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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 (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 38 samples Submitted 2025/12/12 Platform GPL24676Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 38 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
38 samples: 29 distinct titles, 1 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Multimodal analyses of early, untreated systemic sclerosis skin identify a proinflammatory vascular niche of macrophage-fibroblast signalingJCI insight · 2026
Summary (written by the submitters)
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.
Read the full summary ↓
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.
Published in
Multimodal analyses of early, untreated systemic sclerosis skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling
Jarnagin HC, Parvizi R, Gong Z et al. · JCI insight 2026 · PMID 41411065 · doi:10.1172/jci.insight.198954
This dataset
Open GSE312129 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE312129_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1372212 and SRA study SRP650465. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41411065) ↗
Study design
29 distinct titles, 1 of them repeated
Visium, SSc ×10

How we read this: Read from 38 sample titles: 29 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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