Microanatomy of the Human Atherosclerotic Plaque by Single-Cell Transcriptomics

These are the single-cell RNAseq data from the Athero-Express Biobank Study as used after quality control in the paper referenced below; below the abstract.
<br>
<br>
<b>Rationale</b></br>
Atherosclerotic lesions are known for their cellular heterogeneity, yet the molecular complexity within the cells of human plaques has not been fully assessed.</br></br>

<b>Objective</b></br>
Using single-cell transcriptomics and chromatin accessibility, we gained a better understanding of the pathophysiology underlying human atherosclerosis.</br></br>

<b>Methods and Results</b></br>
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.</br></br>

<b>Conclusions</b></br>
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.</br ></br></br >

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

We also made a <em>private</em> GitHub repository (<a href="https://github.com/CirculatoryHealth/AE_TEMPLATE_SCRNASEQ_DATA_SHARE" target="_blank">https://github.com/CirculatoryHealth/AE_TEMPLATE_SCRNASEQ_DATA_SHARE</a>) to enable easy sharing with third parties, publicly or privately.
</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>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.