AtherosclerosisGenomicsPeer-reviewed journal article
Single-Cell RNA-Seq Reveals Adventitial Fibroblast Alterations during Mouse Atherosclerosis
Lauren E. FriesiD, Allen Y. ChungiD, Hyun-Kyung ChangiD, Timothy L. YuaniD, Robert C. BaueriD
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- top 23%
Abstract
BackgroundAtherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality in the western world despite the success of lipid lowering therapies, highlighting the need for novel lipid-independent therapeutic strategies. Genome-wide association studies (GWAS) have identified numerous genes associated with ASCVD that function in the vessel wall, suggesting that vascular cells mediate ASCVD, and that the genes and pathways essential for this vascular cell function may be novel therapeutic targets for the treatment of ASCVD. Furthermore, some of these implicated genes appear to function in the adventitial layer of the vasculature, suggesting these cells are able to potentiate ASCVD. MethodsTo investigate the role of adventitial cells in atherosclerosis, we conducted single-cell RNA sequencing (scRNA-seq) of the aortic adventitia during atherogenesis in male Ldlr-/- mice via pools of three mice, two samples per condition. We cross-referenced the scRNA-seq data with human ASCVD GWAS to identify regulators of adventitial responses in ASCVD. These regulators were then validated in vitro in human adventitial fibroblasts. ResultsWe identified four adventitial fibroblast populations, all of which displayed shifts in population size and gene expression over the course of atherogenesis. SERPINH1, an ASCVD-linked GWAS gene, was differentially expressed in adventitial fibroblasts during atherogenesis. Knockdown of SERPINH1 in vitro reduced fibroblast migration and altered subcluster marker gene expression. ConclusionsThese findings reveal dynamic changes in adventitial fibroblasts during atherosclerosis and suggest that reduced SERPINH1 expression disrupts adventitial fibroblast function, contributing to ASCVD progression.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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