential lipid lipoproteins and PCSK9 in women with normal, uncomplicated pregnancies and deliveries.

METHODS

We performed a comprehensive lipid and lipoprotein profile during each trimester of pregnancy in 70 mostly Caucasian women with uncomplicated normal pregnancies and deliveries. Based on their first trimester BMI, we placed them into one of three categories: (<25 kg/m² n=23, 25-30 kg/m² n=25, or >30 n=22) kg/m². Cholesterol, triglycerides, LDL cholesterol (LDL-c), non-HDL particles, and lipoprotein(a) were measured by spectrophotometry, ion mobility, and immunoturbidimetric assays. Elisa assay determined PCSK9 (active and total). Homeostatic Model Assessment (HOMA-IR) assessed insulin resistance in the second and third trimesters of pregnancy.

RESULTS

Total and active PCSK9, LDL-c, and nonHDL particle concentrations were higher than reported for non-pregnant normal values, increased after the first trimester of pregnancy, and were highest from mid-gestation to the last trimester of pregnancy in the overweight and the obese.

CONCLUSION

PCSK9 levels rise as normal pregnancy progresses. Levels are higher in persons who are obese, even after adjustment for insulin resistance. Defining normal PCSK9 levels during pregnancy must adjust for gestational age and BMI.

Identification of Key Genes Associated with Endothelial Cell Dysfunction in Atherosclerosis Using Multiple Bioinformatics Tools

Atherosclerosis is the most notable cardiovascular disease, the latter being the main cause of death globally. Endothelial cell dysfunction plays a major role in the pathogenesis of atherosclerosis. However, it is currently unclear which genes are involved between endothelial cell dysfunction and atherosclerosis. This study was aimed at identifying these genes. Based on the GSE83500 dataset, the quantification of endothelial cell function was conducted using single-sample gene set enrichment analysis; the coexpression modules were conducted using weighted correlation network analysis. After building module-trait relationships, tan and yellow modules were regarded as hub modules. 10 hub genes from each hub module were identified by the protein-protein interaction network analysis. The key genes (RAB5A, CTTN, ITGB1, and MMP9) were obtained by comparing the expression differences of the hub gene between atherosclerotic and normal groups from the GSE28829 and GSE43292 datasets, respectively. ROC analysis showed the diagnostic value of key genes. Moreover, the differential expression of key genes in normal and atherosclerotic aortic walls was verified. In vitro, we establish a model of ox-LDL-injured endothelial cells and transfect RAB5A overexpression and shRNA plasmids. The results showed that overexpression of RAB5A ameliorates the proliferation and migration function of ox-LDL-injured endothelial cells, including the ability of tubule formation. It was speculated that the interferon response, Notch signaling pathways, etc. were involved in this function of RAB5A by using gene set variation analysis. With the multiple bioinformatics analysis methods, we detected that yellow and tan modules are related to the abnormal proliferation and migration of endothelial cells associated with atherosclerosis. RAB5A, CTTN, ITGB1, and MMP9 can be used as potential targets for therapy and diagnostic markers. In vitro, overexpression of RAB5A can ameliorate the proliferation and migration function of ox-LDL-injured endothelial cells, and the possible molecules involved in this process were speculated.

Effect of APOB polymorphism rs562338 (G/A) on serum proteome of coronary artery disease patients: a "proteogenomic" approach

