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

These are the single-cell RNAseq data from the Athero-Express Biobank Study as used after quality control in the paper referenced below; abstract below.</br></br>

<b>Background</b></br>
Genome-wide association studies (GWAS) 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 identification of candidate genes. However, the assayed tissues are often non-diseased and heterogeneous in cell composition confounding the candidate prioritization. We collected single-cell transcriptomics (scRNA-seq) from atherosclerotic plaques and aimed to identify cell-type-specific expression of disease-associated genes.</br ></br >

<b>Methods and Results</b></br>
To identify disease-associated candidate genes, we applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic, cardiometabolic, and other traits. Next we intersected these candidates with single-cell transcriptomics (scRNA-seq) to identify those genes that are specifically expressed in individual cell (sub)populations of atherosclerotic plaques. We derive an enrichment score and show that loci that associated with coronary artery disease demonstrated a prominent substrate in plaque smooth muscle cells (SKI, KANK2, SORT1), endothelial cells (SLC44A1, ATP2B1), and macrophages (APOE, HNRNPUL1). Further sub clustering of SMC-subtypes revealed genes in risk loci for coronary calcification specifically enriched in a synthetic cluster of SMCs. To verify the robustness of our approach, we used liver-derived scRNAseq-data and showed enrichment of circulating lipids-associated loci in hepatocytes.</br ></br>

<b>Conclusion</b></br>
We confirm known gene-cell pairs relevant for atherosclerotic disease, and discovered novel pairs pointing to new biological mechanisms amenable for therapy. 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.</br></br>

<strong>Athero-Express Biobank Study</strong></br>
The AE started in 2002 and now includes over 3,500 patients who underwent surgery to remove atherosclerotic plaques (endarterectomy) from one (or more) of their major arteries (majority carotids and femorals); this is further described <a href="https://doi.org/10.34894/4IKE3T" target="_blank">here</a>. The study design and staining protocols are described by <a href="https://pubmed.ncbi.nlm.nih.gov/15678794/" target="_blank">Verhoeven <em>et al.</em></a>.</br></br>

<b>GitHub</b></br>
A link to the public GitHub repository: <a href="https://github.com/CirculatoryHealth/gwas2single" target="_blank">https://github.com/CirculatoryHealth/gwas2single</a>. This contains all scripts used for the data, which is pseudonymized and shared here.</br></br>

<b>Additional data</b></br>
Additional clinical data is available upon discussion and signing a Data Sharing Agreement (see Terms of Access).</br></br>

<b>PlaqView</b></br>
In collaboration with the <a href="http://millerlab.org" target="_blank">http://millerlab.org</a> from the University of Virginia (USA) we created <a href="https://www.plaqview.com" target="_blank">PlaqView.com</a>. You can query any gene of interest in many carotid-plaque datasets, including ours. From our experience we know that usually this suffices most research questions and prevents the lengthy process of obtaining these data through a DSA.