Since the 1950's the incidence of type 1 diabetes (T1D) has risen steadily in developed nations. In the United States alone, an estimated 30,000 new cases are diagnosed annually. B cells are increasingly recognized as major players in T1D. This conclusion is based in part on the recent success of anti-CD20 (Rituximab) therapy, which broadly depletes the entire B cell subpopulation, in delaying disease progression both in NOD mice and new onset human patients. In T1D, auto-antibodies against islet antigens (i.e. insulin) are produced but not required for disease. B cells are thus more likely to promote 2 cell destruction and disease progression through antigen presentation and cytokine production. This project aims to characterize the rare, but dangerous, population of B cells specific for insulin. We have developed an innovative method to enrich for and isolate insulin-specific B cells from the repertoire of normal and diabetic mice. This allows us to analyze both phenotype and function. NOD mice transgenic for the 125Tg heavy chain have an anti-insulin biased B cell repertoire. The mice display increased disease incidence (both in time of onset and proportion of mice developing T1D). Examining insulin-specific B cells in these mice alongside their diabetes resistant C57BL/6 transgenic counterparts will further define how B cell tolerance is breeched in one background, but not the other. The roles of anatomical localization, antibiotic treatment, and pancreas injury on the function of these cells will also be addressed. The knowledge gained through this project will ultimately reveal new B cell therapeutic targets and strategies, as well as biomarkers useful in diagnosis, monitoring and personalization of therapy for T1D.
Insulin-specific B cells are increasingly recognized as major players in type 1 diabetes (T1D). This project aims to better understand the molecular processes that normally silence these autoreactive lymphocytes as well as the factors that cause this silencing to fail, ultimately giving rise to disease. Data generated will assist in the development of new therapies that specifically target these pathogenic cells while leaving the remainder of the immune system unperturbed.
