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Spatial and single cell transcriptomics in the human Entorhinal Cortex across diverse risk of Alzheimer’s disease

GSE308007 Homo sapiens (human) Single-cell RNA-seq 31 samples Submitted 2025/11/14 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 31 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
31 samples: 31 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
APOE E4 Alzheimer's Risk Converges on an Oligodendrocyte Subtype in the Human Entorhinal CortexbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
We present the first spatially-resolved transcriptomics and single-nucleus RNA-sequencing integrated dataset from the entorhinal cortex (ERC) of postmortem human brain donors. ERC is implicated in early progression of Alzheimer’s Disease (AD) and we chose this brain region to study gene expression changes associated with AD risk by comparing APOE E2 and E4 allele carriers.
Read the full summary ↓
Donors with no AD diagnosis or widespread neurodegeneration were exclusively selected. As AD risk is increased in African Ancestry in contrast to European Ancestry backgrounds, and AD risk is also increased in women compared to men, our dataset included donors from these different backgrounds. We identified a pre-myleinating oligodendrocyte sub-cluster with transcriptomic changes strongly associated with APOE E4 carriers. These changes were present in both ancestry backgrounds, although they were more pronounced in African Ancestry donors. To facilitate future studies based on this dataset, we provided the raw and processed data, and created interactive web applications.
Published in
APOE E4 Alzheimer's Risk Converges on an Oligodendrocyte Subtype in the Human Entorhinal Cortex
Huuki-Myers LA, Divecha HR, Bach SV et al. · bioRxiv : the preprint server for biology 2025 · PMID 41332786 · doi:10.1101/2025.11.20.689483
This dataset
Open GSE308007 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 GSE308007_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1328504. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41332786) ↗
Study design
31 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 31 sample titles: 31 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
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.