Predictive biomarkers for EAE development

EAE 发展的预测生物标志物

• 批准号: 8701655
• 负责人: THOMAS G. FORSTHUBER
• 金额: $ 22.05万
• 依托单位: UNIVERSITY OF TEXAS SAN ANTONIO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-03-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8701655
• 关键词: Adoptive Transfer; Alleles; Animals; B-Lymphocytes; Biological Markers; C57BL/6 Mouse; Cells; Central Nervous System Diseases; Clinical; Demyelinations; Development; Disease; Disease Marker; Disease Progression; Disease remission; Electrophoresis; Enzyme-Linked Immunosorbent Assay; Experimental Autoimmune Encephalomyelitis; Goals; Granulocyte-Macrophage Colony-Stimulating Factor; HLA-DR2 Antigen; Immune system; Incidence; Individual; Inflammatory; Interferons; Interleukin-17; Magnetism; Mediator of activation protein; Methods; Modeling; Multiple Sclerosis; Mus; Nature; Neuraxis; Outcome; Pathogenesis; Pathology; Patients; Preparation; Protein Isoforms; Proteins; Proteome; Proteomics; Publishing; Relapse; Relative (related person); Reporting; Research; Research Personnel; SJL/J Mouse; Sampling; Serum; Set protein; Severities; Severity of illness; Specimen; Standardization; Symptoms; System; T-Lymphocyte; TNF gene; Testing; Time; Tissues; Translating; base; cytokine; drug development; enzyme linked immunospot assay; expectation; microwave electromagnetic radiation; novel; pre-clinical; protein expression; public health relevance; therapy development

DESCRIPTION (provided by applicant): Approximately 1/1000 people develop multiple sclerosis (MS), but even among people that express the MS- associated MHC II allele HLA-DR2 we cannot predict who will develop disease and only 1/200 HLA-DR2+ people ever will. Surprisingly, even in studies of the murine experimental autoimmune encephalomyelitis (EAE) model of MS, where active or passive disease is induced under well-defined conditions, not all of the genetically-identical mice develop disease with the same trajectory or severity and we cannot accurately predict who will develop disease. In our own preliminary studies we have identified several protein biomarker candidates that correlate with onset, peak, and remission of EAE using a novel quantitative proteomics method that we recently reported (Raphael, I. Electrophoresis, 2012). Furthermore, we have developed a method to induce EAE of predetermined severity using adoptive transfer EAE in combination with pre-transfer cytokine ELISPOT analysis. Importantly, we have preliminary results that predicted candidate protein biomarkers can be detected in serum of mice with EAE by ELISA. By combining these approaches for inducing EAE and correlating protein expression to disease progression we will provide proof-of-principle in a unique system to identifying predictive markers of disease incidence and severity. The objective of this proposal is to provide proof-of-principle of predictive biomarkers using the EAE model. Our central hypothesis is that the clinical onset of EAE symptoms is preceded by release of CNS disease- specific proteins into blood (serum) that can be used to predict which animal will develop disease and how severe. This hypothesis is based on our own preliminary results and supported by published studies. The rationale for the proposed research is that proof-of-principle in the EAE model will provide the basis for developing homologous predictive biomarkers for MS patients, which will revolutionize treatment and drug development for MS. We will test our central hypothesis with the following specific aims: Aim 1. To determine key CNS disease-related protein isoforms with altered expression in CNS tissue prior to the onset of EAE and as a function of disease severity. Aim 2. To determine the CNS disease-related proteins isoforms released into blood (serum) most predictive of EAE incidence and severity. We expect that the proposed studies will provide important information that is currently not available and that will have significant and lasting impact on research and treatment of MS.

描述（由申请人提供）：大约1/1000的人会患上多发性硬化症（MS），但即使在表达MS相关MHC II等位基因HLA-DR2的人中，我们也无法预测谁会患上这种疾病，只有1/200的HLA-DR2+的人会患上这种疾病。令人惊讶的是，即使在MS小鼠实验性自身免疫性脑脊髓炎（EAE）模型的研究中，在明确的条件下诱导主动或被动疾病，并非所有基因相同的小鼠都以相同的轨迹或严重程度发展疾病，我们无法准确预测谁会发展疾病。在我们自己的初步研究中，我们使用了一种新的定量蛋白质组学方法，确定了几种与EAE发病、峰值和缓解相关的蛋白质生物标志物候选物（Raphael， I. Electrophoresis, 2012）。此外，我们开发了一种方法，利用过继性转移EAE结合转移前细胞因子ELISPOT分析，诱导预定严重程度的EAE。重要的是，我们有初步的结果，预测候选蛋白生物标志物可以通过ELISA在EAE小鼠血清中检测到。通过结合这些方法来诱导EAE和将蛋白质表达与疾病进展相关联，我们将在一个独特的系统中提供原理证明，以确定疾病发病率和严重程度的预测标记。本提案的目的是使用EAE模型提供预测性生物标志物的原理证明。我们的中心假设是，EAE症状的临床发作之前，中枢神经系统疾病特异性蛋白释放到血液（血清）中，可用于预测哪种动物会发病及其严重程度。这一假设是基于我们自己的初步结果，并得到了已发表研究的支持。本研究的基本原理是EAE模型的原理验证将为开发MS患者的同源预测性生物标志物提供基础，这将彻底改变MS的治疗和药物开发。我们将以以下具体目标验证我们的中心假设：确定EAE发病前CNS组织中表达改变的关键CNS疾病相关蛋白亚型及其与疾病严重程度的关系。目标2。确定释放到血液（血清）中最能预测EAE发病率和严重程度的中枢神经系统疾病相关蛋白亚型。我们期望拟议的研究将提供目前无法获得的重要信息，并将对MS的研究和治疗产生重大而持久的影响。