Evidence map›Paper›PMID 35653192›Full record

ArticleJCI insight2022

Multimodal analyses of vitiligo skin identify tissue characteristics of stable disease.

Jessica Shiu, Lihua Zhang, Griffin Lentsch, Jessica L Flesher, Suoqin Jin, Christopher Polleys, Seong Jin Jo, Craig Mizzoni, Pezhman Mobasher, Jasmine Kwan and 6 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JCI insight, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04374435 (Evaluating the Efficacy of the Melanocyte Keratinocyte Transplantation Procedure in the Treatment of Vitiligo), which is not on this map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% of its field
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.

NCT04374435 naterminatednot on this map

Evaluating the Efficacy of the Melanocyte Keratinocyte Transplantation Procedure in the Treatment of Vitiligo

TypeinterventionalSponsorUniversity of California, IrvineRan2017 to 2022Enrolled17ConditionsVitiligoArmsMKTP with Surgical blade, MKTP with Negative Pressure Instrument, Suction blister grafting without cell dissociation
3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Melanocyte loss dominates the vitiligo transcriptome: a rank-based meta-analysis.medRxiv : the preprint server for health sciences · 2026
    Article
  6. Inflammatory niches as spatial drivers of disease mechanisms and targets for personalized treatment.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026
    Review
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  8. Article
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  18. Review
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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

16 authors at 7 institutions in 4 countries.

Jessica ShiuDepartment of Dermatology.
Lihua ZhangDepartment of Mathematics.
Griffin LentschBeckman Laser Institute and Medical Clinic, University of California, Irvine (UC Irvine), Irvine, California, USA.
Jessica L FlesherCutaneous Biology Research Center, Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA.
Suoqin JinDepartment of Mathematics.
Christopher PolleysDepartment of Biomedical Engineering, Tufts University, Medford, Massachusetts, USA.
Seong Jin JoDepartment of Dermatology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Craig MizzoniDepartment of Biomedical Engineering, Tufts University, Medford, Massachusetts, USA.
Pezhman MobasherDepartment of Dermatology.
Jasmine KwanDepartment of Biomedical Engineering, Tufts University, Medford, Massachusetts, USA.
Francisca Rius-DiazDepartment of Preventive Medicine and Public Health, University of Malaga, Malaga, Spain.
Bruce J TrombergNSF-Simons Center for Multiscale Cell Fate Research, and.
Irene GeorgakoudiDepartment of Biomedical Engineering, Tufts University, Medford, Massachusetts, USA.
Qing NieDepartment of Mathematics.
Mihaela BaluBeckman Laser Institute and Medical Clinic, University of California, Irvine (UC Irvine), Irvine, California, USA.
Anand K GanesanDepartment of Dermatology.
Tufts University · USToronto Metropolitan University · CAUniversity of California, Irvine · USMassachusetts General Hospital · USSeoul National University · KRUC Irvine Health · USUniversidad de Málaga · ES

Funding

University of California Health Participation in the National COVID Cohort Collaborative (N3C)UL1TR001414 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M, VILAIN, ERIC J. · 2015 to 2023
$35.1M
Shared Resource Core: Single Cell AnalysisU54CA217378 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI GANESAN, ANAND K · 2018 to 2022
$9.7M
Institutional Career Development CoreKL2TR001416 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI CAIOZZO, VINCENT JAMES, DEMETRIOU, MICHAEL · 2015 to 2023
$5.6M
UCI P30 Skin Center Systems Biology CoreP30AR075047 · NIAMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LANDER, ARTHUR D · 2019 to 2025
$5.1M
Development of a fast scanning, extended field-of-view multiphoton microscope for clinical skin imagingR01EB026705 · NIBIB · UNIVERSITY OF CALIFORNIA-IRVINE · PI Mihaela Balu, Anand K Ganesan · 2018 to 2026
$4.2M
Multiscale Models of Wound Cell Plasticity for RegenerationU01AR073159 · NIAMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI DAI, XING, NIE, QING · 2018 to 2022
$3.5M
PacBio RS Single Molecule, Real-Time (SMRT) DNA SequencerS10OD010794 · OD · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2012 to 2012
$600k
High-Throughput DNA SequencerS10OD021718 · OD · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2016 to 2016
$600k
High Throughput DNA SequencerS10RR025496 · NCRR · UNIVERSITY OF CALIFORNIA-IRVINE · PI SANDMEYER, SUZANNE · 2009 to 2009
$500k
Identifying the Molecular Characteristics of Migrating Melanocytes in Vitiligo SkinR21AR073408 · NIAMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GANESAN, ANAND K · 2018 to 2019
$374k
NCATS NIH HHS KL2 TR001416NCATS NIH HHS UL1 TR001414NCI NIH HHS U54 CA217378NCRR NIH HHS S10 RR025496NIAMS NIH HHS P30 AR075047NIAMS NIH HHS R21 AR073408NIAMS NIH HHS U01 AR073159NIBIB NIH HHS R01 EB026705NIH HHS S10 OD010794NIH HHS S10 OD021718
6 · The paper itself

Abstract

Vitiligo is an autoimmune skin disease characterized by the destruction of melanocytes by autoreactive CD8+ T cells. Melanocyte destruction in active vitiligo is mediated by CD8+ T cells, but the persistence of white patches in stable disease is poorly understood. The interaction between immune cells, melanocytes, and keratinocytes in situ in human skin has been difficult to study due to the lack of proper tools. We combine noninvasive multiphoton microscopy (MPM) imaging and single-cell RNA-Seq (scRNA-Seq) to identify subpopulations of keratinocytes in stable vitiligo patients. We show that, compared with nonlesional skin, some keratinocyte subpopulations are enriched in lesional vitiligo skin and shift their energy utilization toward oxidative phosphorylation. Systematic investigation of cell-to-cell communication networks show that this small population of keratinocyte secrete CXCL9 and CXCL10 to potentially drive vitiligo persistence. Pseudotemporal dynamics analyses predict an alternative differentiation trajectory that generates this new population of keratinocytes in vitiligo skin. Further MPM imaging of patients undergoing punch grafting treatment showed that keratinocytes favoring oxidative phosphorylation persist in nonresponders but normalize in responders. In summary, we couple advanced imaging with transcriptomics and bioinformatics to discover cell-to-cell communication networks and keratinocyte cell states that can perpetuate inflammation and prevent repigmentation.

Indexed as

VitiligoCD8-Positive T-LymphocytesHumansKeratinocytesMelanocytesSkinAutoimmunityDermatologyDiagnostic imagingExpression profilingSkin

Identifiers

PMID35653192
PMCPMC9310536
OpenAlexW4281667756

What OpenQuestion holds

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Registered trials

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 OpenQuestion graph.