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Epigenetic age estimators (clocks) are known to be predictive of human mortality risk. However, it is not yet known whether the epigenetic age of atherosclerotic plaques can be used for predicting secondary events. Here we estimated an age adjusted measure of epigenetic age, epigenetic age acceleration (EAA), using DNA methylation of human atherosclerotic plaques and of blood. EAA of plaque, but not blood, independently predicted secondary events in a 3-year follow-up (HR=1.3, p= 0.018). Plaque EAA concurred with a high metabolic epigenetic and transcriptional state in plaques. Patients with diabetes and a high body mass index had a higher plaque EAA. EAA was lower in female plaques compared to male plaques by approximately 2 years. Single-cell RNA-seq revealed mesenchymal smooth muscle cells and endothelial cells as main drivers of EAA. Plaque-specific ageing may help identify processes that explain poor health outcomes.

Plaque smooth muscle cells are critical players in the initiation and advancement of atherosclerotic disease. They produce extracellular matrix (ECM) components, which play a role in lesion progression and stabilization. Despite clear phenotypic differences between plaque smooth muscle cells and vascular smooth muscle cells (VSMCs), VSMCs are still widely used as a model system in atherosclerotic research.Here we present a conditioned outgrowth method to isolate plaque smooth muscle cells. We obtained plaque cells from 27 donors (24 carotid and 3 femoral endarterectomies). We show that these cells keep their proliferative capacity for eight passages, are transcriptionally stable, retain donor-specific gene expression programs, and express extracellular matrix proteins (FN1, COL1A1, DCN) and smooth muscle cell markers (ACTA2, MYH11, CNN1).Single-cell transcriptomics of plaque tissue and cultured cells reveals that cultured plaque cells closely resemble the myofibroblast fraction of plaque smooth muscle cells. Chromatin immunoprecipitation sequencing (ChIP-seq) shows the presence of histone H3 lysine 4 dimethylation (H3K4me2) at theMYH11promoter, pointing to their smooth muscle cell origin. Finally, we demonstrated that plaque cells can be efficiently transduced (>97%) and are capable to take up oxidized LDL (oxLDL) and undergo calcification.In conclusion, we present a method to isolate and culture primary human plaque cells that retain plaque myofibroblast-like cells’ phenotypical and functional capabilities - making them a suitablein vitromodel for studying selected mechanisms of atherosclerosis.

Women presenting with coronary artery disease (CAD) more often present with fibrous atherosclerotic plaques, which are currently understudied. Phenotypically modulated smooth muscle cells (SMCs) contribute to atherosclerosis in women. How these phenotypically modulated SMCs shape female versus male plaques is unknown. Here, we show sex-stratified gene regulatory networks (GRNs) from human carotid atherosclerotic tissue. Prioritization of these networks identified two main SMC GRNs in late-stage atherosclerosis. Single-cell RNA-sequencing mapped these GRNs to two SMC phenotypes: a phenotypically modulated myofibroblast-like SMC network and a contractile SMC network. The myofibroblast-like GRN was mostly expressed in plaques that were vulnerable in females. Finally, mice orthologs of the female myofibroblast-like genes showed retained expression in advanced plaques from female mice but were downregulated in male mice during atherosclerosis progression. Female atherosclerosis is driven by GRNs that promote a fibrous vulnerable plaque rich in myofibroblast-like SMCs.

BackgroundGenome-wide association studies have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analyzed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene-cell pairs.Methods and ResultsTo identify disease-associated genes, we applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with scRNA-seq data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease loci demonstrated a prominent signal in plaque smooth muscle cells (SKI, KANK2, SORT1) p-adj. = 0.0012, and endothelial cells (SLC44A1, ATP2B1) p-adj. = 0.0011. Further sub clustering revealed genes in risk loci for coronary calcification specifically enriched in a synthetic smooth muscle cell population. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels.ConclusionWe discovered novel gene-cell pairs, on top of known pairs, pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with coronary artery disease reveal prominent association levels in mainly plaque smooth muscle and endothelial cell populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.Translational perspectiveGWAS identified a large number of genomic loci associated with atherosclerotic disease. The translation of these results into drug development and faster diagnostics remains challenging. With our approach, we cross-reference the GWAS findings for atherosclerotic disease with scRNA-seq data of disease-relevant tissue and bring the GWAS findings closer to the functional and mechanistic studies.Abstract Figure

Histopathological studies have revealed key processes of atherosclerotic plaque thrombosis. However, the diversity and complexity of lesion types highlight the need for improved sub- phenotyping. We hypothesized that unbiased clustering of plaques based on gene expression results in an alternative categorization of late-stage atherosclerotic lesions.We analyzed the gene expression profiles of 654 advanced human carotid plaques. The unsupervised, transcriptome-driven clustering revealed five dominant plaque types. These novel plaque phenotypes associated with clinical presentation (pIn conclusion, the definition of the plaque at risk for a thrombotic event can be fine-tuned by in- depth transcriptomic based phenotyping. These differential plaque phenotypes prove clinically relevant for both carotid and coronary artery plaques and point to differential underlying biology of symptomatic lesions.

