Integrated single-cell atlas of human atherosclerotic plaques

Korbinian Traeuble, Matthias Munz, Jessica Pauli, Nadja Sachs, Eshan Vafadarnejad, Tania Carrillo-Roa, Lars Maegdefessel, Peter Kastner () and Matthias Heinig ()
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Korbinian Traeuble: Helmholtz Zentrum München
Matthias Munz: Discovery Sciences, Roche Diagnostics GmbH
Jessica Pauli: TUM University Hospital Rechts der Isar
Nadja Sachs: German Center for Cardiovascular Research, partner site Munich Heart Alliance
Eshan Vafadarnejad: Discovery Sciences, Roche Diagnostics GmbH
Tania Carrillo-Roa: Discovery Sciences, Roche Diagnostics GmbH
Lars Maegdefessel: TUM University Hospital Rechts der Isar
Peter Kastner: Discovery Sciences, Roche Diagnostics GmbH
Matthias Heinig: Helmholtz Zentrum München

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract Atherosclerosis, a major cause of cardiovascular diseases, is characterized by the buildup of lipids and chronic inflammation in the arteries, leading to plaque formation and potential rupture. Despite recent advances in single-cell transcriptomics (scRNA-seq), the underlying immune mechanisms and transformations in structural cells driving plaque progression remain incompletely defined. Existing datasets often lack comprehensive coverage and consistent annotations, limiting the utility of downstream analyses. Here, we present an integrated single-cell atlas of human atherosclerotic plaques, covering roughly 250k high-quality annotated cells. We achieve robust cell type annotations validated by expert consensus and surface protein measurements. Using this atlas, we introduce distinct markers for plaque neutrophils, identify a proangiogenic endothelial cell cluster enriched in advanced lesions, and specialized macrophage subsets. We also establish that fibromyocytes are exclusive to vascular tissue. This comprehensive atlas enables accurate automatic cell type annotation of new datasets, improves experimental design by guiding sample size and detection power, and supports the deconvolution of bulk RNA-seq data. An interactive WebUI makes these resources widely accessible.

Date: 2025
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DOI: 10.1038/s41467-025-63202-x

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