Evidence map›Paper›PMID 41728299›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Melanocyte loss dominates the vitiligo transcriptome: a rank-based meta-analysis.

Xijin Ge

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Xijin GeDepartment of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA.ORCID 0000-0001-7406-3782

Funding

Transcriptome & Networks Analysis CoreP20GM135008 · NIGMS · SOUTH DAKOTA STATE UNIVERSITY · PI Adam David Hoppe · 2022 to 2026
$13.5M
An interactive and reproducible tool for enrichment analysisR01HG013534 · NHGRI · SOUTH DAKOTA STATE UNIVERSITY · PI Xijin Ge · 2024 to 2026
$680k
Commercializing iDEP, an interactive and reproducible tool for analyzing RNA-Seq dataR41HG014101 · NHGRI · RTUTOR, LLC · PI GE, XIJIN · 2025 to 2025
$395k
Democratizing statistical computing through AIR43GM153076 · NIGMS · RTUTOR, LLC · PI BURKHALTER, DANIEL · 2024 to 2024
$274k
NHGRI NIH HHS R01 HG013534NHGRI NIH HHS R41 HG014101NIGMS NIH HHS P20 GM135008NIGMS NIH HHS R43 GM153076
6 · The paper itself

Abstract

Vitiligo is an autoimmune disorder characterized by the destruction of melanocytes. We performed a rank-based meta-analysis of six independent transcriptomic studies (115 samples) spanning microarray, bulk, and single-cell RNA-seq platforms to identify consensus signatures of lesional skin. Robust rank aggregation identified 108 downregulated and 6 upregulated genes. Pathway analysis revealed consistent suppression of melanin synthesis and neural development pathways in vitiligo, whereas immune response activation was heterogeneous across studies. Re-analysis of single-cell data from three studies confirmed melanocyte depletion. The 108 downregulated genes were expressed exclusively in melanocytes. These include neural development genes (PLP1, GPM6B, NRXN3), consistent with melanocytes' neural crest origin. We also identified candidate melanocyte markers, such as CYB561A3 and QPCT, with high melanocyte specificity and consistent downregulation in vitiligo. These findings reveal a robust melanocyte-loss signature in vitiligo, detectable across different studies. Study-dependent immune activation, possibly influenced by sampling method and disease characteristics, warrants further study.

Indexed as

depigmentationgene expression profilingmelanocyte markersrobust rank aggregationsingle-cell RNA-seq

Identifiers

PMID41728299
PMCPMC12919112

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.