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Neuronal DAMPs exacerbate neurodegeneration via astrocytic RIPK3 signaling

GSE237891 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2024/04/05 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 13 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
13 samples
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
Neuronal DAMPs exacerbate neurodegeneration via astrocytic RIPK3 signalingJCI insight · 2024
Summary (written by the submitters)
Astrocyte activation is a common feature of neurodegenerative diseases. However, the ways in which dying neurons influence the activity of astrocytes is poorly understood. RIPK3 signaling has recently been described as a key regulator of neuroinflammation, but whether this kinase mediates astrocytic responsiveness to neuronal death has not yet been studied.
Read the full summary ↓
Here, we used the MPTP model of Parkinson’s disease to show that activation of astrocytic RIPK3 drives dopaminergic cell death and axon damage. Transcriptomic profiling revealed that astrocytic RIPK3 promoted gene expression associated with neuroinflammation and movement disorders, and this coincided with significant engagement of DAMP signaling. Using human cell culture systems, we show that factors released from dying neurons signal through RAGE to induce RIPK3-dependent astrocyte activation. These findings highlight a mechanism of neuron-glia crosstalk in which neuronal death perpetuates further neurodegeneration by engaging inflammatory astrocyte activation via RIPK3.
Published in
Neuronal DAMPs exacerbate neurodegeneration via astrocytic RIPK3 signaling
Chang NP, DaPrano EM, Lindman M et al. · JCI insight 2024 · PMID 38713518 · doi:10.1172/jci.insight.177002
This dataset
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.

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 GSE237891_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA996993 and SRA study SRP450638. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 13 more — browse all 13 samples with per-sample file links →

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