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Transcriptomic profiling of vitiligo patients shows polar immune dysregulation in involved and uninvolved skin

GSE298871 Homo sapiens (human) Single-cell RNA-seq 17 samples Submitted 2025/06/03 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 17 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
17 samples: 17 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
Transcriptomic profiling of vitiligo patients shows polar immune dysregulation in involved and uninvolved skinThe Journal of allergy and clinical immunology · 2025
Summary (written by the submitters)
Background: Vitiligo is a chronic autoimmune skin depigmenting disorder, with a major impact on quality of life. Therapeutic options are still limited, with only one topical JAK inhibitor being FDA-approved. Although vitiligo is primarily regarded as a Th1/IFN-driven disease, emerging evidence suggests the involvement of additional immune axes, but their relevance to disease pathogenesis remains unclear.
Read the full summary ↓
Objective: To obtain a global cutaneous transcriptomic profile of lesional and nonlesional vitiligo. Results: Robust inflammatory dysregulation was captured not only in lesional, but also nonlesional vitiligo skin relative to healthy controls. Lesional samples demonstrated upregulation of Th1 (OASL, CXCL9, CXCL10), Th2 (IL4, IL4R, CCL13, CCL17, CCL22, CCL26), and Th17/22 (IL20, S100A7, S100A8, S100A9, PI3) related markers. Similarly, nonlesional samples demonstrated activation of Th1 (CXCL9, OASL), Th2 (IL4R, IL10, CCL13, CCL17, CCL22), and Th17/22 (PI3, DEFB4A) associated markers. Clinical severity scores (VASI and/or VIDA) significantly and positively correlated with multiple inflammatory mediators (i.e., CXCL14, IL25, IL17RC) in lesional and/or nonlesional vitiligo skin. On a single-cell level, IL13 and IFNG expression were primarily found in nonlesional helper T cells and in lesional proliferating T cells, respectively. Conclusions: Our findings show that immune dysregulation in vitiligo involves immune axes beyond Th1/Tc1, with upregulation of particularly type 2 markers already in nonlesional skin, suggesting a role during early lesion formation. Capsule Summary: We suggest that the inflammatory dysregulation of vitiligo is more complex than previously appreciated, involving not only Th1, but also Th2 and some components of Th17/22 immune axes, even in clinically normal appearing skin. Clinical implications: The dysregulation of multiple inflammatory mediators in nonlesional vitiligo skin might have major implications for future targeted treatment approaches.
Published in
Transcriptomic profiling of vitiligo patients shows polar immune dysregulation in involved and uninvolved skin
Brunner PM, David E, Del Duca E et al. · The Journal of allergy and clinical immunology 2025 · PMID 40513622 · doi:10.1016/j.jaci.2025.06.002
This dataset
Open GSE298871 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 GSE298871_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 PRJNA1271538. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40513622) ↗
Study design
17 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 11 samples read as cases, 6 as controls.

How we read this: Read from 17 sample titles: 17 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
Datasets on a similar topic

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