Evidence map›Paper›PMID 35464413›Full record

ArticleFrontiers in immunology2022

Skin Interstitial Fluid and Plasma Multiplex Cytokine Analysis Reveals IFN-γ Signatures and Granzyme B as Useful Biomarker for Activity, Severity and Prognosis Assessment in Vitiligo.

Chau Yee Ng, Yen-Chuan Chiu, Yu-Pei Chan, Yu-Jr Lin, Pei-Han Chung, Wen-Hung Chung, Cheng-Lung Ku

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% 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.

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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Vitiligo-like depigmentation as an accessible readout of antitumour immunity in melanoma immunotherapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
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

7 authors at 3 institutions in 1 country.

Chau Yee NgVitiligo Clinic and Research Center, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Yen-Chuan ChiuVitiligo Clinic and Research Center, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Yu-Pei ChanVitiligo Clinic and Research Center, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Yu-Jr LinDepartment of Statistics, Chang Gung University, Taoyuan, Taiwan.
Pei-Han ChungDepartment of Pharmacology, Elixiron Immunotherapeutics Inc., Taipei City, Taiwan.
Wen-Hung ChungDepartment of Dermatology, Chang Gung Memorial Hospital, Linkou Branch, Taoyuan, Taiwan.
Cheng-Lung KuGraduate Institute of Clinical Medical Science, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Chang Gung Memorial Hospital · TWChang Gung University · TWElixiron Immunotherapeutics (Taiwan) · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The course of vitiligo is unpredictable, with periods of disease flare-ups and prolonged recovery periods. It is essential to establish a biomarker profile as a substitute marker for disease activity to predict disease activity, severity, and prognosis prediction. The use of localized skin interstitial fluid as biomarkers has recently gained interest, but extensive studies of the association between skin interstitial fluid, plasma, and the disease course is lacking. This study aims to evaluate the cytokine expression profiles in the skin and plasma and the utility of the biomarker panel in assessing disease activity, severity, and prognosis in patients with vitiligo. Methods: In this prospective cohort study, 86 patients and 34 healthy controls were recruited from the outpatient department of a tertiary medical center from March 2019 to September 2021. All patients were of Asian ethnicity. Two independent investigators evaluated disease activity and severity with longitudinal follow-ups for treatment response for a-12 month period. Ultrasensitive multiplex cytokine panel and single-molecule counting technology immunoassays were used to study the cytokine expression in skin interstitial fluid and plasma. Results: IFN-γ and its' signature cytokines, including CXCL9, CXCL10, and GzmB, are most highly expressed in the vitiligo patients' lesion skin interstitial fluid and plasma compared to healthy control. By way of comparison, no significant changes in IL-1β, IL-13, IL-15, IL-17A, IL-18 were observed. Receiver operating characteristic analysis revealed that IFN-γ is the most sensitive and specific marker in predicting disease activity, followed by CXCL10 and GzmB. CXCL-9 was sensitive and specific in diagnosing vitiligo disease severity. The decrease in IFN-γ expression level is positively correlated with the treatment response. Conclusion: IFN-γ, CXCL9, CXCL10, and GzmB are highly expressed in vitiligo patients' lesion skin and plasma and may serve as biomarkers for the clinical activity, severity, and prognosis prediction in vitiligo patients. Among all, IFN-γ exerts the highest predictive value in disease activity and treatment response, supporting the critical role of IFN-γ in the pathogenesis of vitiligo.

Indexed as

VitiligoBiomarkersCytokinesExtracellular FluidGranzymesHumansInterferon-gammaPrognosisProspective StudiesBiomarkersCytokinesGranzymesInterferon-gammabiomarkergranzyme Binterferon gammamultiplex cytokine assayvitiligo

Identifiers

PMID35464413
PMCPMC9021541
OpenAlexW4225526666

What OpenQuestion 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 OpenQuestion graph.