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Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association study data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm–Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.

Introduction: Inflammation is a key driver of atherosclerosis. The identification of new treatments and strategies targeting the specific inflammatory signaling that persists in optimally treated atherosclerotic patients remain an unmet clinical need. Hypothesis: The integration of time-of-flight mass cytometry (CyTOF), gene expression analysis, and drug repositioning computational approaches applied to pre-clinical validation in models of the disease using non-invasive imaging will help to identify drugs tailored to residual inflammatory signaling in patients with atherosclerosis. Methods: We developed a new systems biology pipeline to identify new therapeutic/indication pair that combines CyTOF and RNA sequencing (RNA-seq) data analysis of clinical samples from patients with carotid and coronary artery disease (CVD) ( Fig. 1A ). This approach allowed the identification of new uses for existing compounds. The predicted anti-atherosclerotic effect was validated in ApoE-/- mice and in a rabbit model of atherosclerosis using 18 F-Fluorodeoxyglucose (FDG) PET-MRI. Results: We found a specific inflammatory signature in CD14 + monocytes stimulated with CVD plasma that was used to identify 50 small molecules predicted to reverse this signature. CyTOF screening of the top eight candidate compounds showed that Saracatinib—a phase 2a-ready Src/Abl inhibitor—blunted the inflammatory response found in CD14 + monocytes ( Fig. 1B ). The anti-atherosclerotic efficacy of Saracatinib was confirmed in ApoE-/- mice fed a high fat diet ( Fig.1C ). In the atherosclerotic rabbit model, Saracatinib reduced plaque inflammation measured as reduction of 18 F-FDG uptake by PET-MRI ( Fig. 1D ). Conclusions: These data support the use of our integrated systems biology pipeline as a powerful approach to identify new immune signature specific to patients with atherosclerosis that can be leveraged to identify new indications for existing drugs to treat cardiovascular disease.

AimThe role of platelets in atherosclerosis remains incompletely understood. Variants in genes encoding the soluble guanylyl cyclase (sGC) in platelets are associated with coronary artery disease (CAD) risk. Here we sought to investigate the contribution of platelet sGC to atherosclerosis and the therapeutic potential of targeting sGC in atherosclerosis.Methods and ResultsWe genetically deleted sGC in platelets of atherosclerosis-prone Ldlr-/- mice. By intravital fluorescence microscopy such Pf4-Cre+Gucy1b1flox/floxLdlr-/- mice displayed enhanced leukocyte adhesion to atherosclerotic plaques in comparison with their litter mates. Moreover, histological and flow cytometry analyses revealed more numerous inflammatory leukocytes and larger plaque sizes in aortic tissue of Ldlr-/- mice lacking sGC in platelets. In vitro, supernatant from activated platelets lacking sGC promoted leukocyte adhesion to endothelial cells (EC) via enhanced EC activation. Using cytokine profiling, we identified reduced angiopoietin-1 release by Pf4-Cre+Gucy1b1flox/flox and human GUCY1A1 risk allele carrier platelets to be responsible for enhanced activation of EC and subsequent leukocyte adhesion. Pharmacological sGC stimulation increased platelet angiopoietin-1 release in vitro and reduced recruitment of adoptively transferred leukocytes in Ldlr-/- mice fed a Western diet. Pharmacological sGC stimulation further reduced atherosclerotic plaque formation and vascular inflammation.ConclusionLoss of sGC in platelets contributes to atherosclerotic plaque formation via reduced release of the soluble factor angiopoietin-1 and, subsequently, enhanced leukocyte recruitment. Pharmacological sGC stimulation might represent a novel therapeutic strategy to prevent and treat CAD.Translational perspectiveReduced platelet soluble guanylyl cyclase activity contributes to atherosclerotic plaque formation and vascular inflammation. Stimulators of the soluble guanylyl cyclase, an emerging class of drugs already used in pulmonary hypertension and heart failure, are able to reduce atherosclerosis and inflammation in this preclinical model. Together with evidence from human genetics, our findings suggest a promising role of soluble guanylyl cyclase stimulation to prevent coronary artery disease.

The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.

Endothelial-mesenchymal transition (EndMT) is associated with various cardiovascular diseases and in particular with atherosclerosis and plaque instability. However, the molecular pathways that govern EndMT are poorly defined. Specifically, the role of epigenetic factors and histone deacetylases (HDACs) in controlling EndMT and the atherosclerotic plaque phenotype remains unclear. Here, we identified histone deacetylation, specifically that mediated by HDAC9 (a class IIa HDAC), as playing an important role in both EndMT and atherosclerosis. Using in vitro models, we found class IIa HDAC inhibition sustained the expression of endothelial proteins and mitigated the increase in mesenchymal proteins, effectively blocking EndMT. Similarly, ex vivo genetic knockout of Hdac9 in endothelial cells prevented EndMT and preserved a more endothelial-like phenotype. In vivo, atherosclerosis-prone mice with endothelial-specific Hdac9 knockout showed reduced EndMT and significantly reduced plaque area. Furthermore, these mice displayed a more favorable plaque phenotype, with reduced plaque lipid content and increased fibrous cap thickness. Together, these findings indicate that HDAC9 contributes to vascular pathology by promoting EndMT. Our study provides evidence for a pathological link among EndMT, HDAC9, and atherosclerosis and suggests that targeting of HDAC9 may be beneficial for plaque stabilization or slowing the progression of atherosclerotic disease.