In the current study, APOB (rs1052031) genotype-guided proteomic analysis was performed in a cohort of Pakistani population. A total of 700 study subjects, including Coronary Artery Disease (CAD) patients (n = 480) and healthy individuals (n = 220) as a control group were included in the study. Genotyping was carried out by using tetra primer-amplification refractory mutation system-based polymerase chain reaction (T-ARMS-PCR) whereas mass spectrometry (Orbitrap MS) was used for label free quantification of serum samples. Genotypic frequency of GG genotype was found to be 90.1%, while 6.4% was for GA genotype and 3.5% was for AA genotypes in CAD patients. In the control group, 87.2% healthy subjects were found to have GG genotype, 11.8% had GA genotype, and 0.9% were with AA genotypes. Significant (p = 0.007) difference was observed between genotypic frequencies in the patients and the control group. The rare allele AA was found to be strongly associated with the CAD [OR: 4 (1.9-16.7)], as compared to the control group in recessive genetic model (p = 0.04). Using label free proteomics, altered expression of 60 significant proteins was observed. Enrichment analysis of these protein showed higher number of up-regulated pathways, including phosphatidylcholine-sterol O-acyltransferase activator activity, cholesterol transfer activity, and sterol transfer activity in AA genotype of rs562338 (G>A) as compared to the wild type GG genotype. This study provides a deeper insight into CAD pathobiology with reference to proteogenomics, and proving this approach as a good platform for identifying the novel proteins and signaling pathways in relation to cardiovascular diseases.

Gene-Environment Interactions for Cardiovascular Disease

PURPOSE OF REVIEW

We provide an overview of recent findings with respect to gene-environment (GxE) interactions for cardiovascular disease (CVD) risk and discuss future opportunities for advancing the field.

RECENT FINDINGS

Over the last several years, GxE interactions for CVD have mostly been identified for smoking and coronary artery disease (CAD) or related risk factors. By comparison, there is more limited evidence for GxE interactions between CVD outcomes and other exposures, such as physical activity, air pollution, diet, and sex. The establishment of large consortia and population-based cohorts, in combination with new computational tools and mouse genetics platforms, can potentially overcome some of the limitations that have hindered human GxE interaction studies and reveal additional association signals for CVD-related traits. The identification of novel GxE interactions is likely to provide a better understanding of the pathogenesis and genetic liability of CVD, with significant implications for healthy lifestyles and therapeutic strategies.

The association study between CYP20A1, CYP4F2, CYP2D6 gene polymorphisms and coronary heart disease risk in the Han population in southern China

BACKGROUND

Coronary heart disease (CHD) is a disease that seriously harms human health. Genetic factors seriously affect the CHD susceptibility. The CYP20A1, CYP4F2 and CYP2D6 are important drug metabolism enzymes in the human body.

OBJECTIVE

We aimed to explore the association between CYP20A1, CYP4F2, CYP2D6 single nucleotide polymorphisms (SNPs) and CHD risk in the Chinese Southern Han population.

METHODS

Based on the 'case-control' experimental design (505 cases and 508 controls), we conducted an association study between 5 candidate SNPs selected from CYP20A1 (rs2043449), CYP4F2 (rs2108622, rs3093106, rs309310), CYP2D6 (rs1065852) and CHD risk. Logistic regression was used to analyze the CHD susceptibility under different genetic models. Multi-factor dimensionality reduction (MDR) was used to analyze the interaction of 'SNP-SNP' in CHD risk.

RESULTS

Our results showed that under multiple genetic models, CYP2D6 rs1065852 significantly increased the CHD risk in these participants who are ≤ 60 years old (OR 1.40, CI 1.07-1.82, p = 0.013), smokers (OR 1.40, CI 1.02-1.93, p = 0.039), or have family history (OR 1.24, CI 1.02-1.51, p = 0.035). CYP4F2 SNPs rs2108622 (OR 0.63, CI 0.43-0.93, p = 0.020), rs3093106 (OR 0.52, CI 0.29-0.92, p = 0.023), and rs309310 (OR 0.55, CI 0.31-0.96, p = 0.033) were potentially associated with the course of CHD patients.

CONCLUSION

Our study found that CY2D6 rs1065852 has an outstanding and significant association with increased CHD risk. Our study provided data supplements for CHD genetic susceptibility loci, and also provided a new and valuable reference for CHD drug treatment.

