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A fully iPSC-derived 3D model of the human blood-brain barrier for exploring neurovascular disease mechanisms and therapeutic interventions

GSE302761 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2025/08/26 Platform GPL28337
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 5 × iPSC-derived endothelial cells vs 5 × iPSC-derived smooth muscle cells vs 4 × iPSC-derived pericytesGroups 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
A fully iPS-cell-derived 3D model of the human blood-brain barrier for exploring neurovascular disease mechanisms and therapeutic interventionsNature neuroscience · 2026
Summary (written by the submitters)
Integrity of the blood-brain barrier (BBB) is critical for brain homeostasis, and its malfunction contributes to neurovascular and neurodegenerative disorders. So far, mechanistic studies on BBB function have been mostly conducted in rodent and non-physiological in vitro models, which recapitulate some disease features, but have limited translatability to humans and pose challenges for drug discovery.
Read the full summary ↓
Here we report on a fully human iPSC-derived, microfluidic 3D BBB model consisting of endothelial cells (EC), mural cells, and astrocytes. Our model expresses typical cell fate markers, forms a barrier in vessel-like tubes, and enables perfusion, including with human blood. We optimized iPSC differentiations and validated cellular fates by comparison to published datasets and extensive benchmarking vs. primary cells with proteomic profiles provided in an online database. To demonstrate suitability for translational research, we applied the model to investigate deficiency of FOXF2, a major risk gene for cerebral small vessel disease. Deletion of FOXF2 in EC induced key features of BBB dysfunction, including compromised cell junction integrity and enhanced caveolae formation. Proteomic analysis further revealed dysregulation of endocytosis and cell junction pathways. Disease features phenocopied those seen in mice with endothelial cell-specific Foxf2 deficiency, validating the relevance of our in vitro model to investigate in vivo phenotypes of neurovascular disease. Moreover, lipid-nanoparticle-based treatment with Foxf2 mRNA rescued BBB deficits in our FOXF2 KO model, demonstrating its potential for drug development.
Published in
A fully iPS-cell-derived 3D model of the human blood-brain barrier for exploring neurovascular disease mechanisms and therapeutic interventions
González-Gallego J, Todorov-Völgyi K, Müller SA et al. · Nature neuroscience 2026 · PMID 41398476 · doi:10.1038/s41593-025-02123-w
This dataset
Open GSE302761 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 GSE302761_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 PRJNA1292123 and SRA study SRP601188. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41398476) ↗
Study design
5 × iPSC-derived endothelial cells vs 5 × iPSC-derived smooth muscle cells vs 4 × iPSC-derived pericytes

Supports a between-group comparison across 14 samples.

How we read this: 3 replicated groups read from 14 sample titles; they account for 14 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.