Transcriptome-wide association studies (TWAS) explore genetic variants affecting gene expression for association with a trait. Here we studied coronary artery disease (CAD) using this approach by first determining genotype-regulated expression levels in nine CAD relevant tissues by EpiXcan in two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these data we next imputed gene expression in respective nine tissues from individual level genotype data on 37,997 CAD cases and 42,854 controls for a subsequent gene-trait association analysis. Transcriptome-wide significant association (P < 3.85e-6) was observed for 114 genes, which by genetic means were differentially expressed predominately in arterial, liver, and fat tissues. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel (CAND1, EGFLAM, EZR, FAM114A1, FOCAD, GAS8, HOMER3, KPTN, MGP, NLRC4, RGS19, SDCCAG3, STX4, TSPAN11, TXNRD3, UFL1, WASF1, and WWP2). Gene set analyses showed that TWAS genes were strongly enriched in CAD-related pathways and risk traits. Associations with CAD or related traits were also observed for damaging mutations in 67 of these TWAS genes (11 novel) in whole-exome sequencing data of UK Biobank. Association studies in human genotype data of UK Biobank and expression-trait association statistics of atherosclerosis mouse models suggested that newly identified genes predominantly affect lipid metabolism, a classic risk factor for CAD. Finally, CRISPR/Cas9-based gene knockdown of RGS19 and KPTN in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Taken together, our TWAS approach was able to i) prioritize genes at known GWAS risk loci and ii) identify novel genes which are associated with CAD.

Aims De-differentiation and activation of pro-inflammatory pathways are key transitions vascular smooth muscle cells (SMCs) make during atherogenesis. Here, we explored the upstream regulators of this 'atherogenic transition'. Methods and results Genome-wide sequencing studies, including ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) and RNA-seq, were performed on cells isolated from both murine SMC-lineage tracing models of atherosclerosis and human atherosclerotic lesions. At the bulk level, alterations in chromatin accessibility were associated with the atherogenic transitioning of lesional SMCs, especially in relation to genes that govern differentiation status and complement-dependent inflammation. Using computational biology, we observed that a transcription factor previously related to coronary artery disease, ATF3 (Activating transcription factor 3), was predicted to be an upstream regulator of genes altered during the transition. At the single-cell level, our results indicated that ATF3 is a key repressor of SMC transitioning towards the subset of cells that promote vascular inflammation by activating the complement cascade. The expression of ATF3 and complement component C3 were negatively correlated in SMCs from human atherosclerotic lesions, suggesting translational relevance. Phenome-wide association studies indicated that genetic variation that results in reduced expression of ATF3 is correlated with an increased risk for atherosclerosis, and the expression of ATF3 was significantly downregulated in humans with advanced vascular disease. Conclusion Our study indicates that the plasticity of atherosclerotic SMCs may in part be explained by dynamic changes in their chromatin architecture, which in turn may contribute to their maladaptive response to inflammation-induced stress. Translational perspective The recent CANTOS and COLCOT trials have shown that targeting inflammatory pathways lowers the risk of major adverse cardiovascular events. However, more specific targets are needed to avoid immunosuppressive side effects. Our data identify an upstream regulator of pro-inflammatory SMCs, ATF3, which is involved in the initial atherogenic transitioning of lesional SMCs. Restoring ATF3 activity may prevent the de-differentiation of SMCs and offer a novel translational approach for the suppression of complement-dependent inflammation in atherosclerotic lesions.

