Autoimmune diseases are difficult to diagnose, as the symptoms can be typical of other conditions and quite vague. No currently available blood test accurately excludes or includes the possibility of an autoimmune disease in a subject, and a battery of tests and a period of observation are usually required. A single test that could readily distinguish between an autoimmune and non-autoimmune disorder would allow physicians to focus efforts on the specific disease that affects the patient. This is critical for diabetes since the treatments for type I and type II diabetics are completely different. 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. 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 on these data, 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 distinguished autoimmune patients from others with 100% accuracy. We now want to turn our attention to diabetes. The first goal of this proposal is to collect gene expression data from patients with type I and type II diabetes to design a test with optimal predictive power. The second goal is to validate the test by examining individuals who have hyperglycemia but do not yet carry a clear-cut diagnosis of either type of diabetes. 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 and non-autoimmune diseases.
