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Mutations in PSEN1 predispose inflammation in an astrocyte model of familial Alzheimer’s disease through disrupted regulated intramembrane proteolysis

GSE298491 Homo sapiens (human) RNA-seq (gene expression) 80 samples Submitted 2025/06/25 Platform GPL30173Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 80 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
Homo sapiens (human)
Samples
80 samples: 80 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.
Paper
Mutations in PSEN1 predispose inflammation in an astrocyte model of familial Alzheimer's disease through disrupted regulated intramembrane proteolysisMolecular neurodegeneration · 2025
Summary (written by the submitters)
Mutations in PSEN1 cause familial Alzheimer’s disease with almost complete penetrance. Age at onset is highly variable between different PSEN1 mutations and even within families with the same mutation. Current research into late onset Alzheimer’s disease implicates inflammation in both disease onset and progression. PSEN1 is the catalytic subunit of gamma-secretase, responsible for regulated intramembrane proteolysis of numerous substrates that include cytokine receptors.
Read the full summary ↓
For this reason, we tested the hypothesis that mutations in PSEN1 impact inflammatory responses in astrocytes, thereby contributing to disease progression. We developed patient-derived models of iPSC-astrocytes, representing three lines harbouring PSEN1 mutations and six control lines (including two isogenic controls). Transcriptomic and biochemical assays were used to investigate differential inflammatory responses to TNFa, IL1a and C1q. We show that PSEN1 is upregulated in response to inflammatory stimuli, and this upregulation is disrupted by pathological PSEN1 mutations. Using transcriptomic analyses, we demonstrate that PSEN1 mutant astrocytes have an augmented inflammatory profile in their basal state, concomitant with gene expression signatures revealing dysregulated intramembrane proteolysis and JAK-STAT signalling. Detailed investigation of the JAK-STAT2 signalling pathway showed reduced cell surface expression of IFNAR2, lower STAT2 phosphorylation cascades and delayed NFκB nuclear localisation in PSEN1 mutant astrocytes in response to inflammatory stimuli, thereby implicating the notion of altered cytokine signalling cascades. Finally, we use small molecule modulators of gamma-secretase to confirm a role for PSEN1/gamma-secretase in regulating the astrocytic response to inflammatory stimuli. Together, these data suggest that mutations in PSEN1 enhance cytokine signalling via impaired regulated intramembrane proteolysis, thereby predisposing astrocytic inflammatory profiles. These findings support a two-hit contribution of PSEN1 mutations to fAD pathogenesis, not only impacting APP and Abeta processing but also altering the cellular response to inflammation.
Published in
Mutations in PSEN1 predispose inflammation in an astrocyte model of familial Alzheimer's disease through disrupted regulated intramembrane proteolysis
Ziff OJ, Parfitt GM, Jolly S et al. · Molecular neurodegeneration 2025 · PMID 40542358 · doi:10.1186/s13024-025-00864-7
This dataset
Open GSE298491 in finder → Find more human 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 GSE298491_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 PRJNA1269544 and SRA study SRP588633. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40542358) ↗
Study design
80 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 80 sample titles: 80 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

+ 40 more — browse all 80 samples with per-sample file links →

Datasets on a similar topic

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