Background: Although sex differences in coronary artery disease are widely accepted with women developing more stable atherosclerosis than men, the underlying pathobiology of such differences remains largely unknown. In coronary artery disease, recent integrative systems biological studies have inferred gene regulatory networks (GRNs). Within these GRNs, key driver genes have shown great promise but have thus far been unidentified in women. Methods: We generated sex-specific GRNs of the atherosclerotic arterial wall in 160 women and age-matched men in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). We integrated the female GRNs with single-cell RNA-sequencing data of the human atherosclerotic plaque and single-cell RNA sequencing of advanced atherosclerotic lesions from wild type and Klf4 knockout atherosclerotic smooth muscle cell (SMC) lineage-tracing mice. Results: By comparing sex-specific GRNs, we observed clear sex differences in network activity within the atherosclerotic tissues. Genes more active in women were associated with mesenchymal cells and endothelial cells, whereas genes more active in men were associated with the immune system. We determined that key drivers of GRNs active in female coronary artery disease were predominantly found in (SMCs by single-cell sequencing of the human atherosclerotic plaques, and higher expressed in female plaque SMCs, as well. To study the functions of these female SMC key drivers in atherosclerosis, we examined single-cell RNA sequencing of advanced atherosclerotic lesions from wild type and Klf4 knockout atherosclerotic SMC lineage-tracing mice. The female key drivers were found to be expressed by phenotypically modulated SMCs and affected by Klf4, suggesting that sex differences in atherosclerosis involve phenotypic switching of plaque SMCs. Conclusions: Our systems approach provides novel insights into molecular mechanisms that underlie sex differences in atherosclerosis. To discover sex-specific therapeutic targets for atherosclerosis, an increased emphasis on sex-stratified approaches in the analysis of multi-omics data sets is warranted.

Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights., Some cholesterol-lowering drugs can increase the risk of type 2 diabetes, but the mechanism behind this is not fully understood. Here the authors show that there is a single genetic regulatory module that influences both cholesterol levels and glucose levels, providing a link between cholesterol levels and diabetes.

Atherosclerosis is the process underlying heart attack and stroke. Despite decades of research, its pathogenesis remains unclear. Dogma suggests that atherosclerotic plaques expand primarily via the accumulation of cholesterol and inflammatory cells. However, recent evidence suggests that a substantial portion of the plaque may arise from a subset of “dedifferentiated” vascular smooth muscle cells (SMCs) which proliferate in a clonal fashion. Herein we use multicolor lineage-tracing models to confirm that the mature SMC can give rise to a hyperproliferative cell which appears to promote inflammation via elaboration of complement-dependent anaphylatoxins. Despite being extensively opsonized with prophagocytic complement fragments, we find that this cell also escapes immune surveillance by neighboring macrophages, thereby exacerbating its relative survival advantage. Mechanistic studies indicate this phenomenon results from a generalized opsonin-sensing defect acquired by macrophages during polarization. This defect coincides with the noncanonical up-regulation of so-called don’t eat me molecules on inflamed phagocytes, which reduces their capacity for programmed cell removal (PrCR). Knockdown or knockout of the key antiphagocytic molecule CD47 restores the ability of macrophages to sense and clear opsonized targets in vitro, allowing for potent and targeted suppression of clonal SMC expansion in the plaque in vivo. Because integrated clinical and genomic analyses indicate that similar pathways are active in humans with cardiovascular disease, these studies suggest that the clonally expanding SMC may represent a translational target for treating atherosclerosis.

Atherosclerosis is characterized by the retention of modified lipoproteins in the arterial wall. These modified lipoproteins activate resident macrophages and the recruitment of monocyte-derived cells, which differentiate into mononuclear phagocytes that ingest the deposited lipoproteins to become “foam cells”: a hallmark of this disease. In this Part 2 of a 4-part review series covering the macrophage in cardiovascular disease, we critically review the contributions and relevant pathobiology of monocytes, macrophages, and foam cells as relevant to atherosclerosis. We also review evidence that via various pathways, a failure of the resolution of inflammation is an additional key aspect of this disease process. Finally, we consider the likely role played by genomics and biological networks in controlling the macrophage phenotype in atherosclerosis. Collectively, these data provide substantial insights on the atherosclerotic process, while concurrently offering numerous molecular and genomic candidates that appear to hold great promise for selective targeting as clinical therapies.

Summary Mesenchymal stem cells (MSCs) reportedly exist in a vascular niche occupying the outer adventitial layer. However, these cells have not been well characterized in vivo in medium- and large-sized arteries in humans, and their potential pathological role is unknown. To address this, healthy and diseased arterial tissues were obtained as surplus surgical specimens and freshly processed. We identified that CD90 marks a rare adventitial population that co-expresses MSC markers including PDGFRα, CD44, CD73, and CD105. However, unlike CD90, these additional markers were widely expressed by other cells. Human adventitial CD90+ cells fulfilled standard MSC criteria, including plastic adherence, spindle morphology, passage ability, colony formation, and differentiation into adipocytes, osteoblasts, and chondrocytes. Phenotypic and transcriptomic profiling, as well as adoptive transfer experiments, revealed a potential role in vascular disease pathogenesis, with the transcriptomic disease signature of these cells being represented in an aortic regulatory gene network that is operative in atherosclerosis., Highlights • We identify, in situ and in vivo, adventitial CD90+ MSCs in human arteries • Human adventitial CD90+ cells fulfill all criteria for an MSC population • Other markers, such as CD44 and PDGFRα, were non-specific for adventitial MSCs • The CD90+ MSC transcriptomic signature suggests a major role in vascular disease, MSCs reportedly exist in a specific vascular niche, but these cells have not been well characterized in medium- and large-sized human arteries. To address this, surplus arterial tissues were obtained at surgery and freshly processed. We show that CD90 marks a human adventitial MSC population, with the CD90+ MSC transcriptomic signature being represented in an atherosclerotic regulatory gene network.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

