Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease

Advancements in Omics and Breakthrough Gene Therapies: A Glimpse into the Future of Peripheral Artery Disease

Peripheral artery disease (PAD), a highly prevalent global disease, associates with significant morbidity and mortality in affected patients. Despite progress in endovascular and open revascularization techniques for advanced PAD, these interventions grapple with elevated rates of arterial restenosis and vein graft failure attributed to intimal hyperplasia (IH). Novel multiomics technologies, coupled with sophisticated analyses tools recently powered by advances in artificial intelligence, have enabled the study of atherosclerosis and IH with unprecedented single-cell and spatial precision. Numerous studies have pinpointed gene hubs regulating pivotal atherogenic and atheroprotective signaling pathways as potential therapeutic candidates. Leveraging advancements in viral and nonviral gene therapy (GT) platforms, gene editing technologies, and cutting-edge biomaterial reservoirs for delivery uniquely positions us to develop safe, efficient, and targeted GTs for PAD-related diseases. Gene therapies appear particularly fitting for ex vivo genetic engineering of IH-resistant vein grafts. This manuscript highlights currently available state-of-the-art multiomics approaches, explores promising GT-based candidates, and details GT delivery modalities employed by our laboratory and others to thwart mid-term vein graft failure caused by IH, as well as other PAD-related conditions. The potential clinical translation of these targeted GTs holds the promise to revolutionize PAD treatment, thereby enhancing patients' quality of life and life expectancy.

Functional and Multi-Omics Effects of an Optimized CRISPR-Mediated FURIN Depletion in U937 Monocytes

The pro-protein convertase FURIN (PCSK3) is implicated in a wide range of normal and pathological biological processes such as infectious diseases, cancer and cardiovascular diseases. Previously, we performed a systemic inhibition of FURIN in a mouse model of atherosclerosis and demonstrated significant plaque reduction and alterations in macrophage function. To understand the cellular mechanisms affected by FURIN inhibition in myeloid cells, we optimized a CRISPR-mediated gene deletion protocol for successfully deriving hemizygous (HZ) and nullizygous (NZ) FURIN knockout clones in U937 monocytic cells using lipotransfection-based procedures and a dual guide RNA delivery strategy. We observed differences in monocyte and macrophage functions involving phagocytosis, lipid accumulation, cell migration, inflammatory gene expression, cytokine release patterns, secreted proteomics (cytokines) and whole-genome transcriptomics between wild-type, HZ and NZ FURIN clones. These studies provide a mechanistic basis on the possible roles of myeloid cell FURIN in cardiovascular disorders.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Identification of the susceptible genes and mechanism underlying the comorbid presence of coronary artery disease and rheumatoid arthritis: a network modularization analysis

OBJECTIVE

The comorbidities of coronary artery disease (CAD) and rheumatoid arthritis (RA) are mutual risk factors, which lead to higher mortality, but the biological mechanisms connecting the two remain unclear. Here, we aimed to identify the risk genes for the comorbid presence of these two complex diseases using a network modularization approach, to offer insights into clinical therapy and drug development for these diseases.

METHOD

The expression profile data of patients CAD with and without RA were obtained from the GEO database (GSE110008). Based on the differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) was used to construct a gene network, detect co-expression modules, and explore their relation to clinical traits. The Zsummary index, gene significance (GS), and module membership (MM) were utilized to screen the important differentiated modules and hub genes. The GO and KEGG pathway enrichment analysis were applied to analyze potential mechanisms.

RESULT

Based on the 278 DEGs obtained, 41 modules were identified, of which 17 and 24 modules were positively and negatively correlated with the comorbid occurrence of CAD and RA (CAD&RA), respectively. Thirteen modules with Zsummary < 2 were found to be the underlying modules, which may be related to CAD&RA. With GS ≥ 0.5 and MM ≥ 0.8, 49 hub genes were identified, such as ADO, ABCA11P, POT1, ZNF141, GPATCH8, ATF6 and MIA3, etc. The area under the curve values of the representative seven hub genes under the three models (LR, KNN, SVM) were greater than 0.88. Enrichment analysis revealed that the biological functions of the targeted modules were mainly involved in cAMP-dependent protein kinase activity, demethylase activity, regulation of calcium ion import, positive regulation of tyrosine, phosphorylation of STAT protein, and tissue migration, etc. CONCLUSION: Thirteen characteristic modules and 49 susceptibility hub genes were identified, and their corresponding molecular functions may reflect the underlying mechanism of CAD&RA, hence providing insights into the development of clinical therapies against these diseases.

Advances and Challenges for GWAS Analysis in Cardiac Diseases: A Focus on Coronary Artery Disease (CAD)

The achievement of genome-wide association studies (GWAS) has rapidly progressed our understanding of the etiology of coronary artery disease (CAD). It unlocks new strategies to strengthen the stalling of CAD drug development. In this review, we highlighted the recent drawbacks, mainly pointing out those involved in identifying causal genes and interpreting the connections between disease pathology and risk variants. We also benchmark the novel insights into the biological mechanism behind the disease primarily based on outcomes of GWAS. Furthermore, we also shed light on the successful discovery of novel treatment targets by introducing various layers of "omics" data and applying systems genetics strategies. Lastly, we discuss in-depth the significance of precision medicine that is helpful to improve through GWAS analysis in cardiovascular research.

Genetically personalised organ-specific metabolic models in health and disease

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Shared genetics between classes of obesity and psychiatric disorders: A large-scale genome-wide cross-trait analysis

AIMS

Epidemiological studies demonstrate an association between classes of obesity and psychiatric disorders, although little is known about shared genetics and causality of association. Thus, we aimed to investigate shared genetics and causal link between different classes of obesity and psychiatric disorders.

