← BioTransfer GEO Dataset Finder
GEO series

Castration Model Illuminates Sex Differences in Healthy Aging: Insights from Metabolome and Transcriptome Analyses

GSE252625 Mus musculus (mouse) RNA-seq (gene expression) 46 samples Submitted 2025/10/01 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 46 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
46 samples: 31 distinct titles, 7 of them repeatedGroups 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)
Females typically outlive males, a disparity mitigated by castration, yet the molecular underpinnings remain elusive. Our study leverages untargeted metabolomics and RNA sequencing to uncover the pivotal compounds and genes influencing healthy aging post-castration, examining serum, kidney, and liver biospecimens from 12-week and 18-month old castrated male mice and their unaltered counterparts.
Read the full summary ↓
Behavioral tests and LC-MS/MS metabolomics reveal that castrated males exhibit altered steroid hormones, superior cognitive performance, and higher levels of anti-oxidative compounds like taurine, despite identical diets. Integrated metabolome-transcriptome analysis confirms reduced lipid peroxidation and oxidative stress in female and castrated male mice, suggesting a protective mechanism against aging. Histological examinations post-cisplatin treatment highlight the model’s applicability in studying drug toxicity and reveal varying susceptibility in organ-specific toxicities, underlining the crucial role of sex hormones in physiological defenses. In essence, our castration model unveils a feminized metabolic and transcriptomic intermediary, serving as a robust tool for studying gender-specific aspects of healthy aging and exploring sex hormone-induced differences in diverse biomedical domains.
This dataset
Open GSE252625 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 GSE252625_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 PRJNA1061179 and SRA study SRP482345. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
31 distinct titles, 7 of them repeated
L_Case ×5 18m_K_Case ×3 K_ShamF ×3 K_ShamM ×3 L_ShamF ×3 L_ShamM ×3 K_Case ×2

How we read this: Read from 46 sample titles: 31 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.