The volume and diversity of data in biomedical research have been rapidly increasing in recent years. While such data hold significant promise for accelerating discovery, their use entails many challenges including: the need for adequate computational infrastructure, secure processes for data sharing and access, tools that allow researchers to find and integrate diverse datasets, and standardized methods of analysis. These are just some elements of a complex ecosystem that needs to be built to support the rapid accumulation of these data. The NIH Big Data to Knowledge (BD2K) initiative aims to facilitate digitally enabled biomedical research. Within the BD2K framework, the Commons initiative is intended to establish a virtual environment that will facilitate the use, interoperability, and discoverability of shared digital objects used for research. The BD2K Commons Framework Pilots Working Group (CFPWG) was established to clarify goals and work on pilot projects that address existing gaps toward realizing the vision of the BD2K Commons. This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States. (C) 2017 Elsevier Inc. All rights reserved.

OBJECTIVE Inflammation may contribute to an increased risk of cardiovascular disease (CVD) in HIV-1 infection. MicroRNAs (miRNAs) are involved in the regulation of inflammation. In treated HIV-1-infected individuals, we aimed to identify differentially expressed miRNAs with known roles in inflammation and CVD risk and to investigate associations between these and systemic inflammation. METHODS In a screening cohort including 14 HIV-1-infected individuals and 9 uninfected controls, microarray profiling was performed using peripheral blood mononuclear cells (PBMCs). Differentially regulated miRNAs previously related to inflammation and CVD were validated using real-time quantitative reverse-transcription polymerase chain reaction in 26 HIV-1-infected individuals and 20 uninfected controls. Validated miRNAs were measured in PBMCs, CD4 and CD8 T cells. Interleukin-6, tumor necrosis factor-alpha, high-sensitivity C-reactive protein, lipopolysaccharide (LPS), cytomegalovirus immunoglobulin G, lipids, and fasting glucose were measured, and associations with validated miRNAs were assessed with multiple linear regression analysis. RESULTS Upregulation of miR-210, miR-7, and miR-331 was found in PBMCs from HIV-1-infected individuals when compared with those from uninfected controls (P < 0.005). In contrast, miR-210 and miR-331 were downregulated in CD8 T cells. In multivariate analysis, miR-210 in CD8 T cells was negatively associated with LPS (P = 0.023) and triglycerides (P = 0.003) but positively associated with tumor necrosis factor-alpha (P = 0.004). MiR-7 in PBMC was positively associated with interleukin-6 (P = 0.025) and fasting glucose (P = 0.005), whereas miR-331 was negatively associated with LPS (P = 0.006). In PBMCs from HIV-1-infected individuals with low cytomegalovirus immunoglobulin G, miR-7, miR-29a, miR-221, and miR-222 were downregulated. CONCLUSION In 2 independent cohorts, miR-210, miR-7, and miR-331 were differentially regulated in treated HIV-1-infected individuals and associated with markers of systemic inflammation.

Background: Antiretroviral therapy (ART) for HIV infection increases risk for coronary artery disease (CAD), presumably by causing dyslipidemia and increased atherosclerosis. We applied systems pharmacology to identify and validate specific regulatory gene networks through which ART drugs may promote CAD. Methods: Transcriptional responses of human cell lines to 15 ART drugs retrieved from the Library of Integrated Cellular Signatures (overall 1127 experiments) were used to establish consensus ART gene/transcriptional signatures. Next, enrichments of differentially expressed genes and gene-gene connectivity within these ART-consensus signatures were sought in 30 regulatory gene networks associated with CAD and CAD-related phenotypes in the Stockholm Atherosclerosis Gene Expression study. Results: Ten of 15 ART signatures were significantly enriched both for differential expression and connectivity in a specific atherosclerotic arterial wall regulatory gene network (AR-RGN) causal for CAD involving RNA processing genes. An atherosclerosis in vitro model of cholestryl ester-loaded foam cells was then used for experimental validation. Treatments of these foam cells with ritonavir, nelfinavir, and saquinavir at least doubled cholestryl ester accumulation ( P =0.02, 0.0009, and 0.02, respectively), whereas RNA silencing of the AR-RGN top key driver, PQBP1 (polyglutamine binding protein 1), significantly curbed cholestryl ester accumulation following treatment with any of these ART drugs by >37% ( P Conclusions: By applying a novel systems pharmacology data analysis framework, 3 commonly used ARTs (ritonavir, nelfinavir, and saquinavir) were found altering the activity of AR-RGN, a regulatory gene network promoting foam cell formation and risk of CAD. Targeting AR-RGN or its top key driver PQBP1 may help reduce CAD side effects of these ART drugs.

