Enhancement of Biomarkers for Type 1 Diabetes

1 型糖尿病生物标志物的增强

• 批准号: 8306343
• 负责人: MASSIMO T PIETROPAOLO
• 金额: $ 58.25万
• 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/8306343
• 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，拟议的研究将调查新的免疫生物标志物在同一地理区域的T1DM患者和非T1DM患者一级亲属的最大人群队列中的作用。国际合作临床研究网络，如TrialNet （://www.diabetestrialnet.org）和免疫耐受网络（://www.immunetolerance.org）正在进行越来越多的T1DM试点试验，以寻找T1DM的治疗方法。由于目前可用的生物标记物无法识别足够数量的个体参加这些试验，因此有许多正在进行中的预防试验无法进行。关于如何开发新的策略来提高多种标记物的敏感性，进而有效地将一级亲属纳入T1DM预防试验的讨论已经无休无止。根据我们最新的初步数据，目前应用的一个主要假设是，与传统的胰岛自身抗体标志物相比，检测针对IA-2、GAD65特异性表位的抗体的新型生物标志物和新发现的抗原ZnT8的组合将进一步提高T1DM进展的敏感性和预测价值。拟议的研究将在密歇根大学进行，使用匹兹堡儿童医院队列，该队列目前有161名一级亲属，他们在随访期间从1万多名T1DM先证亲属中转化为胰岛素需用糖尿病（转换者）。这个独特的血清样本档案是检验我们免疫学假设的理想选择。这是所有中心中转换器数量最多的，因此，到下一个赠款期结束时，应该有200多个转换器可用。由于不可能从有发展为T1DM风险的受试者获得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细胞反应在人类疾病自然史中的作用是完全合适的。我们建立了数学模型，考虑了新的和传统的胰岛自身抗体生物标志物（Specific Aim I）和在T1DM进展过程中导致2细胞破坏的高亲和T细胞（Specific Aim II）。我们将基于实验室的方法与T1DM进展的数学建模相结合，并组建了一个前所未有的免疫学研究和2细胞破坏数学预测模型的领先专家团队。模拟T1DM进展的关键要素（胰岛自身抗体、T细胞亲和力、内质网应激和UPR相互作用）与实验设计非常吻合，可能最终验证T细胞子集和/或UPR途径作为药物靶点，并证明对指导治疗T1DM的药物发现有用。拟议研究的结果应允许开发新的生物标志物，模拟与T1DM进展相关的关键因素，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。