Integrative Prioritization of Causal Genes for Coronary Artery Disease

Integrated Analysis of Genomic and Genome-Wide Association Studies Identified Candidate Genes for Nutrigenetic Studies in Flavonoids and Vascular Health: Path to Precision Nutrition for (Poly)phenols

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.

Prioritization of genes for translation: a computational approach

INTRODUCTION

Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation.

AREAS COVERED

In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes.

EXPERT OPINION

Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

Omics Approaches Unveiling the Biology of Human Atherosclerotic Plaques

Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the buildup of plaques with the accumulation and transformation of lipids, immune cells, vascular smooth muscle cells, and necrotic cell debris. Plaques with collagen-poor thin fibrous caps infiltrated by macrophages and lymphocytes are considered unstable because they are at the greatest risk of rupture and clinical events. However, the current histologic definition of plaque types may not fully capture the complex molecular nature of atherosclerotic plaque biology and the underlying mechanisms contributing to plaque progression, rupture, and erosion. The advances in omics technologies have changed the understanding of atherosclerosis plaque biology, offering new possibilities to improve risk prediction and discover novel therapeutic targets. Genomic studies have shed light on the genetic predisposition to atherosclerosis, and integrative genomic analyses expedite the translation of genomic discoveries. Transcriptomic, proteomic, metabolomic, and lipidomic studies have refined the understanding of the molecular signature of atherosclerotic plaques, aiding in data-driven hypothesis generation for mechanistic studies and offering new prospects for biomarker discovery. Furthermore, advancements in single-cell technologies and emerging spatial analysis techniques have unveiled the heterogeneity and plasticity of plaque cells. This review discusses key omics-based discoveries that have advanced the understanding of human atherosclerotic plaque biology, focusing on insights derived from omics profiling of human atherosclerotic vascular specimens.

Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables

Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outcome of interest. At genomic loci with pleiotropic gene regulatory effects, that is, loci where the same genetic variants are associated to multiple nearby genes, MVMR can potentially be used to predict candidate causal genes. However, consensus in the field dictates that the genetic instruments in MVMR must be independent (not in linkage disequilibrium), which is usually not possible when considering a group of candidate genes from the same locus. Here we used causal inference theory to show that MVMR with correlated instruments satisfies the instrumental set condition. This is a classical result by Brito and Pearl (2002) for structural equation models that guarantees the identifiability of individual causal effects in situations where multiple exposures collectively, but not individually, separate a set of instrumental variables from an outcome variable. Extensive simulations confirmed the validity and usefulness of these theoretical results even at modest sample sizes ( n ≳ 500   - 1000 ) . Importantly, the causal effect estimates remain unbiased and their variance small when instruments are highly correlated. We applied MVMR with correlated instrumental variable sets at genome-wide significant loci for coronary artery disease (CAD) risk using expression Quantitative Trait Loci (eQTL) data from seven vascular and metabolic tissues in the STARNET study. Our method predicts causal genes at twelve loci, each associated with multiple colocated genes in multiple tissues. We confirm causal roles for PHACTR1 and ADAMTS7 in arterial tissues, among others. However, the extensive degree of regulatory pleiotropy across tissues and the limited number of causal variants in each locus still require that MVMR is run on a tissue-by-tissue basis, and testing all gene-tissue pairs with cis-eQTL associations at a given locus in a single model to predict causal gene-tissue combinations remains infeasible. Our results show that within tissues, MVMR with dependent, as opposed to independent, sets of instrumental variables significantly expands the scope for predicting causal genes in disease risk loci with pleiotropic regulatory effects. However, considering risk loci with regulatory pleiotropy that also spans across tissues remains an unsolved problem.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells

BACKGROUND

Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1-four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 (FHL5; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci.

METHODS

We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells.

RESULTS

We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling.

CONCLUSIONS

Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.

Noninvasive Plaque Imaging to Accelerate Coronary Artery Disease Drug Development

Coronary artery disease (CAD) remains the leading cause of adult mortality globally. Targeting known modifiable risk factors has had substantial benefit, but there remains a need for new approaches. Improvements in invasive and noninvasive imaging techniques have enabled an increasing recognition of distinct quantitative phenotypes of coronary atherosclerosis that are prognostically relevant. There are marked differences in plaque phenotype, from the high-risk, lipid-rich, thin-capped atheroma to the low-risk, quiescent, eccentric, nonobstructive calcified plaque. Such distinct phenotypes reflect different pathophysiologic pathways and are associated with different risks for acute ischemic events. Noninvasive coronary imaging techniques, such as computed tomography, positron emission tomography, and coronary magnetic resonance imaging, have major potential to accelerate cardiovascular drug development, which has been affected by the high costs and protracted timelines of cardiovascular outcome trials. This may be achieved through enrichment of high-risk phenotypes with higher event rates or as primary end points of drug efficacy, at least in phase 2 trials, in a manner historically performed through intravascular coronary imaging studies. Herein, we provide a comprehensive review of the current technology available and its application in clinical trials, including implications for sample size requirements, as well as potential limitations. In its effort to accelerate drug development, the US Food and Drug Administration has approved surrogate end points for 120 conditions, but not for CAD. There are robust data showing the beneficial effects of drugs, including statins, on CAD progression and plaque stabilization in a manner that correlates with established clinical end points of mortality and major adverse cardiovascular events. This, together with a clear mechanistic rationale for using imaging as a surrogate CAD end point, makes it timely for CAD imaging end points to be considered. We discuss the importance of global consensus on these imaging end points and protocols and partnership with regulatory bodies to build a more informed, sustainable staged pathway for novel therapies.