We describe a novel Bayesian method for estimating protein concentration and phosphorylation site occupancy ratios from mass spectrometry experiments. Our variance model assigns standard deviations to all quantitative ratios, even when only a single peptide is observed, increasing the number of quantifiable observations in a sample compared to conventional methods. We further demonstrate the application of this method using a dataset investigating the impact of the PRKAR1A-RET gene fusion in immortalized thyroid cells.

Background Genetic variants currently known to affect coronary artery disease (CAD) risk explain less than one-quarter of disease heritability. The heritability contribution of gene regulatory networks (GRNs) in CAD, which are modulated by both genetic and environmental factors, is unknown. Objectives This study sought to determine the heritability contributions of single nucleotide polymorphisms affecting gene expression (eSNPs) in GRNs causally linked to CAD. Methods Seven vascular and metabolic tissues collected in 2 independent genetics-of-gene-expression studies of patients with CAD were used to identify eSNPs and to infer coexpression networks. To construct GRNs with causal relations to CAD, the prior information of eSNPs in the coexpression networks was used in a Bayesian algorithm. Narrow-sense CAD heritability conferred by the GRNs was calculated from individual-level genotype data from 9 European genome-wide association studies (GWAS) (13,612 cases, 13,758 control cases). Results The authors identified and replicated 28 independent GRNs active in CAD. The genetic variation in these networks contributed to 10.0% of CAD heritability beyond the 22% attributable to risk loci identified by GWAS. GRNs in the atherosclerotic arterial wall (n = 7) and subcutaneous or visceral abdominal fat (n = 9) were most strongly implicated, jointly explaining 8.2% of CAD heritability. In all, these 28 GRNs (each contributing to >0.2% of CAD heritability) comprised 24 to 841 genes, whereof 1 to 28 genes had strong regulatory effects (key disease drivers) and harbored many relevant functions previously associated with CAD. The gene activity in these 28 GRNs also displayed strong associations with genetic and phenotypic cardiometabolic disease variations both in humans and mice, indicative of their pivotal roles as mediators of gene–environmental interactions in CAD. Conclusions GRNs capture a major portion of genetic variance and contribute to heritability beyond that of genetic loci currently known to affect CAD risk. These networks provide a framework to identify novel risk genes/pathways and study molecular interactions within and across disease-relevant tissues leading to CAD.

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

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., Author summary It is now estimated that nearly ~50% of one’s lifetime risk for coronary artery disease is genetically predetermined. While genetic studies have led to the identification of several novel disease risk factors, the mechanisms driving many of these associations are yet to be fully identified. Here, we take advantage of a recent finding identifying genetic variation in a smooth muscle cell restricted gene called Leiomodin1, and investigate the causal gene and mechanism by which this risk factor predisposes individuals to coronary artery disease. By implementing several complementary approaches, we extend previous findings demonstrating that this genetic variant is associated with attenuated expression of Leiomodin 1. Interestingly, we demonstrate that this association is attributed to altered binding of a transcription factor Forkhead Box 3. More importantly, we show that reduced Leiomodin 1 results in phenotypic modulation of smooth muscle cells, a process related to diseases such as atherosclerosis. Interestingly, Leiomodin 1 levels were found to be reduced in smooth muscle cells within atherosclerotic lesions relative to those around the fibrous cap. These studies provide new insights into the heritable mechanisms of coronary artery disease with Leiomodin 1 as a potential therapeutic target.

Objective— A large number of genetic loci have been associated with risk of coronary artery disease (CAD) through genome-wide association studies, however, for most loci the underlying biological mechanism is unknown. Determining the molecular pathways and cellular processes affected by these loci will provide new insights into CAD pathophysiology and may lead to new therapies. The CAD-associated variants at 10p11.23 fall in JCAD , which encodes an endothelial junction protein, however, its molecular function in endothelial cells is not known. In this study, we characterize the molecular role of JCAD (junctional cadherin 5 associated) in endothelial cells. Approach and Results— We show that JCAD knockdown in endothelial cells affects key phenotypes related to atherosclerosis including proliferation, migration, apoptosis, tube formation, and monocyte binding. We demonstrate that JCAD interacts with LATS2 (large tumor suppressor kinase 2) and negatively regulates Hippo signaling leading to increased activity of YAP (yes-associated protein), the transcriptional effector of the pathway. We also show by double siRNA knockdown that the phenotypes caused by JCAD knockdown require LATS2 and that JCAD is involved in transmission of RhoA-mediated signals into the Hippo pathway. In human tissues, we find that the CAD-associated lead variant, rs2487928, is associated with expression of JCAD in arteries, including atherosclerotic arteries. Gene co-expression analyses across disease-relevant tissues corroborate our phenotypic findings and support the link between JCAD and Hippo signaling. Conclusions— Our results show that JCAD negatively regulates Hippo signaling in endothelial cells and we suggest that JCAD contributes to atherosclerosis by mediating YAP activity and contributing to endothelial dysfunction.