Multiomics Analysis Coupled with Text Mining Identify Novel Biomarker Candidates for Recurrent Cardiovascular Events

Recurrent cardiovascular events remain an enigma that accounts for >30% of deaths worldwide. While heredity and human genetics variation play a key role, host-environment interactions offer a sound conceptual framework to dissect the molecular basis of recurrent cardiovascular events from genes and proteins to metabolites, thus accounting for environmental contributions as well. We report here a multiomics systems science approach so as to map interindividual variability in susceptibility to recurrent cardiovascular events. First, we performed data and text mining through a mixed-methods content analysis to select genomic variants, 10 single nucleotide polymorphisms, and microRNAs (miR-10a, miR-21, and miR-20a), minimizing bias in candidate marker selection. Next, we validated our in silico data in a patient cohort suffering from recurrent cardiovascular events (a cross-sectional study design and sampling). Our findings report a key role in low-density lipoprotein clearance for rs11206510 (p < 0.01) and rs515135 (p < 0.05). miR-10a (p < 0.05) was significantly associated with heart failure, while increased expression levels for miR-21 and miR-20a associated with atherosclerosis. In addition, liquid chromatography-mass spectrometry-based (LC-MS-based) proteomics analyses identified that vascular diameter and cholesterol levels are among the key factors to be considered in recurrent cardiovascular events. From a methodology innovation standpoint, this study offers a strategy to enhance the signal-to-noise ratios in mapping novel biomarker candidates wherein each research and conceptual step were interrogated for their validity and in turn, enriched one another, ideally translating information growth to knowledge growth.

Polygenic risk scores in coronary artery disease

PURPOSE OF REVIEW

Large genome-wide association studies (GWAS) have identified variants accounting for a substantial portion of the heritable risk for coronary artery disease (CAD). These studies have catalyzed drug discovery and generated the possibility of improved risk prediction and stratification. Here, we review the current state-of-the art in polygenic risk scores (PRSs) and look to the future, as these scores move towards clinical application.

RECENT FINDINGS

Over the last decade, multilocus PRSs for CAD have expanded to include millions of variants and demonstrated strong association with CAD outcomes, even when adjusted for traditional risk factors. Recently, PRSs have shown better prediction of CAD outcomes than any single traditional risk factor alone. Advances in statistical methods used to generate PRSs have improved their predictive ability and transferability between populations with varied ancestries. Initial clinical studies have also demonstrated the potential of genetic information to impact shared decision-making between patients and providers, leading to improved outcomes.

SUMMARY

PRSs can improve risk stratification for CAD especially in white/European populations and have the potential to alter routine clinical care. However, unlocking this potential will require additional research in PRSs in nonwhite populations and substantial investment in clinical implementation studies.

Blood Group Types O and Non-O Are Associated With Coronary Collateral Circulation Development

Blood group types are associated with coronary artery disease. However, data are scarce about the impact of blood group types on coronary collateral circulation. In this study, we aimed to investigate the relationship between the blood group types and coronary collateral circulation. Two hundred and twelve patients who underwent coronary angiography in our department and had a stenosis of ≥ 90% in at least one major epicardial vessel were included in our study. Collateral degree was graded according to Rentrop-Cohen classification. After grading, patients were divided into poor coronary collateral circulation (Rentrop grade 0 and 1) and good coronary collateral circulation (Rentrop 2 and 3) groups. The ABO blood type of all participants was determined. The incidence rates of O blood group type were significantly higher in the good coronary collateral group compared to the poor collateral group (37.9% vs 17.1%, P < .001). The O type blood group was an independent predictor of good coronary collateral circulation (odds ratio = 1.83, 95% confidence interval = 1.56-6.18, P = .015). Coronary collateral circulation is associated with blood group types. The O blood group predicts good coronary collateral development among patients with coronary artery disease.

