Key points are not available for this paper at this time.
BACKGROUND: Carotid artery stenosis (CAS) is a major cause of ischemic stroke, yet reliable molecular biomarkers for early identification remain limited. METHODS: We integrated single-cell RNA sequencing (scRNA-seq), bulk transcriptomics, and in-house multi-omics data, applying WGCNA and machine learning to identify endothelial cell-derived diagnostic biomarkers, validated across independent GEO and ZZ cohorts at single-cell, transcriptomic, and proteomic levels. RESULTS: scRNA-seq identified endothelial enrichment in CAS and yielded 836 markers. Integrative analysis (DEGs + WGCNA) defined 80 candidates, with NRP1 and XAF1 selected by machine learning. Both were consistently upregulated and validated across multi-omics datasets, showing strong diagnostic performance. CONCLUSION: NRP1 and XAF1 represent novel endothelial cell-derived biomarkers with potential utility for early CAS screening and clinical diagnosis.
Wu et al. (Mon,) studied this question.