GEO series

Transcriptomic analysis of fibroblast from 10 Ehlers-Danlos SYndrome (EDS) patients.

GSE270199 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2025/06/10 Platform GPL24676

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: 14 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: Multi-OMICs analysis on tridimensional fibroblast spheroids to model vascular Ehlers-Danlos syndrome pathogenesisBiochimica et biophysica acta. Molecular basis of disease · 2025

Summary (written by the submitters)

Ehlers-Danlos SYndrome (SEDSY) was performed compared to 4 control healty samples with the aim to identify dysregulated genes and pathways and to use this information to propose potential drugs that could be repurposed for the treatment, based on computational approaches to drug repositioning.In summary, this comprehensive study expands our understanding of the molecular basis of Ehlers-Danlos syndrome, particularly relating to COL3A1 mutations.

Read the full summary ↓

The integration of transcriptomic analysis, pathway studies, and drug repurposing strategies provides a robust framework for identifying potential therapeutic strategies for EDS.

Published in

Multi-OMICs analysis on tridimensional fibroblast spheroids to model vascular Ehlers-Danlos syndrome pathogenesis

Micale L, Di Muro E, De Cegli R et al. · Biochimica et biophysica acta. Molecular basis of disease 2025 · PMID 40345454 · doi:10.1016/j.bbadis.2025.167896

This dataset

Open GSE270199 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 GSE270199_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 PRJNA1125404 and SRA study SRP514777. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40345454) ↗

Study design

14 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 14 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

GSM8336700 C3B_healthy
GSM8336701 C2B_healthy
GSM8336702 RR_healthy
GSM8336703 C1A_healthy
GSM8336704 20-3156_pat
GSM8336705 20-3154_pat
GSM8336706 20-4456_pat
GSM8336707 VL_pat
GSM8336708 GAU_pat
GSM8336709 19-1597_pat
GSM8336710 SF_pat
GSM8336711 22-0547_pat
GSM8336712 22-0548_pat
GSM8336713 20-4222_pat

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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.