Gene Expression and Diagnosis of Autoimmune Disease

描述（由申请人提供）：自身免疫性疾病，如系统性红斑狼疮、类风湿性关节炎、I型糖尿病和多发性硬化症，被认为是由先天性或适应性免疫应答异常引起的。自身免疫性疾病通常难以诊断，因为症状可能是其他疾病的典型症状，并且非常模糊，例如肌肉骨骼投诉和疼痛，头痛或头晕。没有可用的血液检查可以准确地排除具有这些症状的受试者中自身免疫性疾病的可能性。充其量，通常需要一系列测试和一段时间的观察才能确定患者确实患有自身免疫性疾病。因此，一个单一的测试，可以很容易地排除自身免疫性疾病的可能性将允许医生把他们的努力集中在谁有严重疾病的可能性最大的病人。利用微阵列技术，我们比较了四种不同的自身免疫性疾病，免疫前后的正常对照个体，和其他慢性疾病的个体之间的外周血单核细胞基因表达的差异。令人惊讶的是，我们发现每个患有自身免疫性疾病的个体都有一个共同的基因表达特征，该特征独立于特定的自身免疫性疾病，但与正常的免疫反应完全不同，并且在患有其他慢性疾病的个体中没有观察到。基于这些观察，我们开发了一种简单的测试，用于排除受试者患有自身免疫性疾病的可能性。该测试的主要优点是它比目前可用的测试更快，更准确。到目前为止，这项测试已经以100%的准确率从正常患者中预测出了自身免疫性患者。该提案的第一个目标是从足够数量的个体中收集基因表达数据，以设计具有最佳预测能力的测试。第二个目标是通过检查一组尚未明确诊断为自身免疫性疾病的个体来验证该测试。长期目标是利用微阵列实验的结果来开发对自身免疫性疾病个体的治疗管理具有预测价值的测试。这些包括对疾病进行分类，预测严重程度和预测最佳治疗方案的测试。

DESCRIPTION (provided by the applicant): Autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis, type I diabetes, and multiple sclerosis, are thought to arise from abnormalities of innate or adaptive immune responses. Autoimmune diseases are often difficult to diagnose, as the symptoms can be typical of other conditions and quite vague, such as musculoskeletal complaints and pain, headaches or dizziness. No available blood test can accurately exclude the possibility of an autoimmune disease in a subject with these symptoms. At best, a battery of tests and a period of observation are usually required to establish that a patient does in fact have an autoimmune disorder. Thus, a single test that could readily exclude the possibility of an autoimmune disease would allow physicians to focus their efforts on patients who have the greatest likelihood of serious disease. Using microarray technology, we have compared differences in gene expression in peripheral blood mononuclear cells among individuals with four distinct autoimmune diseases, normal control individuals before and after immunization, and individuals with other chronic diseases. Surprisingly, we find that each individual with autoimmune disease has a common gene expression signature that is independent of the specific autoimmune disease but is totally distinct from the normal immune response and is not observed in individuals with other chronic diseases. Based upon these observations, we have developed a simple test for excluding the possibility that a subject has an autoimmune disorder. The main advantage of this test is that it is a quicker and more accurate test than those currently available. This test has thus far predicted autoimmune patients from normal patients with 100 percent accuracy. The first goal of this proposal is to collect gene expression data from a sufficient number of individuals to design a test with optimal predictive power. The second goal is to validate the test by examining a cohort of individuals who do not yet carry a clear-cut diagnosis of an autoimmune disease. Long-term goals are to use results from microarray experiments to develop tests that have predictive value for the therapeutic management of individuals with autoimmune diseases. These include tests that classify diseases, predict severity, and predict the best therapeutic options.