<i>In silico</i> mapping of coronary artery disease genes

To date, more than 100 loci associated with coronary artery disease (CAD) have been detected in large-scale genome-wide studies. For some of the several hundreds of genes located in these loci, roles in the pathogenesis of the disease have been shown. However, the genetic mechanisms and specific genes controlling this disease are still not fully understood. This study is aimed at in silico search for new CAD genes. We performed a gene-based association analysis, where all polymorphic variants within a gene are analyzed simultaneously. The analysis was based on the results of the genome-wide association studies (GWAS) available from the open databases MICAD (120,575 people, 85,112 markers) and UK Biobank (337,199 people, 10,894,597 markers). We used the sumFREGAT package implementing a wide range of new methods for gene-based association analysis using summary statistics. We found 88 genes demonstrating significant gene-based associations. Forty-four of the identified genes were already known as CAD genes. Furthermore, we identified 28 additional genes in the known CAD loci. They can be considered as new candidate genes. Finally, we identified sixteen new genes (AGPAT4, ARHGEF12, BDP1, DHX58, EHBP1, FBF1, HSPB9, NPBWR2, PDLIM5, PLCB3, PLEKHM2, POU2F3, PRKD2, TMEM136, TTC29 and UTP20) outside the known loci. Information about the functional role of these genes allows us to consider many of them as candidates for CAD. The 41 identified genes did not have significant GWAS signals and they were identified only due to simultaneous consideration of all variants within the gene in the framework of gene-based analysis. These results demonstrate that gene-based association analysis is a powerful tool for gene mapping. The method can utilize huge amounts of GWAS results accumulated in the world to map different traits and diseases. This type of studies is widely available, as it does not require additional material costs.

Impact of renin-angiotensin-aldosterone system polymorphisms on myocardial perfusion: Correlations with myocardial single photon emission computed tomography-derived parameters

BACKGROUND

Renin-angiotensin-aldosterone system (RAAS) has an important role in atherosclerosis. We investigated the effects of six RAAS gene polymorphisms on myocardial perfusion.

METHODS AND RESULTS

We examined 810 patients with known or suspected coronary artery disease (CAD) using stress-rest myocardial single-photon emission computed tomography. Summed stress score (SSS), summed rest score (SRS), summed difference score (SDS), transient ischemic dilation (TID), and lung/heart ratio (LHR) were recorded. The following gene polymorphisms were investigated: angiotensin-converting enzyme (ACE) insertion/deletion (I/D), angiotensinogen (AGT) M235T and T174M, angiotensin II type 1 receptor (AT1R) A1166C, renin (REN) C5312T, and angiotensin II type 2 receptor (AT2R) C3123A. The heterozygotes or homozygotes on ACE D allele were 7.54 times more likely to have abnormal SSS, while the AGT (T174M) heterozygotes were 5.19 times more likely to have abnormal SSS. The homozygotes of ACE D had significantly higher values on TID and LHR, while the AGT (T174M) heterozygotes had higher values on TID. The AT1R heterozygotes had greater odds for having SSS ≥ 3. The patients carried AT1R homozygosity of C allele had significantly higher values on TID, while heterozygotes of AT1R had significantly higher values on LHR.

CONCLUSIONS

Among the polymorphisms investigated, ACE D allele had the strongest association with abnormal myocardial perfusion.

Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland

Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.

Metabolic and genetic profiling of young adults with and without a family history of premature coronary heart disease (MAGNETIC). Study design and methodology

INTRODUCTION

First-degree relatives of individuals with premature coronary artery disease (CAD) are at increased risk of CAD. The research hypothesis of this project assumes that there are differences in the metabolic profiles between individuals with and without a positive family history (FH) of premature CAD.

MATERIAL AND METHODS

The study group will comprise healthy patients (n = 500) aged 18-35 years with a FH of premature CAD, and the control group (n = 500) will consist of healthy subjects without a FH of premature CAD. Blood tests assessing the lipid profile will be carried out. Patients will respond to a questionnaire regarding FH and dietary habits. Measurement of carotid intima media thickness will be performed. Analysis of single-nucleotide polymorphisms (SNPs) associated with premature CAD will be carried out for every patient. Metabolomic profiling will be performed using a high-sensitivity Bruker AVANCE II 600 MHz NMR spectroscope.

