Replication Data for: Transcriptomic-based clustering of human atherosclerotic plaques identifies subgroups with different underlying biology and clinical presentation

DOI

Background These data are used in this paper by Mokry et al. Abstract Histopathological studies have revealed key processes of atherosclerotic plaque thrombosis. However, the diversity and complexity of lesion types highlight the need for improved sub-phenotyping. Here we analyze the gene expression profiles of 654 advanced human carotid plaques. The unsupervised, transcriptome-driven clustering revealed five dominant plaque types. These plaque phenotypes were associated with clinical presentation and showed differences in cellular compositions. Validation in coronary segments showed that the molecular signature of these plaques was linked to coronary ischemia. One of the plaque types with the most severe clinical symptoms pointed to both inflammatory and fibrotic cell lineages. This highlighted plaque phenotype showed high expression of genes involved in active inflammatory processes, neutrophil degranulation, matrix turnover, and metabolism. Further, we did a preliminary analysis of potential circulating biomarkers that mark the different plaques phenotypes. In conclusion, the definition of the plaque at risk for a thrombotic event can be fine-tuned by in-depth transcriptomic-based phenotyping. These differential plaque phenotypes prove clinically relevant for both carotid and coronary artery plaques and point to distinct underlying biology of symptomatic lesions.

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..

A link to the public GitHub repository can be found here: https://github.com/CirculatoryHealth/PlaqueCluster.

Important notice on availability of data The data are sensitive since they involve personal information of patients. There are also restrictions on use by commercial parties, and on sharing openly based on (inter)national laws and regulations and the written informed consent. Therefore these data (and additional clinical data) are only available upon discussion and signing a Data Sharing Agreement (see Terms of Access) and within a specially designed UMC Utrecht provided environment.

Identifier
DOI https://doi.org/10.34894/D1MDKL
Related Identifier https://doi.org/10.1101/2021.11.25.21266855
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/D1MDKL
Provenance
Creator Michal Mokry ORCID logo; Sander W. van der Laan ORCID logo; Gerard Pasterkamp
Publisher DataverseNL
Contributor dLAB Datamanagement; Michal Mokry; Sander W. van der Laan
Publication Year 2022
Rights info:eu-repo/semantics/closedAccess
OpenAccess false
Contact dLAB Datamanagement (UMC Utrecht); Michal Mokry (UMC Utrecht); Sander W. van der Laan (UMC Utrecht)
Representation
Resource Type Dataset
Format application/pdf; application/msword; text/plain
Size 61663; 64158; 34816; 3186
Version 2.0
Discipline Life Sciences; Medicine