GEO series

Cerebrospinal fluid-driven ependymal motile cilia defects are implicated in multiple sclerosis

GSE301585 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2025/12/31 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 15 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 15 samples: 14 distinct titles, 1 of them repeatedGroups 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: Cerebrospinal fluid-driven ependymal motile cilia defects are implicated in multiple sclerosisBrain : a journal of neurology · 2026

Summary (written by the submitters)

Background: Multiple sclerosis is a neurodegenerative autoimmune disorder of the central nervous system (CNS) in which autoreactive immune cells migrate through a damaged blood brain barrier, resulting in focal demyelinating lesions of both the white and grey matter. Of increasing interest is the repeated observation that beyond focal lesions, there are also diffuse, surface-in gradients of pathology in MS, wherein damage is most severe directly adjacent to cerebrospinal fluid (CSF)-contacting surfaces, such as the subpial and periventricular areas.

Read the full summary ↓

This observation suggests that toxic factors within MS CSF may be contributing to the emer-gence and/or evolution of surface-in gradients. Directly separating the CSF from the periventricular parenchyma are ependymal cells – a glial epithelium that expresses tufts of motile cilia which are critical for circulating CSF solutes and regulating local fluid flow. While damage to ependymal cilia has the potential to drastically modify CSF homeostasis and thus contribute to the damage of CSF exposed regions, these motile cellular structures have yet to be investigated in the context of MS. Methods: We first conducted single cell RNA sequencing of fresh human periventricular brain tissue containing ependymal cells from MS patients and non-MS disease controls. We subse-quently collected CSF from MS patients and exposed cultured rodent ependymal cells to this CSF in order to evaluate impact on ependymal ciliary function. To complement our direct eval-uation of cilia in the context of MS, we also confirmed whether cilia were altered in a classic animal model of MS, experimental autoimmune encephalomyelitis (EAE), and also designed a novel transgenic animal model to evaluate the cellular and behavioural effect(s) of adult ep-endymal ciliary disruption. Results: Single cell RNA sequencing analysis of human ependymal cells in MS demonstrated largescale dysregulation of ciliary genes; in situ stains of MS brain tissue confirmed a loss of ependymal cilia in MS compared to control. Exposure of ependymal cells to MS CSF led to transcriptional modification of ciliary gene expression and reduced ciliary beating frequency. Likewise, analysis of ependymal cells in EAE also demonstrated altered cilia gene expression. Conditional knockout of the critical cilia-associated gene Ccdc39 in ependymal cells led to transient ventricular enlargement, increased periventricular microglial density, and alterations in nesting behaviour. Conclusion: These data suggest that cilia are dysregulated in CNS autoimmunity. More im-portantly, however, they provide evidence to suggest that ependymal cilia disruption could play an active role in the development of periventricular pathology in MS, and can lead to behav-ioural deficits that may underlie aspects non-motor MS symptomatology.

Published in

Cerebrospinal fluid-driven ependymal motile cilia defects are implicated in multiple sclerosis

Bigotte M, Groh AMR, Afanasiev E et al. · Brain : a journal of neurology 2026 · PMID 41277219 · doi:10.1093/brain/awaf440

This dataset

Open GSE301585 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 GSE301585_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 PRJNA1285692. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41277219) ↗

Study design

14 distinct titles, 1 of them repeated

Patient6_LV ×2

How we read this: Read from 15 sample titles: 14 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

GSM9085898 Patient1_3V
GSM9085899 Patient1_LV
GSM9085900 Patient2_3V
GSM9085901 Patient2_LV
GSM9085902 Patient3_3V
GSM9085903 Patient3_LV
GSM9085904 Patient4_3V
GSM9085905 Patient4_LV
GSM9085906 Patient5_LV
GSM9085907 Patient6_LV1
GSM9085908 Patient6_LV2
GSM9085909 Patient7_3V
GSM9085910 Patient7_LV
GSM9085911 Patient8_3V
GSM9085912 Patient8_LV

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