A multi-dataset single-cell meta-analysis of human keloid skin across Asian, Black and White populations reveals endothelial and mesenchymal programs linked to ethnic disparities
Abstract
Introduction Keloid is a fibroproliferative scar with marked ethnic disparities, disproportionately affecting Asian and Black populations. Single-cell RNA sequencing (scRNA-seq) studies have mapped keloid pathology, but cross-study differences complicate generalization. We performed a meta-analysis to identify composition and transcriptional programs associated with keloid across ethnicities. Methods We aggregated human skin scRNA-seq datasets containing keloid and healthy samples with documented ethnicity (Asian, Black, White). After quality control and batch integration (scVI/scANVI), we annotated cell types and subtypes. Differential abundance was estimated with scCODA, Milo, and propeller. Pseudobulk differential expression was meta-analyzed using random-effects models. Ligand-receptor signaling was inferred with CellChat/NicheNet. Results The harmonized atlas comprised 112 donors, 147 samples, and 487,293 cells from 8 studies. Keloid demonstrated higher proportions of vascular endothelial cells and fibroblasts across all methods. Ethnicity-stratified analysis revealed endothelial expansion in Asian and Black relative to White populations, while fibroblast expansion was greater in White keloids. Endothelial subtyping showed increased post-capillary venules and arteriolar states. Fibroblast analysis revealed expansion of mesenchymal/ADAM12+ and pro-inflammatory populations. Meta-analysis implicated TGF-β/SMAD, integrin/FAK, and YAP/TAZ mechanotransduction pathways as…
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