Clinical dilemma: Recent advances in biologic therapies for rheumatic diseases provide a means for more profound disease management. Proper diagnosis is a necessary aspect of choosing the proper biologic therapy. While disease diagnosis, based on clinical findings and laboratory tests, is effective in a significant number of patients, it can be problematic in patients with early disease, mild symptoms, or unclear presentation, leading to delayed or inappropriate treatment with poor patient outcomes and/or exposures to unnecessary drug toxicities. This problem is due in part to limitations of specificity and sensitivity of current rheumatology diagnostic laboratory tests. Many of these tests are designed to include or rule out one disease, which may be inadequate to obtain a diagnosis if the results are negative. Our preliminary data suggest that a single blood test can be developed which is capable of sensitive and specific disease diagnosis of many common rheumatic diseases using gene expression profiling of peripheral blood. We also have data suggesting that this multi-disease test is effective in patients with early disease prior to full clinical differentiation and may aid in guiding earlier treatment which can dramatically improve outcomes. ? Approach: To assess the potential of gene expression-based diagnostic testing, clinical samples were collected from a cohort of patients with definitive forms of inflammatory disease, and broad-based gene expression profiling was performed. Multivariate algorithms identified 38 genes that distinguished controls and the four inflammatory diseases tested with high specificity and sensitivity. We have subsequently collected RNA from a second larger patient cohort with sufficient size to power a study to distinguish among a set of rheumatic diseases that can be difficult to distinguish, namely rheumatoid arthritis, osteoarthritis, systemic lupus erythematosus, and ankylosing spondylitis. Biostatistical analyses of gene expression profiles will allow us to translate these findings into two high throughput clinical tests, the first based on gene expression results and the second based on serum protein biomarkers. Finally, we will assess the prognostic power of gene expression profiling by examining results from patients early in their disease cycle with undifferentiated arthritis to determine who is likely to develop erosive disease and who is likely to go into remission. These findings will allow physicians to use more proactive forms of therapy in early undifferentiated arthritis to delay onset of erosive disease and to use less expensive drugs with fewer side effects for patients that are likely to remit.
This study will identify novel blood markers (biomarkers) for some of the more common forms of rheumatic diseases. These biomarkers will be used by physicians to accurately diagnose these diseases and to help distinguish patients who are more likely to develop severe forms of disease from those likely to go into remission. Earlier diagnosis and treatment are linked to better outcome in patients. ? ?
