The development of autoimmune diabetes in the nonobese diabetic (NOD) mouse results from a breakdown in tolerance to pancreatic islet antigens. CD28-B7 and CD40 ligand–CD40 (CD40L-CD40) costimulatory pathways affect the development of disease and are promising therapeutic targets. Indeed, it was shown previously that diabetes fails to develop in NOD–B7-2–/– and NOD-CD40L–/– mice. In this study, we examined the relative role of these 2 costimulatory pathways in the balance of autoimmunity versus regulation in NOD mice. We demonstrate that initiation but not effector function of autoreactive T cells was defective in NOD–B7-2–/– mice. Moreover, the residual proliferation of the autoreactive cells was effectively controlled by CD28-dependent CD4+CD25+ regulatory T cells (Treg’s), as depletion of Treg’s partially restored proliferation of autoreactive T cells and resulted in diabetes in an adoptive-transfer model. Similarly, disruption of the CD28-B7 pathway and subsequent Treg deletion restored autoimmunity in NOD-CD40L–/– mice. These results demonstrate that development of diabetes is dependent on a balance of pathogenic and regulatory T cells that is controlled by costimulatory signals. Thus, elimination of Treg’s results in diabetes even in the absence of costimulation, which suggests a need for alternative strategies for immunotherapeutic approaches.
Hélène Bour-Jordan, Benoît L. Salomon, Heather L. Thompson, Gregory L. Szot, Matthew R. Bernhard, Jeffrey A. Bluestone
Usage data is cumulative from April 2023 through April 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 263 | 37 |
54 | 22 | |
Figure | 118 | 10 |
Supplemental data | 9 | 1 |
Citation downloads | 12 | 0 |
Totals | 456 | 70 |
Total Views | 526 |
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.