PHACTR1, a coronary artery disease risk gene, mediates endothelial dysfunction

Genome-wide association studies (GWAS) have recently identified phosphatase and actin regulator-1 (PHACTR1) as a critical risk gene associated with polyvascular diseases. However, it remains largely unclear how PHACTR1 is involved in endothelial dysfunction. Here, by mining published datasets of human stable and vulnerable/ruptured plaque tissues, we observed upregulated expression of PHACTR1 in vulnerable/ruptured plaques. Congruent with these data, we demonstrated increased Phactr1 gene expression in aortic endothelium from ApoE^-/- mice fed a western type diet compared with that in normal C57BL/6J mice. Relevantly, PHACTR1 gene expression was upregulated by pro-inflammatory and pro-atherogenic stimuli, including TNF-α, IL-1β and oxidized LDL (oxLDL). By employing next-generation RNA sequencing, we demonstrate that PHACTR1 overexpression disrupts pathways associated with endothelial homeostasis. Cell biological studies unravel that PHACTR1 mediates endothelial inflammation and monocyte adhesion by activating NF-κB dependent intercellular adhesion molecule 1 (ICAM1) and vascular cell adhesion molecule 1 (VCAM1) expression. In addition, overexpression of PHACTR1 also reduces the generation of nitric oxide (NO) by inhibiting Akt/eNOS activation. In-house compound screening of vasoprotective drugs identifies several drugs, including lipid-lowering statins, decreases PHACTR1 gene expression. However, PHACTR1 gene expression was not affected by another lipid-lowering drug-fenofibrate. We also performed a proteomic study to reveal PHACTR1 interacting proteins and validated that PHACTR1 can interact with heat shock protein A8 (HSPA8) which was reported to be associated with coronary artery disease and eNOS degradation. Further studies are warranted to confirm the precise mechanism of PHACTR1 in driving endothelial dysfunction. In conclusion, by using systems biology approach and molecular validation, we disclose the deleterious effects of PHACTR1 on endothelial function by inducing endothelial inflammation and reducing NO production, highlighting the potential to prevent endothelial dysfunction and atherosclerosis by targeting PHACTR1 expression. The precise role of endothelial cell PHACTR1 in polyvascular diseases remains to be validated in diseased conditions.

Opportunities and Challenges in Understanding Atherosclerosis by Human Biospecimen Studies

Over the last few years, new high-throughput biotechnologies and bioinformatic methods are revolutionizing our way of deep profiling tissue specimens at the molecular levels. These recent innovations provide opportunities to advance our understanding of atherosclerosis using human lesions aborted during autopsies and cardiac surgeries. Studies on human lesions have been focusing on understanding the relationship between molecules in the lesions with tissue morphology, genetic risk of atherosclerosis, and future adverse cardiovascular events. This review will highlight ways to utilize human atherosclerotic lesions in translational research by work from large cardiovascular biobanks to tissue registries. We will also discuss the opportunities and challenges of working with human atherosclerotic lesions in the era of next-generation sequencing.

Transcriptomic Profile of Genes Regulating the Structural Organization of Porcine Atrial Cardiomyocytes during Primary In Vitro Culture

Numerous cardiovascular diseases (CVD) eventually lead to severe myocardial dysfunction, which is the most common cause of death worldwide. A better understanding of underlying molecular mechanisms of cardiovascular pathologies seems to be crucial to develop effective therapeutic options. Therefore, a worthwhile endeavor is a detailed molecular characterization of cells extracted from the myocardium. A transcriptomic profile of atrial cardiomyocytes during long-term primary cell culture revealed the expression patterns depending on the duration of the culture and the heart segment of origin (right atrial appendage and right atrium). Differentially expressed genes (DEGs) were classified as involved in ontological groups such as: “cellular component assembly”, “cellular component organization”, “cellular component biogenesis”, and “cytoskeleton organization”. Transcriptomic profiling allowed us to indicate the increased expression of COL5A2, COL8A1, and COL12A1, encoding different collagen subunits, pivotal in cardiac extracellular matrix (ECM) structure. Conversely, genes important for cellular architecture, such as ABLIM1, TMOD1, XIRP1, and PHACTR1, were downregulated during in vitro culture. The culture conditions may create a favorable environment for reconstruction of the ECM structures, whereas they may be suboptimal for expression of some pivotal transcripts responsible for the formation of intracellular structures.

Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases

Cardiovascular diseases (CVD) are diverse disorders affecting the heart and vasculature in millions of people worldwide. Like other fields, CVD research has benefitted from the deluge of multiomics biomedical data. Current CVD research focuses on disease etiologies and mechanisms, identifying disease biomarkers, developing appropriate therapies and drugs, and stratifying patients into correct disease endotypes. Systems biology offers an alternative to traditional reductionist approaches and provides impetus for a comprehensive outlook toward diseases. As a focus area, network medicine specifically aids the translational aspect of in silico research. This review discusses the approach of network medicine and its application to CVD research.

PPARγ Gene Polymorphisms, Metabolic Disorders, and Coronary Artery Disease

Being activated by endogenous and exogenous ligands, nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) enhances insulin sensitivity, promotes adipocyte differentiation, stimulates adipogenesis, and has the properties of anti-atherosclerosis, anti-inflammation, and anti-oxidation. The Human PPARγ gene (PPARG) contains thousands of polymorphic loci, among them two polymorphisms (rs10865710 and rs7649970) in the promoter region and two polymorphisms (rs1801282 and rs3856806) in the exonic region were widely reported to be significantly associated with coronary artery disease (CAD). Mechanistically, PPARG polymorphisms lead to abnormal expression of PPARG gene and/or dysfunction of PPARγ protein, causing metabolic disorders such as hypercholesterolemia and hypertriglyceridemia, and thereby increasing susceptibility to CAD.