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Multi-omic characterization of human sural nerves across polyneuropathies [snRNA-seq]

GSE285983 Homo sapiens (human) Single-nucleus RNA-seq 37 samples Submitted 2025/06/28 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 37 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Samples
37 samples: 37 × single nucleus RNA sequencing SGroups 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-omic identification of perineurial hyperplasia and lipid-associated nerve macrophages in human polyneuropathiesNature communications · 2025
Summary (written by the submitters)
Diseases of peripheral nerves termed polyneuropathies (PNPs) are common, mechanistically heterogeneous, and challenging to diagnose. Here, we integrated single nucleusi transcriptomics of peripheral nerves from 33 human PNP patients and four controls (365,708 nuclei) with subcellular spatial transcriptomics. We identified novel and human-specific nerve cell type markers including unexpectedly heterogeneous perineurial fibroblasts.
Read the full summary ↓
All PNPs shared a loss of myelinating and an increase in repair Schwann cells and endoneurial lipid-associated macrophages. Transcriptional changes affected multiple cells outside of the endoneurium across PNPs, suggesting PNPs as ‘pan-nerve diseases’. Spatially, PNPs showed a previously unknown perineurial hyperplasia and fibrotic dispersion and this was most pronounced in immune-mediated PNPs. Single cell transcriptomics supported the differential diagnosis of PNPs with potential for future unbiased diagnostic classification.
Published in
Multi-omic identification of perineurial hyperplasia and lipid-associated nerve macrophages in human polyneuropathies
Heming M, Börsch AL, Wolbert J et al. · Nature communications 2025 · PMID 40849297 · doi:10.1038/s41467-025-62964-8
This dataset
Open GSE285983 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 GSE285983_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 PRJNA1207198 and SRA study SRP555641. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40849297) ↗
Study design
37 × single nucleus RNA sequencing S

Supports a between-group comparison across 37 samples.

How we read this: 1 replicated groups read from 37 sample titles; they account for 37 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.