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Very long-chain ceramides in skeletal muscle associate with systemic insulin resistance independent of obesity

GSE290031 Mus musculus (mouse) RNA-seq (gene expression) 92 samples Submitted 2025/08/06 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 92 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
92 samples
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
Muscle very long-chain ceramides associate with insulin resistance independently of obesityMolecular metabolism · 2025
Summary (written by the submitters)
Lipids are bioactive signaling molecules implicated in tissue-specific and whole-body insulin resistance, with ceramides and diacylglycerols (DAGs) as prominent species. Their precise roles remain unclear. Here, we leverage natural genetic variation in 399 male Diversity Outbred Australia (DOz) mice fed chow or a high-fat diet to examine the relationship between muscle lipids and insulin sensitivity.
Read the full summary ↓
Fat mass was significantly associated with 55% of muscle lipid features and whole-body insulin sensitivity, with DAGs enriched in this association. To disentangle adiposity and muscle lipid contributions, we used: (1) linear models correcting lipid features for fat mass, and (2) insulin sensitivity quartiles within adiposity bins. Both approaches identified very long-chain ceramides, not DAGs, as linked to insulin resistance. RNA sequencing and proteomics from the same muscles associated these ceramides with cellular stress, mitochondrial dysfunction, and protein synthesis regulation. Meanwhile, DAGs correlated with leptin gene expression, suggesting an adipocyte, rather than myocyte, origin. These findings highlight very long-chain ceramides as key muscle lipids associated with insulin resistance, independent of adiposity.
Published in
Muscle very long-chain ceramides associate with insulin resistance independently of obesity
Madsen S, Cutler HB, Cooke KC et al. · Molecular metabolism 2025 · PMID 40653086 · doi:10.1016/j.molmet.2025.102212
This dataset
Open GSE290031 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 GSE290031_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 PRJNA1225791 and SRA study SRP565115. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40653086) ↗
Study design
A cohort of 92 individual samples

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

How we read this: Sample titles run Geniad56 … Geniad117 and carry no group information.

Samples in this study

+ 52 more — browse all 92 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.