METHODS

We used genome-wide association study (GWAS) summary data range from 9725 to 500,199 sample sizes of European descent, conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between the classes of obesity and anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, schizophrenia, anxiety disorders and Tourette syndrome. We conducted transcriptome-wide association study analysis (TWAS) to identified variants regulated gene expression in those related disorders. Finally, pathway enrichment analysis to identified major pathways.

RESULTS

In the combined analysis, we replicated 211 previously reported loci and discovered 58 novel independent loci that were associated with all three classes of obesity and related psychiatric disorders. Functional analysis revealed that the identified variants regulated gene expression in major tissues belonging to exocrine/endocrine, digestive, circulatory, adipose, digestive, respiratory, and nervous systems, such as DCC, NEGR1, INO80E. Mendelian randomization analyses suggested that there may be a two-way or one-way causal relationship between obesity and psychiatric disorders.

CONCLUSION

This large-scale genome-wide cross-trait analysis identified shared genetics and potential causal links between classes of obesity and psychiatric disorders (attention deficit hyperactivity disorder, autism spectrum disorder, anorexia nervosa, major depressive disorder, schizophrenia, and obsessive-compulsive disorder). Such shared genetics suggests potential new biological functions in common among them.

Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR

Coronary artery disease (CAD) is a complex, multifactorial disease caused, in particular, by inflammation and cholesterol metabolism. At the molecular level, the role of tissue-specific signaling pathways leading to CAD is still largely unexplored. This study relied on two main resources: (1) genes with impact on atherosclerosis/CAD, and (2) liver-specific transcriptome analyses from human and mouse studies. The transcription factor activating transcription factor 3 (ATF3) was identified as a key regulator of a liver network relevant to atherosclerosis and linked to inflammation and cholesterol metabolism. ATF3 was predicted to be a direct and indirect (via MAF BZIP Transcription Factor F (MAFF)) regulator of low-density lipoprotein receptor (LDLR). Chromatin immunoprecipitation DNA sequencing (ChIP-seq) data from human liver cells revealed an ATF3 binding motif in the promoter regions of MAFF and LDLR. siRNA knockdown of ATF3 in human Hep3B liver cells significantly upregulated LDLR expression (p < 0.01). Inflammation induced by lipopolysaccharide (LPS) stimulation resulted in significant upregulation of ATF3 (p < 0.01) and subsequent downregulation of LDLR (p < 0.001). Liver-specific expression data from human CAD patients undergoing coronary artery bypass grafting (CABG) surgery (STARNET) and mouse models (HMDP) confirmed the regulatory role of ATF3 in the homeostasis of cholesterol metabolism. This study suggests that ATF3 might be a promising treatment candidate for lowering LDL cholesterol and reducing cardiovascular risk.

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

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

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.

The Path to Therapeutic Furin Inhibitors: From Yeast Pheromones to SARS-CoV-2

The spurious acquisition and optimization of a furin cleavage site in the SARS-CoV-2 spike protein is associated with increased viral transmission and disease, and has generated intense interest in the development and application of therapeutic furin inhibitors to thwart the COVID-19 pandemic. This review summarizes the seminal studies that informed current efforts to inhibit furin. These include the convergent efforts of endocrinologists, virologists, and yeast geneticists that, together, culminated in the discovery of furin. We describe the pioneering biochemical studies which led to the first furin inhibitors that were able to block the disease pathways which are broadly critical for pathogen virulence, tumor invasiveness, and atherosclerosis. We then summarize how these studies subsequently informed current strategies leading to the development of small-molecule furin inhibitors as potential therapies to combat SARS-CoV-2 and other diseases that rely on furin for their pathogenicity and progression.

In silico genome-wide gene-based association analysis reveals new genes predisposing to coronary artery disease

Genome-wide association study (GWAS) have identified more than 300 single nucleotide polymorphisms at 163 independent loci associated with coronary artery disease (CAD). However, there is no full understanding about the causal genes for CAD and the mechanisms of their action. We aimed to perform a post GWAS analysis to identify genes whose polymorphism may influence the risk of CAD. Using the UK Biobank GWAS summary statistics, we performed a gene-based association analysis. We found 63 genes significantly associated with CAD due to their within-gene polymorphisms. Many of these genes are well known. Some known CAD genes such as FURIN and SORT1 did not show the gene-based association because their variants had low GWAS signals or gene-based association was inflated by the strong GWAS signal outside the gene. For several known CAD genes, we demonstrated that their effects could be explained not only or not at all by their own variants but by the variants within the neighboring genes controlling their expression. Using several bioinformatics techniques, we suggested potential mechanisms underlying gene-CAD associations. Three genes, CDK19, NCALD, and ARHGEF12 were not previously associated with CAD. The role of these genes should be clarified in further studies.

Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study

Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.

Downregulation of Endothelial Plexin A4 Under Inflammatory Conditions Impairs Vascular Integrity

Objective: Besides hyperlipidemia, inflammation is an important determinant in the initiation and the progression of atherosclerosis. As Neuroimmune Guidance Cues (NGCs) are emerging as regulators of atherosclerosis, we set out to investigate the expression and function of inflammation-regulated NGCs. Methods and results: NGC expression in human monocytes and endothelial cells was assessed using a publicly available RNA dataset. Next, the mRNA levels of expressed NGCs were analyzed in primary human monocytes and endothelial cells after stimulation with IL1β or TNFα. Upon stimulation a total of 14 and 19 NGCs in monocytes and endothelial cells, respectively, were differentially expressed. Since plexin A4 (PLXNA4) was strongly downregulated in endothelial cells under inflammatory conditions, the role of PLXNA4 in endothelial function was investigated. Knockdown of PLXNA4 in endothelial cells markedly impaired the integrity of the monolayer leading to more elongated cells with an inflammatory phenotype. In addition, these cells showed an increase in actin stress fibers and decreased cell-cell junctions. Functional assays revealed decreased barrier function and capillary network formation of the endothelial cells, while vascular leakage and trans-endothelial migration of monocytes was increased. Conclusion: The current study demonstrates that pro-inflammatory conditions result in differential expression of NGCs in endothelial cells and monocytes, both culprit cell types in atherosclerosis. Specifically, endothelial PLXNA4 is reduced upon inflammation, while PLXNA4 maintains endothelial barrier function thereby preventing vascular leakage of fluids as well as cells. Taken together, PLXNA4 may well have a causal role in atherogenesis that deserves further investigation.

