| First Author | Antal Z | Year | 2012 |
| Journal | J Immunol | Volume | 188 |
| Issue | 11 | Pages | 5766-75 |
| PubMed ID | 22539795 | Mgi Jnum | J:188404 |
| Mgi Id | MGI:5440506 | Doi | 10.4049/jimmunol.1102930 |
| Citation | Antal Z, et al. (2012) Beyond HLA-A*0201: new HLA-transgenic nonobese diabetic mouse models of type 1 diabetes identify the insulin C-peptide as a rich source of CD8+ T cell epitopes. J Immunol 188(11):5766-75 |
| abstractText | Type 1 diabetes is an autoimmune disease characterized by T cell responses to beta cell Ags, including insulin. Investigations employing the NOD mouse model of the disease have revealed an essential role for beta cell-specific CD8(+) T cells in the pathogenic process. As CD8(+) T cells specific for beta cell Ags are also present in patients, these reactivities have the potential to serve as therapeutic targets or markers for autoimmune activity. NOD mice transgenic for human class I MHC molecules have previously been employed to identify T cell epitopes having important relevance to the human disease. However, most studies have focused exclusively on HLA-A*0201. To broaden the reach of epitope-based monitoring and therapeutic strategies, we have looked beyond this allele and developed NOD mice expressing human beta(2)-microglobulin and HLA-A*1101 or HLA-B*0702, which are representative members of the A3 and B7 HLA supertypes, respectively. We have used islet-infiltrating T cells spontaneously arising in these strains to identify beta cell peptides recognized in the context of the transgenic HLA molecules. This work has identified the insulin C-peptide as an abundant source of CD8(+) T cell epitopes. Responses to these epitopes should be of considerable utility for immune monitoring, as they cannot reflect an immune reaction to exogenously administered insulin, which lacks the C-peptide. Because the peptides bound by one supertype member were found to bind certain other members also, the epitopes identified in this study have the potential to result in therapeutic and monitoring tools applicable to large numbers of patients and at-risk individuals. |
