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Podocyte Aging with and without Hypertension: A Comparative Study in Young and Middle-Aged Mice

GSE281003 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/11/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 15 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.
Summary (written by the submitters)
Recent studies show that acute injury to non-aged podocytes induces many similarities to healthy aged podocytes, such as decreased lifespan and health-span. Like healthy aged podocytes, injury to young mouse and human podocytes can induce a senescent phenotype. This begs the question if injury to young podocytes phenocopies a healthy middle-aged podocyte, and if the pathways underlying senescence and other injury responses overlap between injured young podocytes and healthy middle-aged podocytes.
Read the full summary ↓
To address this knowledge gap we induced hypertension, a major cause of chronic kidney disease, in young mice (4m of age~20-year-old human) and in middle-aged mice (18m of age, ~55+ year old human) with deoxycorticosterone and high salt (DOCA) and compared outcomes to non-hypertensive healthy middle-aged mice. In both healthy middle-aged mice and in young mice with hypertension, the increase in age-related senescent genes p16 and p19, along with the stress-related senescent genes p21 and p53 were similar. Bulk RNA-sequencing of podocytes showed that the senescent associated secretory phenotype and individual genes from several aging gene sets were also similar between middle-aged mice and young mice with hypertension. Of the highest enriched Hallmark pathways in middle-aged podocytes, 95% were also enriched in young mice treated with DOCA. Gene set enrichment analysis of podocytes showed that 36 genes overlapped between middle-aged mice, and young and middle-aged mice given DOCA, while 119 genes identified were “DOCA-specific”. These results suggest that hypertension in young mice induces podocyte injury and an aging/senescent phenotype that is similar to the one of podocytes from healthy middle-aged mice.
This dataset
Open GSE281003 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 GSE281003_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 PRJNA1181818 and SRA study SRP543026. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
15 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 15 sample titles: 15 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.