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Integrative single cell analysis of progressive multiple sclerosis induced neural stem cells reveals epigenetically dysregulated type-I-interferon signaling

GSE297192 Homo sapiens (human) Single-cell RNA-seq 25 samples Submitted 2025/10/10 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 25 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: 25 samples: 24 × CGroups 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: Integrated omics reveals disease-associated radial glia-like cells with epigenetically dysregulated interferon response in multiple sclerosisNeuron · 2025

Summary (written by the submitters)

Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system, which currently lacks effective therapies that provide regeneration and stop disease progression. A suggested link is anticipated between the development of progressive MS (PMS) and aging, as suggested by recent work identifying hallmarks of cellular senescence in numerous cell types both in vitro with patient cell lines and in vivo in the post-mortem MS brain, including neural stem cells (NSCs).

Read the full summary ↓

Using an inducible system, directly reprogramming human fibroblasts into induced NSCs (iNSCs), we generated control and PMS iNSC cell lines, which was found to maintain epigenetic age. Here we performed multi-omics, including bulk RNA, single-cell (sc) RNA, single-nucleus (sn) RNA and ATAC, and whole genome bisulfite sequencing. Here, we show that PMS iNSCs have overall increases in senescence and inflammatory associated genes using bulk sequencing. We next identified a unique subcluster of cells within the PMS iNSCs that have a pro-inflammatory and senescent phenotype, associated with interferon gene activation using sc-RNA seq. Within this specific subcluster there is higher expression of genes associated with inflammatory protein secretion, as well as the senescence associated secretory phenotype (SASP). A similar clustering pattern was observed in the ATAC-seq data, a large main cluster and a small inflammatory cluster primarily comprising of PMS iNSCs. Differentially accessible regions within the PMS cluster revealed promoter sites of inflammatory-associated genes to be more accessible correlating with gene expression. Our results highlight a novel cellular mechanism in PMS wherein NSCs are interferon-responsive and senescent-like which may impact other cells within the lesion leading to chronic inflammation.

Published in

Integrated omics reveals disease-associated radial glia-like cells with epigenetically dysregulated interferon response in multiple sclerosis

Park B, Nicaise AM, Tsitsipatis D et al. · Neuron 2025 · PMID 41075785 · doi:10.1016/j.neuron.2025.09.022

This dataset

Open GSE297192 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 GSE297192_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 PRJNA1262970 and SRA study SRP585247. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41075785) ↗

Study design

24 × C

Supports a between-group comparison across 24 samples.

How we read this: 1 replicated groups read from 25 sample titles; they account for 24 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

GSM8985311 C1 C
GSM8985312 C2 C
GSM8985313 C3 C
GSM8985314 C4 C
GSM8985315 C5 C
GSM8985316 C6 C
GSM8985317 C7 C
GSM8985318 C8 C
GSM8985319 C9 C
GSM8985320 C10 C
GSM8985321 C11 C
GSM8985322 C12 C
GSM8985323 C13 C
GSM8985324 C14 C
GSM8985325 C15 C
GSM8985326 C16 C
GSM8985327 C17 C
GSM8985328 C18 C
GSM8985329 C18_2
GSM8985330 C19 C
GSM8985331 C20 C
GSM8985332 C21 C
GSM8985333 C22 C
GSM8985334 C23 C
GSM8985335 C24 C

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