Genome-wide association studies have associated a large number of loci with coronary artery disease (CAD) risk. The CAD-associated variants at 10 p11.23 fall in JCAD, which encodes an endothelial junction protein. We set out to investigate the function of JCAD in endothelial cells using knockdown of JCAD in comparison to a non-targeting control siRNA. Knockdown of JCAD reduced cellular proliferation by approximately 15% after 48 hours (p=0.0002). A wound healing assay showed approximately 30% reduction in migration in JCAD knockdown cells (p=0.001). Apoptosis of JCAD knockdown cells was increased by approximately 50% compared to control siRNA treated cells (p=0.005). A matrigel tube-formation assay was used to determine the cells angiogenic capability and showed a reduction in tubule length formed of roughly 25% (p=0.0007). To determine if JCAD is involved in regulation of monocyte adhesion we used an in vitro monocyte adhesion assay and found that JCAD knockdown in endothelial cells reduced adhesion by approximately 30% (p=0.0001). JCAD knockdown in endothelial cells also decreased adhesion molecule expression as measured by qPCR – ICAM1 was reduced by around 18% (p=0.022), VCAM1 was reduced by 25% (p=0.008) and SELE was reduced by 22% although this wasn’t statistically significant (p=0.092). JCAD has recently been shown to interact with LATS2, a core kinase of the Hippo signalling pathway. We therefore sought to determine if the regulation of endothelial cell function by JCAD occurs via Hippo pathway regulation. We confirmed the physical interaction between JCAD and LATS2 by immunoprecipitation. LATS2 acts via phosphorylation of the Hippo pathway effector YAP which excludes YAP from the nucleus preventing it from promoting target gene expression. We demonstrated increased YAP phosphorylation in cells following JCAD knockdown and by immunofluorescence we showed that JCAD siRNA reduced YAP nuclear/cytoplasmic ratio (p=0.0001). We also detected reduced expression of YAP target genes by qPCR. Using double JCAD and LATS2 siRNA treatments, we have also demonstrated that the regulation of endothelial cell phenotypes by JCAD requires LATS2. Additionally, co-expression analysis of RNA-seq data from normal and atherosclerotic blood vessels found JCAD as a key driver of a module enriched for genes involved in YAP/TAZ signalling, supporting our in vitro findings. We also identified an eQTL for the lead CAD associated SNP at 10 p11.23 with JCAD expression, suggesting that altered transcriptional regulation of JCAD is the causal mechanism at this locus. These data suggest that JCAD encodes a novel regulator of Hippo signalling in endothelial cells and suggest that the variants at the 10 p11.23 CAD locus act through JCAD to increase endothelial cell dysfunction via Hippo signalling.

Dilated cardiomyopathy (DCM) can be caused by mutations in the cardiac protein phospholamban (PLN). We used CRISPR/Cas9 to insert the R9C PLN mutation at its endogenous locus into a human induced pluripotent stem cell (hiPSC) line from an individual with no cardiovascular disease. R9C PLN hiPSC-CMs display a blunted β-agonist response and defective calcium handling. In 3D human engineered cardiac tissues (hECTs), a blunted lusitropic response to β-adrenergic stimulation was observed with R9C PLN. hiPSC-CMs harboring the R9C PLN mutation showed activation of a hypertrophic phenotype, as evidenced by expression of hypertrophic markers and increased cell size and capacitance of cardiomyocytes. RNA-seq suggests that R9C PLN results in an altered metabolic state and profibrotic signaling, which was confirmed by gene expression analysis and picrosirius staining of R9C PLN hECTs. The expression of several miRNAs involved in fibrosis, hypertrophy, and cardiac metabolism were also perturbed in R9C PLN hiPSC-CMs. This study contributes to better understanding of the pathogenic mechanisms of the hereditary R9C PLN mutation in the context of human cardiomyocytes.

Inter-tissue communication via secreted proteins has been established as a vital mechanism for proper physiologic homeostasis. Here, we report a bioinformatics framework using a mouse reference population, the Hybrid Mouse Diversity Panel (HMDP), which integrates global multi-tissue expression data and publicly available resources to identify and functionally annotate novel circuits of tissue-tissue communication. We validate this method by showing that we can identify known as well as novel endocrine factors responsible for communication between tissues. We further show the utility of this approach by identification and mechanistic characterization of two new endocrine factors. Adipose-derived Lipocalin-5 is shown to enhance skeletal muscle mitochondrial function, and liver-secreted Notum promotes browning of white adipose tissue, also known as "beiging." We demonstrate the general applicability of the method by providing in vivo evidence for three additional novel molecules mediating tissue-tissue interactions.

