Abstract
Multiple sclerosis is a demyelinating disease of the central nervous system with a presumed autoimmune etiology. Previous microarray analyses identified conserved gene expression signatures in peripheral blood mononuclear cells of patients with autoimmune diseases. We used quantitative real-time polymerase chain reaction analysis to identify a minimum number of genes of which transcript levels discriminated multiple sclerosis patients from patients with other chronic diseases and from controls. We used a computer program to search quantitative transcript levels to identify optimum ratios that distinguished among the different categories. A combination of a 4-ratio equation using expression levels of five genes segregated the multiple sclerosis cohort (n = 55) from the control cohort (n = 49) with a sensitivity of 91% and specificity of 98%. When autoimmune and other chronic disease groups were included (n = 78), this discriminator still performed with a sensitivity of 79% and a specificity of 87%. This approach may have diagnostic utility not only for multiple sclerosis but also for other clinically complex autoimmune diseases.
Original language | English (US) |
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Pages (from-to) | 197-204 |
Number of pages | 8 |
Journal | Journal of Molecular Diagnostics |
Volume | 9 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2007 |
All Science Journal Classification (ASJC) codes
- Pathology and Forensic Medicine
- Molecular Medicine