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Inflammation and lymphocyte activation during longitudinal progression to rheumatoid arthritis in at-risk individuals

GSE274680 Homo sapiens (human) RNA-seq (gene expression) 243 samples Submitted 2025/09/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 243 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
243 samples: 243 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
Progression to rheumatoid arthritis in at-risk individuals is defined by systemic inflammation and by T and B cell dysregulationScience translational medicine · 2025
Summary (written by the submitters)
Rheumatoid Arthritis is a chronic immune-mediated disease characterized by joint inflammation, autoantibodies, and systemic inflammatory features. Autoantibodies, including anti-citrullinated protein antibodies are highly predictive biomarkers that pre-date clinical disease and can be used to identify individuals “at-risk” for RA. We performed a prospective, longitudinal multi omic study of at-risk individuals at multiple timepoints to characterize their immune state.
Read the full summary ↓
One-third of patients progressed to clinically active RA during the study. We show that at-risk RA subjects have systemic inflammation with features like those observed in active RA despite having no clinical disease. Progression to active disease was especially apparent in the T and B cells compartments, with pro-pathogenic features recognized in naive cells. We identify key molecular and cellular alterations in innate and adaptive immunity that accompany this inflammatory state.
Published in
Progression to rheumatoid arthritis in at-risk individuals is defined by systemic inflammation and by T and B cell dysregulation
He Z, Glass MC, Venkatesan P et al. · Science translational medicine 2025 · PMID 40991726 · doi:10.1126/scitranslmed.adt7214
This dataset
Open GSE274680 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 GSE274680_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1147649. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40991726) ↗
Study design
243 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 243 sample titles: 243 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

+ 203 more — browse all 243 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.