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Senescent Endothelial Cells in Cerebral Microcirculation Are Key Drivers of Age-Related Blood-Brain Barrier Disruption, Microvascular Rarefaction, and Neurovascular Coupling Impairment in Mice

GSE325187 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/03/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 8 × isolated living cells from very aged mouse brain vs 4 × isolated living cells from young mouse brain vs 4 × isolated living cells from middle aged mouse brain vs 4 × isolated living cells from aged mouse brainGroups 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)
With advancing age, neurovascular dysfunction manifests as impaired neurovascular coupling (NVC), microvascular rarefaction, and blood-brain barrier (BBB) disruption, contributing to vascular cognitive impairment (VCI). Our previous research established a causal link between vascular senescence induced cerebromicrovascular dysfunction and cognitive decline in accelerated aging models.
Read the full summary ↓
The present study examines whether chronological aging promotes endothelial senescence, adversely affecting neurovascular health, and whether senolytic therapies can enhance neurovascular function and cognitive performance in aged mice. We used transgenic p16-3MR mice to identify and eliminate senescent cells and employed genetic (ganciclovir) and pharmacological (ABT263/Navitoclax) senolytic approaches. Evaluations included spatial memory performance, NVC responses, cortical microvascular density, BBB permeability, and detection of senescent endothelial cells via flow cytometry. Brain endothelial cells exhibited heightened sensitivity to aging-induced senescence, undergoing senescence at a greater rate and earlier than other brain cell types, particularly during middle age. This microvascular endothelial cell senescence was associated with NVC dysfunction, microvascular rarefaction, BBB disruption, and deteriorating cognitive performance. On the other hand, senolytic treatments in aged mice improved NVC responses, BBB integrity, microvascular density, and learning capabilities. Notably, these findings suggest that the most effective time window for senolytic treatment is in middle-aged mice, where early intervention could better prevent neurovascular dysfunction and mitigate age-related cognitive impairment.
This dataset
Open GSE325187 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 GSE325187_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 PRJNA1438785 and SRA study SRP684601. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 × isolated living cells from very aged mouse brain vs 4 × isolated living cells from young mouse brain vs 4 × isolated living cells from middle aged mouse brain vs 4 × isolated living cells from aged mouse brain

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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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