RESULTS

The results of this study will include a comparison of metabolic profiles assessed by 1H-NMR spectroscopy in the study and control groups and the results of analyses of the relationship between the metabolic profiles and genetic risk score calculated based on evaluated SNPs associated with premature CAD.

CONCLUSIONS

This study will deepen our knowledge of the aetiopathogenesis of atherosclerosis by identifying metabolic patterns associated with a positive FH of premature CAD. Obtaining a detailed FH will enable adjustments for major risk factors of premature CAD in the proband's first-degree relatives. This research project also provides a chance to discover new biomarkers associated with the risk of premature CAD.

Enhancement of Functionality and Therapeutic Efficacy of Cell-Based Therapy Using Mesenchymal Stem Cells for Cardiovascular Disease

Cardiovascular disease usually triggers coronary heart disease, stroke, and ischemic diseases, thus promoting the development of functional failure. Mesenchymal stem cells (MSCs) are cells that can be isolated from various human tissues, with multipotent and immunomodulatory characteristics to help damaged tissue repair and avoidance of immune responses. Much research has proved the feasibility, safety, and efficiency of MSC-based therapy for cardiovascular disease. Despite the fact that the precise mechanism of MSCs remains unclear, their therapeutic capability to treat ischemic diseases has been tested in phase I/II clinical trials. MSCs have the potential to become an effective therapeutic strategy for the treatment of ischemic and non-ischemic cardiovascular disorders. The molecular mechanism underlying the efficacy of MSCs in promoting engraftment and accelerating the functional recovery of injury sites is still unclear. It is hypothesized that the mechanisms of paracrine effects for the cardiac repair, optimization of the niche for cell survival, and cardiac remodeling by inflammatory control are involved in the interaction between MSCs and the damaged myocardial environment. This review focuses on recent experimental and clinical findings related to cardiovascular disease. We focus on MSCs, highlighting their roles in cardiovascular disease repair, differentiation, and MSC niche, and discuss their therapeutic efficacy and the current status of MSC-based cardiovascular disease therapies.

Effects of early intravenous low-dose of metoprolol on cardiac sympathetic activities and electrophysiological properties in myocardial infarction heart

This study observed the effects of early intravenous low-doses of metoprolol on cardiac sympathetic activities and electrophysiological properties in myocardial infarction (MI) dogs. Thirty two mongrel dogs with the first diagonal branch of the left anterior descending coronary artery ligated were randomly divided into three groups: The low-dose group was given metoprolol 0.6 mg/kg immediately by intravenous injection (n=12); the target-dose group was given metoprolol 1.6 mg/kg (n=12), and the control group was injected with normal saline at the same dose of the target-dose group (n=8). Norepinephrine (NE) and epinephrine (E) levels in the coronary sinus (CS) blood as well as the ventricular effective refractory period (ERP) were all measured during the experiments. We found that NE and E concentrations in the three groups were all increased compared with the previous measurement before ligation. ERP values after MI were significantly decreased in all three groups compared with the first measurements. The three groups all exhibited uneven shortness of ERP among different regions, with significant shortness in infarcted area. Furthermore, there was no difference between the low and target-dose of metoprolol in the reduction of regional ERP, and the same effect was also observed in induced arrhythmias. In conclusion, a lower dose of metoprolol performed similarly as target-dose in reducing the catecholamine concentrations in dogs with MI. Our study demonstrated that a lower dose of metoprolol may be reasonable compared with the target-dose in β-blocker therapy due to similar effect and lower toxicity.