Background and aims The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets. Methods Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets. Results We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView ( www.plaqview.com ), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge. Conclusions This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation.

Sex differences are evident in the clinical presentation and underlying histology of atherosclerotic disease with women developing more stable atherosclerotic lesions than men. It is unknown whether this is explained by sex differences in gene regulation in cellular compartments of atherosclerotic plaques. To study sex differences in gene regulation we performed genome-wide DNA methylation and transcriptomics analysis on plaques of 485 carotid endarterectomy patients (31% female). Sex-differential DNA methylation at 4,848 sites in the autosome was enriched for cell-fate commitment and developmental processes, and its deconvolution predicted more smooth muscle cells in females, as compared to more immune cells in males. RNA-sequencing of the same plaques corroborated the sex differences in DNA methylation predicted cell-types, in which genes that were higher expressed in females were enriched for TGF-beta signaling and extracellular matrix biology. In addition, female-biased genes were enriched for targeting by regulatory loci based on sex differential methylation. Lastly, by using single-cell RNA sequencing we showed that these female-biased genes are mostly expressed in smooth muscle cells, and higher expressed in smooth muscle cells from female (predominantly stable) plaques as compared to male (relatively unstable) plaques. Our approach identified female-biased genes in smooth muscle cells in fibrous atherosclerotic plaques. This points towards new mechanisms in smooth muscle cell biology of stable atherosclerotic plaques and offers new directions for research to develop new sex-specific therapeutics for atherosclerotic disease.

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.

Supplemental Digital Content is available in the text., Rationale: Atherosclerotic lesions are known for their cellular heterogeneity, yet the molecular complexity within the cells of human plaques has not been fully assessed. Objective: Using single-cell transcriptomics and chromatin accessibility, we gained a better understanding of the pathophysiology underlying human atherosclerosis. Methods and Results: We performed single-cell RNA and single-cell ATAC sequencing on human carotid atherosclerotic plaques to define the cells at play and determine their transcriptomic and epigenomic characteristics. We identified 14 distinct cell populations including endothelial cells, smooth muscle cells, mast cells, B cells, myeloid cells, and T cells and identified multiple cellular activation states and suggested cellular interconversions. Within the endothelial cell population, we defined subsets with angiogenic capacity plus clear signs of endothelial to mesenchymal transition. CD4+ and CD8+ T cells showed activation-based subclasses, each with a gradual decline from a cytotoxic to a more quiescent phenotype. Myeloid cells included 2 populations of proinflammatory macrophages showing IL (interleukin) 1B or TNF (tumor necrosis factor) expression as well as a foam cell-like population expressing TREM2 (triggering receptor expressed on myeloid cells 2) and displaying a fibrosis-promoting phenotype. ATACseq data identified specific transcription factors associated with the myeloid subpopulation and T cell cytokine profiles underlying mutual activation between both cell types. Finally, cardiovascular disease susceptibility genes identified using public genome-wide association studies data were particularly enriched in lesional macrophages, endothelial, and smooth muscle cells. Conclusions: This study provides a transcriptome-based cellular landscape of human atherosclerotic plaques and highlights cellular plasticity and intercellular communication at the site of disease. This detailed definition of cell communities at play in atherosclerosis will facilitate cell-based mapping of novel interventional targets with direct functional relevance for the treatment of human disease.

For decades, the pathological definition of the vulnerable plaque led to invaluable insights into the mechanisms that underlie myocardial infarction and stroke. Beyond plaque rupture, other mechanisms, such as erosion, may elicit thrombotic events underlining the complexity and diversity of the atherosclerotic disease. Novel insights, based on single-cell transcriptomics and other "omics" methods, provide tremendous opportunities in the ongoing search for cell-specific determinants that will fine-tune the description of the thrombosis prone lesion. It coincides with an increasing awareness that knowledge on lesion characteristics, cell plasticity and clinical presentation of ischemic cardiovascular events have shifted over the past decades. This shift correlates with an observed changes of cell composition towards phenotypical stabilizing of human plaques. These stabilization features and mechanisms are directly mediated by the cells present in plaques and can be mimicked in vitro via primary plaque cells derived from human atherosclerotic tissues. In addition, the rapidly evolving of sequencing technologies identify many candidate genes and molecular mechanisms that may influence the risk of developing an atherosclerotic thrombotic event - which bring the next challenge in sharp focus: how to translate these cell-specific insights into tangible functional and translational discoveries?

