GEO series

Intestinal interoceptive dysfunction drives age-associated cognitive decline [RNA-Seq]

GSE307834 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2025/11/22 Platform GPL19057

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: 5 × RNA-Seq, Cohouse Young vs 5 × RNA-Seq, Cohouse Old vs 5 × RNA-Seq, Young vs 5 × RNA-Seq, OldGroups 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)

Aging is accompanied by declining memory function, necessitating the development of effective countermeasures1. Brain- extrinsic factors influencing cognitive decline, including the intestinal microbiome, have emerged as attractive targets for peripheral interventions2-6, but the underlying mechanisms remain largely unclear.

Read the full summary ↓

Here, by charting a high-resolution map of microbiome aging and its functional consequences throughout the lifespan of mice, we identify a mechanism whereby age- associated inhibition of gut-brain signalling results in impaired novelty-induced neuronal activation in the hippocampus and loss of memory encoding. Specifically, gut bacteria producing medium-chain fatty acids, such as Parabacteroides goldsteinii, accumulate over the lifespan and drive intestinal myeloid cell inflammation through GPR84 signalling. As a result, the function of afferent gut-innervating vagal neurons is impaired, the interoceptive signal received by the brain is weakened, and hippocampal function declines. We leverage this pathway to define interventions that restore memory in aged mice, such as phage targeting of Parabacteroides, GPR84 inhibition, and restoration of vagal activity. These findings indicate a key role for interoceptive signalling from the gastrointestinal tract in regulating brain aging and suggest that interoceptomimetics that stimulate gut-brain communication may counteract age-associated cognitive decline.

This dataset

Open GSE307834 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 GSE307834_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 PRJNA1327388 and SRA study SRP619249. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × RNA-Seq, Cohouse Young vs 5 × RNA-Seq, Cohouse Old vs 5 × RNA-Seq, Young vs 5 × RNA-Seq, Old

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

GSM9232370 RNA-Seq, Cohouse Young 1 RNA-Seq, Cohouse Young
GSM9232371 RNA-Seq, Cohouse Old 1 RNA-Seq, Cohouse Old
GSM9232372 RNA-Seq, Cohouse Young 2 RNA-Seq, Cohouse Young
GSM9232373 RNA-Seq, Cohouse Young 3 RNA-Seq, Cohouse Young
GSM9232374 RNA-Seq, Cohouse Old 2 RNA-Seq, Cohouse Old
GSM9232375 RNA-Seq, Young 1 RNA-Seq, Young
GSM9232376 RNA-Seq, Old 1 RNA-Seq, Old
GSM9232377 RNA-Seq, Cohouse Old 3 RNA-Seq, Cohouse Old
GSM9232378 RNA-Seq, Old 2 RNA-Seq, Old
GSM9232379 RNA-Seq, Cohouse Young 4 RNA-Seq, Cohouse Young
GSM9232380 RNA-Seq, Old 3 RNA-Seq, Old
GSM9232381 RNA-Seq, Cohouse Young 5 RNA-Seq, Cohouse Young
GSM9232382 RNA-Seq, Young 2 RNA-Seq, Young
GSM9232383 RNA-Seq, Old 4 RNA-Seq, Old
GSM9232384 RNA-Seq, Young 3 RNA-Seq, Young
GSM9232385 RNA-Seq, Old 5 RNA-Seq, Old
GSM9232386 RNA-Seq, Cohouse Old 4 RNA-Seq, Cohouse Old
GSM9232387 RNA-Seq, Young 4 RNA-Seq, Young
GSM9232388 RNA-Seq, Cohouse Old 5 RNA-Seq, Cohouse Old
GSM9232389 RNA-Seq, Young 5 RNA-Seq, Young

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