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

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

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.

Datasets10
Size~335 MB
AssayVisium
Samplehuman · zone of skin
KindOther
Flag a data issue
PMID:41411065 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse312129")
cohort.members        # the 10 datasets as a table

print(cohort.licenses())              # check the terms before you download

sdatas = cohort.to_dict()             # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")
Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse312129")
coll.ordered_artifacts.to_dataframe()   # the 10 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse312129 --dest data/

Licenses: 10 CC BY 4.0

Open in Vitessce
Visium
Human zone of skin
GSM9338174
human zone of skin systemic sclerosis 36.8 MB H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size36.8 MB
H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338173
human zone of skin systemic sclerosis 31.7 MB 4,890 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size31.7 MB
Spots4,890
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338175
human zone of skin systemic sclerosis 35.2 MB 4,833 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size35.2 MB
Spots4,833
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338176
human zone of skin systemic sclerosis 31.9 MB 4,957 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size31.9 MB
Spots4,957
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338178
human zone of skin systemic sclerosis 29.2 MB 4,453 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size29.2 MB
Spots4,453
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338172
human zone of skin systemic sclerosis 34.9 MB 4,925 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size34.9 MB
Spots4,925
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338179
human zone of skin systemic sclerosis 30.1 MB 4,950 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size30.1 MB
Spots4,950
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338171
human zone of skin systemic sclerosis 31.3 MB 4,381 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size31.3 MB
Spots4,381
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338180
human zone of skin systemic sclerosis 37.1 MB 4,541 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size37.1 MB
Spots4,541
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human zone of skin
GSM9338177
human zone of skin systemic sclerosis 36.4 MB 4,899 spots silver H&E
TechnologyVisium
Organismhuman
Tissuezone of skin
Conditionsystemic sclerosis
Size36.4 MB
Spots4,899
silver H&E Open in Vitessce

Cite this collection

doi.org/10.1172/jci.insight.198954 ↗
BibTeX
@article{Jarnagin_2025,
  title = {Multimodal analyses of early, untreated systemic sclerosis skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling},
  volume = {11},
  ISSN = {2379-3708},
  url = {http://dx.doi.org/10.1172/jci.insight.198954},
  DOI = {10.1172/jci.insight.198954},
  number = {3},
  journal = {JCI Insight},
  publisher = {American Society for Clinical Investigation},
  author = {Jarnagin, Helen C. and Parvizi, Rezvan and Gong, Zhiyun and Gedert, Rosemary and Xing, Xianying and Tsoi, Lam (Alex) C. and Bogle, Rachael and Morrisson, Madeline J. and Perreard, Laurent and Pioli, Patricia A. and Kolling, Fred and Gudjonsson, Johann E. and Khanna, Dinesh and Whitfield, Michael L.},
  year = {2025},
  month = Dec
}