International journal of general medicine · 2026
Endothelial Cell Heterogeneity in Carotid Plaque Calcification: An Exploratory Single-Cell Transcriptomic Study with Proteomic Support.
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Zhou Yicong, Lin Dandan, Yan Yan, Zhao Minghan, Wang Xuelin, Lv Xin, Meng Chaoyue, Liu Xiaoyun
Аннотация
BACKGROUND: Carotid plaque calcification is an active multicellular process with heterogeneous clinical implications. However, endothelial cell (EC) heterogeneity and plaque-region-specific EC states associated with calcified lesions remain incompletely characterized.
METHODS: We performed an exploratory integrative analysis of the public single-cell RNA sequencing dataset GSE159677, comprising paired calcified core (AC) and proximal adjacent (PA) tissues from three patients, together with a single-center proteomic cohort of three additional patients with paired AC and PA samples. Major plaque cell populations and EC subclusters were identified by unsupervised clustering and canonical markers. Calcium signaling activity, pathway enrichment, ligand-receptor communication, and Monocle2 pseudotime trajectories were analyzed. Transcriptomic findings were compared with differentially expressed proteins to identify cross-omics candidate molecules.
RESULTS: A total of 35,890 cells were classified into seven major cell types. AC and PA tissues showed distinct cellular compositions and signaling patterns. Re-clustering of 4,925 ECs identified six subclusters, including a calcium signaling-high EC cluster enriched for extracellular matrix organization, inflammatory signaling, cytoskeletal regulation, and endothelial-to-mesenchymal transition-related programs. CellChat analysis indicated plaque-region-specific communication networks involving ECs, immune cells, fibroblasts, and smooth muscle cells. Pseudotime analysis suggested heterogeneous EC state transitions rather than a definitive longitudinal progression. Cross-omics comparison identified eight candidate molecules, FABP4, FABP5, MYL12A, POSTN, S100A10, SERPINB1, SOD2, and TMSB10, with concordant changes across transcriptomic and preliminary proteomic analyses.
CONCLUSION: These exploratory findings characterize plaque-region-specific EC heterogeneity associated with carotid plaque calcification and nominate candidate pathways and molecules for further validation in larger cohorts and functional models.
METHODS: We performed an exploratory integrative analysis of the public single-cell RNA sequencing dataset GSE159677, comprising paired calcified core (AC) and proximal adjacent (PA) tissues from three patients, together with a single-center proteomic cohort of three additional patients with paired AC and PA samples. Major plaque cell populations and EC subclusters were identified by unsupervised clustering and canonical markers. Calcium signaling activity, pathway enrichment, ligand-receptor communication, and Monocle2 pseudotime trajectories were analyzed. Transcriptomic findings were compared with differentially expressed proteins to identify cross-omics candidate molecules.
RESULTS: A total of 35,890 cells were classified into seven major cell types. AC and PA tissues showed distinct cellular compositions and signaling patterns. Re-clustering of 4,925 ECs identified six subclusters, including a calcium signaling-high EC cluster enriched for extracellular matrix organization, inflammatory signaling, cytoskeletal regulation, and endothelial-to-mesenchymal transition-related programs. CellChat analysis indicated plaque-region-specific communication networks involving ECs, immune cells, fibroblasts, and smooth muscle cells. Pseudotime analysis suggested heterogeneous EC state transitions rather than a definitive longitudinal progression. Cross-omics comparison identified eight candidate molecules, FABP4, FABP5, MYL12A, POSTN, S100A10, SERPINB1, SOD2, and TMSB10, with concordant changes across transcriptomic and preliminary proteomic analyses.
CONCLUSION: These exploratory findings characterize plaque-region-specific EC heterogeneity associated with carotid plaque calcification and nominate candidate pathways and molecules for further validation in larger cohorts and functional models.