Atherosclerotic plaque (AP) is a complex pathological formation, containing numerous interacting cell types. Our understanding of the cellular composition and dynamics of AP is mainly based on the evaluation of a limited number of known markers and therefore may be incomplete and biased. Here we employ single cell transcriptomics (scRNAseq) to identify and define cell types in human plaques and to reconstruct their lineage trees and relationships.We have performed scRNAseq on atherosclerotic plaques obtained from 3 (discovery cohort) and 6 (validation cohort) carotid endarterectomy patients. We have employed the scRNAseq based on CEL-seq2/SORT-seq protocol coupled with fluorescence-activated cell sorting. This method allowed us to specifically select viable and nucleated single cells. Finally we have used RaceID and StemID algorithm to identify common and rare cell types and to perform the lineage tracing analysis.We have identified 15 different cell subtypes, among others endothelial cells (EC), macrophages and smooth muscle cells (SMC). Besides these major types we were able to detect less frequent cell populations - including ACKR1+ venular endothelial cells. Notably, we were able to find individual cells and cell clusters co-expressing both EC and SMC genes, such as SPARC, COL6A1, PECAM1 and CD34. These cells exhibited increased median transcriptome entropy and connectivity, relative to other EC and SMC clusters - altogether supporting their progenitor role and suggesting the plasticity of cell identity in AP.ScRNAseq enabled us to identify and define cell subtypes present in human AP. Our data suggest the cellular lineage plasticity in human AP.

To date, genome-wide association studies (GWAS) have identified hundreds of risk loci for coronary artery disease (CAD), and other cardiometabolic diseases and traits. However, identifying the key genes for atherosclerotic disease in these loci remains challenging. Here, we systematically mapped 14 GWAS and leveraged transcriptomics of advanced atherosclerotic plaques (AP) at a single-cell resolution.We isolated viable, nucleated single-cells from plaques of 3 carotid endarterectomy patients using enzymatic digestion and fluorescence-activated cell sorting. We applied a CEL-seq2/SORT-seq protocol and the Seurat pipeline for single-cell RNA sequencing (scRNAseq) and cell identification, respectively. Next we annotated public GWAS data of cardiovascular diseases, and cardiometabolic traits using FUMA, which is based on LD clumping, physical location, regulatory and transcriptomic data.Using scRNAseq we identified 11 cellular clusters in AP, and integrated these data to map 1,336 loci across 14 cardiometabolic GWAS. For CAD 105 mapped genes in 35 established loci were differentially expressed between cellular clusters. Some of these loci harboured upto 10 differentially expressed genes, highly expressed in endothelial cells, mast cells, and smooth muscle cells. Notably, some CAD genes are almost exclusively expressed in a specific cell: in the NOS3 locus, KCNH2 is highly expressed in mast cells, whereas NOS3 itself, but also AMPD2 (SORT1 locus) are highly expressed in endothelial cells.We systematically mapped and annotated risk loci, and integrated this at a single-cell resolution with transcriptomics from AP. We identified specific genes and cellular clusters relevant to atherosclerotic plaques development and progression, informative for future mechanistic studies.

Atherosclerotic lesions are known for their complex and diverse cellular heterogeneity, yet the exact cellular composition of human plaques remains unclear. Here we aim to provide a comprehensive overview of the cellular content of advanced atherosclerotic lesions using single-cell RNA sequencing (scRNAseq), to increase our understanding of the pathophysiologic processes underlying atherosclerosis.Advanced carotid plaques were obtained from 3 male endarterectomy patients. Plaques were enzymatically digested and live cells were sorted using FACS. Subsequently, we performed scRNAseq on a total of 3456 plaque derived cells.Unsupervised clustering revealed 11 distinct cell populations, including macrophages, CD4+and CD8+T-cells, B-cells, mast cells, endothelial cells, and smooth muscle cells. Interestingly, we were able to distinguish multiple subclusters for the smooth muscle cells, macrophages, and T-cells. We observed a contractile and synthetic smooth muscle cell cluster and three different macrophage clusters, including inflammatory, wound healing and antigen presenting macrophages. Finally, CD8+T-cells could be subdivided into three clusters based on their activation state, with a clear division between cytolytic effectors and quiescent memory CD8+T-cells. We developed a technique to perform scRNAseq on advanced human atherosclerotic lesions to unravel the cellular landscape within the plaques. We now provide, for the first time, an explicit expression profile of the different cells and their subtypes in atherosclerosis.

Atherosclerosis still is the primary cause of death worldwide. Our characterization of the atherosclerotic lesion is mainly rooted in definitions based on pathological descriptions. We often speak in absolutes regarding plaque phenotypes: vulnerable vs. stable plaques or plaque rupture vs. plaque erosion. By focusing on these concepts, we may have oversimplified the atherosclerotic disease and its mechanisms. The widely used definitions of pathology-based plaque phenotypes can be fine-tuned with observations made with various -omics techniques. Recent advancements in single-cell transcriptomics provide the opportunity to characterize the cellular composition of the atherosclerotic plaque. This additional layer of information facilitates the in-depth characterization of the atherosclerotic plaque. In this review, we discuss the impact that single-cell transcriptomics may exert on our current understanding of atherosclerosis.