Transcription Factor MAFF (MAF Basic Leucine Zipper Transcription Factor F) Regulates an Atherosclerosis Relevant Network Connecting Inflammation and Cholesterol Metabolism

BACKGROUND

Coronary artery disease (CAD) is a multifactorial condition with both genetic and exogenous causes. The contribution of tissue-specific functional networks to the development of atherosclerosis remains largely unclear. The aim of this study was to identify and characterize central regulators and networks leading to atherosclerosis.

METHODS

Based on several hundred genes known to affect atherosclerosis risk in mouse (as demonstrated in knockout models) and human (as shown by genome-wide association studies), liver gene regulatory networks were modeled. The hierarchical order and regulatory directions of genes within the network were based on Bayesian prediction models, as well as experimental studies including chromatin immunoprecipitation DNA-sequencing, chromatin immunoprecipitation mass spectrometry, overexpression, small interfering RNA knockdown in mouse and human liver cells, and knockout mouse experiments. Bioinformatics and correlation analyses were used to clarify associations between central genes and CAD phenotypes in both human and mouse.

RESULTS

The transcription factor MAFF (MAF basic leucine zipper transcription factor F) interacted as a key driver of a liver network with 3 human genes at CAD genome-wide association studies loci and 11 atherosclerotic murine genes. Most importantly, expression levels of the low-density lipoprotein receptor (LDLR) gene correlated with MAFF in 600 CAD patients undergoing bypass surgery (STARNET [Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task]) and a hybrid mouse diversity panel involving 105 different inbred mouse strains. Molecular mechanisms of MAFF were tested in noninflammatory conditions and showed positive correlation between MAFF and LDLR in vitro and in vivo. Interestingly, after lipopolysaccharide stimulation (inflammatory conditions), an inverse correlation between MAFF and LDLR in vitro and in vivo was observed. Chromatin immunoprecipitation mass spectrometry revealed that the human CAD genome-wide association studies candidate BACH1 (BTB domain and CNC homolog 1) assists MAFF in the presence of lipopolysaccharide stimulation with respective heterodimers binding at the MAF recognition element of the LDLR promoter to transcriptionally downregulate LDLR expression.

CONCLUSIONS

The transcription factor MAFF was identified as a novel central regulator of an atherosclerosis/CAD-relevant liver network. MAFF triggered context-specific expression of LDLR and other genes known to affect CAD risk. Our results suggest that MAFF is a missing link between inflammation, lipid and lipoprotein metabolism, and a possible treatment target.

Down-regulated RGS5 by genetic variants impairs endothelial cell function and contributes to coronary artery disease

AIMS

Genetic contribution to coronary artery disease (CAD) remains largely unillustrated. Although transcriptomic profiles have identified dozens of genes that are differentially expressed in normal and atherosclerotic vessels, whether those genes are genetically associated with CAD remains to be determined. Here, we combined genetic association studies, transcriptome profiles and in vitro and in vivo functional experiments to identify novel susceptibility genes for CAD.

METHODS AND RESULTS

Through an integrative analysis of transcriptome profiles with genome-wide association studies for CAD, we obtained 18 candidate genes and selected one representative single nucleotide polymorphism (SNP) for each gene for multi-centred validations. We identified an intragenic SNP, rs1056515 in RGS5 gene (odds ratio = 1.17, 95% confidence interval =1.10-1.24, P = 3.72 × 10-8) associated with CAD at genome-wide significance. Rare genetic variants in linkage disequilibrium with rs1056515 were identified in CAD patients leading to a decreased expression of RGS5. The decreased expression was also observed in atherosclerotic vessels and endothelial cells treated by various cardiovascular risk factors. Through siRNA knockdown and adenoviral overexpression, we further showed that RGS5 regulated endothelial inflammation, vascular remodelling, as well as canonical NF-κB signalling activation. Moreover, CXCL12, a specific downstream target of the non-canonical NF-κB pathway, was strongly affected by RGS5. However, the p100 processing, a well-documented marker for non-canonical NF-κB pathway activation, was not altered, suggesting an existence of a novel mechanism by which RGS5 regulates CXCL12.

CONCLUSIONS

We identified RGS5 as a novel susceptibility gene for CAD and showed that the decreased expression of RGS5 impaired endothelial cell function and functionally contributed to atherosclerosis through a variety of molecular mechanisms. How RGS5 regulates the expression of CXCL12 needs further studies.

Elevated FURIN levels in predicting mortality and cardiovascular events in patients with acute myocardial infarction

OBJECTIVES

Proprotein convertase subtilisin/kexin (PCSK) family member 3 (FURIN) has been suggested to be involved in the development of atherosclerosis. The aim of this study was to investigate the prognostic implication of FURIN in patients after acute myocardial infarction (AMI).

METHODS

This prospective study analyzed data from a total of 1312 consecutive patients hospitalized with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction from August 2013 to June 2016. FURIN levels were analyzed in plasma obtained from AMI patients.

RESULTS

The study included 1312 AMI patients. The patient population was predominantly male (63%) with a median age of 66 years (IQR: 19 years), and 59% were STEMI patients. During a follow-up of 2 years, 117 patients died, and 377 patients reached the combined endpoints of major adverse cardiac events (MACE). Patients with elevated FURIN levels had increased risk of MACE, all-cause mortality, recurrent MI and hospitalization for HF (log-rank test, p < 0.0001). After adjusting for clinical risk factors and established markers, the association of FURIN concentrations with the risk of MACE and its individual components and cardiovascular death was statistically significant in the higher tertile of FURIN concentrations. After the addition of FURIN to the models, FURIN showed additive prognostic significance for 2-year clinical outcomes. Variable importance plots of the models showed that FURIN was of high importance to predict both occurrence of MACE and all-cause mortality.

