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, Matthias Heinig
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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. The underlying causal immune mechanisms and alterations in structural cell composition and plasticity driving plaque progression remain incompletely defined. Recent advances in single-cell transcriptomics (scRNA-seq) have provided deeper insights into the roles of immune and non-immune cells in atherosclerosis. However, existing public scRNA-seq datasets often lack comprehensive cell type coverage and consistent annotations, posing challenges for downstream analyses. In this study, we present an integrated single-cell atlas of human atherosclerotic plaques, encompassing 261,747 high-quality annotated cells from carotid, coronary, and femoral arteries. By benchmarking and applying the best-performing data integration method, scPoli, we achieved robust cell type annotations validated by expert consensus and surface protein measurements. This comprehensive atlas enables accurate automatic cell type annotation of new datasets, optimal experimental design, and deconvolution of existing as well as novel bulk RNA-seq data to comprehensively determine cell type proportions in human atherosclerotic lesions. It facilitates future studies by providing an interactive WebUI for easy data annotation and experimental design, while supporting various downstream applications, including integration of genetic association studies and experimental planning.
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人类动脉粥样硬化斑块的综合单细胞图谱
动脉粥样硬化是心血管疾病的主要病因,其特征是动脉中脂类和慢性炎症的堆积,导致斑块形成和潜在破裂。驱动斑块发展的潜在因果免疫机制和结构细胞组成及可塑性的改变仍未完全明确。单细胞转录组学(scRNA-seq)的最新进展使人们对免疫和非免疫细胞在动脉粥样硬化中的作用有了更深入的了解。然而,现有的公共 scRNA-seq 数据集往往缺乏全面的细胞类型覆盖和一致的注释,给下游分析带来了挑战。在本研究中,我们展示了人类动脉粥样硬化斑块的综合单细胞图谱,包括来自颈动脉、冠状动脉和股动脉的 261,747 个高质量注释细胞。通过基准测试和应用性能最佳的数据整合方法 scPoli,我们实现了经专家共识和表面蛋白测量验证的强大细胞类型注释。该综合图谱能对新数据集进行准确的自动细胞类型注释、优化实验设计、对现有和新的大量 RNA-seq 数据进行解卷积,从而全面确定人类动脉粥样硬化病变中的细胞类型比例。它提供了一个交互式 WebUI,便于数据注释和实验设计,同时支持各种下游应用,包括整合遗传关联研究和实验计划,从而为未来的研究提供了便利。
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