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10.1172/jci.insight.198954
1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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Xing, X.
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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Tsoi, L.
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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Bogle, R.
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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Khanna, D.
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1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, United States of America
2Department of Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, United States of America
3Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, United States of America
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Published December 18, 2025 - More info
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 earliest events of 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 spatial transcriptomic methods to comprehensively determine the molecular changes in these individuals. We identified an immunomodulatory niche within the papillary, hypodermis, and vascular regions that are enriched for activated myeloid cells and fibroblasts characterized by expression of genes such as CXCL12, APOE, and C7. 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 the IL6-JAK-STAT signaling and the enrichment of oxidative phosphorylation pathways. Ligand-receptor analysis revealed that SSc macrophages secrete PDGF and TGF-β to activate the SSc-dominant fibroblast subclusters. Spatial transcriptomic analyses showed monocyte-derived MRC1+ macrophages express PDGF near PDGFRhighTHY1high fibroblasts. Multi-omic data integration and spatial transcriptomic neighborhood analysis revealed the co-localization of fibroblasts, macrophages, and T cells around the vasculature. These data suggest that interactions between activated immune cells and immunomodulatory fibroblasts around vascular niches are an early event in scleroderma pathogenesis.