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Decoding spatial gene activity changes in multiple sclerosis lesion progression

GSE208747 Homo sapiens (human) RNA-seq (gene expression) 218 samples Submitted 2024/08/05 Platform GPL30173Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 218 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
218 samples: 196 distinct titles, 10 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
Spatially resolved gene signatures of white matter lesion progression in multiple sclerosisNature neuroscience · 2024
Summary (written by the submitters)
Multiple sclerosis (MS) is an inflammatory disease of the central nervous system characterised by myelin loss and progressive neurodegeneration. To better understand MS lesion initiation and progression, we generated spatial gene activity maps of white (WM) and grey matter (GM) MS lesions. In different MS lesion types, we detected novel transcriptional domains, including an identifiable rim around active WM lesions.
Read the full summary ↓
These active lesion rims were characterised by changes in astrocytic, oligodendrocytic, and microglial gene activity. Furthermore, we identified three novel WM lesion trajectories, predicting how normal appearing WM could progress into WM lesions, with lesion rims, active lesion cores, and mixed active/inactive lesion cores as potential outcomes. Our findings offer new insights into MS lesion progression, and the dynamic molecular and cellular processes that underlie MS.
Published in
Spatially resolved gene signatures of white matter lesion progression in multiple sclerosis
Alsema AM, Wijering MHC, Miedema A et al. · Nature neuroscience 2024 · PMID 39501035 · doi:10.1038/s41593-024-01765-6
This dataset
Open GSE208747 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 GSE208747_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 PRJNA860953 and SRA study SRP387778. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39501035) ↗
Study design
196 distinct titles, 10 of them repeated
act/inact ×6 subpial ×5 active ×4 CGM ×3 NAWM ×3 NAGM ×3 CWM ×2 Lesion A2-1, ROI 2918 ×2 +2 more

Supports a case/control comparison: 190 samples read as cases, 2 as controls.

How we read this: Read from 218 sample titles: 196 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

+ 178 more — browse all 218 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.