AIMS: In multiple sclerosis patients, treatment with recombinant IFN-beta (rIFN-beta) is partially efficient in reducing clinical exacerbations. However, its molecular mechanism of action is still under scrutiny. MATERIALS & METHODS: We used DNA microarrays (Affymetrix, CA, USA) and peripheral mononuclear blood cells from 25 relapsing remitting multiple sclerosis patients to analyze the longitudinal transcriptional profile within 2 years of rIFN-beta administration. Sets of differentially expressed genes were attained by applying a combination of independent criteria, thereby providing efficient data curation and gene filtering that accounted for technical and biological noise. Gene ontology term-association analysis and scientific literature text mining were used to explore evidence of gene interaction. RESULTS: Post-therapy initiation, we identified 42 (day 2), 175 (month 1), 103 (month 12) and 108 (month 24) differentially expressed genes. Increased expression of established IFN-beta marker genes, as well as differential expression of circulating IFN-beta-responsive candidate genes, were observed. MS4A1 (CD20), a known target of B-cell depletion therapy, was significantly downregulated after one month. CMPK2, FCER1A, and FFAR2 appeared as hitherto unrecognized multiple sclerosis treatment-related differentially expressed genes that were consistently modulated over time. Overall, 84 interactions between 54 genes were attained, of which two major gene networks were identified at an earlier stage of therapy: the first (n = 15 genes) consisted of mostly known IFN-beta-activated genes, whereas the second (n = 12) mainly contained downregulated genes that to date have not been associated with IFN-beta effects in multiple sclerosis array research. CONCLUSION: We achieved both a broadening of the knowledge of IFN-beta mechanism-of-action-related constituents and the identification of time-dependent interactions between IFN-beta regulated genes.
AIMS: In multiple sclerosispatients, treatment with recombinant IFN-beta (rIFN-beta) is partially efficient in reducing clinical exacerbations. However, its molecular mechanism of action is still under scrutiny. MATERIALS & METHODS: We used DNA microarrays (Affymetrix, CA, USA) and peripheral mononuclear blood cells from 25 relapsing remitting multiple sclerosispatients to analyze the longitudinal transcriptional profile within 2 years of rIFN-beta administration. Sets of differentially expressed genes were attained by applying a combination of independent criteria, thereby providing efficient data curation and gene filtering that accounted for technical and biological noise. Gene ontology term-association analysis and scientific literature text mining were used to explore evidence of gene interaction. RESULTS: Post-therapy initiation, we identified 42 (day 2), 175 (month 1), 103 (month 12) and 108 (month 24) differentially expressed genes. Increased expression of established IFN-beta marker genes, as well as differential expression of circulating IFN-beta-responsive candidate genes, were observed. MS4A1 (CD20), a known target of B-cell depletion therapy, was significantly downregulated after one month. CMPK2, FCER1A, and FFAR2 appeared as hitherto unrecognized multiple sclerosis treatment-related differentially expressed genes that were consistently modulated over time. Overall, 84 interactions between 54 genes were attained, of which two major gene networks were identified at an earlier stage of therapy: the first (n = 15 genes) consisted of mostly known IFN-beta-activated genes, whereas the second (n = 12) mainly contained downregulated genes that to date have not been associated with IFN-beta effects in multiple sclerosis array research. CONCLUSION: We achieved both a broadening of the knowledge of IFN-beta mechanism-of-action-related constituents and the identification of time-dependent interactions between IFN-beta regulated genes.
Authors: Alexander Hundeshagen; Michael Hecker; Brigitte Katrin Paap; Charlotte Angerstein; Ole Kandulski; Christian Fatum; Christiane Hartmann; Dirk Koczan; Hans-Juergen Thiesen; Uwe Klaus Zettl Journal: J Neuroinflammation Date: 2012-06-22 Impact factor: 8.322
Authors: Michael Hecker; Brigitte Katrin Paap; Robert Hermann Goertsches; Ole Kandulski; Christian Fatum; Dirk Koczan; Hans-Peter Hartung; Hans-Juergen Thiesen; Uwe Klaus Zettl Journal: PLoS One Date: 2011-12-27 Impact factor: 3.240