Author(s): Wong FS, Wen L
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Abstract Many autoimmune diseases have genetic associations with the Major Histocompatibility Complex (MHC) class II loci. Susceptibility to Type 1 diabetes mellitus (TIDM) is particularly associated with Human Leucocyte Antigen (HLA) DR3, 4 and associated DQ2, 8 alleles and this is well documented in genetic association studies. These molecules play an important role in presentation of peptide antigens after intracellular processing to CD4 T lymphocytes. During the last decade, a number of approaches have been used to elucidate the molecular basis for the association of particular alleles with susceptibility to or protection from TIDM. These studies have focused on investigating the structure of the antigen presenting molecules, together with their peptides. Through binding studies, peptide elution, molecular modelling and crystallization of the peptide MHC complex, it has been possible to define the peptide binding regions and examine the stability of binding of peptides from putative autoantigens. This knowledge has also facilitated the development of reagents such as multimeric MHC-peptide complexes that will help to track the low frequency, potentially pathogenic antigen specific cells. Recently, HLA transgenic mice have been generated and used to study T cell epitopes. In addition, although it is clear that the presence of HLA molecules alone does not by itself cause disease, these transgenic mice will develop diabetes when there is an islet "insult", even if the islet "insult" is, itself, not sufficient to precipitate disease in the absence of the HLA class II transgene. These mice will allow further study of the role of these HLA molecules in vivo. We now have a much greater general understanding of the possible reasons why particular molecules may encode susceptibility to or protection from disease. All these studies will provide information to ultimately define a rational basis for the development of targeted immunotherapy.
This article was published in Curr Mol Med
and referenced in Journal of Proteomics & Bioinformatics