The effect of the microbiome on the development and severity of uveitis

描述（由申请人提供）：越来越多的证据表明，在自身免疫性疾病中出现错误的免疫耐受的形成在很大程度上受到共生微生物群的影响。尽管微生物组和自身免疫之间的关系已经在自身免疫性疾病（如类风湿关节炎、炎症性肠病和多发性硬化症）中得到了研究，但尚未对自身免疫性葡萄膜炎（一种潜在的疾病）进行研究

DESCRIPTION (provided by applicant): There is increasing evidence that the shaping of the immunological tolerance that goes awry in autoimmune disease is heavily influenced by commensal microbiota. Although this relationship between the microbiome and autoimmunity has been studied for autoimmune diseases such as rheumatoid arthritis, inflammatory bowel disease, and multiple sclerosis, it has not been investigated for autoimmune uveitis, a potentially blinding inflammatory condition affecting the eyes. Studying the relationship of the microbiome with uveitis may reveal important insights into the pathogenesis of this disease, but more importantly, may result in potential intervention through the use of novel treatment strategies. The hypothesis of this study is that altering the gut flora will affect the clinical severity of uvitis. The first aim to test this hypothesis involves administering broad-spectrum antibiotics to reduce gut flora and to determine how and why this affects uveitis disease severity. Two animal models of autoimmune uveitis, experimental autoimmune uveitis (EAU), and aggrecan-induced uveitis will be tested for this purpose. Disease severity, relative abundances of bowel microorganisms, and the contribution of regulatory T lymphocytes will be assessed. To evaluate the microbiota, a well-developed rapid but robust technique to quantitatively characterize the microbiome of complex biological environments, such as the gut, will be used (Biome representational in silico karyotyping or BRISK). In the second and third aims, the effects of probiotics (commensal microrganisms that can regulate self-tolerance) and prebiotics (diets that affect the innate microbiome in a specific way) will be investigated for their effects on clinical disease severity and the ability to alter gut flora in the disease models above.