GWAS Reveal Targets in Vessel Wall Pathways to Treat Coronary Artery Disease

Pharmacogenomics-based systematic review of coronary artery disease based on personalized medicine procedure

Background

Coronary artery disease (CAD) is the most common reason for mortality and disability-adjusted life years (DALYs) lost globally. This study aimed to suggest a new gene list for the treatment of CAD by a systematic review of bioinformatics analyses of pharmacogenomics impacts of potential genes and variants.

Methods

PubMed search was filtered by the title including Coronary Artery Disease during 2020-2023. To find the genes with pharmacogenetic impact on the CAD, additional filtrations were considered according to the variant annotations. Protein-Protein Interactions (PPIs), Gene-miRNA Interactions (GMIs), Protein-Drug Interactions (PDIs), and variant annotation assessments (VAAs) performed by STRING-MODEL (ver. 12), Cytoscape (ver. 3.10), miRTargetLink.2., NetworkAnalyst (ver 0.3.0), and PharmGKB.

Results

Results revealed 5618 publications, 1290 papers were qualified, and finally, 650 papers were included. 4608 protein-coding genes were extracted, among them, 1432 unique genes were distinguished and 530 evidence-based repeated genes remained. 71 genes showed a pharmacogenetics-related variant annotation in at least (entirely 6331 annotations). Variant annotation assessment (VAA) showed 532 potential variants for the final report, and finally, the concluding PGs list represented 175 variants. Based on the function and MAF, 57 nonsynonymous variants of 29 Pharmacogenomics-related genes were associated with CAD.

Conclusion

Conclusively, evaluating circulating miR33a in individuals' plasma with CAD, and genotyping of rs2230806, rs2230808, rs2487032, rs12003906, rs2472507, rs2515629, and rs4149297 (ABCA1 variants) lead to precisely prescribing of well-known drugs. Also, the findings of this review can be used in both whole-genome sequencing (WGS) and whole-exome sequencing (WES) analysis in the prognosis and diagnosis of CAD.

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.

Vascular smooth muscle cells in low SYNTAX scores coronary artery disease exhibit proinflammatory transcripts and proteins correlated with IL1B activation

BACKGROUND AND AIMS

The SYNTAX score is clinically validated to stratify number of lesions and pattern of CAD. A better understanding of the underlying molecular mechanisms influencing the pattern and complexity of coronary arteries lesions among CAD patients is needed.

METHODS

Human arterial biopsies from 49 patients (16 low-SYNTAX-score (LSS, <23), 16 intermediate-SYNTAX-score (ISS, 23 to 32) and 17 high-SYNTAX-score (HSS, >32)) were evaluated using Affymetrix GeneChip® Human Genome U133 Plus 2.0 microarray. The data were validated by Next-Generation Sequencing (NGS). Primary VSMC from patients with low and high SYNTAX scores were isolated and compared using immunohistochemistry, qPCR and immunoblotting to confirm mRNA and proteomic results.

RESULTS

The IL1B was verified as the top upstream regulator of 47 inflammatory DEGs in LSS patients and validated by another sets of patient samples using NGS analysis. The upregulated expression of IL1B was translated to increased level of IL1β protein in the LSS tissue based on immunohistochemical quantitative analysis. Plausibility of idea that IL1B in the arterial wall could be originated from VSMC was checked by exposing culture to proinflammatory conditions where IL1B came out as the top DEG (logFC = 7.083, FDR = 1.38 × 10-114). The LSS patient-derived primary VSMCs confirmed higher levels of IL1B mRNA and protein.

CONCLUSIONS

LSS patients could represent a group of patients where IL1B could play a substantial role in disease pathogenesis. The LSS group could represent a plausible cohort of patients for whom anti-inflammatory therapy could be considered.

Coronary artery disease and cancer: a significant resemblance

Cancer and coronary artery disease (CAD) are two of the most common causes of death, and they frequently coexist, especially as the world's population ages. CAD can develop prior to or following cancer diagnosis, as well as a side effect of cancer treatment. CAD develops as complex interactions of lifestyle and hereditary variables, just like the development of the most complex and non-communicable diseases. Cancer is caused by both external/acquired factors (tobacco, food, physical activity, alcohol consumption, epigenetic alterations) and internal/inherited factors (genetic mutations, hormones, and immunological diseases). The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) system has recently emerged as a strong tool for gene therapy for both cancer as well as CAD treatment due to its great accuracy and efficiency. A deeper understanding of the complex link between CAD and cancer should lead to better prevention, faster detection, and safer treatment strategies.

