Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis

Abstract

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

Dissecting the polygenic basis of atherosclerosis using disease associated cell state signatures

“…Importantly, the genetic variation in the Vcam1+ SMCs and Col2a1+ SMCs contributed to CAD heritability beyond other cell states, suggesting that these cell states are particularly important in understanding the pathobiology of atherosclerosis. This is also supported by other recent studies looking into the cell type specific expression of predicted GWAS target genes 45,46 . Substantial ongoing efforts are looking into applying CAD PRS in the clinical practice including risk prediction, patient stratification and treatment response.…”

TXNIP Suppresses the Osteochondrogenic Switch of Vascular Smooth Muscle Cells in Atherosclerosis

“…In order to determine the relevance of the obtained mouse experimental data to human diseases, we first determined whether modulated VSMC and osteochondrogenic populations exist in human atherosclerotic lesions. To this end, we obtained VSMCs and fibroblast-like cells from scRNA-seq data from a total of 48 patient samples across 4 previous studies (GSE155512, 14 n =3; GSE159677, 23 n =3; GSE131780, 29 n =4; Slenders et al, 35 n =38) and then integrated them with WT mice scRNA-seq data ( Figure S9A through S9H ). Joint clustering showed that, in accordance with previous reports, 14 – 16 both modulated VSMC (cluster 0) and osteochondrogenic populations (cluster 6) also exist in human atherosclerotic lesions ( Figure S9D ).…”

Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis

“…Our granular SMC annotations were also critical to define etiologic SMC phenotypes for cardiovascular diseases and traits. Previous work from our group and others [93][94][95] has established a substantial contribution of SMCs towards CAD risk. By leveraging larger cell numbers, we further separated the SMC signal to prioritize fibromyocytes and foam-like SMCs underlying cardiovascular diseases.…”