Autoimmune diseases are thought to arise from abnormalities in innate or adaptive immune responses and most likely have both genetic and environmental components. Diagnosis of autoimmune disease is often difficult, as the symptoms can be relatively nonspecific. Furthermore, no available blood test can accurately exclude the possibility of an autoimmune disease in a subject with such symptoms. At best, a battery of tests and evaluation by a specialist physician over a period of time are required to establish that a patient does in fact have an autoimmune disorder. Initial studies have demonstrated that measurement of gene expression in peripheral blood samples separates subjects with autoimmune disorders from healthy controls with a high degree of accuracy. In the first part of the Phase II period, these observations were extended to demonstrate that expression levels of a less than six genes measured by quantitative real-time PCR can produce similar results. The results show that separation of MS patients from normal controls can be achieved with a high degree of accuracy. Other findings indicate utility of this approach in the diagnosis of patients with rheumatoid arthritis and systemic lupus erythematosus. It is now proposed to extend and expand these results to include larger and more diverse patient groups and to evaluate longitudinal changes.
Three specific aims are proposed:
Specific Aim I. To better define optimum diagnostic tests for MS, RA, and SLE, we will determine test performance in subjects with other neurologic, other rheumatologic conditions or other chronic diseases.
Specific Aim II. We will evaluate test performance in cohorts of individuals from different geographic regions, in individuals with early or incomplete disease, in first-degree unaffected relatives of individuals with MS, RA, or SLE, and in subjects prior to and after initiation of standard therapies for each disease.
Specific Aim III. We will design test standards and perform validation studies for our tests as required for FDA approval. We anticipate that the result of these studies will be marketed tests for autoimmune diagnosis that will have a significant impact on patient care.
Autoimmune diseases affect 5% of the population. Unlike many other chronic diseases, these maladies can afflict children and young adults, with long-term health consequences. Diagnosis in early disease stages would be facilitated by the availability of more accurate blood tests, and this is key to timely institution of definitive therapies for prevention of irreversible organ damage.
|Spurlock 3rd, Charles F; Tossberg, John T; Guo, Yan et al. (2015) Defective structural RNA processing in relapsing-remitting multiple sclerosis. Genome Biol 16:58|
|Crooke, Philip S; Tossberg, John T; Horst, Sara N et al. (2012) Using gene expression data to identify certain gastro-intestinal diseases. J Clin Bioinforma 2:20|
|Tossberg, J T; Crooke, P S; Henderson, M A et al. (2012) Gene-expression signatures: biomarkers toward diagnosing multiple sclerosis. Genes Immun 13:146-54|
|Spurlock 3rd, Charles F; Tossberg, John T; Fuchs, Howard A et al. (2012) Methotrexate increases expression of cell cycle checkpoint genes via JNK activation. Arthritis Rheum 64:1780-9|
|Spurlock 3rd, Charles F; Aune, Zachary T; Tossberg, John T et al. (2011) Increased sensitivity to apoptosis induced by methotrexate is mediated by JNK. Arthritis Rheum 63:2606-16|
|Wang, Lily; Jia, Peilin; Wolfinger, Russell D et al. (2011) An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies. Bioinformatics 27:686-92|
|Grayson, B L; Wang, L; Aune, T M (2011) Peripheral blood gene expression profiles in metabolic syndrome, coronary artery disease and type 2 diabetes. Genes Immun 12:341-51|
|Grayson, Britney L; Smith, Mary Ellen; Thomas, James W et al. (2010) Genome-wide analysis of copy number variation in type 1 diabetes. PLoS One 5:e15393|
|Liu, Zheng; Maas, Kevin; Aune, Thomas M (2006) Identification of gene expression signatures in autoimmune disease without the influence of familial resemblance. Hum Mol Genet 15:501-9|