Enhancement of Biomarkers for Type 1 Diabetes

1 型糖尿病生物标志物的增强

• 批准号: 8114993
• 负责人: MASSIMO T PIETROPAOLO
• 金额: $ 58.16万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-05-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8114993
• 关键词: Achievement; Affect; Algorithms; Alleles; Amino Acids; Antibodies; Antibody Formation; Antigens; Appearance; Archives; Area; Autoantibodies; Autoantigens; Autoimmune Process; Avidity; Behavior; Beta Cell; Binding; Biological Assay; Biological Markers; CD4 Positive T Lymphocytes; Categories; Cell Death; Cells; Clinical; Clinical Research; Clinical Trials; Collaborations; Colorado; Coupled; Data; Detection; Development; Diabetes Mellitus; Disease; Disease Outcome; Drug Delivery Systems; Elements; Enrollment; Epidemiology; Epitopes; Equation; Equilibrium; Exhibits; Experimental Designs; Extinction (Psychology); Extracellular Domain; First Degree Relative; Future; Goals; Grant; Human; Immune; Immune Tolerance; Immunologics; Immunology; Immunotherapy; Individual; Insulin; Insulin-Dependent Diabetes Mellitus; Interferon Type II; International; Intervention Trial; Investigation; Laboratories; Lead; Letters; Leukocytes; Measures; Methodology; Michigan; Modeling; Names; National Institute of Diabetes and Digestive and Kidney Diseases; Natural History; Neurosecretory Systems; Onset of illness; Outcome; Pancreas; Pathogenesis; Pathway interactions; Patients; Pediatric Hospitals; Peptides; Population; Predictive Value; Predisposition; Prevention; Principal Investigator; Process; Proteins; Protocols documentation; Public Health; Publishing; Relative (related person); Reporting; Research; Research Personnel; Risk; Risk Assessment; Role; Rough endoplasmic reticulum; Sample Size; Sampling; Screening procedure; Serum; Staging; Stress; Structure of beta Cell of islet; T cell response; T-Lymphocyte; T-Lymphocyte Subsets; TNFRSF10A gene; Techniques; Testing; Time; Tissues; Universities; Validation; Washington; Work; autoreactive T cell; base; cell injury; cohort; design; diabetes risk; diabetic patient; drug discovery; endocrine pancreas development; epidemiology study; follow-up; high risk; human disease; inclusion criteria; islet; islet cell antibody; lymph nodes; mathematical model; multi-scale modeling; non-diabetic; novel; novel strategies; pilot trial; population based; pre-clinical; predictive modeling; prevent; proband; programs; protein aggregate; public health relevance; response; symposium; type I diabetic; zinc-binding protein

DESCRIPTION (provided by applicant): The proposed research, based on our prior 8-year achievements, will investigate the role of new immunologic biomarkers in the largest population-based cohort of first degree relatives of T1DM patients with and without T1DM from the same geographical area. Growing number of pilot trials for T1DM are being conducted by international collaborative clinical research networks, such as TrialNet (://www.diabetestrialnet.org) and the Immune Tolerance Network (://www.immunetolerance.org) in an effort to find the cure for T1DM. There are many prevention trials in the pipeline that cannot be performed because the currently available biomarkers cannot identify a sufficient number of individuals to be enrolled in these trials. Endless discussions have taken place on how to develop new strategies to enhance sensitivity of multiple markers and in turn effectively enroll first-degree relatives in T1DM prevention trials. Based on our most recent preliminary data, a major hypothesis of the present application is that a combination of novel biomarkers detecting antibodies directed to IA-2, GAD65 specific epitopes and the newly discovered antigen ZnT8 will further enhance sensitivity and the predictive value of T1DM progression as compared to conventional islet autoantibody markers. The proposed research will be performed at the University of Michigan using the Children's Hospital of Pittsburgh cohort, which currently has 161 first degree relatives, who converted to insulin-requiring diabetes during follow-up (converters) from a pool of over 10,000 relatives of T1DM probands. This unique serum sample archive is ideal to test our immunologic hypotheses. This represents the largest number of converters of any center and as such, more than 200 converters should be available by the end of the next grant period. Because it is impossible to have access to pancreatic tissue and pancreatic lymph nodes from subjects at risk of developing T1DM, we feel that it is entirely appropriate to develop predictive models of pancreatic 2 cell destruction to understand the role of pathogenic T cell responses during the natural history of human disease. We have constructed mathematical models taking into consideration new and conventional islet autoantibody biomarkers (Specific Aim I) and high avidity T cells which leads to 2 cell destruction during T1DM progression (Specific Aim II). We have coupled laboratory-based methodology with mathematical modeling of T1DM progression and have assembled an unprecedented team of leading experts in immunology research and mathematical predictive models of 2 cell destruction. Modeling key elements of T1DM progression (islet autoantibodies, T cell avidity, ER stress and UPR interactions) fits well with the experimental design and may ultimately validate a subset of T cells and/or the UPR pathway as drug targets and prove useful in guiding drug discovery to treat T1DM. The outcome of the proposed investigation should allow for the development of new biomarkers, modeling of key elements associated with T1DM progression and facilitate major clinical trials aimed at evaluating new approaches for understanding, preventing and treating Type 1 diabetes. PUBLIC HEALTH RELEVANCE: The use of immuno-epidemiology studies can be applied to reliably identify the earliest signs of islet autoantibodies which indicate that the autoimmune process leading to pancreatic 2 cell injury has already initiated. It is likely that the appearance of these white cells contribute to the destructive process of pancreatic 2 cells, a prelude of clinically overt Type 1 diabetes mellitus. Our research has major public health implications and together with modeling of key elements of Type 1 diabetes progression these studies will also provide a conceptual framework for designing new algorithms used for enrolling new subjects at risk in major clinical trials aimed at preventing Type 1 diabetes.

