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High protein intake causes gene-length-dependent transcriptional decline, shortens lifespan and accelerates ageing in progeroid DNA repair‐deficient mice

GSE293207 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/05/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × Ercc1 d/- AIN93G control # vs 4 × Ercc1 d/- low protein - high carb # vs 4 × Ercc1 d/- low carbohydrate - high protein # vs 4 × Ercc1 d/- low fat - high carb #Groups 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
High protein intake causes gene-length-dependent transcriptional decline, shortens lifespan and accelerates ageing in progeroid DNA repair-deficient micenpj metabolic health and disease · 2025
Summary (written by the submitters)
Dietary composition can significantly influence health and lifespan, however, robust knowledge on which food components, at what concentration exert which long-term health effects is still incomplete. Here, we explored the effects of dietary protein intake on Ercc1Δ/- DNA-repair-deficient mice, which are an excellent model for accelerated ageing and are hyperresponsive to the anti-ageing effect of dietary restriction.
Read the full summary ↓
Restricting dietary protein by 50% extended lifespan in male mice, but not in females. Restricting protein levels beyond 80% improved various neurological health parameters, while a further reduction to 95% affected appetite and became distinctly detrimental. Conversely, a near doubling of protein intake and isocaloric compensatory lowering with carbohydrates significantly shortened lifespan in both sexes. Gene expression analysis of liver from mice on a high-protein, low-carbohydrate diet to those on high-carbohydrate, low-protein revealed increased expression of oxidative phosphorylation, enrichment of processes associated with tissue injury, inflammation, and gene-length-dependent transcriptional decline (GLTD), recently shown to be indicative of DNA damage accumulation causing transcription stress, and cellular ageing. Finally, GLTD was also identified by reanalysis of publicly available data of wild-type mice, rats and humans on high-protein diets, suggesting that increased dietary protein enhances GLTD and accelerates systemic ageing. Together, our findings have implications for nutritional guidelines for progeroid DNA-repair-deficient human syndromes, caution against excessive protein intake in the context of sustaining health, and suggest GLTD as a sensitive read-out of overall health and a predictor of biological ageing.
Published in
High protein intake causes gene-length-dependent transcriptional decline, shortens lifespan and accelerates ageing in progeroid DNA repair-deficient mice
van Galen I, Birkisdóttir MB, Ozinga RA et al. · npj metabolic health and disease 2025 · PMID 40416846 · doi:10.1038/s44324-025-00064-3
This dataset
Open GSE293207 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 GSE293207_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 PRJNA1243345 and SRA study SRP573887. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40416846) ↗
Study design
4 × Ercc1 d/- AIN93G control # vs 4 × Ercc1 d/- low protein - high carb # vs 4 × Ercc1 d/- low carbohydrate - high protein # vs 4 × Ercc1 d/- low fat - high carb #

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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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