CONCLUSIONS

We found that FURIN was associated with all-cause mortality and recurrent cardiovascular events in AMI patients independent of conventional risk factors and established markers.

Prediction Power on Cardiovascular Disease of Neuroimmune Guidance Cues Expression by Peripheral Blood Monocytes Determined by Machine-Learning Methods

Atherosclerosis is the underlying pathology in a major part of cardiovascular disease, the leading cause of mortality in developed countries. The infiltration of monocytes into the vessel walls of large arteries is a key denominator of atherogenesis, making monocytes accountable for the development of atherosclerosis. With the development of high-throughput transcriptome profiling platforms and cytometric methods for circulating cells, it is now feasible to study in-depth the predicted functional change of circulating monocytes reflected by changes of gene expression in certain pathways and correlate the changes to disease outcome. Neuroimmune guidance cues comprise a group of circulating- and cell membrane-associated signaling proteins that are progressively involved in monocyte functions. Here, we employed the CIRCULATING CELLS study cohort to classify cardiovascular disease patients and healthy individuals in relation to their expression of neuroimmune guidance cues in circulating monocytes. To cope with the complexity of human datasets featured by noisy data, nonlinearity and multidimensionality, we assessed various machine-learning methods. Of these, the linear discriminant analysis, Naïve Bayesian model and stochastic gradient boost model yielded perfect or near-perfect sensibility and specificity and revealed that expression levels of the neuroimmune guidance cues SEMA6B, SEMA6D and EPHA2 in circulating monocytes were of predictive values for cardiovascular disease outcome.

Identification of genetic loci jointly influencing coronary artery disease risk and sleep traits of insomnia, sleep duration, and chronotype

BACKGROUND

Accumulating evidence suggests a relationship between coronary artery disease (CAD) and sleep problems. Our study is aimed to investigate the shared genetic loci underlying this phenotypic association.

METHODS

Combining summary statistics from different genome-wide association studies, we investigated overlap in single-nucleotide polymorphisms (SNPs) associated with CAD and sleep traits (insomnia symptoms, sleep duration, and chronotype) using conditional/conjunctional false discovery rate (condFDR/conjFDR) approach. Relevant variants are further evaluated for differential expression analysis, expression quantitative trait locus (eQTL) functionality, and gene ontology (GO) enrichment analysis.

RESULTS

We observed substantial genetic enrichment in CAD condition on associations with sleep traits, which indicating polygenic overlap. Using conjFDR analysis, 26 loci jointly influencing CAD and sleep traits were identified. One locus was shared between CAD and sleep duration and represented the strongest shared signal detected (closest gene, MSL2; chromosome 3q22.3; conjFDR = 1.77 × 10^-4). A consistent direction of allelic effect was observed between CAD and insomnia symptoms, while bi-directional effects were recognized between CAD, sleep duration, and chronotype. Replicable eQTL functionality was further identified for two loci: rs28398825 for FCHO1 in the frontal cortex and blood tissue, and rs8072451 for LRRC37A and its duplicate LRRC37A2 in several brain regions and blood tissue. GO analysis of the loci shared between CAD and sleep traits implicated cellular component related to synapse.

CONCLUSIONS

Our findings provide new insight into the relationship between CAD and sleep traits. The mechanisms underlying these associations warrant further investigation.

Turning genome-wide association study findings into opportunities for drug repositioning

Drug development is a very costly and lengthy process, while repositioned or repurposed drugs could be brought into clinical practice within a shorter time-frame and at a much reduced cost. Numerous computational approaches to drug repositioning have been developed, but methods utilizing genome-wide association studies (GWASs) data are less explored.

The past decade has observed a massive growth in the amount of data from GWAS; the rich information contained in GWAS has great potential to guide drug repositioning or discovery. While multiple tools are available for finding the most relevant genes from GWAS hits, searching for top susceptibility genes is only one way to guide repositioning, which has its own limitations.

Here we provide a comprehensive review of different computational approaches that employ GWAS data to guide drug repositioning. These methods include selecting top candidate genes from GWAS as drug targets, deducing drug candidates based on drug-drug and disease-disease similarities, searching for reversed expression profiles between drugs and diseases, pathway-based methods as well as approaches based on analysis of biological networks. Each method is illustrated with examples, and their respective strengths and limitations are discussed. We also discussed several areas for future research.

High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways

Supplemental Digital Content is available in the text.

Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease.

Exome-Wide Association Study Reveals Several Susceptibility Genes and Pathways Associated With Acute Coronary Syndromes in Han Chinese

Genome-wide association studies have identified more than 150 susceptibility loci for coronary artery disease (CAD); however, there is still a large proportion of missing heritability remaining to be investigated. This study sought to identify population-based genetic variation associated with acute coronary syndromes (ACS) in individuals of Chinese Han descent. We proposed a novel strategy integrating a well-developed risk prediction model into control selection in order to lower the potential misclassification bias and increase the statistical power. An exome-wide association analysis was performed for 1,669 ACS patients and 1,935 healthy controls. Promising variants were further replicated using the existing in silico dataset. Additionally, we performed gene- and pathway-based analyses to investigate the aggregate effect of multiple variants within the same genes or pathways. Although none of the association signals were consistent across studies after Bonferroni correction, one promising variant, rs10409124 at STRN4, showed potential impact on ACS in both European and East Asian populations. Gene-based analysis explored four genes (ANXA7, ZNF655, ZNF347, and ZNF750) that showed evidence for association with ACS after multiple test correction, and identification of ZNF655 was successfully replicated by another dataset. Pathway-based analysis revealed that 32 potential pathways might be involved in the pathogenesis of ACS. Our study identified several candidate genes and pathways associated with ACS. Future studies are needed to further validate these findings and explore these genes and pathways as potential therapeutic targets in ACS.

