Go to JCI Insight
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Advertising
  • Job board
  • Contact
  • Clinical Research and Public Health
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Gastroenterology
    • Immunology
    • Metabolism
    • Nephrology
    • Neuroscience
    • Oncology
    • Pulmonology
    • Vascular biology
    • All ...
  • Videos
    • Conversations with Giants in Medicine
    • Video Abstracts
  • Reviews
    • View all reviews ...
    • Complement Biology and Therapeutics (May 2025)
    • Evolving insights into MASLD and MASH pathogenesis and treatment (Apr 2025)
    • Microbiome in Health and Disease (Feb 2025)
    • Substance Use Disorders (Oct 2024)
    • Clonal Hematopoiesis (Oct 2024)
    • Sex Differences in Medicine (Sep 2024)
    • Vascular Malformations (Apr 2024)
    • View all review series ...
  • Viewpoint
  • Collections
    • In-Press Preview
    • Clinical Research and Public Health
    • Research Letters
    • Letters to the Editor
    • Editorials
    • Commentaries
    • Editor's notes
    • Reviews
    • Viewpoints
    • 100th anniversary
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • Reviews
  • Review series
  • Conversations with Giants in Medicine
  • Video Abstracts
  • In-Press Preview
  • Clinical Research and Public Health
  • Research Letters
  • Letters to the Editor
  • Editorials
  • Commentaries
  • Editor's notes
  • Reviews
  • Viewpoints
  • 100th anniversary
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Advertising
  • Job board
  • Contact

Usage Information

IL-1α, IL-1β, and IFN-γ mark β cells for Fas-dependent destruction by diabetogenic CD4+ T lymphocytes
Abdelaziz Amrani, … , Sonny Bou, Pere Santamaria
Abdelaziz Amrani, … , Sonny Bou, Pere Santamaria
Published February 15, 2000
Citation Information: J Clin Invest. 2000;105(4):459-468. https://doi.org/10.1172/JCI8185.
View: Text | PDF
Article

IL-1α, IL-1β, and IFN-γ mark β cells for Fas-dependent destruction by diabetogenic CD4+ T lymphocytes

  • Text
  • PDF
Abstract

Cytokines such as IL-1α, IL-1β, and IFN-γ have long been implicated in the pathogenesis of autoimmune diabetes, but the mechanisms through which they promote diabetogenesis remain unclear. Here we show that CD4+ T lymphocytes propagated from transgenic nonobese diabetic (NOD) mice expressing the highly diabetogenic, β cell–specific 4.1-T-cell receptor (4.1-TCR) can kill IL-1α–, IL-1β–, and IFN-γ–treated β cells from NOD mice. Untreated NOD β cells and cytokine-treated β cells from Fas-deficient NOD.lpr mice are not targeted by these T cells. Killing of islet cells in vitro was associated with cytokine-induced upregulation of Fas on islet cells and was independent of MHC class II expression. Abrogation of Fas expression in 4.1-TCR–transgenic NOD mice afforded nearly complete protection from diabetes and did not interfere with the development of the transgenic CD4+ T cells or with their ability to cause insulitis. In contrast, abrogation of perforin expression did not affect β cell–specific cytotoxicity or the diabetogenic potential of these T cells. These data demonstrate a novel mechanism of action of IL-1α, IL-1β, and IFN-γ in autoimmune diabetes, whereby these cytokines mark β cells for Fas-dependent lysis by autoreactive CD4+ T cells.

Authors

Abdelaziz Amrani, Joan Verdaguer, Shari Thiessen, Sonny Bou, Pere Santamaria

×

Usage data is cumulative from July 2024 through July 2025.

Usage JCI PMC
Text version 535 89
PDF 204 7
Figure 592 10
Citation downloads 98 0
Totals 1,429 106
Total Views 1,535
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2025 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

Sign up for email alerts