Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis.

BACKGROUND: While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remains poorly understood. METHODS: Single-cell RNA sequencing data generated with SmartSeq2 (≈8000 genes/cell) in 16 588 single cells isolated during atherosclerosis progression in Ldlr-/-Apob100/100 mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease patients in the STARNET (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task) study. RESULTS: Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by 3 smooth muscle cells (SMCs), and 3 macrophage subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type proinflammatory/Trem2-high lipid-associated (macrophage) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of 3 arterial wall GRNs: GRN33 (macrophage), GRN39 (SMC), and GRN122 (macrophage) with major contributions to coronary artery disease heritability and strong associations with clinical scores of coronary atherosclerosis severity. The presence and pathophysiological relevance of GRN39 were verified in 5 independent RNAseq data sets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM in cultured human coronary artery SMCs. CONCLUSIONS: By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a coronary artery disease framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced, symptomatic atherosclerosis.

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.

Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence.

Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of their in vivo cell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits-which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.

A spatial human thymus cell atlas mapped to a continuous tissue axis.

T cells develop from circulating precursors, which enter the thymus and migrate throughout specialised sub-compartments to support maturation and selection. This process starts already in early fetal development and is highly active until the involution of the thymus in adolescence. To map the micro-anatomical underpinnings of this process in pre- vs. post-natal states, we undertook a spatially resolved analysis and established a new quantitative morphological framework for the thymus, the Cortico-Medullary Axis. Using this axis in conjunction with the curation of a multimodal single-cell, spatial transcriptomics and high-resolution multiplex imaging atlas, we show that canonical thymocyte trajectories and thymic epithelial cells are highly organised and fully established by post-conception week 12, pinpoint TEC progenitor states, find that TEC subsets and peripheral tissue genes are associated with Hassall's Corpuscles and uncover divergence in the pace and drivers of medullary entry between CD4 vs. CD8 T cell lineages. These findings are complemented with a holistic toolkit for spatial analysis and annotation, providing a basis for a detailed understanding of T lymphocyte development.

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

The development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. Ex vivo screens, using human samples, showed that saracatinib-a phase 2a-ready SRC and ABL inhibitor-reversed the inflammatory responses induced by ASCVD plasma. In Apoe-/- mice, saracatinib reduced atherosclerosis progression by reprogramming reparative macrophages. In a rabbit model of advanced atherosclerosis, saracatinib reduced plaque inflammation measured by [18F] fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. Here we show a systems immunology-driven drug repurposing with a preclinical validation strategy to aid the development of cardiovascular immunotherapies.

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.

Erratum: Publisher Correction: Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

[This corrects the article DOI: 10.1038/s44161-023-00278-y.].

A mechanistic framework for cardiometabolic and coronary artery diseases.

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.

Transcriptome-wide association study of coronary artery disease identifies novel susceptibility genes.

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 < 3.85e-6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes, 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.

Dynamic changes in chromatin accessibility are associated with the atherogenic transitioning of vascular smooth muscle cells.

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 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, Activating transcription factor 3 (ATF3), 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 was 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 down-regulated 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.

Loss of soluble guanylyl cyclase in platelets contributes to atherosclerotic plaque formation and vascular inflammation.

Variants in genes encoding the soluble guanylyl cyclase (sGC) in platelets are associated with coronary artery disease (CAD) risk. Here, by using histology, flow cytometry and intravital microscopy, we show that functional loss of sGC in platelets of atherosclerosis-prone Ldlr-/- mice contributes to atherosclerotic plaque formation, particularly via increasing in vivo leukocyte adhesion to atherosclerotic lesions. In vitro experiments revealed that supernatant from activated platelets lacking sGC promotes leukocyte adhesion to endothelial cells (ECs) by activating ECs. Profiling of platelet-released cytokines indicated that reduced platelet angiopoietin-1 release by sGC-depleted platelets, which was validated in isolated human platelets from carriers of GUCY1A1 risk alleles, enhances leukocyte adhesion to ECs. I mp or ta ntly, p ha rm ac ol ogical sGC stimulation increased platelet angiopoietin-1 release in vitro and reduced leukocyte recruitment and atherosclerotic plaque formation in atherosclerosis-prone Ldlr-/- mice. Therefore, pharmacological sGC stimulation might represent a potential therapeutic strategy to prevent and treat CAD.

Integrative Prioritization of Causal Genes for Coronary Artery Disease.

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.

Histone deacetylase 9 promotes endothelial-mesenchymal transition and an unfavorable atherosclerotic plaque phenotype.

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.

An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease.

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.

Sex-Stratified Gene Regulatory Networks Reveal Female Key Driver Genes of Atherosclerosis Involved in Smooth Muscle Cell Phenotype Switching.

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.

Unraveling tumor-immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy.

In metastatic cancer, the degree of heterogeneity of the tumor microenvironment (TME) and its molecular underpinnings remain largely unstudied. To characterize the tumor-immune interface at baseline and during neoadjuvant chemotherapy (NACT) in high-grade serous ovarian cancer (HGSOC), we performed immunogenomic analysis of treatment-naive and paired samples from before and after treatment with chemotherapy. In treatment-naive HGSOC, we found that immune-cell-excluded and inflammatory microenvironments coexist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of TME cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following NACT, increased natural killer (NK) cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor-immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors.

Clonally expanding smooth muscle cells promote atherosclerosis by escaping efferocytosis and activating the complement cascade.

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.

Contribution of Gene Regulatory Networks to Heritability of Coronary Artery Disease.

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.

Systems Pharmacology Identifies an Arterial Wall Regulatory Gene Network Mediating Coronary Artery Disease Side Effects of Antiretroviral Therapy.

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<0.05). 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.