4.5 Article

Rapamycin/GABA combination treatment ameliorates diabetes in NOD mice

Journal

MOLECULAR IMMUNOLOGY
Volume 73, Issue -, Pages 130-137

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.molimm.2016.01.008

Keywords

Rapamycin; GABA; Autoimmune diabetes

Funding

  1. Natural Science Foundation of China [81200617, 81500590]
  2. Natural Science Foundation of Chongqing Science & Technology Commission [cstc2012jjA10033]

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Type 1 diabetes (Ti D) is one of the most common autoimmune diseases, affecting nearly 20 million people worldwide. The pathogenesis of T1D is characterized by the progressive destruction of insulin-producing pancreatic beta-cells by autoreactive T cells. The significant role of immunomodulation in preserving residual insulin-producing beta-cells in newly diagnosed Tl D has not been confirmed yet. However, a combination of treatments acting via distinct mechanisms is widely considered to be the most promising future therapeutic approach in this respect. Rapamycin and gamma-aminobutyric acid (GABA) administration alone showed no effects on late-stage disease. By contrast, combined rapamycin/GABA treatment effectively suppressed autoimmune responses to islet cells and improved islet function in recent-onset diabetes. In particular, after the onset of hyperglycemia, those treated with the rapamycin/GABA combination showed significant amelioration of diabetes amelioration compared to those treated with either rapamycin or GABA alone. This protective effect of the rapamycin/GABA combination treatment in nonobese diabetic (NOD) mice was exerted through two distinct mechanisms. Rapamycin induced regulatory T cells and consequently suppressed targeted autoimmune responses to islet cells, which may be relevant to the reduced insulitis observed in rapamycin-treated NOD mice. By contrast, treatment with GABA improved islet function in diabetic NOD mice. We believe that our observations are highly relevant to establishing clinical strategies for the prevention and treatment of T1D in future. (c) 2016 Elsevier Ltd. All rights reserved.

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