GEO series

Positive feedback between cDC1s and CD8+ T cells typifies the inflammation of HLA-B27+ arthritis

GSE213095 Homo sapiens (human) Single-cell RNA-seq 46 samples Submitted 2026/02/22 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 46 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 46 samples: 46 samples, each with a distinct title — no replicated groupsGroups 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: XCR1(+) Conventional Type 1 Dendritic Cells Exacerbate the Inflammation in Osteogenic Arthritis Through IL-17A(+)CD8(+) T CellsArthritis & rheumatology (Hoboken, N.J.) · 2026

Summary (written by the submitters)

Enthesitis-related arthritis (ERA) is a subtype of juvenile idiopathic arthritis (JIA) with enthesitis and sacroiliitis, which differ from other types of JIA in symptoms, pathogenesis, and outcome. Although the association of human leukocyte antigen-B27 (HLA-B27) with ERA has been confirmed for decades, the pathogenesis of ERA is poorly understood.

Read the full summary ↓

Here, we performed single-cell RNA-seq of 1,73,134 mononuclear cells extricated from patients with oligoarthritis (OligoA) or ERA and integrated 58,725 PBMCs of healthy people to profile the immune characteristic that discriminates ERA from OligoA. We found that conventional type 1 dendritic cells (cDC1s) were enriched in the joints of patients with ERA and exhibited a high level of MHC class I antigen presentation. Central memory CD8+ T cells critically contributed to the elevation of XCL1, recruiting XCR1+ cDC1 in joints of ERA. Flow cytometry and enzyme-linked immunosorbent assay (ELISA) analyses confirmed an increased proportion and interaction of cDC1s and CD8+ T cells. In addition, macrophages occupied the causal position in the pathogenesis of OligoA, along with high expression of MHC class II molecules on macrophages and cDC2s in the joints. This study suggests that the positive feedback between cDC1s and CD8+ T cells is a key mediator of HLA-B27-positive arthritis pathogenesis.

Published in

XCR1(+) Conventional Type 1 Dendritic Cells Exacerbate the Inflammation in Osteogenic Arthritis Through IL-17A(+)CD8(+) T Cells

Shao F, Zhang S, Wu Z et al. · Arthritis & rheumatology (Hoboken, N.J.) 2026 · PMID 41640334 · doi:10.1002/art.70069

This dataset

Open GSE213095 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 GSE213095_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA879087. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41640334) ↗

Study design

46 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 46 sample titles: 46 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

GSM6571551 JIA-OligoA-1-PBMC 5'
GSM6571552 JIA-OligoA-1-SFMC 5'
GSM6571553 JIA-OligoA-2-PBMC 5'
GSM6571554 JIA-OligoA-2-SFMC 5'
GSM6571555 JIA-OligoA-3-PBMC 5'
GSM6571556 JIA-OligoA-4-PBMC 5'
GSM6571557 JIA-OligoA-4-SFMC 5'
GSM6571558 JIA-OligoA-5-PBMC 5'
GSM6571559 JIA-OligoA-5-SFMC 5'
GSM6571560 JIA-OligoA-6-PBMC 5'
GSM6571561 JIA-OligoA-6-SFMC 5'
GSM6571562 JIA-OligoA-6.1-SFMC 5'
GSM6571563 JIA-OligoA-7-PBMC 5'
GSM6571564 JIA-OligoA-7-SFMC 5'
GSM6571565 JIA-ERA-1-PBMC 5'
GSM6571566 JIA-ERA-1-SFMC 5'
GSM6571567 JIA-ERA-2-PBMC 5'
GSM6571568 JIA-ERA-2-SFMC 5'
GSM6571569 JIA-ERA-3-PBMC 5'
GSM6571570 JIA-ERA-3-SFMC 5'
GSM6571571 JIA-ERA-4-PBMC 5'
GSM6571572 JIA-ERA-4-SFMC 5'
GSM6571573 JIA-ERA-5-PBMC 5'
GSM6571574 JIA-OligoA-1-PBMC TCR
GSM6571575 JIA-OligoA-1-SFMC TCR
GSM6571576 JIA-OligoA-2-PBMC TCR
GSM6571577 JIA-OligoA-2-SFMC TCR
GSM6571578 JIA-OligoA-3-PBMC TCR
GSM6571579 JIA-OligoA-4-PBMC TCR
GSM6571580 JIA-OligoA-4-SFMC TCR
GSM6571581 JIA-OligoA-5-PBMC TCR
GSM6571582 JIA-OligoA-5-SFMC TCR
GSM6571583 JIA-OligoA-6-PBMC TCR
GSM6571584 JIA-OligoA-6-SFMC TCR
GSM6571585 JIA-OligoA-6.1-SFMC TCR
GSM6571586 JIA-OligoA-7-PBMC TCR
GSM6571587 JIA-OligoA-7-SFMC TCR
GSM6571588 JIA-ERA-1-PBMC TCR
GSM6571589 JIA-ERA-1-SFMC TCR
GSM6571590 JIA-ERA-2-PBMC TCR

+ 6 more — browse all 46 samples with per-sample file links →

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