The genetic architecture of coronary artery disease (CAD), which represents the leading cause of death worldwide, has been investigated in both human populations and mouse models. However, whether the two species share similar genetic underpinnings has not been thoroughly evaluated. We hypothesize that a comprehensive data-driven integrative study leveraging multi-omics data resources will allow a tissue-specific, systems level assessment of the key similarities and differences in disease networks between mouse and man. To derive CAD genetic networks in mouse, we used genetic data from genome-wide association studies (GWAS) of atherosclerosis and functional genomics data of aorta and liver tissues from >100 strains profiled in an Atherosclerosis Hybrid Mouse Diversity Panel. To model human CAD genetic networks, we used human CAD GWAS from CARDIoGRAM+C4D, and functional genomics data from aorta and coronary arteries, and liver tissues from the Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task and Genotype-Tissue Expression biobanks. We identified coexpression network modules and biological pathways that were significantly associated with genetic signals in each species. This tissue-specific analysis revealed that ~75 and ~80% of the pathways and networks were shared between species for vascular and liver tissues, respectively. The shared processes between species for both tissues included lipid and lipoprotein metabolism, MAPK, TCA, and notch signaling pathways; for vascular tissues the shared terms included biological oxidations, interferon, and cytokine signaling; for liver tissue, fatty acid metabolism, TGF-beta signaling, leukocyte transendothelial migration were shared between species. Viral myocarditis, platelet-derived growth factor signaling, fibrinolysis, and IL6/7 pathways were identified as human-specific, while insulin and nerve growth factor signaling were found to be mouse-specific. This cross-species tissue-specific integrative analysis provides insights into the convergent and divergent causal mechanisms underlying CAD between species and highlights the conditions in which mouse may or may not serve as a surrogate model for human CAD in disease mechanistic and preclinical studies.

Atherosclerosis is characterized by the retention of modified lipoproteins in the arterial wall. These modified lipoproteins activate resident macrophages and the recruitment of monocyte-derived cells, which differentiate into mononuclear phagocytes that ingest the deposited lipoproteins to become "foam cells": a hallmark of this disease. In this Part 2 of a 4-part review series covering the macrophage in cardiovascular disease, we critically review the contributions and relevant pathobiology of monocytes, macrophages, and foam cells as relevant to atherosclerosis. We also review evidence that via various pathways, a failure of the resolution of inflammation is an additional key aspect of this disease process. Finally, we consider the likely role played by genomics and biological networks in controlling the macrophage phenotype in atherosclerosis. Collectively, these data provide substantial insights on the atherosclerotic process, while concurrently offering numerous molecular and genomic candidates that appear to hold great promise for selective targeting as clinical therapies.

Introduction: Endocrine proteins play central roles at all stages of coronary artery disease (CAD) development from endothelium activation, leukocyte migration to foam cell formation, smooth muscle cell migration and the formation of advanced atherosclerotic plaques. Although some endocrine factors already have been identified, the systemic landscape of endocrine signaling acting between fat, liver, skeletal muscle and the arterial wall in CAD remains largely unknown. Hypothesis: Systemic endocrine signaling underlying cross-tissue metabolic and arterial wall networks is essential for CAD development. Methods: We studied the underlying endocrine signaling between tissues by inferring 89 cross-tissue and 135 tissue-specific regulatory-gene networks (RGNs) from genotype and RNA-seq data in seven tissues including blood, arterial and metabolic tissues isolated from 672 CAD patients in the Stockholm Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study. Within the cross-tissue RGNs, we detected 1,358 transcripts encoding secreted proteins and identified their cross-tissue target transcripts. Next, we validated these endocrine factors and their cross-tissue regulatory interactions using expression data from mice and experimentally in relevant cell models. Results: As judged from a super-network containing all RGNs, a majority of identified endocrine factors in cross-tissue RGNs were found between visceral abdominal fat and liver. However, one RGN active in visceral abdominal fat contained the endocrine factors: ALB, APOH, APOC3, APOA2, AHSG, AMBP, FGA, FGB, FGG, and GC, targeting an arterial wall RGN enriched for blood microparticle genes and for CAD risk genes identified by genome-wide association studies, and was associated with SYNTAX scores of the STARNET patients. Conclusions: Previously unknown endocrine factors acting in cross-tissue RGNs contribute to CAD and may be useful as targets for novel CAD therapies.

