Search

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.

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.

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.