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Single-nuclei multiome and spatial analyses of early, untreated SSc skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling

GSE312129 Homo sapiens Expression profiling by high throughput sequencing; Other; Genome binding/occupancy profiling by high throughput sequencing 38 samples 2025/12/12 GPL24676GPL30173
Summary
Uncovering the early interactions and spatial distribution of dermal fibroblasts and immune cells in treatment-naïve diffuse cutaneous systemic sclerosis (dcSSc) patients is critical to understanding the initiating events skin fibrosis. We generated an integrated multiomic dataset of early, treatment naïve dcSSc skin. Skin biopsies were analyzed by single-nuclei multiome sequencing (snRNA-seq and snATAC-seq) and two different paired spatial transcriptomic platforms to comprehensively describe the molecular changes in these individuals. We identified a proinflammatory niche within papillary, hypodermis, and vascular niches, that are enriched for activated myeloid cells and proinflammatory fibroblasts characterized by expression of proinflammatory cytokines. Pathway analyses showed significant enrichment of PI3K-AKT-mTOR signaling pathway expression in these cellular niches, driven by profibrotic growth factor signaling networks. Macrophage subclustering showed SSc-specific macrophage activation of IL6-JAK-STAT signaling and the enrichment of oxidative phosphorylation pathways. Ligand-receptor analysis revealed that SSc macrophages secrete PDGF and TGFB to activate the inflammatory SSc-dominant fibroblast subclusters. Spatial transcriptomic analyses showed infiltrating macrophages secreted PDGF and TGFB, modulating fibroblast activation in these niches. Multiomic data integration and spatial transcriptomic neighborhood analysis showed co-localization of fibroblasts, macrophages, and T cells around the vasculature. These data suggest that interactions between activated immune cells and proinflammatory fibroblasts around vascular niches are an early event in scleroderma pathogenesis.
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NCBI GEO page ↗ Paper (PMID 41411065) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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