Dilated cardiomyopathy (DCM) can be caused by genetic mutations in numerous cardiac proteins, including phospholamban (PLN). PLN mutations are quite rare and obtaining patient samples for mechanistic insights can be challenging. We used genome editing with CRISPR/Cas9 to successfully insert R14del and R9C PLN mutations into a human induced pluripotent stem cell (hiPSC) line from an individual with no cardiovascular disease. HiPSC-cardiomyocytes (hiPSC-CMs) with the inserted R14del PLN mutation recapitulate the phenotype observed in patient-derived R14del hiPSC-CMs, characterized by abnormal intracellular calcium cycling and arrhythmogenicity. Insertion of R9C PLN results in hiPSC-CMs displaying an abnormal response to β-agonists, defective calcium handling, and a hypertrophic phenotype. In human engineered cardiac tissues (hECTs) created from hiPSC-CMs in a 3D matrix, R14del results in a progressive worsening of developed force and R9C PLN demonstrates an abnormal lusitropic response following β-adrenergic stimulation. Further, transcriptional profiling using RNAseq suggests a role for lipid metabolism in R14del. DNA methylation studies showed that differentially expressed genes were enriched for lipoprotein metabolism and chylomicron-mediated lipid transport pathways in R14del PLN. This was also confirmed with the observation of lipid deposition in R14del hECTs and human myocardial tissues from explanted hearts of affected patients. Furthermore, small RNAseq identified 2 miRNAs that were differentially regulated in R14del hiPSC-CMs (miR-449c-5p and miR-483-3p). For R9C PLN, RNAseq suggests that the mutation results in profibrotic signaling, activation of autophagy, and an altered metabolic state. Our findings demonstrate that gene editing of hiPSCs can be used to successfully create models and delineate molecular mechanisms of human PLN mutations associated with DCM.

Signaling networks are nonlinear and complex, involving a large ensemble of dynamic interaction states that fluctuate in space and time. However, therapeutic strategies, such as combination chemotherapy, rarely consider the timing of drug perturbations. If we are to advance drug discovery for complex diseases, it will be essential to develop methods capable of identifying dynamic cellular responses to clinically relevant perturbations. Here, we present a Bayesian dose-response framework and the screening of an oncological drug matrix, comprising 10,000 drug combinations in melanoma and pancreatic cancer cell lines, from which we predict sequentially effective drug combinations. Approximately 23% of the tested combinations showed high-confidence sequential effects (either synergistic or antagonistic), demonstrating that cellular perturbations of many drug combinations have temporal aspects, which are currently both underutilized and poorly understood. Signaling networks are nonlinear and complex, involving a large ensemble of dynamic interaction states that fluctuate in space and time. However, therapeutic strategies, such as combination chemotherapy, rarely consider the timing of drug perturbations. If we are to advance drug discovery for complex diseases, it will be essential to develop methods capable of identifying dynamic cellular responses to clinically relevant perturbations. Here, we present a Bayesian dose-response framework and the screening of an oncological drug matrix, comprising 10,000 drug combinations in melanoma and pancreatic cancer cell lines, from which we predict sequentially effective drug combinations. Approximately 23% of the tested combinations showed high-confidence sequential effects (either synergistic or antagonistic), demonstrating that cellular perturbations of many drug combinations have temporal aspects, which are currently both underutilized and poorly understood.

Integrating data from multiple regulatory layers across cancer types could elucidate additional mechanisms of oncogenesis. Using antibody-based protein profiling of 736 cancer cell lines, along with matching transcriptomic data, we show that pan-cancer bimodality in the amounts of mRNA, protein, and protein phosphorylation reveals mechanisms related to the epithelial-mesenchymal transition (EMT). Based on the bimodal expression of E-cadherin, we define an EMT signature consisting of 239 genes, many of which were not previously associated with EMT. By querying gene expression signatures collected from cancer cell lines after small-molecule perturbations, we identify enrichment for histone deacetylase (HDAC) inhibitors as inducers of EMT, and kinase inhibitors as mesenchymal-to-epithelial transition (MET) promoters. Causal modeling of protein-based signaling identifies putative drivers of EMT. In conclusion, integrative analysis of pan-cancer proteomic and transcriptomic data reveals key regulatory mechanisms of oncogenic transformation., Author summary Profiling molecular and phenotypic characteristics of large collections of cancer cell lines can be used to identify distinct and common oncogenic pathways across cancer types. So far, most large-scale data obtained from cancer cell lines have been at the genomic, transcriptomic, and phenotypic levels. Recently, high-quality data at the level of cell signaling through protein abundances and phosphorylation sites has become available. By integrating this newly generated protein data with prior transcriptomic data, and by visualizing all cancer cell lines using dimensionality reduction techniques, pan-cancer cell lines are strikingly shown to organize into a gradient of epithelial to mesenchymal types. Interestingly, many of the measured proteins and transcripts display bimodality; the expression of genes, proteins, and protein phosphorylations is either high or low, strongly suggesting that they act as molecular switches. Focusing on further characterizing molecular switches of epithelial-mesenchymal transitions, we identify candidate regulators and small molecules that can induce or reverse such transition, as well as potential causal relationships between proteins. Since the mesenchymal state of tumors is known to be associated with metastasis and later-stage cancer development, better understanding the regulatory mechanisms of epithelial-to-mesenchymal transition can lead to improved targeted therapeutics.