The Integrated Landscape of Biological Candidate Causal Genes in Coronary Artery Disease

Background

Genome-wide association studies (GWASs) have identified more than 150 genetic loci that demonstrate robust association with coronary artery disease (CAD). In contrast to the success of GWAS, the translation from statistical signals to biological mechanism and exploration of causal genes for drug development remain difficult, owing to the complexity of gene regulatory and linkage disequilibrium patterns. We aim to prioritize the plausible causal genes for CAD at a genome-wide level.

Methods

We integrated the latest GWAS summary statistics with other omics data from different layers and utilized eight different computational methods to predict CAD potential causal genes. The prioritized candidate genes were further characterized by pathway enrichment analysis, tissue-specific expression analysis, and pathway crosstalk analysis.

Results

Our analysis identified 55 high-confidence causal genes for CAD, among which 15 genes (LPL, COL4A2, PLG, CDKN2B, COL4A1, FES, FLT1, FN1, IL6R, LPA, PCSK9, PSRC1, SMAD3, SWAP70, and VAMP8) ranked the highest priority because of consistent evidence from different data-driven approaches. GO analysis showed that these plausible causal genes were enriched in lipid metabolic and extracellular regions. Tissue-specific enrichment analysis revealed that these genes were significantly overexpressed in adipose and liver tissues. Further, KEGG and crosstalk analysis also revealed several key pathways involved in the pathogenesis of CAD.

Conclusion

Our study delineated the landscape of CAD potential causal genes and highlighted several biological processes involved in CAD pathogenesis. Further studies and experimental validations of these genes may shed light on mechanistic insights into CAD development and provide potential drug targets for future therapeutics.

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.

FURIN Inhibition Reduces Vascular Remodeling and Atherosclerotic Lesion Progression in Mice

Objective- Atherosclerotic coronary artery disease is the leading cause of death worldwide, and current treatment options are insufficient. Using systems-level network cluster analyses on a large coronary artery disease case-control cohort, we previously identified PCSK3 (proprotein convertase subtilisin/kexin family member 3; FURIN) as a member of several coronary artery disease-associated pathways. Thus, our objective is to determine the role of FURIN in atherosclerosis. Approach and Results- In vitro, FURIN inhibitor treatment resulted in reduced monocyte migration and reduced macrophage and vascular endothelial cell inflammatory and cytokine gene expression. In vivo, administration of an irreversible inhibitor of FURIN, α-1-PDX (α1-antitrypsin Portland), to hyperlipidemic Ldlr^-/- mice resulted in lower atherosclerotic lesion area and a specific reduction in severe lesions. Significantly lower lesional macrophage and collagen area, as well as systemic inflammatory markers, were observed. MMP2 (matrix metallopeptidase 2), an effector of endothelial function and atherosclerotic lesion progression, and a FURIN substrate was significantly reduced in the aorta of inhibitor-treated mice. To determine FURIN's role in vascular endothelial function, we administered α-1-PDX to Apoe^-/- mice harboring a wire injury in the common carotid artery. We observed significantly decreased carotid intimal thickness and lower plaque cellularity, smooth muscle cell, macrophage, and inflammatory marker content, suggesting protection against vascular remodeling. Overexpression of FURIN in this model resulted in a significant 67% increase in intimal plaque thickness, confirming that FURIN levels directly correlate with atherosclerosis. Conclusions- We show that systemic inhibition of FURIN in mice decreases vascular remodeling and atherosclerosis. FURIN-mediated modulation of MMP2 activity may contribute to the atheroprotection observed in these mice.

2018 George Lyman Duff Memorial Lecture: Genetics and Genomics of Coronary Artery Disease: A Decade of Progress

Recent studies have led to a broader understanding of the genetic architecture of coronary artery disease and demonstrate that it largely derives from the cumulative effect of multiple common risk alleles individually of small effect size rather than rare variants with large effects on coronary artery disease risk. The tools applied include genome-wide association studies encompassing over 200 000 individuals complemented by bioinformatic approaches including imputation from whole-genome data sets, expression quantitative trait loci analyses, and interrogation of ENCODE (Encyclopedia of DNA Elements), Roadmap Epigenetic Project, and other data sets. Over 160 genome-wide significant loci associated with coronary artery disease risk have been identified using the genome-wide association studies approach, 90% of which are situated in intergenic regions. Here, I will describe, in part, our research over the last decade performed in collaboration with a series of bright trainees and an extensive number of groups and individuals around the world as it applies to our understanding of the genetic basis of this complex disease. These studies include computational approaches to better understand missing heritability and identify causal pathways, experimental approaches, and progress in understanding at the molecular level the function of the multiple risk loci identified and potential applications of these genomic data in clinical medicine and drug discovery.

Exploring the underlying biology of intrinsic cardiorespiratory fitness through integrative analysis of genomic variants and muscle gene expression profiling

