Replication Data for: "Single-cell T-cell Receptor sequencing of paired human atherosclerotic plaques and blood reveals autoimmune-like features of expanded effector T-cells."

DOI

These are the single-cell TCR sequencing (scTCRseq) on human carotid artery plaques from the Athero-Express Biobank Study as used after quality control in the paper referenced below; below the abstract.

Abstract We applied single-cell TCR sequencing (scTCRseq) on human carotid artery plaques and patient matched PBMC samples to assess the extent of TCR clonality and antigen specific activation within the various T-cell subsets on 3 patients, and applied bulk CDR3b sequencing of matched PBMC and plaque material of 10 patients. CellChat was used to analyze potential interactions of effector CD4+ T-cells with foam cells in the plaque. Finally, we integrated a published scTCRseq dataset of the autoimmune disease psoriatic arthritis to assess commonalities and differences between the two diseases. In this repository we provide the raw atherosclerosis TCRseq data, the bulk sequencing data, and the code that was used for the analysis of the data.

GitHub A link to the public GitHub repository: link. This contains all scripts used for the data, which is pseudonymized and shared here.

Athero-Express Biobank Study 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 here. The study design and staining protocols are described by Verhoeven et al.

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

PlaqView Please note, that we will also integrate these data through PlaqView, but they are not available yet.In collaboration with the http://millerlab.org from the University of Virginia (USA) we created PlaqView.com. 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.

Identifier
DOI https://doi.org/10.34894/DDYKLL
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/DDYKLL
Provenance
Creator Sander W. van der Laan ORCID logo; Marie A.C. Depuydt ORCID logo; Frank H. Schaftenaar; Bram Slütter ORCID logo; Menno P.J. de Winther ORCID logo
Publisher DataverseNL
Contributor dLAB data management; Sander W. van der Laan; Bram Slütter; Menno P.J. de Winther
Publication Year 2022
Rights info:eu-repo/semantics/closedAccess
OpenAccess false
Contact dLAB data management (UMC Utrecht); Sander W. van der Laan (UMC Utrecht); Bram Slütter (Leiden Academic Centre for Drug Research, Division of Biotherapeutics, Leiden University); Menno P.J. de Winther (Amsterdam University Medical Centers-Location AMC, University of Amsterdam, Experimental Vascular Biology, Department of Medical Biochemistry, Amsterdam Cardiovascular Sciences, Amsterdam Infection and Immunity)
Representation
Resource Type Dataset
Format application/pdf; application/msword; application/gzip; application/vnd.openxmlformats-officedocument.spreadsheetml.sheet; text/csv; text/plain
Size 61663; 64158; 34816; 10287; 37031; 13877; 41124; 12450; 20500; 48150; 47353; 48608; 10506; 41514; 20194; 1671102; 333437; 333529; 10066180; 1687919; 9347399; 974482; 7380321; 2318690; 12351507; 58983852; 53480203; 68011672; 28370652; 12243735; 10274435; 28160914; 47906114; 10911808; 53305969; 68176837; 4646; 1805
Version 1.0
Discipline Life Sciences; Medicine