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Irisin improves obesity and glucose intolerance through an IL-33-ST2 pathway

GSE283234 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2025/12/05 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 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
Mus musculus (mouse)
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Irisin is secreted by muscle, increased with exercise, and conveys certain physiological benefits. Earlier studies showed that short-term irisin treatment caused browning of subcutaneous adipose tissue (SAT) in mice, with improved glucose tolerance; the effects of more chronic irisin treatment and mechanisms at play have not been explored.
Read the full summary ↓
We demonstrate here that chronic irisin application improves obesity and dramatically reduces glucose intolerance. This treatment increases an IL-33+ mesenchymal stromal cell (mSC) population in visceral fat tissue while genetic ablation of irisin reduces plasma IL-33 levels and decreases thermogenic gene expression in SAT. Importantly, irisin directly induces IL-33 expression in mSCs and preserves ST2+ regulatory T (Treg) cells. Inhibition of IL-33 blunts these irisin-mediated effects on energy expenditure and glucose homeostasis, largely through IL33-mediated regulation of ST2+ Treg cells. These data indicate that irisin improves obesity and glucose intolerance, with no muscle loss, through a key immunomodulatory pathway in obese mice.
This dataset
Open GSE283234 in finder → Find more mouse 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 GSE283234_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 PRJNA1192701 and SRA study SRP548574. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
eWATgfpCHW ×3 eWATgfpHFD ×3 eWATirCHW ×3 eWATirHFD ×3 iWATgfpCHW ×3 iWATgfpHFD ×3 iWATirCHW ×3 iWATirHFD ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 of them. 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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