Intrinsic cardiorespiratory fitness (CRF) is defined as the level of CRF in the sedentary state. There are large individual differences in intrinsic CRF among sedentary adults. The physiology of variability in CRF has received much attention, but little is known about the genetic and molecular mechanisms that impact intrinsic CRF. These issues were explored in the present study by interrogating intrinsic CRF-associated DNA sequence variation and skeletal muscle gene expression data from the HERITAGE Family Study through an integrative bioinformatics guided approach. A combined analytic strategy involving genetic association, pathway enrichment, tissue-specific network structure, cis-regulatory genome effects, and expression quantitative trait loci was used to select and rank genes through a variation-adjusted weighted ranking scheme. Prioritized genes were further interrogated for corroborative evidence from knockout mouse phenotypes and relevant physiological traits from the HERITAGE cohort. The mean intrinsic V̇o2max was 33.1 ml O2·kg-1·min-1 (SD = 8.8) for the sample of 493 sedentary adults. Suggestive evidence was found for gene loci related to cardiovascular physiology (ATE1, CASQ2, NOTO, and SGCG), hematopoiesis (PICALM, SSB, CA9, and CASQ2), skeletal muscle phenotypes (SGCG, DMRT2, ADARB1, and CASQ2), and metabolism (ATE1, PICALM, RAB11FIP5, GBA2, SGCG, PRADC1, ARL6IP5, and CASQ2). Supportive evidence for a role of several of these loci was uncovered via association between DNA variants and muscle gene expression levels with exercise cardiovascular and muscle physiological traits. This initial effort to define the underlying molecular substrates of intrinsic CRF warrants further studies based on appropriate cohorts and study designs, complemented by functional investigations. NEW & NOTEWORTHY Intrinsic cardiorespiratory fitness (CRF) is measured in the sedentary state and is highly variable among sedentary adults. The physiology of variability in intrinsic cardiorespiratory fitness has received much attention, but little is known about the genetic and molecular mechanisms that impact intrinsic CRF. These issues were explored computationally in the present study, with further corroborative evidence obtained from analysis of phenotype data from knockout mouse models and human cardiovascular and skeletal muscle measurements.

Functional regulatory mechanism of smooth muscle cell-restricted LMOD1 coronary artery disease locus

Recent genome-wide association studies (GWAS) have identified multiple new loci which appear to alter coronary artery disease (CAD) risk via arterial wall-specific mechanisms. One of the annotated genes encodes LMOD1 (Leiomodin 1), a member of the actin filament nucleator family that is highly enriched in smooth muscle-containing tissues such as the artery wall. However, it is still unknown whether LMOD1 is the causal gene at this locus and also how the associated variants alter LMOD1 expression/function and CAD risk. Using epigenomic profiling we recently identified a non-coding regulatory variant, rs34091558, which is in tight linkage disequilibrium (LD) with the lead CAD GWAS variant, rs2820315. Herein we demonstrate through expression quantitative trait loci (eQTL) and statistical fine-mapping in GTEx, STARNET, and human coronary artery smooth muscle cell (HCASMC) datasets, rs34091558 is the top regulatory variant for LMOD1 in vascular tissues. Position weight matrix (PWM) analyses identify the protective allele rs34091558-TA to form a conserved Forkhead box O3 (FOXO3) binding motif, which is disrupted by the risk allele rs34091558-A. FOXO3 chromatin immunoprecipitation and reporter assays show reduced FOXO3 binding and LMOD1 transcriptional activity by the risk allele, consistent with effects of FOXO3 downregulation on LMOD1. LMOD1 knockdown results in increased proliferation and migration and decreased cell contraction in HCASMC, and immunostaining in atherosclerotic lesions in the SMC lineage tracing reporter mouse support a key role for LMOD1 in maintaining the differentiated SMC phenotype. These results provide compelling functional evidence that genetic variation is associated with dysregulated LMOD1 expression/function in SMCs, together contributing to the heritable risk for CAD.

Are toll-like receptors potential drug targets for atherosclerosis? Evidence from genetic studies to date

Low-density lipoprotein cholesterol lowering, most notably via statin therapy, has successfully reduced the burden of coronary artery disease (CAD) in recent decades. However, the residual risk remaining even after aggressive lipid lowering has renewed interest in alternative targets. Anti-inflammatory drugs are thought to have much potential in this context, but side effects associated with long-term use of conventional anti-inflammatories, such as NSAIDs and glucocorticoids, preclude their use as preventive agents for CAD. Evidence from epidemiological studies and murine models of atherosclerosis suggests that toll-like receptors (TLRs) may have utility as targets for more focused anti-inflammatories, but it remains unclear if this pathway is causally related to CAD in man. Here, we review recent insight into this question gained from genetic studies of cardiovascular risk and innate immune function, focussing on the potential of Mendelian randomisation approaches based on intracellular-signalling pathways to identify and prioritise targets for drug development.

Guidance Molecules in Vascular Smooth Muscle

Several highly conserved families of guidance molecules, including ephrins, Semaphorins, Netrins, and Slits, play conserved and distinct roles in tissue remodeling during tissue patterning and disease pathogenesis. Primarily, these guidance molecules function as either secreted or surface-bound ligands that interact with their receptors to activate a variety of downstream effects, including cell contractility, migration, adhesion, proliferation, and inflammation. Vascular smooth muscle cells, contractile cells comprising the medial layer of the vessel wall and deriving from the mural population, regulate vascular tone and blood pressure. While capillaries lack a medial layer of vascular smooth muscle, mural-derived pericytes contribute similarly to capillary tone to regulate blood flow in various tissues. Furthermore, pericyte coverage is critical in vascular development, as perturbations disrupt vascular permeability and viability. During cardiovascular disease, smooth muscle cells play a more dynamic role in which suppression of contractile markers, enhanced proliferation, and migration lead to the progression of aberrant vascular remodeling. Since many types of guidance molecules are expressed in vascular smooth muscle and pericytes, these may contribute to blood vessel formation and aberrant remodeling during vascular disease. While vascular development is a large focus of the existing literature, studies emerged to address post-developmental roles for guidance molecules in pathology and are of interest as novel therapeutic targets. In this review, we will discuss the roles of guidance molecules in vascular smooth muscle and pericyte function in development and disease.

