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Isogenic Human Stem Cell Models Reveal Mutation-Dependent Protective Mechanisms of APOE3 Christchurch

GSE338592 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2026/07/14 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 6 conditions, mostly in triplicateGroups 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)
The rare APOE3 Christchurch (APOE3ch) variant has been linked to exceptional resilience against Alzheimer’s disease (AD), yet its protective mechanisms remain unclear. Here, we examined how APOE3ch modulates AD-related phenotypes across distinct autosomal-dominant AD mutations using isogenic human induced pluripotent stem cell (hiPSC)–derived neural cultures.
Read the full summary ↓
Using prime editing, we introduced APOE3ch into hiPSC lines carrying PSEN1 E280A or APP duplication (APPdp) mutations and differentiated them into neuron–astrocyte cultures. APOE3ch did not affect neural differentiation or APOE secretion but produced mutation-dependent effects on disease-relevant pathways. In APPdp cultures, APOE3ch reduced amyloidogenic APP processing, Aβ40/42 production, and tau phosphorylation. In contrast, PSEN1 E280A cultures showed enhanced non-amyloidogenic processing and extensive transcriptional remodeling without reduced Aβ. Transcriptomic analyses revealed convergent activation of Wnt and cadherin signaling across both genetic backgrounds, alongside mutation-specific pathway changes. Together, these findings establish APOE3ch as a context-dependent modifier of AD pathology.
This dataset
Open GSE338592 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 GSE338592_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 PRJNA1495217 and SRA study SRP717937. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
PS1 E280A APOE3ch, clone 1 ×3 PS1 E280A APOE3 ×3 APPdp APOE3 ×3 PS1 E280A APOE3ch, clone 2 ×2 PS1 E280A APOE3ch, clone 3 ×2 APPdp APOE3ch, clone 1 ×2 APPdp APOE3, clone 1 ×1

Supports a between-group comparison across 15 samples.

How we read this: 6 replicated groups read from 16 sample titles; they account for 15 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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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.