描述（由申请人提供）：基于我们之前8年的成果，拟定的研究将在来自同一地理区域的T1 DM伴和不伴T1 DM患者的一级亲属的最大人群队列中研究新免疫学生物标志物的作用。越来越多的T1 DM试点试验正在由国际合作临床研究网络进行，如TrialNet（：www.diabetestrialnet.org）和免疫耐受网络（：www.immunetolerance.org），以寻找T1 DM的治愈方法。有许多预防试验正在进行中，但无法进行，因为目前可用的生物标志物无法识别足够数量的个体参加这些试验。关于如何开发新的策略以提高多种标志物的敏感性，从而有效地在T1 DM预防试验中招募一级亲属，已经进行了无休止的讨论。基于我们最新的初步数据，本申请的主要假设是检测针对IA-2、GAD 65特异性表位和新发现的抗原ZnT 8的抗体的新型生物标志物的组合与常规胰岛自身抗体标志物相比将进一步增强T1 DM进展的灵敏度和预测值。这项拟议的研究将在密歇根大学使用匹兹堡儿童医院队列进行，该队列目前有161名一级亲属，他们在随访期间从超过10，000名T1 DM先证者亲属中转化为需要胰岛素的糖尿病。这种独特的血清样本档案是测试我们免疫学假设的理想选择。这代表了任何中心的最大数量的转换器，因此，到下一个资助期结束时，应该有200多个转换器可用。由于不可能获得有发生T1 DM风险的受试者的胰腺组织和胰腺淋巴结，我们认为开发胰腺2细胞破坏的预测模型以了解致病性T细胞应答在人类疾病自然史中的作用是完全合适的。我们构建了数学模型，考虑了新的和传统的胰岛自身抗体生物标志物（特异性目标I）和高亲和力T细胞，其导致T1 DM进展期间2细胞破坏（特异性目标II）。我们将基于实验室的方法与T1 DM进展的数学建模相结合，并组建了一支前所未有的免疫学研究和2细胞破坏数学预测模型方面的领先专家团队。模拟T1 DM进展的关键要素（胰岛自身抗体、T细胞亲合力、ER应激和UPR相互作用）与实验设计非常吻合，并可能最终验证T细胞亚群和/或UPR通路作为药物靶点，并证明可用于指导药物发现以治疗T1 DM。拟议研究的结果应允许开发新的生物标志物，建立与T1 DM进展相关的关键要素模型，并促进旨在评估了解，预防和治疗1型糖尿病的新方法的主要临床试验。 公共卫生关系：免疫流行病学研究的使用可以应用于可靠地识别胰岛自身抗体的最早迹象，这表明导致胰腺2细胞损伤的自身免疫过程已经开始。很可能这些白色细胞的出现促成了胰腺2细胞的破坏过程，这是临床上明显的1型糖尿病的前奏。我们的研究具有重大的公共卫生意义，这些研究与1型糖尿病进展的关键因素建模一起，还将为设计新算法提供概念框架，用于在旨在预防1型糖尿病的重大临床试验中招募新的风险受试者。