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Interferons are the key cytokines acting on pancreatic islets in type 1 diabetes

GSE235683 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/01/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 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
Interferons are key cytokines acting on pancreatic islets in type 1 diabetesDiabetologia · 2024
Summary (written by the submitters)
The pro-inflammatory cytokines IFNα, IFNγ, IL-1β and TNFα may contribute to innate and adaptive immune responses during islet inflammation (insulitis) in type 1 diabetes (T1D). We used deep RNA-sequencing analysis to characterize the response of human pancreatic beta cells to each cytokine individually and compared the signatures obtained with those present in islets of individuals affected by T1D.
Read the full summary ↓
IFNα and IFNγ had a much greater impact on the beta cell transcriptome when compared to IL-1β and TNFα. The IFN-induced gene signatures have a strong correlation with those observed in beta cells from T1D patients, and the level of expression of specific IFN-stimulated genes is positively correlated with proteins present in islets of these individuals, regulating beta cell responses to “danger signals” such as viral infections. These data suggest that IFNα and IFNγ are the central cytokines at the islet level in T1D, contributing to the triggering and amplification of autoimmunity.
Published in
Interferons are key cytokines acting on pancreatic islets in type 1 diabetes
Coomans de Brachène A, Alvelos MI, Szymczak F et al. · Diabetologia 2024 · PMID 38409439 · doi:10.1007/s00125-024-06106-7
This dataset
Open GSE235683 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 GSE235683_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 PRJNA986896 and SRA study SRP445597. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38409439) ↗
Study design
18 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 18 sample titles: 18 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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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.