Genetics of coronary artery disease in the post-GWAS era

During the past decade, genome-wide association studies (GWAS) have transformed our understanding of many heritable traits. Three recent large-scale GWAS meta-analyses now further markedly expand the knowledge on coronary artery disease (CAD) genetics in doubling the number of loci with genome-wide significant signals. Here, we review the unprecedented discoveries of CAD GWAS on low-frequency variants, underrepresented populations, sex differences and integrated polygenic risk. We present the milestones of CAD GWAS and post-GWAS studies from 2007 to 2021, and the trend in identification of variants with smaller odds ratio by year due to the increasing sample size. We compile the 321 CAD loci discovered thus far and classify candidate genes as well as distinct functional pathways on the road to indepth biological investigation and identification of novel treatment targets. We draw attention to systems genetics in integrating these loci into gene regulatory networks within and across tissues. We review the traits, biomarkers and diseases scrutinized by Mendelian randomization studies for CAD. Finally, we discuss the potentials and concerns of polygenic scores in predicting CAD risk in patient care as well as future directions of GWAS and post-GWAS studies in the field of precision medicine.

Vascular smooth muscle cells in atherosclerosis: time for a re-assessment

Vascular smooth muscle cells (VSMCs) are key participants in both early and late-stage atherosclerosis. VSMCs invade the early atherosclerotic lesion from the media, expanding lesions, but also forming a protective fibrous cap rich in extracellular matrix to cover the 'necrotic' core. Hence, VSMCs have been viewed as plaque-stabilizing, and decreased VSMC plaque content-often measured by expression of contractile markers-associated with increased plaque vulnerability. However, the emergence of lineage-tracing and transcriptomic studies has demonstrated that VSMCs comprise a much larger proportion of atherosclerotic plaques than originally thought, demonstrate multiple different phenotypes in vivo, and have roles that might be detrimental. VSMCs down-regulate contractile markers during atherosclerosis whilst adopting alternative phenotypes, including macrophage-like, foam cell-like, osteochondrogenic-like, myofibroblast-like, and mesenchymal stem cell-like. VSMC phenotypic switching can be studied in tissue culture, but also now in the media, fibrous cap and deep-core region, and markedly affects plaque formation and markers of stability. In this review, we describe the different VSMC plaque phenotypes and their presumed cellular and paracrine functions, the regulatory mechanisms that control VSMC plasticity, and their impact on atherogenesis and plaque stability.

Precision Medicine Approaches to Vascular Disease: JACC Focus Seminar 2/5

In this second of a 5-part Focus Seminar series, we focus on precision medicine in the context of vascular disease. The most common vascular disease worldwide is atherosclerosis, which is the primary cause of coronary artery disease, peripheral vascular disease, and a large proportion of strokes and other disorders. Atherosclerosis is a complex genetic disease that likely involves many hundreds to thousands of single nucleotide polymorphisms, each with a relatively modest effect for causing disease. Conversely, although less prevalent, there are many vascular disorders that typically involve only a single genetic change, but these changes can often have a profound effect that is sufficient to cause disease. These are termed "Mendelian vascular diseases," which include Marfan and Loeys-Dietz syndromes. Given the very different genetic basis of atherosclerosis versus Mendelian vascular diseases, this article was divided into 2 parts to cover the most promising precision medicine approaches for these disease types.

Microanatomy of the Human Atherosclerotic Plaque by Single-Cell Transcriptomics

RATIONALE

Atherosclerotic lesions are known for their cellular heterogeneity, yet the molecular complexity within the cells of human plaques has not been fully assessed.

OBJECTIVE

Using single-cell transcriptomics and chromatin accessibility, we gained a better understanding of the pathophysiology underlying human atherosclerosis.

METHODS AND RESULTS

We performed single-cell RNA and single-cell ATAC sequencing on human carotid atherosclerotic plaques to define the cells at play and determine their transcriptomic and epigenomic characteristics. We identified 14 distinct cell populations including endothelial cells, smooth muscle cells, mast cells, B cells, myeloid cells, and T cells and identified multiple cellular activation states and suggested cellular interconversions. Within the endothelial cell population, we defined subsets with angiogenic capacity plus clear signs of endothelial to mesenchymal transition. CD4+ and CD8+ T cells showed activation-based subclasses, each with a gradual decline from a cytotoxic to a more quiescent phenotype. Myeloid cells included 2 populations of proinflammatory macrophages showing IL (interleukin) 1B or TNF (tumor necrosis factor) expression as well as a foam cell-like population expressing TREM2 (triggering receptor expressed on myeloid cells 2) and displaying a fibrosis-promoting phenotype. ATACseq data identified specific transcription factors associated with the myeloid subpopulation and T cell cytokine profiles underlying mutual activation between both cell types. Finally, cardiovascular disease susceptibility genes identified using public genome-wide association studies data were particularly enriched in lesional macrophages, endothelial, and smooth muscle cells.

