Single-cell RNA-seq analysis of mouse carotid artery under disturbed flow and human carotid plaques identifies key cell populations in atherosclerosis development.

Atherosclerosis tends to occur in regions of disturbed blood flow. This study explored how disturbed flow aggravates atherosclerosis using single-cell RNA-seq (scRNA-seq) datasets from mouse carotid arteries under disturbed flow and human carotid artery plaques. The scRNA-seq datasets were obtained from the GEO (GSE159677, GSE43292, GSE163154, and GSE41571) and SRA (PRJNA722117) databases and were processed using Seurat. Functional enrichment analysis was conducted using Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO). Single-cell Flux Estimation Analysis (scFEA) was used to analyze cell type-specific changes in metabolism and "transcriptomic noise analysis" to examine senescence. GWAS-significant cardiovascular disease (CVD) risk genes were used to calculate risk gene scores for main cell populations. CellChat and Cytosig were used to analyze cell communication and cytokines. scRNA-seq identified seven cell clusters in mouse arteries: endothelial cells (ECs), vascular smooth muscle cells (VSMCs), fibroblasts, pericytes, macrophages, neutrophils, and T cells. Fibroblasts showed the most pronounced changes, particularly in inflammation and TGF-β signaling pathways. ECs, VSMCs, and fibroblasts had the highest enrichment of CVD risk gene scores, with fibroblasts showing most significant increases in gene risk scores after disturbed flow stimulation. A distinct fibroblast subgroup displayed high enrichment in inflammation and ossification-related pathways. CD36 + positive ECs exhibited significant senescence phenotypes following disturbed flow stimulation. Notable increases in VEGFA