Common atherosclerosis genetic risk factors and subclinical atherosclerosis in rheumatoid arthritis: the relevance of disease duration

Rheumatoid arthritis (RA) is a common systemic autoimmune disease characterized by increased cardiovascular morbidity. Several previous studies assessed associations between common atherosclerotic genetic risk factors and subclinical atherosclerosis (SA) in RA patients, yet most of them gave negative results. We undertook a cross-sectional study to evaluate the association between previously reported SNPs and subclinical atherosclerosis in a cohort of Polish RA patients. 29 SNPs associated with atherosclerosis in general population were genotyped in 289 RA patients: 116 patients with SA (increased carotid intima-media thickness and/or presence of carotid plaque) and 173 patients without SA. To assess the cumulative effect of SNPs we calculated 3 weighted genetic risk scores: GRS_IMT, GRS_CP and GRS_CAD, comprising intima-media thickness-associated SNPs, carotid plaque-associated SNPs and coronary artery disease-associated SNPs, respectively. None of the SNPs showed a significant association with SA. However, we found an association between SA and GRS_IMT. Interestingly, this association was limited to patients with short disease duration (P = 0.00004 vs. P > 0.5, for comparison of GRS_IMT among patients within the 1st quartile of disease duration vs. others, respectively). Patients within the 1st quartile of disease duration were more frequently disease modifying anti-rheumatic drugs (DMARDs)-naïve and less frequently treated with biologics. Our study suggests that in patients with early RA subclinical atherosclerosis may be driven by similar genetic factors as in general population, while in long-lasting disease, the role common genetic risk factors may decrease. Possibly, this effect may be due to the influence of DMARDs.

Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach

Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels. Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed. In this review, we will summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI; with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) over the last 10 years. Moreover, in addition to the autosomal genome, we will also consider the genetic variation in our “second genome”—the mitochondrial genome. Finally, we will summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine.

Genetic Markers for Coronary Artery Disease

Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting.

Novel molecular targets for coronary angiogenesis and ischemic heart disease

Coronary artery disease (CAD) is the number one cause of death among men and women in the USA. Genetic predisposition and environmental factors lead to the development of atherosclerotic plaques in the vessel walls of the coronary arteries, resulting in decreased myocardial perfusion. Treatment includes a combination of revascularization procedures and medical therapy. Because of the high surgical risk of many of the patients undergoing revascularization procedures, medical therapies to reduce ischemic disease are an area of active research. Small molecule, cytokine, endothelial progenitor cell, stem cell, gene, and mechanical therapies show promise in increasing the collateral growth of blood vessels, thereby reducing myocardial ischemia.

Polymorphisms of CYP2C8, CYP2C9 and CYP2C19 and risk of coronary heart disease in Russian population

Epoxyeicosatrienoic acids (EETs) are important vasoactive products of arachidonic acid metabolism with a wide range of biological actions in the cardiovascular system. The present study investigated whether single nucleotide polymorphisms (SNP) of genes coding cytochrome P450 2C subfamily, enzymes involved in biosynthesis of EETs, are associated with the risk of coronary heart disease (CHD). A total of 1255 unrelated Russian subjects comprising 561 patients with angiographically diagnosed CHD and 694 age- and sex-matched healthy subjects were included in the study. DNA samples from all study participants were genotyped for six common SNPs rs7909236, rs1934953 of CYP2C8, rs9332242, rs4918758 and rs61886769 of CYP2C9 and rs4244285 of CYP2C19 using by the Mass-ARRAY 4 system. SNP rs4918758 of CYP2C9 was associated with decreased risk of CHD (codominant model) at a borderline significance with odds ratio adjusted for sex and age 0.61 (95% CI: 0.41-0.92, P=0.038, Q=0.20). SNP rs9332242 of CYP2C9 showed a trend towards association with increased CHD risk in cigarette smokers (P=0.049, Q=0.29). Log-likelihood ratio test (LRT) pointed out epistatic interactions between rs9332242 and rs61886769 of CYP2C9 (codominant model, P_interaction=0.02), however, this P-value did not survive after correction for multiple tests. Bioinformatic analysis revealed a regulatory potential for a majority of the investigated SNPs. Our preliminary results demonstrate that polymorphisms of genes encoding CYP2C subfamily represent potential genetic markers of CHD susceptibility. Further studies are required to substantiate the contribution of these genes to the disease risk.