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

Coronary artery disease (CAD) is the leading cause of mortality worldwide and poses a considerable public health burden. Recent genome-wide association studies (GWAS) have revealed >100 genetic loci associated with CAD susceptibility in humans. While a number of these loci harbor gene targets of currently approved therapies, such as statins and PCSK9 inhibitors, the majority of the annotated genes at these loci encode for proteins involved in vessel wall function with no known drugs available. Importantly many of the associated genes linked to vascular (smooth muscle, endothelial, and macrophage) cell processes are now organized into distinct functional pathways, e.g., vasodilation, growth factor responses, extracellular matrix and plaque remodeling, and inflammation. In this mini-review, we highlight the most recently identified loci that have predicted roles in the vessel wall and provide genetic context for pre-existing therapies as well as new drug targets informed from GWAS. With the development of new modalities to target these pathways, (e.g., antisense oligonucleotides, CRISPR/Cas9, and RNA interference) as well as the computational frameworks to prioritize or reposition therapeutics, there is great opportunity to close the gap from initial genetic discovery to clinical translation for many patients affected by this common disease.

Translating GWAS Findings to Novel Therapeutic Targets for Coronary Artery Disease

The success of genome-wide association studies (GWAS) has significantly advanced our understanding of the etiology of coronary artery disease (CAD) and opens new opportunities to reinvigorate the stalling CAD drug development. However, there exists remarkable disconnection between the CAD GWAS findings and commercialized drugs. While this could implicate major untapped translational and therapeutic potentials in CAD GWAS, it also brings forward extensive technical challenges. In this review we summarize the motivation to leverage GWAS for drug discovery, outline the critical bottlenecks in the field, and highlight several promising strategies such as functional genomics and network-based approaches to enhance the translational value of CAD GWAS findings in driving novel therapeutics

Genome-Wide Association and Functional Studies Identify SCML4 and THSD7A as Novel Susceptibility Genes for Coronary Artery Disease

OBJECTIVE

The genetic contribution to coronary artery disease (CAD) remains largely unclear. We combined genetic screening with functional characterizations to identify novel loci and candidate genes for CAD.

APPROACH AND RESULTS

We performed genome-wide screening followed by multicenter validation in 8 cohorts consisting of 21 828 participants of Han ethnicity and identified 3 novel intragenic SNPs (single nucleotide polymorphisms), rs9486729 (SCML4 [Scm polycomb group protein-like 4]; odds ratio, 1.25; 95% CI, 1.17-1.34; P=3.51×10^-11), rs17165136 (THSD7A [thrombospondin type 1 domain-containing 7A]; odds ratio 1.28; 95% CI, 1.21-1.35; P<1.00×10^-25), and rs852787 (DAB1 [disabled-1]; odds ratio, 1.29; 95% CI, 1.21-1.38; P=2.02×10^-14), associated with CAD with genome-wide significance. The risk allele of rs9486729 and protective allele of rs17165136 were associated with the decreased expression of their host genes, SCML4 and THSD7A, respectively, whereas rs852787 did not have transcriptional effects on any gene. Knockdown of SCML4 activated endothelial cells by increasing the expression of IL-6, E-selectin, and ICAM and weakened their antiapoptotic activity, whereas the knockdown of THSD7A had little effect on these endothelial cell functions but attenuated monocyte adhesion via decreasing the expression of ICAM, L-selectin, and ITGB2. We further showed that inhibiting the expression of SCML4 exacerbated endothelial dysfunction and vascular remodeling in a rat model with partial carotid ligation.

CONCLUSIONS

We identify 3 novel loci associated with CAD and show that 2 genes, SCML4 and THSD7A, make functional contributions to atherosclerosis. How rs852787 and its host gene DAB1 are linked to CAD needs further studies.

Systems healthcare: a holistic paradigm for tomorrow

Systems healthcare is a holistic approach to health premised on systems biology and medicine. The approach integrates data from molecules, cells, organs, the individual, families, communities, and the natural and man-made environment. Both extrinsic and intrinsic influences constantly challenge the biological networks associated with wellness. Such influences may dysregulate networks and allow pathobiology to evolve, resulting in early clinical presentation that requires astute assessment and timely intervention for successful mitigation. Herein, we describe the components of relevant biological systems and the nature of progression from at-risk to manifest disease. We illustrate the systems approach by examining two relevant clinical examples: Alzheimer's and cardiovascular diseases. The implications of systems healthcare management are examined through the lens of economics, ethics, policy and the law. Finally, we propose the need to develop new educational paradigms to enhance the training of the health professional in an era of systems medicine.

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

PURPOSE OF REVIEW

We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD) and discuss areas of research that provide excellent opportunities for further exploration.

RECENT FINDINGS

Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.

The Genetics of Ischemic Heart Disease: From Current Knowledge to Clinical Implications

Ischemic heart disease continues to cause high morbidity and mortality. Its prevalence is expected to increase due to population aging, and its prevention is a major goal of health policies. The risk of developing ischemic heart disease is related to a complex interplay between genetic, environmental, and lifestyle factors. In the last decade, considerable progress has been made in knowledge of the genetic architecture of this disease. This narrative review provides an overview of current knowledge of the genetics of ischemic heart disease and of its translation to clinical practice: identification of new therapeutic targets, assessment of the causal relationship between biomarkers and disease, improved risk prediction, and identification of responders and nonresponders to specific drugs (pharmacogenomics).

Identification of 15 novel risk loci for coronary artery disease and genetic risk of recurrent events, atrial fibrillation and heart failure

Coronary artery disease (CAD) is the major cause of morbidity and mortality in the world. Identification of novel genetic determinants may provide new opportunities for developing innovative strategies to predict, prevent and treat CAD. Therefore, we meta-analyzed independent genetic variants passing P <× 10^-5 in CARDIoGRAMplusC4D with novel data made available by UK Biobank. Of the 161 genetic variants studied, 71 reached genome wide significance (p < 5 × 10^-8) including 15 novel loci. These novel loci include multiple genes that are involved in angiogenesis (TGFB1, ITGB5, CDH13 and RHOA) and 2 independent variants in the TGFB1 locus. We also identified SGEF as a candidate gene in one of the novel CAD loci. SGEF was previously suggested as a therapeutic target based on mouse studies. The genetic risk score of CAD predicted recurrent CAD events and cardiovascular mortality. We also identified significant genetic correlations between CAD and other cardiovascular conditions, including heart failure and atrial fibrillation. In conclusion, we substantially increased the number of loci convincingly associated with CAD and provide additional biological and clinical insights.

Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype

BACKGROUND

Genetic studies for complex diseases have predominantly discovered main effects at individual loci, but have not focused on genomic and environmental contexts important for a phenotype. Gene Set Enrichment Analysis (GSEA) aims to address this by identifying sets of genes or biological pathways contributing to a phenotype, through gene-gene interactions or other mechanisms, which are not the focus of conventional association methods.

RESULTS

Approaches that utilize GSEA can now take input from array chips, either gene-centric or genome-wide, but are highly sensitive to study design, SNP selection and pruning strategies, SNP-to-gene mapping, and pathway definitions. Here, we present lessons learned from our experience with GSEA of heart failure, a particularly challenging phenotype due to its underlying heterogeneous etiology.

CONCLUSIONS

This case study shows that proper data handling is essential to avoid false-positive results. Well-defined pipelines for quality control are needed to avoid reporting spurious results using GSEA.

Genomic and transcriptomic predictors of response levels to endurance exercise training

Predicting the responsiveness to regular exercise is a topic of great relevance due to its potential role in personalized exercise medicine applications. The present review focuses on cardiorespiratory fitness (commonly measured by maximal oxygen uptake, V̇O2 max ), a trait with wide-ranging impact on health and performance indicators. Gains in V̇O2 max demonstrate large inter-individual variation even in response to standardized exercise training programmes. The estimated ΔVO2 max heritability of 47% suggests that genomic-based predictors alone are insufficient to account for the total trainability variance. Candidate gene and genome-wide linkage studies have not significantly contributed to our understanding of the molecular basis of trainability. A genome-wide association study suggested that V̇O2 max trainability is influenced by multiple genes of small effects, but these findings still await rigorous replication. Valuable evidence, however, has been obtained by combining skeletal muscle transcript abundance profiles with common DNA variants for the prediction of the V̇O2 max response to exercise training. Although the physiological determinants of V̇O2 max measured at a given time are largely enunciated, what is poorly understood are the details of tissue-specific molecular mechanisms that limit V̇O2 max and related signalling pathways in response to exercise training. Bioinformatics explorations based on thousands of variants have been used to interrogate pathways and systems instead of single variants and genes, and the main findings, along with those from exercise experimental studies, have been summarized here in a working model of V̇O2 max trainability.

Systems Analysis of Thrombus Formation

The systems analysis of thrombosis seeks to quantitatively predict blood function in a given vascular wall and hemodynamic context. Relevant to both venous and arterial thrombosis, a Blood Systems Biology approach should provide metrics for rate and molecular mechanisms of clot growth, thrombotic risk, pharmacological response, and utility of new therapeutic targets. As a rapidly created multicellular aggregate with a polymerized fibrin matrix, blood clots result from hundreds of unique reactions within and around platelets propagating in space and time under hemodynamic conditions. Coronary artery thrombosis is dominated by atherosclerotic plaque rupture, complex pulsatile flows through stenotic regions producing high wall shear stresses, and plaque-derived tissue factor driving thrombin production. In contrast, venous thrombosis is dominated by stasis or depressed flows, endothelial inflammation, white blood cell-derived tissue factor, and ample red blood cell incorporation. By imaging vessels, patient-specific assessment using computational fluid dynamics provides an estimate of local hemodynamics and fractional flow reserve. High-dimensional ex vivo phenotyping of platelet and coagulation can now power multiscale computer simulations at the subcellular to cellular to whole vessel scale of heart attacks or strokes. In addition, an integrated systems biology approach can rank safety and efficacy metrics of various pharmacological interventions or clinical trial designs.

Applications and Limitations of Mouse Models for Understanding Human Atherosclerosis

Most of the biological understanding of mechanisms underlying coronary artery disease (CAD) derives from studies of mouse models. The identification of multiple CAD loci and strong candidate genes in large human genome-wide association studies (GWASs) presented an opportunity to examine the relevance of mouse models for the human disease. We comprehensively reviewed the mouse literature, including 827 literature-derived genes, and compared it to human data. First, we observed striking concordance of risk factors for atherosclerosis in mice and humans. Second, there was highly significant overlap of mouse genes with human genes identified by GWASs. In particular, of the 46 genes with strong association signals in CAD GWASs that were studied in mouse models, all but one exhibited consistent effects on atherosclerosis-related phenotypes. Third, we compared 178 CAD-associated pathways derived from human GWASs with 263 from mouse studies and observed that the majority were consistent between the species.

Precise Network Modeling of Systems Genetics Data Using the Bayesian Network Webserver

The Bayesian Network Webserver (BNW, http://compbio.uthsc.edu/BNW ) is an integrated platform for Bayesian network modeling of biological datasets. It provides a web-based network modeling environment that seamlessly integrates advanced algorithms for probabilistic causal modeling and reasoning with Bayesian networks. BNW is designed for precise modeling of relatively small networks that contain less than 20 nodes. The structure learning algorithms used by BNW guarantee the discovery of the best (most probable) network structure given the data. To facilitate network modeling across multiple biological levels, BNW provides a very flexible interface that allows users to assign network nodes into different tiers and define the relationships between and within the tiers. This function is particularly useful for modeling systems genetics datasets that often consist of multiscalar heterogeneous genotype-to-phenotype data. BNW enables users to, within seconds or minutes, go from having a simply formatted input file containing a dataset to using a network model to make predictions about the interactions between variables and the potential effects of experimental interventions. In this chapter, we will introduce the functions of BNW and show how to model systems genetics datasets with BNW.

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data

Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer’s disease, non-alcoholic fatty liver disease, and Huntington’s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer’s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer’s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.