GWAS to single cell: Intersecting single-cell transcriptomics and genome wide association studies identifies crucial cell-populations and candidate genes for atherosclerosis.
This readme accompanies the paper "GWAS to single cell: Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis." by Slenders L. et al. European Heart Journal Open 2022.
Background
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.
Methods and Results
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.
Conclusion
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.
You can load this project in RStudio by opening the file called 'gwas2single.Rproj'.
| File | Description | Usage |
|---|---|---|
| README.md | Description of project | Human editable |
| gwas2single.Rproj | Project file | Loads project |
| LICENSE | User permissions | Read only |
| .worcs | WORCS metadata YAML | Read only |
| prepare_data.R | Script to process raw data | Human editable |
| renv.lock | Reproducible R environment | Read only |
The data associated with this project is public and references are available in the paper. The original single-cell RNA sequencing data from the Athero-Express is available through DataverseNL. The remaining summary results and parsed data will be deposited on Zenodo under 10.5281/zenodo.4823040.
This project uses the Workflow for Open Reproducible Code in Science (WORCS) to ensure transparency and reproducibility. The workflow is designed to meet the principles of Open Science throughout a research project.
To learn how WORCS helps researchers meet the TOP-guidelines and FAIR principles, read the preprint at https://osf.io/zcvbs/
- To get started with
worcs, see the setup vignette - For detailed information about the steps of the WORCS workflow, see the workflow vignette
Please refer to the vignette on reproducing a WORCS project for step by step advice.
Dr. Sander W. van der Laan is funded through grants from the Netherlands CardioVascular Research Initiative of the Netherlands Heart Foundation (CVON 2011/B019 and CVON 2017-20: Generating the best evidence-based pharmaceutical targets for atherosclerosis [GENIUS I&II]). We are thankful for the support of the ERA-CVD program ‘druggable-MI-targets’ (grant number: 01KL1802), the EU H2020 TO_AITION (grant number: 848146), and the Leducq Fondation ‘PlaqOmics’.
Plaque samples are derived from carotid endarterectomies as part of the Athero-Express Biobank Study which is an ongoing study in the UMC Utrecht.
The framework was based on the WORCS package.
_Version:_ v1.0.3</br>
_Last update:_ 2022-04-20</br>
_Written by:_ Sander W. van der Laan (s.w.vanderlaan-2[at]umcutrecht.nl).
* v1.0.3 Update to DataverseNL link.
* v1.0.2 Linking of Zenodo data repository.
* v1.0.1 Zenodo release.
* v1.0.0 Initial version.
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