CONCLUSIONS

This study provides a transcriptome-based cellular landscape of human atherosclerotic plaques and highlights cellular plasticity and intercellular communication at the site of disease. This detailed definition of cell communities at play in atherosclerosis will facilitate cell-based mapping of novel interventional targets with direct functional relevance for the treatment of human disease.

Genetic Insights Into Smooth Muscle Cell Contributions to Coronary Artery Disease

Coronary artery disease is a complex cardiovascular disease involving an interplay of genetic and environmental influences over a lifetime. Although considerable progress has been made in understanding lifestyle risk factors, genetic factors identified from genome-wide association studies may capture additional hidden risk undetected by traditional clinical tests. These genetic discoveries have highlighted many candidate genes and pathways dysregulated in the vessel wall, including those involving smooth muscle cell phenotypic modulation and injury responses. Here, we summarize experimental evidence for a few genome-wide significant loci supporting their roles in smooth muscle cell biology and disease. We also discuss molecular quantitative trait locus mapping as a powerful discovery and fine-mapping approach applied to smooth muscle cell and coronary artery disease-relevant tissues. We emphasize the critical need for alternative genetic strategies, including cis/trans-regulatory network analysis, genome editing, and perturbations, as well as single-cell sequencing in smooth muscle cell tissues and model organisms, under both normal and disease states. By integrating multiple experimental and analytical modalities, these multidimensional datasets should improve the interpretation of coronary artery disease genome-wide association studies and molecular quantitative trait locus signals and inform candidate targets for therapeutic intervention or risk prediction.

Next-generation drug repurposing using human genetics and network biology

Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatments have high costs that are difficult to justify for small markets that include rare diseases. Drug repurposing, involving the identification of single or combinations of existing drugs based on human genetics data and network biology approaches represents a next-generation approach that has the potential to increase the speed of drug discovery at a lower cost. This Pharmacological Perspective reviews progress and perspectives in combining human genetics, especially genome-wide association studies, with network biology to drive drug repurposing for rare and common diseases with monogenic or polygenic etiologies. Also, highlighted here are important features of this next generation approach to drug repurposing, which can be combined with machine learning methods to meet the challenges of personalized medicine.

Contributions of Interactions Between Lifestyle and Genetics on Coronary Artery Disease Risk

PURPOSE OF THE REVIEW

To summarize current knowledge on interactions between genetic variants and lifestyle factors (G×L) associated with the development of coronary artery disease (CAD) and prioritize future research.

RECENT FINDINGS

Genetic risk and combined lifestyle factors and behaviors have a log-additive effect on the risk of developing CAD. First, we describe genetic and lifestyle factors associated with CAD and then focus on G×L interactions. The majority of G×L interaction studies are small-scale candidate gene studies that lack replication and therefore provide spurious results. Only a few studies, of which most use genetic risk scores or genome-wide approaches to test interactions, are robust in number and analysis strategy. These studies provide evidence for the existence of G×L interactions in the development of CAD. Further G×L interactions studies are important as they contribute to our understanding of disease pathophysiology and possibly provide insights for improving interventions or personalized recommendations.

Multi-contrast imaging information of coronary artery wall based on magnetic resonance angiography

In order to explore the most suitable image acquisition method for coronary artery wall, the display ability and image quality of segmentation breath-holding target volume acquisition method (the breath-holding method) and real-time navigation whole-hearted acquisition method (the navigation method) of coronary artery magnetic resonance angiography (CMRA) were compared. 26 healthy volunteers were selected to accept the CMRA in 1.5 tunnels magneto-resistance (TMR) equipment by the 2 acquisition methods respectively. The arteries were divided into 9 segments according to the standards of the American Heart Association (AHA). The images were evaluated by 2 magnetic resonance physicians. Satisfaction rate and success rate of each segment of the coronary artery were counted. The results showed that the signal to noise ratio (SNR) and the carrier to noise ratio (CNR) of the images obtained by the breath-holding method were higher than those obtained by the navigation method (P<0.05). Therefore, the segmentation breath-holding target volume acquisition method is proved to have a higher image quality and the simpler and more convenient operations, which is more suitable for the acquisition of positioning images of CMRA.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.